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[NEU] [hoch] JetBrains PyCharm: Schwachstelle ermöglicht Codeausführung

Fri, 24 Jul 2026 11:41:31 +0200

Ein entfernter, anonymer Angreifer kann eine Schwachstelle in JetBrains PyCharm ausnutzen, um beliebigen Programmcode auszuführen.

JetBrains seeks to unify fragmented AI-based software development with governance suite

Thu, 09 Jul 2026 15:03:58 +0200

AI promised to make software development faster, but for many enterprises, it has also created a new management challenge: developers increasingly rely on a mix of coding assistants, AI agents, and models that operate in isolation, making it harder for engineering leaders to govern usage, share knowledge, and control costs.

JetBrains has sought to address these challenges with a new suite of tools and capabilities named JetBrains AI for Teams and Organizations that supports nearly all coding tools, their respective CLIs, and most IDEs, such as Claude, Codex, Gemini, Junie, IntelliJ, Pycharm, and Rider, with support for VS Code to be added soon.

The suite, which consists of capabilities like team automations and cloud agents, JetBrains Context, JetBrains Central, and JetBrains Central CLI, will allow enterprises to manage AI-assisted software development from a single control layer while allowing developers to continue using their preferred coding assistants and IDEs, Oleg Koverznev, head of agent systems at JetBrains, wrote in a blog post.

While team automations and cloud agents are intended to let AI agents run long-running engineering tasks in managed cloud environments and trigger workflows based on repository events or schedules, JetBrains Context is designed to provide a shared understanding of project code, documentation, and development activity across tools, Koverznev added.

Complementing those collaboration capabilities, JetBrains Central serves as the administrative layer for governance, access control, and usage management, with the Central CLI extending those controls to the command-line and automation workflows, Kovernznev further added.

Tool sprawl to reduced operational friction

Fragmentation of AI-assisted coding tools and development environments adds complexity for enterprises and their leaders.

“Fragmentation of AI coding tools is an evolving problem for enterprises. A year ago, the conversation was whether to even allow an AI assistant. Now a single team is running Copilot, Claude Code, Cursor, and a few homegrown agents at once,” said Muskan Bandta, cloud associate at FinOps services providing firm ZopDev.

“The pain leaders raise with us isn’t the tools themselves. It’s that nobody can answer three questions: who is using what, what is it costing us, and is it actually safe? Fragmentation became a governance and cost problem the moment agents started touching real codebases and running up real bills,” Bandta added.

These governance and cost issues are increasing demand for suites, such as JetBrains AI for Teams and Organizations, that can coordinate AI-assisted software development across teams.

For development teams specifically, such suites with a centralized context layer can reduce operational friction, according to Nitish Tyagi, senior principal analyst at Gartner.

“Rather than teams manually configuring multiple AI coding tools, maintaining prompts, or repeatedly supplying context, a centralized context layer enables agents to work with a more consistent understanding of the organization’s codebase, standards, documentation, and workflows,” Tyagi said.

“Over time, this can help accelerate parts of the software development lifecycle by reducing time spent searching for information, understanding legacy code, onboarding developers, and reworking outputs that lack the necessary business context. The primary value is not necessarily that agents write more code, but that they produce more relevant and organization-aware outputs,” Tyagi added.

More so because, a shared context layer for AI agents primarily helps development teams by reducing knowledge silos, Tyagi further added.

Governance and cost management as benefits

The benefits of the suite, according to Bandta, transcend developer productivity and should help CIOs with governance and cost management.

“The suite will enable engineering leaders to gain greater control over what information can be accessed by different agents and teams, helping reduce security and compliance risks. For example, enterprises can prevent agents from directly accessing sensitive repositories or business-critical data,” echoed Tyagi.

“Secondly, as the platform is continuously refining and managing context, agents get optimized and more relevant context to deliver higher quality output at lower cost,” Tyagi added.

The launch of JetBrains’ new suite, analysts pointed out, also reflects a broader shift in the software development tools market, where vendors are evolving from integrated development environments.

“This launch signals the evolution of the IDE into an ‘agentic development environment’. A platform where developers increasingly orchestrate fleets of AI agents instead of writing every line of code themselves,” Bandta said.

“The segment is splitting into agents that do the work and platforms that govern them, and the platform layer is where enterprise budgets will concentrate,” Bandta noted, adding that she expects rival vendors, including Microsoft, to pursue similar strategies.

The new capabilities, according to JetBrains, will be rolled out gradually to business customers throughout July and August.

Larson: Are insecure code completions a vulnerability?

Wed, 10 Jun 2026 18:59:26 +0200

Seth Larson, the Python Software Foundation's security developer-in-residence, has written about the difficulty in classifying insecure code completion in the PyCharm IDE using its Full Line code completion plugin. Larson discovered that the plugin, which uses a local "deep learning module" to offer code completions, suggests code that would lead to severe vulnerabilities. He was unsure whether it warranted a CVE or not, however:

I reported this behavior to JetBrains for "Full Line Code Completion" v253.29346.142 and clearly their support staff weren't certain whether this defect was a security vulnerability or not either. When I asked to publish a blog post about this behavior after they confirmed this report wasn't a "direct security vulnerability" (which I agree with) but then was asked not to publicize my report and referred to PyCharm's Coordinated Disclosure Policy so... which is it? Security vulnerability or not?

I ended up waiting the 90 days anyway and I didn't hear back with any substantive update from the development team. I double-checked again today using "Full Line Code Completion" v261.24374.152 and the behavior is identical, suggesting the same insecure code for both contexts.

This isn't meant to be a specific dig at PyCharm or JetBrains, I have no-doubt that examples like this exist in every code generation model available.

How to use virtual environments in Python

Wed, 10 Jun 2026 02:03:11 +0200

Of all the reasons Python is a hit with developers, one of the biggest is its broad and ever-expanding selection of third-party packages. Convenient toolkits for everything from ingesting and formatting data to high-speed math and machine learning are just an import or pip install away.

But what happens when those packages don’t play nice with each other? What do you do when different Python projects need competing or incompatible versions of the same add-ons? That’s where Python virtual environments come into play.

What are Python virtual environments?

A virtual environment is a way to have multiple, parallel instances of the Python interpreter, each with different sets of packages and different configurations. Each virtual environment contains a discrete copy of the Python interpreter, including copies of its support utilities (such as the package manager pip).

The packages installed in each virtual environment are seen only in that virtual environment and no other. Even large, complex packages with platform-dependent binaries can be corralled off from each other in virtual environments.

Why use Python virtual environments?

There are a few common use cases for a virtual environment:

You’re developing multiple projects that depend on different versions of the same packages, or you have a project that must be isolated from certain packages because of a namespace collision. This is the most standard use case.
You’re working in a Python environment where you can’t modify the site-packages directory. This may be because you’re working in a highly controlled environment, such as managed hosting, or on a server where the choice of interpreter (or packages used in it) can’t be changed because of production requirements.
You want to experiment with a specific combination of packages under highly controlled circumstances, for instance to test cross-compatibility or backward compatibility.
You want to run a “baseline” version of the Python interpreter on a system with no third-party packages, and only install third-party packages for each individual project as needed.

Nothing says you can’t simply unpack a Python library into a subfolder of a project and use it that way. Likewise, you could download a standalone copy of the Python interpreter, unpack it into a folder, and use it to run scripts and packages devoted to it.

But managing such cobbled-together projects soon becomes difficult. It only seems easier to do that at first. Working with packages that have binary components, or that rely on elaborate third-party dependencies, can be a nightmare. Worse, reproducing such a setup on someone else’s machine, or on a new machine you manage, is tricky.

The best long-term solution is to use Python’s native mechanisms for creating, reproducing, and working with virtual environments.

How to use virtual environments in Python 3

Python has native tooling for virtual environments that makes the whole process quite simple. This wasn’t always the case, but now all supported versions of Python use the native virtual environment tool, venv.

Create the Python virtual environment

To create a virtual environment in a given directory, type:

python3 -m venv /path/to/venv

For instance, to create the virtual environment in the current directory, using the subdirectory .venv type:

python3 -m venv .venv

On Microsoft Windows, you can use py instead of python3 to reliably access an installed Python version. (See this article for more about using the py launcher in Windows.)

The exact name for the virtual environment directory is arbitrary, but it’s typically .venv.

The whole process of setting up the virtual environment may take a minute or two. When it’s finished, you should see that directory with a few subdirectories in it. The most important subdirectory is bin on Unix or Scripts on Windows, which is where you’ll find the copy of the Python interpreter for the virtual environment along with its utilities.

Note that because each virtual environment contains its own copy of the Python interpreter, it can be fairly large. A Python 3.13 virtual environment will consume anywhere from 14MB to 26MB of disk space, depending on the operating system.

Venvs and version control

If you are setting up a virtual environment in a project directory managed with some kind of version control system (e.g., Git), exclude the environment directory from tracking before you make any commits after creating the venv.

Venvs should not be tracked along with their associated code, as they are meant to be destroyed and recreated as needed. You should, however, track the requirements.txt or pyproject.toml files associated with the project, as those are used to describe what gets installed in the venv for that project.

Activate the Python virtual environment

Before you can use this virtual environment, you need to explicitly activate it. Activation makes the virtual environment the default Python interpreter for the duration of a shell session.

You’ll need to use different syntax for activating the virtual environment depending on which operating system and command shell you’re using.

On Unix or MacOS, using the bash shell: source /path/to/venv/bin/activate
On Unix or MacOS, using the csh shell: source /path/to/venv/bin/activate.csh
On Unix or MacOS, using the fish shell: source /path/to/venv/bin/activate.fish
On Windows using the Command Prompt: path/to/venv/Scripts/Activate.bat
On Windows using PowerShell: path/to/venv/Scripts/Activate.ps1

Note that the activated environment only works for the context it was activated in. For instance, if you launch two instances of PowerShell, A and B, and you activate the virtual environment in instance A, that environment will apply only to A, not B.

Many Python IDEs will automatically detect and activate a virtual environment if one is found in the current project directory. Visual Studio Code, for instance, can do this when the Python extension is enabled. Opening a terminal inside Visual Studio Code will automatically activate the selected virtual environment. PyCharm automatically creates a virtual environment for each new project and enables it automatically.

Configure and use the Python virtual environment

Once you’ve activated the new virtual environment, you can use the pip package manager to add and change packages for it. You’ll find pip in the Scripts subdirectory of the virtual environment on Windows, and in the bin subdirectory on Unix OSes.

If you’re already familiar with the way pip works, you’re set. It should be just the same in a virtual environment. Just make sure you’re using the instance of pip that manages packages for the virtual environment in the context where it was activated—e.g., the bash session or Windows CLI/PowerShell session. If you want to verify that you’re using the right pip and the right virtual environment, type pip -V and check that the path it displays points to a subdirectory of your virtual environment.

Note that when you want to upgrade pip in a virtual environment, it’s best to use the command python3 -m pip install -U pip. This ensures the upgrade process is run in such a way that Python doesn’t lock crucial files. The command pip install -U pip may not be able to complete the upgrade properly.

To use the virtual environment you created to run Python scripts, simply invoke Python from the command line in the context where you activated it. For instance, to run a script, just run python3 myscript.py.

With PyCharm, you can use the IDE’s own package management interface to manage the packages installed in your project.

Managing packages in Python virtual environments

When you create a new virtual environment, pip will be installed, but that’s all. You’ll need to install any other packages you want to use in the environment. For projects with complex requirements, it is customary to keep in the root of the project a requirements.txt file that lists the requirements for the project. This way, if you need to recreate the virtual environment, you can reinstall all of the needed packages with the command pip install -r requirements.txt.

More recently, a new project metadata format has emerged for Python projects, called pyproject.toml. A pyproject.toml file contains the package requirements of the project, but also a great deal of other information about it. To install those requirements, you’d run pip install . in the same directory as the pyproject.toml file.

Note that the copy of pip that lives in a virtual environment is local to that virtual environment. Each virtual environment has its own copy, which will need to be updated and maintained independently. This is why you may get warnings about pip being out of date in some virtual environments but not others; pip has to be updated in each virtual environment separately.

Deactivating the Python virtual environment

When you’re done using the virtual environment, you can just terminate the session where you were using it. If you want to continue to work in the same session but with the default Python interpreter instead, type deactivate at the prompt. Windows users on the Command Prompt need to run deactivate.bat from the Scripts subdirectory, but Unix users and Windows users running PowerShell can simply type deactivate in any directory.

Removing the Python virtual environment

Virtual environments are self-contained. When you no longer need the virtual environment, you can simply delete its directory. Just make sure you first close any running copies of Python that use the virtual environment.

Whenever you want to refresh or recreate a virtual environment, you can simply delete the current environment directory and recreate the venv as described above (see “Managing packages in Python virtual environments”). This is typically the easiest way to upgrade a project to a newer version of Python: delete or temporarily re-name the venv directory (in case the new version doesn’t work), then create a new one and install the project requirements into it.

If you have many older projects that aren’t being actively used, you can remove their environments to save space. They can be recreated easily whenever needed, although you will want to note which version of Python was used to create them along with the needed packages (typically recorded in requirements.txt or pyproject.toml).

Relocating the Python virtual environment

It’s tempting to assume a virtual environment can be copied and moved around along with its project. Don’t do this. Virtual environments are tied to the location of the Python installation on the system where they’re created. If you want to move the project to another system, leave out the venv directory, and recreate the venv on the target machine. Do copy and move the requirements.txt or pyproject.toml file with the project, because those files are needed to recreate the venv on the other system.

How to use virtual environments in Python 2

With Python 2, virtual environments aren’t a native feature of the language. Instead, you need to install third-party libraries to create and manage virtual environments.

The most popular and widely used of these projects is virtualenv, which handles creating the directory structure and copying the needed files into a virtual environment. To install virtualenv, just use pip install virtualenv. To create a virtual environment directory with it, type virtualenv /path/to/directory. Activating and deactivating the virtual environment works the same way as it does for virtual environments in Python 3 (see above).

Note that Python 2 should not be used for any new development. Virtual environments in Python 2, like Python 2 itself, should be used only for the maintenance of legacy projects that should eventually be migrated to Python 3.

Virtual environments and the main Python package directory

Normally, when you create a venv, it cannot work with the packages already present in the Python installation that created it. This is by design, as it ensures that packages installed globally don’t interfere with local ones.

You can override this behavior, but only when you first create a virtual environment. If you pass the flag --system-site-packages to venv when you run it, the created venv will have access to the parent Python’s package directory.

Using Python virtual environments with Jupyter notebooks

If you’re using Jupyter notebooks (aka IPython notebooks), and you already have Jupyter installed systemwide, create your virtual environment and activate it. Then, from your virtual environment directory, run pip install ipykernel to add the needed components for IPython. Finally, run ipython kernel install —user —name=, where project_name is a name you want to associate with that particular project. From there you should be able to launch Jupyter and switch to the IPython kernel you installed inside the virtual environment.

Upgrading Python virtual environments

When you upgrade a Python runtime on your system, virtual environments that use that version of Python aren’t automatically upgraded. That’s your responsibility. And that’s by design, because unwitting upgrades to Python versions can break their attendant packages.

If you’ve upgraded an existing Python interpreter with a minor point upgrade—e.g., from Python 3.13.1 to Python 3.13.3—you can upgrade any corresponding virtual environments easily enough. From a command prompt in the project directory, enter:

python -m venv /path/to/venv --upgrade

Don’t activate the virtual environment beforehand, or the upgrade may not work.

Alternatively, as noted above (see “Removing the Python virtual environment”), you could elect to remove the venv completely and recreate it using your requirements.txt or pyproject.toml file.

If you’ve installed a major new version of Python—e.g., you already have Python 3.10 and you now install Python 3.11 alongside it—you’ll need to create a new virtual environment that specifically uses the new major point version. Do not attempt to upgrade an existing virtual environment to a higher major point version of Python.

v2.1.166

Sat, 06 Jun 2026 03:01:16 +0200

What's changed

Added fallbackModel setting to configure up to three fallback models tried in order when the primary model is overloaded or unavailable; --fallback-model now also applies to interactive sessions
Added glob pattern support in deny rule tool-name position ("*" denies all tools); allow rules reject non-MCP globs, and unknown tool names in deny rules warn at startup
Hardened cross-session messaging: messages relayed via SendMessage from other Claude sessions no longer carry user authority — receivers refuse relayed permission requests, and auto mode blocks them
MAX_THINKING_TOKENS=0, --thinking disabled, and the per-model thinking toggle now disable thinking on models that think by default via the Claude API (3P providers unchanged)
Claude Code now retries a turn once on the fallback model when the API rejects an unexpected non-retryable error; auth, rate-limit, request-size, and transport errors still surface immediately
claude update now announces the target version before downloading instead of going silent
claude agents: typing a URL into the list now filters to the session whose first prompt contained it
Fixed a recurring "image could not be processed" error and extra token usage when an unprocessable image was sent in a session
Fixed remote sessions becoming permanently stuck when a brief backend disruption occurred during worker registration at startup
Fixed flickering in JetBrains IDE terminals (IntelliJ, PyCharm, WebStorm, etc.) on 2026.1+ by enabling synchronized output
Fixed Shift+non-ASCII characters (e.g. Shift+ä → Ä) being dropped in terminals using the Kitty keyboard protocol (WezTerm, Ghostty, kitty)
Fixed PowerShell command validation occasionally hanging far past its time budget on Windows when a killed process's children held its output pipes
Fixed orphaned claude --bg-pty-host processes spinning at 100% CPU after the daemon dies while connected on macOS
Fixed voice mode requiring /login to clear a stale auth check after toggling /voice
Fixed managed settings with an invalid entry silently disabling enforcement of their remaining valid policies
Fixed managed-settings allowedMcpServers/deniedMcpServers predicates not matching when they use ${VAR} references
Fixed background agent sessions that entered a git worktree crash-looping with "No conversation found" when reopened from claude agents
Fixed duplicated thinking text in the Ctrl+O transcript view while streaming
Fixed /doctor showing a contradictory failed "Not inside a remote session" check when run inside a remote session
Fixed the cursor sticking at the end of the first line when typing a multiline prompt in the claude agents dispatch and reply inputs
Fixed blank lines appearing between background agent rows in the task list on terminals without Unicode support

[NEU] [mittel] JetBrains PyCharm: Schwachstelle ermöglicht Cross-Site Scripting

Mon, 01 Jun 2026 11:23:57 +0200

Ein entfernter, anonymer Angreifer kann eine Schwachstelle in JetBrains PyCharm ausnutzen, um einen Cross-Site Scripting Angriff durchzuführen.

CVE-2026-49384 | JetBrains PyCharm up to 2025.3.3 cross site scripting (EUVD-2026-33392)

Sat, 30 May 2026 01:16:33 +0200

A vulnerability was found in JetBrains PyCharm up to 2025.3.3. It has been classified as problematic. This impacts an unknown function. Performing a manipulation results in cross site scripting. This vulnerability is known as CVE-2026-49384. Remote exploitation of the attack is possible. No exploit is available. Upgrading the affected component is recommended.

[Testing Update] 2026-05-18 - Kernels, Heroic Games Launcher, Certbot, Python

Mon, 18 May 2026 20:00:46 +0200

Hello Manjaro user community, here we have another set of package updates. We are continuing our development of the upcoming release of ‘Bian-May’ which can be expected end of May, beginning of June. Development speed may be a little slower the upcoming weeks. However, still let us know any issues you may found thus far.

Current Promotions

Get the latest Gaming Laptop by Slimbook powered by Manjaro: Slimbook Manjaro III
Protect your personal data, keep yourself safe with Surfshark VPN: See current promotion

Recent News

New in Manjaro GNOME! Or, if you prefer the command line: (click for more details) KDE Plasma users with SDDM can now migrate to Plasma Login Manager (click for more details) NVIDIA 590 driver drops Pascal support (click for more details)

Manjaro 26.1 Bian-May - Preview released
Manjaro 26.0 Anh-Linh released
Manjaro Summit public Alpha now available
As of Linux 5.4.302, the 5.4 series is now EOL (End Of Life). Please install 5.10 LTS (Long Term Support) or 5.15 LTS.
As of Linux 6.16.12, the 6.16 series is now EOL (End Of Life). Please install 6.18 LTS (Long Term Support) and/or 6.12 LTS.
As of Linux 6.17.13, the 6.17 series is now EOL (End Of Life). Please install 6.18 LTS (Long Term Support) and/or 6.12 LTS.
As of Linux 6.19.14, the 6.19 series is now EOL (End Of Life). Please install 7.0, and/or 6.18 LTS (Long Term Support) and/or 6.12 LTS.

Previous News Finding information easier about Manjaro (click for more details)

Notable Package Updates

Kernel updates
Heroic Games Launcher 2.22.0
certbot 5.6.0
Updates to python

Additional Info

Python 3.14 info (click for more details) Info about AUR packages (click for more details)

Get our latest daily developer images now from Github: Plasma, GNOME, XFCE. You can get the latest stable releases of Manjaro from CDN77.

Our current supported kernels

linux61 6.1.173
linux66 6.6.140
linux612 6.12.90
linux618 6.18.32
linux70 7.0.9
linux71 7.1.0-rc4
linux61-rt 6.1.167_rt62
linux66-rt 6.6.133_rt73
linux612-rt 6.12.79_rt17
linux617-rt 6.17.5_rt7

Package Changes (5/18/26 15:52 CEST)

testing core x86_64: 12 new and 12 removed package(s)
testing extra x86_64: 455 new and 454 removed package(s)
testing multilib x86_64: 4 new and 4 removed package(s)

:: Different overlay package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2026-05-16           2026-05-18
-------------------------------------------------------------------------------
                            linux612            6.12.88-2            6.12.90-1
                    linux612-headers            6.12.88-2            6.12.90-1
                            linux618            6.18.30-2            6.18.32-1
                    linux618-headers            6.18.30-2            6.18.32-1
                             linux66            6.6.139-1            6.6.140-1
                     linux66-headers            6.6.139-1            6.6.140-1
                             linux70              7.0.7-2              7.0.9-1
                     linux70-headers              7.0.7-2              7.0.9-1
                             linux71           7.1.0rc3-1           7.1.0rc4-1
                     linux71-headers           7.1.0rc3-1           7.1.0rc4-1


:: Different sync package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2026-05-16           2026-05-18
-------------------------------------------------------------------------------
                                dash           0.5.13.2-1           0.5.13.4-1
                            fakeroot             1.37.2-1               1.38-1


:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2026-05-16           2026-05-18
-------------------------------------------------------------------------------
                   game-devices-udev               0.25-1                1.0-1
               heroic-games-launcher             2.21.0-2             2.22.0-1
                  linux612-acpi_call            1.2.2-116            1.2.2-117
                   linux612-bbswitch              0.8-114              0.8-115
                linux612-broadcom-wl     6.30.223.271-115     6.30.223.271-116
               linux612-nvidia-390xx          390.157-116          390.157-117
               linux612-nvidia-470xx       470.256.02-116       470.256.02-117
               linux612-nvidia-570xx        570.211.01-24        570.211.01-25
          linux612-nvidia-570xx-open        570.211.01-24        570.211.01-25
               linux612-nvidia-575xx         575.64.05-43         575.64.05-44
          linux612-nvidia-575xx-open         575.64.05-43         575.64.05-44
               linux612-nvidia-580xx         580.159.03-7         580.159.03-8
          linux612-nvidia-580xx-open         580.159.03-7         580.159.03-8
                     linux612-nvidia          595.71.05-7          595.71.05-8
                linux612-nvidia-open          595.71.05-7          595.71.05-8
                      linux612-r8168          8.056.02-16          8.056.02-17
                  linux612-rtl8723bu           20260507-4           20260507-5
                   linux612-tp_smapi              0.45-60              0.45-61
                linux612-vhba-module          20260313-11          20260313-12
    linux612-virtualbox-host-modules             7.2.8-10             7.2.8-11
                        linux612-zfs              2.4.2-3              2.4.2-4
                  linux618-acpi_call             1.2.2-37             1.2.2-38
                   linux618-bbswitch               0.8-37               0.8-38
                linux618-broadcom-wl      6.30.223.271-37      6.30.223.271-38
               linux618-nvidia-390xx           390.157-38           390.157-39
               linux618-nvidia-470xx        470.256.02-37        470.256.02-38
               linux618-nvidia-570xx        570.211.01-29        570.211.01-30
          linux618-nvidia-570xx-open        570.211.01-29        570.211.01-30
               linux618-nvidia-575xx         575.64.05-37         575.64.05-38
          linux618-nvidia-575xx-open         575.64.05-37         575.64.05-38
               linux618-nvidia-580xx         580.159.03-9        580.159.03-10
          linux618-nvidia-580xx-open         580.159.03-9        580.159.03-10
                     linux618-nvidia          595.71.05-9         595.71.05-10
                linux618-nvidia-open          595.71.05-9         595.71.05-10
                      linux618-r8168          8.056.02-22          8.056.02-23
                  linux618-rtl8723bu           20260507-6           20260507-7
                   linux618-tp_smapi              0.45-37              0.45-38
                linux618-vhba-module          20260313-13          20260313-14
    linux618-virtualbox-host-modules             7.2.8-12             7.2.8-13
                        linux618-zfs              2.4.2-3              2.4.2-4
                   linux66-acpi_call            1.2.2-184            1.2.2-185
                    linux66-bbswitch              0.8-181              0.8-182
                 linux66-broadcom-wl     6.30.223.271-182     6.30.223.271-183
                linux66-nvidia-390xx          390.157-179          390.157-180
                linux66-nvidia-470xx       470.256.02-122       470.256.02-123
                linux66-nvidia-570xx        570.211.01-19        570.211.01-20
           linux66-nvidia-570xx-open        570.211.01-19        570.211.01-20
                linux66-nvidia-575xx         575.64.05-35         575.64.05-36
           linux66-nvidia-575xx-open         575.64.05-35         575.64.05-36
                linux66-nvidia-580xx         580.159.03-5         580.159.03-6
           linux66-nvidia-580xx-open         580.159.03-5         580.159.03-6
                      linux66-nvidia          595.71.05-5          595.71.05-6
                 linux66-nvidia-open          595.71.05-5          595.71.05-6
                       linux66-r8168          8.056.02-13          8.056.02-14
                   linux66-rtl8723bu           20260507-3           20260507-4
                    linux66-tp_smapi              0.45-51              0.45-52
                 linux66-vhba-module           20260313-9          20260313-10
     linux66-virtualbox-host-modules              7.2.8-7              7.2.8-8
                         linux66-zfs              2.4.2-2              2.4.2-3
                   linux70-acpi_call             1.2.2-12             1.2.2-13
                    linux70-bbswitch               0.8-12               0.8-13
                 linux70-broadcom-wl      6.30.223.271-12      6.30.223.271-13
                linux70-nvidia-390xx           390.157-10           390.157-11
                linux70-nvidia-470xx        470.256.02-12        470.256.02-13
                linux70-nvidia-580xx         580.159.03-9        580.159.03-10
           linux70-nvidia-580xx-open         580.159.03-9        580.159.03-10
                      linux70-nvidia          595.71.05-9         595.71.05-10
                 linux70-nvidia-open          595.71.05-9         595.71.05-10
                       linux70-r8168          8.056.02-12          8.056.02-13
                   linux70-rtl8723bu           20260507-6           20260507-7
                    linux70-tp_smapi              0.45-12              0.45-13
                 linux70-vhba-module          20260313-12          20260313-13
     linux70-virtualbox-host-modules             7.2.8-12             7.2.8-13
                         linux70-zfs              2.4.2-3              2.4.2-4
                   linux71-acpi_call            1.2.2-0.5            1.2.2-0.6
                    linux71-bbswitch              0.8-0.5              0.8-0.6
                 linux71-broadcom-wl     6.30.223.271-0.5     6.30.223.271-0.6
                linux71-nvidia-390xx          390.157-0.5          390.157-0.6
                linux71-nvidia-470xx       470.256.02-0.5       470.256.02-0.6
                linux71-nvidia-580xx       580.159.03-0.2       580.159.03-0.3
           linux71-nvidia-580xx-open       580.159.03-0.2       580.159.03-0.3
                      linux71-nvidia        595.71.05-0.4        595.71.05-0.5
                 linux71-nvidia-open        595.71.05-0.4        595.71.05-0.5
                       linux71-r8168         8.056.02-0.5         8.056.02-0.6
                    linux71-tp_smapi             0.45-0.5             0.45-0.6
                 linux71-vhba-module         20260313-0.5         20260313-0.6
     linux71-virtualbox-host-modules            7.2.6-0.1                    -
                         linux71-zfs            2.4.2-0.1            2.4.2-0.2
                              scrcpy                    -              4.0-1.0


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2026-05-16           2026-05-18
-------------------------------------------------------------------------------
                       acme-redirect              0.7.1-2              0.8.1-1
                     add-determinism              0.7.2-1              0.7.3-1
                               amule           1:2.3.3-11           1:2.3.3-12
                              anewer              0.1.6-2              0.1.6-3
                                 ant            1.10.15-1            1.10.17-1
                             ant-doc            1.10.15-1            1.10.17-1
                                apko              1.2.6-1             1.2.12-1
                      audiobookshelf             2.34.0-1             2.35.0-1
                       bbswitch-dkms              0.8-820              0.8-821
                             binocle              0.3.2-2              0.3.2-3
                      bitcoin-daemon               31.0-1               31.0-2
                          bitcoin-qt               31.0-1               31.0-2
                          bitcoin-tx               31.0-1               31.0-2
                          bootconfig              7.0.6-1              7.0.9-1
                                 bpf              7.0.6-1              7.0.9-1
                               bt747              2.2.1-3              2.3.2-1
                                 bun             1.3.13-1             1.3.14-1
                       cargo-nextest            0.9.135-1            0.9.136-1
                          cartridges             2.12.1-3             2.13.1-1
                              catch2             3.14.0-1             3.15.0-1
                           celluloid               0.29-1               0.30-1
                             certbot              5.5.0-1              5.6.0-1
                      certbot-apache              5.5.0-1              5.6.0-1
              certbot-dns-cloudflare              5.5.0-1              5.6.0-1
            certbot-dns-digitalocean              5.5.0-1              5.6.0-1
                certbot-dns-dnsimple              5.5.0-1              5.6.0-1
             certbot-dns-dnsmadeeasy              5.5.0-1              5.6.0-1
                  certbot-dns-gehirn              5.5.0-1              5.6.0-1
                  certbot-dns-google              5.5.0-1              5.6.0-1
                  certbot-dns-linode              5.5.0-1              5.6.0-1
                  certbot-dns-luadns              5.5.0-1              5.6.0-1
                   certbot-dns-nsone              5.5.0-1              5.6.0-1
                     certbot-dns-ovh              5.5.0-1              5.6.0-1
                 certbot-dns-rfc2136              5.5.0-1              5.6.0-1
                 certbot-dns-route53              5.5.0-1              5.6.0-1
             certbot-dns-sakuracloud              5.5.0-1              5.6.0-1
                       certbot-nginx              5.5.0-1              5.6.0-1
                              chawan              0.3.3-2              0.4.0-1
                       checkbashisms             2.26.8-1             2.26.9-1
                                cimg              3.7.5-1              3.7.6-1
                              clpeak              2.0.5-1              2.0.6-1
                         clpeak-cuda              2.0.5-1              2.0.6-1
                           collision             3.14.0-1             3.14.1-1
                            cpupower              7.0.6-1              7.0.9-1
                             crystal             1.20.1-2             1.20.2-1
                        crystal-docs             1.20.1-2             1.20.2-1
                             curtail             1.15.1-1             1.16.1-1
                   deepin-wallpapers           1:1.7.25-1           1:1.7.26-1
                            deja-dup               50.0-1               50.1-1
                              devede             4.21.0-2           4.21.3.1-1
                          diesel-cli              2.3.7-1              2.3.9-1
                             dnsmasq          2.92.rel2-1          2.92.rel2-2
                              docker           1:29.4.3-1           1:29.5.0-1
                       docker-buildx             0.33.0-1             0.34.0-1
                               doctl            1.158.0-1            1.159.0-1
                       dwarffortress              53.12-1              53.13-1
                                 ecb         2.40.1pre-12               2.52-1
                            ejabberd              26.02-1              26.04-1
                             elastic              1.0.2-1              1.0.3-1
                           ethersync              0.8.0-1                    -
                          fastflowlm             0.9.41-1             0.9.42-1
                                 fio               3.41-1               3.42-1
                firefox-adblock-plus             4.31.1-1             4.38.1-1
                           flowblade               2.22-2             2.24.1-1
                             freetds             1.5.17-1             1.5.18-1
                              gaphor              3.3.0-1              3.3.2-1
                             gerbera              3.2.1-2              3.2.1-3
        gnome-shell-extension-vitals             74.0.0-1             76.0.0-1
gnome-shell-extension-weather-oclock               50.2-1               50.3-1
                             go-task             3.50.0-2             3.51.1-1
                             goffice            0.10.60-1            0.10.61-1
                 gpu-screen-recorder             5.13.6-1             5.13.8-1
              gpu-screen-recorder-ui             1.12.0-1             1.12.2-1
                              gramps            2:6.0.7-1            2:6.0.8-1
                              hyperv              7.0.6-1              7.0.9-1
                              hyphen              2.8.8-6              2.8.9-1
                           hyphen-en              2.8.8-6              2.8.9-1
                            hyprland             0.55.1-1             0.55.2-1
                            identity            25.10.1-1              26.03-1
                         imagemagick           7.1.2.22-1           7.1.2.23-1
intel-oneapi-base-toolkit 2025.3.2.21+99f4837a_25b7_425d_a897_60af022676ea-1 -
                intel-oneapi-basekit        2025.0.1.46-1                    -
                  intel-speed-select              7.0.6-1              7.0.9-1
                       intelli-shell              3.4.0-2              3.4.1-1
     intellij-idea-community-edition         4:2026.1.1-1         4:2026.1.2-1
                               iotas             0.12.1-2             2026.6-2
                         jami-daemon           20260206-6           20260206-7
                                josm              19439-1              19555-1
                              kcpuid              7.0.6-1              7.0.9-1
                 kernel-headers-musl            4.19.88-3            6.12.77-1
                              kupfer                327-3                329-1
                      libdatachannel             0.24.2-2             0.24.3-1
                       libexttextcat              3.4.7-2              3.4.8-1
                           libkrunfw              5.3.0-1              5.4.0-1
                         liblockfile             1.17_1-4             1.17_2-1
                           libmythes            1:1.2.5-3            1:1.2.6-1
                            libpaper              2.2.7-1              2.2.8-1
                         libquotient            0.9.6.1-1            0.9.6.1-2
                   libreoffice-fresh             26.2.3-2             26.2.3-3
               libreoffice-fresh-sdk             26.2.3-2             26.2.3-3
                   libreoffice-still             25.8.7-1             25.8.7-2
               libreoffice-still-sdk             25.8.7-1             25.8.7-2
                       libsemigroups              3.6.0-1              3.6.1-1
                           libsigc++             2.12.1-2             2.12.2-1
                       libsigc++-3.0              3.8.0-1              3.8.1-1
                  libsigc++-3.0-docs              3.8.0-1              3.8.1-1
                      libsigc++-docs             2.12.1-2             2.12.2-1
                             libupnp            1.14.26-1            1.14.31-1
                              libvlc             3.0.22-3             3.0.22-4
                               libxi              1.8.2-1              1.8.3-1
                             libzypp            17.38.7-1            17.38.8-1
                        libzypp-docs            17.38.7-1            17.38.8-1
                    linux-tools-meta              7.0.6-1              7.0.9-1
                               lldpd             1.0.21-1             1.0.22-1
                                  ly              1.4.0-1              1.4.1-1
                        man-pages-cs             4.30.0-1             4.30.2-1
                        man-pages-da             4.30.0-1             4.30.2-1
                        man-pages-de             4.30.0-1             4.30.2-1
                        man-pages-el             4.30.0-1             4.30.2-1
                        man-pages-es             4.30.0-1             4.30.2-1
                        man-pages-fi             4.30.0-1             4.30.2-1
                        man-pages-fr             4.30.0-1             4.30.2-1
                        man-pages-hu             4.30.0-1             4.30.2-1
                        man-pages-id             4.30.0-1             4.30.2-1
                        man-pages-it             4.30.0-1             4.30.2-1
                        man-pages-mk             4.30.0-1             4.30.2-1
                        man-pages-nb             4.30.0-1             4.30.2-1
                        man-pages-nl             4.30.0-1             4.30.2-1
                        man-pages-pl             4.30.0-1             4.30.2-1
                     man-pages-pt_br             4.30.0-1             4.30.2-1
                        man-pages-ro             4.30.0-1             4.30.2-1
                        man-pages-ru             4.30.0-1             4.30.2-1
                        man-pages-sr             4.30.0-1             4.30.2-1
                        man-pages-sv             4.30.0-1             4.30.2-1
                        man-pages-uk             4.30.0-1             4.30.2-1
                        man-pages-vi             4.30.0-1             4.30.2-1
                             mdfried             0.20.1-1             0.20.2-1
                         meilisearch           1:1.43.0-1           1:1.43.1-1
                             melange             0.50.2-1             0.50.6-1
                         mermaid-cli            11.14.0-1            11.15.0-1
                              minder             1.17.0-2              2.0.9-1
                           mitmproxy             12.2.1-2             12.2.3-1
                              mousai              0.7.9-2             0.7.10-1
                                 mpd            0.24.11-1            0.24.12-1
                              mqttui             0.22.1-1             0.23.0-1
                         mullvad-vpn             2026.1-1             2026.2-1
                  mullvad-vpn-daemon             2026.1-1             2026.2-1
               netfilter-fullconenat      r73.0cf3b48-517      r73.0cf3b48-518
                           newsflash              5.0.0-1              5.1.0-1
             nextcloud-app-bookmarks           1:16.1.3-1           1:16.1.4-1
                         nodejs-nopt              9.0.0-1             10.0.0-1
                                numa             0.17.0-1             0.18.0-1
                        nwg-displays              0.4.2-1              0.4.3-1
                           nwg-panel            0.10.13-2            0.10.14-1
                          obs-studio             32.1.2-2             32.1.2-3
           obs-studio-plugin-browser             32.1.2-2             32.1.2-3
                              ollama             0.23.2-1             0.23.3-1
                         ollama-cuda             0.23.2-1             0.23.3-1
                         ollama-docs             0.23.2-1             0.23.3-1
                         ollama-rocm             0.23.2-1             0.23.3-1
                       ollama-vulkan             0.23.2-1             0.23.3-1
                            opencode             1.15.0-1             1.15.3-1
                            openfire              5.0.4-1              5.0.5-1
                            openrct2              0.5.0-1              0.5.1-1
                            opensips              3.6.4-1              3.6.5-1
                             openvkl              2.0.1-5              2.0.2-1
                            pack-cli             0.40.4-1             0.40.6-1
                                perf              7.0.6-1              7.0.9-1
             perl-cpan-perl-releases         5.20260320-1         5.20260420-1
                          photoflare             1.6.13-2              1.7.0-1
                             postfix             3.11.2-1             3.11.3-1
                         postfix-cdb             3.11.2-1             3.11.3-1
                        postfix-ldap             3.11.2-1             3.11.3-1
                        postfix-lmdb             3.11.2-1             3.11.3-1
                     postfix-mongodb             3.11.2-1             3.11.3-1
                       postfix-mysql             3.11.2-1             3.11.3-1
                        postfix-pcre             3.11.2-1             3.11.3-1
                       postfix-pgsql             3.11.2-1             3.11.3-1
                      postfix-sqlite             3.11.2-1             3.11.3-1
           pycharm-community-edition           2026.1.1-1           2026.1.2-1
                         python-acme              5.5.0-1              5.6.0-1
                     python-archinfo            9.2.194-1            9.2.215-1
            python-astropy-iers-data 0.2025.9.8.0.36.17-2 0.2026.5.11.1.8.52-1
                        python-black             26.3.1-1             26.5.0-1
                   python-cachetools              7.1.1-1              7.1.2-1
                      python-claripy            9.2.197-1            9.2.215-1
                  python-cli_helpers             2.14.0-1             2.15.0-1
                   python-cloudflare             2.20.0-1              5.1.0-1
                     python-colorcet              3.1.0-4              3.2.1-1
            python-extension-helpers              1.2.0-3              1.4.0-1
                         python-flit             3.12.0-2              4.0.0-1
                       python-fsspec           2026.3.0-1           2026.4.0-1
                       python-genshi             0.7.10-3             0.7.11-1
                  python-iterable-io              1.0.1-2              1.0.4-1
                         python-krb5              0.5.1-5              0.9.0-1
python-magic-wormhole-mailbox-server              0.7.0-1              0.8.0-1
                       python-mpi4py              4.1.1-2              4.1.2-1
                          python-mss             10.1.0-2             10.2.0-1
                     python-narwhals             2.21.0-1             2.21.2-1
                 python-openstacksdk             4.12.0-1             4.13.0-1
                       python-owslib             0.34.1-2             0.35.0-1
                        python-param              2.1.1-4              2.3.3-1
                         python-pika              1.3.2-4              1.4.0-1
            python-py_stringmatching              0.4.6-2              0.4.7-1
                         python-pyct              0.5.0-5              0.6.0-1
                   python-pynitrokey             0.12.1-1             0.12.2-1
                    python-pyscipopt              6.2.0-1              6.2.1-1
                     python-pyspnego             0.11.0-1             0.12.1-1
               python-pytest-aiohttp              1.0.5-5              1.1.0-1
            python-pytest-dependency              0.6.0-4              0.6.1-1
                 python-pytest-order              1.3.0-2              1.4.0-1
                    python-pytest-qt              4.4.0-6              4.5.0-1
         python-pytest-rerunfailures               16.1-2               16.2-1
                      python-pytorch             2.11.0-4             2.12.0-1
                 python-pytorch-cuda             2.11.0-4             2.12.0-1
                  python-pytorch-opt             2.11.0-4             2.12.0-1
             python-pytorch-opt-cuda             2.11.0-4             2.12.0-1
             python-pytorch-opt-rocm             2.11.0-4             2.12.0-1
                 python-pytorch-rocm             2.11.0-4             2.12.0-1
        python-pyxdameraulevenshtein              1.8.0-3             1.10.1-1
                    python-qpageview              1.0.2-1              1.0.4-1
        python-recurring-ical-events              3.8.1-1              3.9.0-1
                   python-repoze.lru               0.7-13                0.8-1
                 python-scikit-build             0.18.1-6             0.19.0-1
                   python-sentry_sdk             2.59.0-1             2.60.0-1
           python-strawberry-graphql            0.315.4-1            0.315.5-1
                       python-syrupy              5.1.0-1              5.2.0-1
                      python-textual              8.2.5-1              8.2.6-1
                     python-tifffile           2026.5.2-1          2026.5.15-1
                   python-torchcodec             0.11.1-1             0.12.0-1
                  python-torchvision             0.26.0-1             0.27.0-1
             python-torchvision-cuda             0.26.0-1             0.27.0-1
                 python-zipstream-ng              1.9.0-2              1.9.2-1
                                 qsv             20.0.0-1             20.1.0-1
                           qwen-code            0.15.10-1            0.15.11-1
                              radcli              1.5.0-2              1.5.1-1
                            radicale             3.5.10-1              3.7.3-1
                             railway              2.9.4-2             2.10.0-1
                            ramalama             0.20.0-1             0.21.0-1
                               ratty              0.3.0-1              0.4.0-1
                              recoll            1.43.14-2            1.43.16-1
                     ruby-chef-utils             19.3.9-1            19.3.14-1
                               rumdl             0.1.91-1             0.1.93-1
                              scrcpy              3.3.4-1                4.0-1
                           sdbus-cpp              2.2.1-1              2.3.0-1
                       sdbus-cpp-doc              2.2.1-1              2.3.0-1
                          sdl2_mixer              2.8.1-2              2.8.2-1
                            sdl2_net            1:2.2.0-2            2:2.4.0-1
                          sdl3_mixer              3.2.0-2              3.2.2-1
                           seaweedfs               4.23-1               4.26-1
                       sentry-native             0.14.0-2             0.14.2-1
                           simutrans            124.3.1-1            124.4.1-1
                             slumber              5.2.5-1              5.3.0-1
                             songrec              0.7.2-1              0.7.3-1
                                sops             3.13.0-1             3.13.1-1
                              srslte             23.11-13              25.10-1
                         srslte-avx2             23.11-13              25.10-1
                              stylua              2.4.1-1              2.5.2-1
                           tailscale             1.96.4-2             1.98.2-1
                                tmon              7.0.6-1              7.0.9-1
                               tombi             0.11.4-1             0.11.5-1
                         torchvision             0.26.0-1             0.27.0-1
                    torchvision-cuda             0.26.0-1             0.27.0-1
                   translate-toolkit             3.19.7-1            3.19.10-1
                       ttf-mona-sans             2.0.24-1             2.0.25-1
                               turbo              2.9.6-1             2.9.14-1
                           turbostat              7.0.6-1              7.0.9-1
                                  ty             0.0.36-1             0.0.37-1
                               typos             1.46.1-1             1.46.2-1
                               ugrep              7.8.1-1              7.8.2-1
                               usbip              7.0.6-1              7.0.9-1
                                vale             3.14.1-1             3.14.2-1
                       video-trimmer              25.03-2              26.03-1
                                 vlc             3.0.22-3             3.0.22-4
                             vlc-cli             3.0.22-3             3.0.22-4
                     vlc-gui-ncurses             3.0.22-3             3.0.22-4
                          vlc-gui-qt             3.0.22-3             3.0.22-4
                      vlc-gui-skins2             3.0.22-3             3.0.22-4
                   vlc-plugin-a52dec             3.0.22-3             3.0.22-4
                    vlc-plugin-aalib             3.0.22-3             3.0.22-4
                     vlc-plugin-alsa             3.0.22-3             3.0.22-4
                      vlc-plugin-aom             3.0.22-3             3.0.22-4
                  vlc-plugin-archive             3.0.22-3             3.0.22-4
                  vlc-plugin-aribb24             3.0.22-3             3.0.22-4
                  vlc-plugin-aribb25             3.0.22-3             3.0.22-4
                      vlc-plugin-ass             3.0.22-3             3.0.22-4
                    vlc-plugin-avahi             3.0.22-3             3.0.22-4
                   vlc-plugin-bluray             3.0.22-3             3.0.22-4
                     vlc-plugin-caca             3.0.22-3             3.0.22-4
                     vlc-plugin-cddb             3.0.22-3             3.0.22-4
               vlc-plugin-chromecast             3.0.22-3             3.0.22-4
                    vlc-plugin-dav1d             3.0.22-3             3.0.22-4
                     vlc-plugin-dbus             3.0.22-3             3.0.22-4
         vlc-plugin-dbus-screensaver             3.0.22-3             3.0.22-4
                      vlc-plugin-dca             3.0.22-3             3.0.22-4
                      vlc-plugin-dvb             3.0.22-3             3.0.22-4
                      vlc-plugin-dvd             3.0.22-3             3.0.22-4
                    vlc-plugin-faad2             3.0.22-3             3.0.22-4
                   vlc-plugin-ffmpeg             3.0.22-3             3.0.22-4
                 vlc-plugin-firewire             3.0.22-3             3.0.22-4
                     vlc-plugin-flac             3.0.22-3             3.0.22-4
               vlc-plugin-fluidsynth             3.0.22-3             3.0.22-4
                 vlc-plugin-freetype             3.0.22-3             3.0.22-4
                      vlc-plugin-gme             3.0.22-3             3.0.22-4
                   vlc-plugin-gnutls             3.0.22-3             3.0.22-4
                vlc-plugin-gstreamer             3.0.22-3             3.0.22-4
                  vlc-plugin-inflate             3.0.22-3             3.0.22-4
                     vlc-plugin-jack             3.0.22-3             3.0.22-4
                  vlc-plugin-journal             3.0.22-3             3.0.22-4
                     vlc-plugin-jpeg             3.0.22-3             3.0.22-4
                     vlc-plugin-kate             3.0.22-3             3.0.22-4
                  vlc-plugin-kwallet             3.0.22-3             3.0.22-4
                vlc-plugin-libsecret             3.0.22-3             3.0.22-4
                     vlc-plugin-lirc             3.0.22-3             3.0.22-4
                  vlc-plugin-live555             3.0.22-3             3.0.22-4
                      vlc-plugin-lua             3.0.22-3             3.0.22-4
                      vlc-plugin-mad             3.0.22-3             3.0.22-4
                 vlc-plugin-matroska             3.0.22-3             3.0.22-4
                     vlc-plugin-mdns             3.0.22-3             3.0.22-4
                  vlc-plugin-modplug             3.0.22-3             3.0.22-4
                    vlc-plugin-mpeg2             3.0.22-3             3.0.22-4
                   vlc-plugin-mpg123             3.0.22-3             3.0.22-4
                      vlc-plugin-mtp             3.0.22-3             3.0.22-4
                 vlc-plugin-musepack             3.0.22-3             3.0.22-4
                      vlc-plugin-nfs             3.0.22-3             3.0.22-4
                   vlc-plugin-notify             3.0.22-3             3.0.22-4
                      vlc-plugin-ogg             3.0.22-3             3.0.22-4
                     vlc-plugin-opus             3.0.22-3             3.0.22-4
                      vlc-plugin-png             3.0.22-3             3.0.22-4
                    vlc-plugin-pulse             3.0.22-3             3.0.22-4
                vlc-plugin-quicksync             3.0.22-3             3.0.22-4
               vlc-plugin-samplerate             3.0.22-3             3.0.22-4
                      vlc-plugin-sdl             3.0.22-3             3.0.22-4
                     vlc-plugin-sftp             3.0.22-3             3.0.22-4
                    vlc-plugin-shout             3.0.22-3             3.0.22-4
                      vlc-plugin-smb             3.0.22-3             3.0.22-4
                     vlc-plugin-soxr             3.0.22-3             3.0.22-4
                    vlc-plugin-speex             3.0.22-3             3.0.22-4
                      vlc-plugin-srt             3.0.22-3             3.0.22-4
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                      vlc-plugin-tag             3.0.22-3             3.0.22-4
                   vlc-plugin-theora             3.0.22-3             3.0.22-4
                  vlc-plugin-twolame             3.0.22-3             3.0.22-4
                     vlc-plugin-udev             3.0.22-3             3.0.22-4
                     vlc-plugin-upnp             3.0.22-3             3.0.22-4
                   vlc-plugin-vorbis             3.0.22-3             3.0.22-4
                      vlc-plugin-vpx             3.0.22-3             3.0.22-4
                     vlc-plugin-x264             3.0.22-3             3.0.22-4
                     vlc-plugin-x265             3.0.22-3             3.0.22-4
                      vlc-plugin-xml             3.0.22-3             3.0.22-4
                     vlc-plugin-zvbi             3.0.22-3             3.0.22-4
                     vlc-plugins-all             3.0.22-3             3.0.22-4
                    vlc-plugins-base             3.0.22-3             3.0.22-4
                   vlc-plugins-extra             3.0.22-3             3.0.22-4
            vlc-plugins-video-output             3.0.22-3             3.0.22-4
           vlc-plugins-visualization             3.0.22-3             3.0.22-4
                         volatility3             2.27.0-2             2.28.0-1
                             vulscan                2.0-5                2.1-1
                              websvn              2.8.6-1              2.8.7-1
                                wike              3.2.0-2              3.2.1-1
                                wine               11.8-1               11.9-1
                        worker-build              0.8.1-1              0.8.3-1
              x86_energy_perf_policy              7.0.6-1              7.0.9-1
                               xonsh             0.23.6-1             0.23.7-1
                              zizmor             1.25.0-1             1.25.2-1
                              zypper            1.14.96-1            1.14.97-1
                                etcd                    -             3.6.11-2
    intel-oneapi-toolkit - 2026.0.0.198+71180075_e4e3_4c6f_bbbb_19017ed0cf7d-2
                        man-pages-ar                    -             4.30.2-1
                              onedpl                    -          2022.12.0-1


:: Different sync package(s) in repository multilib x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2026-05-16           2026-05-18
-------------------------------------------------------------------------------
                      lib32-fakeroot             1.37.2-1               1.38-1
                        lib32-giflib              5.2.2-1              6.1.3-1
                         lib32-libxi              1.8.2-1              1.8.3-1
                    lib32-sdl2_mixer              2.8.1-1              2.8.2-1

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CVE-2026-25847 | JetBrains PyCharm up to 2025.3.1 Jupyter Viewer Page cross site scripting

Thu, 19 Feb 2026 03:05:39 +0100

A vulnerability described as problematic has been identified in JetBrains PyCharm up to 2025.3.1. This issue affects some unknown processing of the component Jupyter Viewer Page. Executing a manipulation can lead to cross site scripting. This vulnerability is handled as CVE-2026-25847. The attack can be executed remotely. There is not any exploit available. Upgrading the affected component is recommended.

Macos user wants to switch

Sat, 14 Feb 2026 03:23:39 +0100

Hi, I am Butterly. I am a photographer, a backend developer, and a high school student.

I have recently tried arch at the request of my science fair mentor. I gave it a full week of developing. This summer I purchased a MacBook Air M4 and have liked it. I needed to move from Microslop, and Lightroom is not very stable on Windows 11 bla bla bla...

I have arch in my homelab on an i5 2400 with an SSD from a discarded computer from my school.

How can I get Arch for development on my macbook as RDP is impractical?

Also, my school laptop does not block port 3389 on the school network. So... maybe i can get Arch reliably over the network for using it at school. Any tips.

I have tried neovim and it seems not bad (moving from JetBrains PyCharm), and I want to keep trying.

generally arch seems fun, and I want to keep exploring.

Please give any tips. All is welcome.

submitted by /u/Vast_Butterfly_5092
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Frida UI tool window inside PyCharm : ZAFridaUI

Fri, 06 Feb 2026 18:36:00 +0100

submitted by /u/StockRip2949
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Linux saved my laptop

Sat, 06 Dec 2025 02:36:13 +0100

I have a ThinkPad T480s that was running windows 10 which was pretty much for learning, getting certifications , some coding and pretty much light stuff. I wanted to do a project which included running code on Pycharm and using android studio to open a virtual android device. My laptop just couldn't take it, it was getting hot like crazy, stuttering all over, I could barley make it run. I was very close to just buy a new one and then I thought to try Linux Mint after some documentation.

Oh man, my fans are barely running now even when I am fully loaded for my project. It runs like a brand new pc. I was expecting to be better, but not that good. Thank you Linux!

submitted by /u/sugardadddyy
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How big tech is creating its own friendly media bubble to ‘win the narrative battle online’

Mon, 01 Dec 2025 09:32:18 +0100

At a time when distrust of big tech is high, Silicon Valley is embracing an alternative ecosystem where every CEO is a star

A montage of Palantir’s CEO, Alex Karp, and waving US flags set to a remix of AC/DC’s Thunderstruck blasts out as the intro for the tech billionaire’s interview with Sourcery, a YouTube show presented by the digital finance platform Brex. Over the course of a friendly walk through the company offices, Karp fields no questions about Palantir’s controversial ties to ICE but instead extolls the company’s virtues, brandishes a sword and discusses how he exhumed the remains of his childhood dog Rosita to rebury them near his current home.

“That’s really sweet,” host Molly O’Shea tells Karp.

I think I understand now…

Mon, 22 Sep 2025 07:51:37 +0200

Firstly, I had no clue where to post this. Given the root of this story is Linux, it felt fitting. If it needs to be taken down for not following the rules, I totally understand.

Secondly, for context; I’ve been a windows user my entire life. If I think back hard enough, I can recall messing with DOS on my father’s PC as a kid. Carried the OS with me as I went through life, we tend to stick to what we know best, right?

Up until recently, I had only held professions that required limited computer savvy. Minimal administrative task, browser based apps, email, CMS. All of those businesses also using windows, so the battle of the OSs was something I’d see in threads and hear discussed amongst friends in tech, but I never bothered to try another OS. Had no need to. I had windows, for both personal and professional use. Although, there was an underlying curiosity and I always wanted to learn more about computers, stemming from becoming a technophile early on in life.

With my new profession being tech-centric (primarily in networking), I had to brush up on my skills and crash course a few unfamiliar practices. I crammed as much YT content I could prior to the second round of interviews. In my internet-based studies, there would always be a thumbnail with a pudgy little penguin starring at me, taunting me, somewhere in my feed.

One night, I had finished a video on subnet masking, brain half mush, and there it was again. The penguin. We starred at each other for a moment. Then, I clicked.

After that initial video, (a “How-To Arch Linux” tutorial) I went down a rabbit hole. I had too many questions. What is Linux? What is a distro? Which is the best? That snowballed into putting mint cinnamon on an old laptop, figuring out package management, what the hell is a bash? The snowball grew. And grew.

The image above is less than impressive, but it does capture the culmination of the enthusiasm I have for this rediscovered passion very well. That’s my monitor displaying the text editor I “wrote” in pycharm (Look, I’m not proud of it, but you have to start somewhere. I generated the code from gpt, but keyed it in manually to get hands on practice understanding code in python) running out of bash in Ubuntu that is running in a vm on my windows pc. Nothing special, but that’s part of my point.

If it wasn’t for that penguin, this journey would have never begun. I would have sat comfortably on an OS that took all the fun out of the equation, never leaving my comfort zone and likely would have never found the motivation to start tinkering and troubleshooting. Discovering linux changed that. I, undoubtedly, know I that have a long way to go, so much more to learn. Although, I think that long road ahead is what excites me the most.

TL:DR Linux inspired me to rekindle my love for computers and I’m stoked to continue learning

submitted by /u/outwardape
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Im a student and planning on switching to Linux. Is that possible?

Sun, 31 Aug 2025 04:06:12 +0200

I mostly use my laptop for office stuff, google meet, zoom and and learning coding (codeblocks and/or pycharm/VSC). Im totally fine with using terminal and Libreoffice but Im just not sure if there are any difficulties except gaming? Besides, which distro should I start with? Im planning to use Linux Mint since it seems similar to windows and the terminal stuff is quite similar to Ubuntu (which I once tried on VM)

submitted by /u/peterth1
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The State of Python 2025

Mon, 18 Aug 2025 23:07:00 +0200

The JetBrains blog presents the results of the eighth annual Python Developers Survey, carried out in partnership with the Python Software Foundation.

This year, 51% of all surveyed Python developers are involved in data exploration and processing, with pandas and NumPy being the tools most commonly used for this.
Many of us in the Python pundit space have talked about Python as being divided into thirds: One-third web development, one-third data science and pure science, and one-third as a catch-all bin.
We need to rethink that positioning now that one of those thirds is overwhelmingly the most significant portion of Python.

10 Best AI Software for Mac in 2025

Mon, 18 Aug 2025 19:21:13 +0200

We tested dozens of AI tools on our MacBook to find the very best. Our list covers a variety of AI-powered applications that run great on macOS – from writing assistants and coding copilots to art generators and productivity boosters. Each pick below runs smoothly on Mac (many are optimized for Apple’s M1/M2 chips) and brings powerful AI features to your desktop. We focused on apps that are either native to macOS or have excellent Mac compatibility (including web apps), and we made sure to include both free options and premium offerings. In this roundup, you’ll find AI software for writing, coding, art creation, automation, voice/video editing, image editing, productivity, and personal assistance. We explain what each tool does, how it works on Mac, its key AI features, pros and cons, and pricing. We made this list by hands-on testing across a range of use cases, so you can trust these are the top performers. Table of contentsOur Picks for the Best AI Apps on Mac1. OpenAI ChatGPT (Desktop & Web)2. Jasper AI3. Grammarly (with GrammarlyGO)4. GitHub Copilot (AI Coding Assistant)5. Midjourney (AI Art Generator via Web/Discord)6. DiffusionBee (Stable Diffusion for Mac, Offline)7. Pixelmator Pro8. Descript9. Notion AI10. Raycast (with AI Assistant)Frequently Asked Questions (FAQ)Comparison Table of Top Mac AI Software Our Picks for the Best AI Apps on Mac Below are our top AI-powered apps for macOS users. Each tool has something unique to offer, but all of them can supercharge your Mac experience in different ways. 1. OpenAI ChatGPT (Desktop & Web) Overview: ChatGPT is a conversational AI assistant that can help with just about anything – writing content, answering questions, brainstorming ideas, coding help, you name it. While originally accessed via web, OpenAI now offers an official ChatGPT for Mac desktop app that feels right at home on macOS. We love how it lets us quickly summon ChatGPT from any screen (using a shortcut) and even search our past conversations. ChatGPT on Mac can be your personal writing coach, research assistant, or coding buddy all in one. macOS Compatibility: The ChatGPT desktop app is a native Mac app built for macOS (released in mid-2024). It runs on macOS 12+ and is optimized for Apple Silicon, so it’s fast and efficient. You can also use ChatGPT through any browser on Mac. The desktop version adds Mac-specific perks like a menu bar icon and the Option+Space shortcut to ask questions about anything on your screen. It syncs your chats across devices via your OpenAI account. Core AI Features: ChatGPT uses OpenAI’s powerful GPT-4 language model (for Plus users) to generate detailed, human-like responses. On Mac, it’s fantastic for drafting essays, composing emails, writing code or debugging, summarizing documents, and providing general knowledge Q&A. You can upload documents in the app and get summaries or explanations. It supports voice input and can even interpret images (with GPT-4 Vision if you have access). Essentially, it’s like having an extremely knowledgeable personal assistant on your Mac that you can chat with naturally. Pros and Cons: Pros: Extremely versatile conversational AI; easy native app with system-wide shortcut; syncs history across devices; no technical skill needed. Great for creative brainstorming, quick research, and coding assistance in one tool. Free tier available for basic use. Cons: The most powerful features (like GPT-4 model access, faster responses) require a subscription. It may occasionally struggle with very recent or specialized queries. Also, heavy use can drain battery a bit on laptops (the app is essentially a web wrapper, so similar to having a browser open). Pricing: ChatGPT offers a free plan that anyone can use with some limitations (uses the older GPT-3.5 model and slower responses). For advanced features, ChatGPT Plus is $20/month – this unlocks GPT-4, faster response times, and priority access. There is also a ChatGPT Enterprise (and a rumored Pro plan around $200/month for high-volume users), but for most individuals the free or $20 plan will suffice. The Mac app itself is free to download; you just log in with your plan. 2. Jasper AI Overview: Jasper is an AI content creation powerhouse popular among writers, marketers, and creatives. We found Jasper incredibly useful for generating blog posts, marketing copy, social media content, and more with minimal effort. It’s a cloud-based tool (web app) with a clean interface that runs well on Mac browsers. Jasper comes loaded with templates and recipes for different writing tasks – from long-form articles to Facebook ad text – making it easy to get started. Simply describe what you need, and Jasper will produce intelligent drafts and ideas. macOS Compatibility: Jasper does not have a native Mac app, but its web platform works flawlessly on macOS in Safari, Chrome, or any browser. There’s also a Chrome extension that integrates Jasper into Gmail, Google Docs, etc., which Mac users can leverage. Performance is smooth on M1/M2 Macs, and you can use Jasper alongside other Mac writing apps without issues (we often have Jasper open in one desktop Space and our text editor in another for a nice workflow). Core AI Features: At its heart, Jasper uses GPT-4 and other models, fine-tuned for content marketing use cases. Key features include an AI document editor (Jasper Chat) where you can interact with the AI to refine content, over 50 copywriting templates (for blog introductions, product descriptions, press releases, SEO meta tags, and so on), and a brand voice feature to tailor the writing style. Jasper can generate ideas when you’re staring at a blank page, help rewrite or expand existing text, and even create AI art (it has a built-in image generation tool). It’s like an all-in-one creative studio powered by AI. Pros and Cons: Pros: Excellent for marketers and writers – saves tons of time on drafting blogs, ads, emails; lots of ready-made templates; supports collaboration (team features) and multi-language content. The outputs are generally high quality and can match a desired tone or style. Jasper’s interface is user-friendly for non-techies. Cons: Jasper is a premium product, so it’s not cheap – no free tier beyond a short trial. You’ll need a subscription to use it regularly. Also, because it’s oriented toward business content, very creative writers (like novelists) might find it a bit constrained unless you use the free-form mode. As a web app, it requires internet access and doesn’t work offline. Pricing: Jasper recently updated its plans. For individuals, the Pro plan is about $69/month (or $59/month billed annually). This includes unlimited AI generations and the core features. They also offer custom Business plans for teams with more advanced control. There’s no unlimited free plan – but Jasper does offer a free trial period (usually 7 days or so) to test it out. It’s one of the pricier tools, but many content professionals find the time saved worth it. 3. Grammarly (with GrammarlyGO) Overview: Grammarly is well-known as an AI-powered writing assistant that helps improve your writing in real time. It’s like having a smart proofreader and editor integrated into your Mac. We included Grammarly because it addresses a different need than generative AI – it fixes grammar, spelling, and clarity, and now with the new GrammarlyGO feature, it can also rewrite and generate text based on your prompts. If you do any writing on your Mac (essays, emails, reports), Grammarly can be a lifesaver for polishing your text and ensuring professional tone. macOS Compatibility: Grammarly offers a native Mac app and menu bar tool, plus browser extensions and integrations. On Mac, you can use Grammarly for Safari/Chrome to get suggestions in web-based editors, or the Grammarly Desktop app which works in apps like Microsoft Word, Pages, Mail, etc. It runs natively on Apple Silicon Macs with no issues. We like that it’s essentially always running in the background checking our writing across apps. The performance is light and it doesn’t slow down your Mac. Core AI Features: Grammarly’s AI continuously checks your text for grammar errors, spelling mistakes, punctuation, and style issues. It provides suggestions in-line that you can accept with a click. Beyond basic corrections, it gives feedback on conciseness, clarity, tone, and even plagiarism detection. The GrammarlyGO feature (for Premium users) adds generative AI capabilities – you can ask it to rewrite a sentence for tone or brevity, continue a piece of text, brainstorm ideas, or even draft a reply to an email based on context. Essentially, GrammarlyGO brings some of the creativity of GPT into the Grammarly interface to help you compose text, not just correct it. Pros and Cons: Pros: Seamless integration on Mac for real-time writing feedback; catches typos and grammar mistakes that Mac’s built-in checker might miss; suggestions for tone and clarity make your writing stronger. The new generative features can help overcome writer’s block. There’s a free plan that covers basic grammar/spell check, which is very useful on its own. Cons: Advanced features require Grammarly Premium subscription, which can be around $12–$30 per month depending on plan. The generative AI (GrammarlyGO) has usage limits even on premium plans. Also, Grammarly needs internet access to work (since it processes text on their servers), which could be a privacy consideration for very sensitive writing – though they do have enterprise options with higher privacy. In rare cases, Grammarly suggestions might not understand nuanced context and you’ll need to use your judgment. Pricing: Grammarly has a free tier that offers basic spelling and grammar correction – great for casual users. Premium plans (which add style improvements, advanced checks, and GrammarlyGO features) start at around $12/month if paid annually (or ~$30 month-to-month). They also have Business plans for teams. If you just need solid proofreading on your Mac, the free version might suffice, but power users will benefit from Premium’s AI rewriting and advanced tonality checks. 4. GitHub Copilot (AI Coding Assistant) Overview: GitHub Copilot is an AI pair programmer that lives inside your code editor. For Mac-based developers, Copilot can dramatically speed up coding by autocompleting lines or even entire functions using AI. We tested Copilot in VS Code on Mac and were amazed as it suggested code in real-time as we typed, often correctly predicting our intentions. It supports a variety of languages (Python, JavaScript, Swift, C++, etc.) and can generate code snippets, help with algorithms, or even explain code. If you do coding on a Mac, Copilot is a game-changer for productivity. macOS Compatibility: Copilot integrates with popular IDEs/editors that run on Mac, including Visual Studio Code, JetBrains IDEs (WebStorm, PyCharm, etc.), Neovim, and even Xcode via unofficial plugins. On our MacBook Air M2, Copilot ran smoothly in VS Code (which itself has an Apple Silicon optimized version). There’s no separate Copilot app to install – you just install the extension in your editor and sign in with GitHub. One thing to note: Microsoft also announced a standalone “Copilot” Windows app, but on macOS this isn’t needed since integration is via editors. All features (including the new Copilot Chat) are available on Mac IDEs. Core AI Features: Copilot uses OpenAI’s Codex model to suggest code as you write. Start typing a function, and Copilot will try to complete it. You can also write a comment describing what you want (e.g., “// function to sort an array of integers”) and Copilot will generate the function code below. It’s trained on a vast dataset of code, so it can often produce standard boilerplate or even complex logic in one go. Recently, GitHub added Copilot Chat, which lets you chat with the AI about your code inside the editor – you can ask for explanation of a piece of code, or get help fixing a bug. It also has Copilot CLI for command-line suggestions, and can help write unit tests or documentation comments. All these make it feel like an AI programmer is collaborating with you. Pros and Cons: Pros: Deeply integrated into coding workflow – feels like magic autocomplete for code; supports many languages and frameworks; saves time on routine code and helps learn by example. Copilot’s suggestions are context-aware, looking at your project and comments. It can even suggest edge cases you might forget. For Mac developers, it works in all major editors. Cons: Not free (after trial). Copilot can sometimes generate code with errors or insecure practices, so you still must review and test everything – it’s not infallible. It also might not handle very unique or project-specific code well since it leans on common patterns. Additionally, there are occasional latency lags when your internet is slow, as it calls the AI API. Copilot’s training on public code raised some license compliance questions (be mindful if it suggests large chunks of verbatim code you don’t understand). Pricing: GitHub Copilot is a subscription service. Individuals can use Copilot for free trial (about 1 month). After that, it costs $10 per month or $100 per year for Copilot Pro. This gets you unlimited code completions and chat. There is also a Copilot Pro+ ($39/month) with larger context window and some advanced features, and a Business plan at $19/user/month for organizations. Students and open-source maintainers may get Copilot free. Considering how much time it can save, many developers find the $10/mo well worth it. 5. Midjourney (AI Art Generator via Web/Discord) Image credit: AiTuts Overview: Midjourney is one of the best AI art generators and it works great on Mac through its web and Discord interface. We’ve used Midjourney to create stunning images and artwork by simply describing what we want in text prompts. The image quality and creativity of Midjourney’s AI model are top-notch – often producing results that look like professional illustrations or photographs. Mac users can access Midjourney by joining the Midjourney Discord server or using their web beta. It’s a cloud-based tool, so all the heavy image generation happens on Midjourney’s servers (no stress on your Mac’s hardware). If you’re into digital art, graphic design, or just need images for projects, Midjourney is a must-try. macOS Compatibility: There is no native Midjourney app, but you use it via Discord on macOS. This means you can either install the Discord app (which has an Apple Silicon version so it runs efficiently) or use Discord web in Safari/Chrome. On our Mac, the Discord app with Midjourney is smooth – you enter a text command (/imagine) with your prompt and the AI generates the image. They also have a newer web interface that works in browser for managing your creations. Midjourney doesn’t utilize your Mac’s GPU/CPU at all for generation, so even an older Intel Mac can use it just as well – all you need is internet. Core AI Features: Midjourney’s primary feature is text-to-image generation. You type a description of an image (the more detailed, the better) and the AI model generates four image variations. You can then upscale any of them to full quality or ask for more variations. The model (currently Midjourney v5.x) excels at artistic styles, lighting, and detailed scenes. It can create everything from realistic landscapes and portraits to fantasy art or logo concepts. Midjourney also allows some image-to-image prompting – you can feed it an existing image to influence the style or content of the result. For Mac users, another benefit is that Midjourney can serve as an AI design assistant, giving you quick concept visuals that you can then refine in Photoshop or other Mac graphics software. Pros and Cons: Pros: Arguably best-in-class image quality among AI generators; easy to use through Discord; no local setup required; huge community sharing prompt ideas. It’s fantastic for visual brainstorming or getting custom graphics when you don’t have illustration skills. Works on any Mac since computation is cloud-based. Cons: Not free beyond a limited trial – requires a subscription for continued use. Working via Discord chat might feel odd or less user-friendly to some (though the web interface is improving). There are also content rules (no explicit or certain banned content in prompts). Since it’s cloud, you need internet and can’t use it offline. Finally, AI art can sometimes produce weird artifacts or need many tries to get exactly what you envision, so it’s a bit of trial and error. Pricing: Midjourney offers a few subscription tiers. The Basic Plan is $10/month which gives roughly 3.3 hours of fast generation time (plenty for casual use). The Standard Plan is $30/month and offers 15 hours fast generation + unlimited relaxed generations (slower queue), which is a sweet spot for most enthusiasts. There’s also a Pro Plan at $60/month with 30 hours and some perks, and even a Mega plan for enterprise. There’s usually a short free trial (about 25 image generations) so you can test it out. The paid plans are monthly and you can cancel anytime. For the quality of images Midjourney produces, many designers find the $10–30 very reasonable. 6. DiffusionBee (Stable Diffusion for Mac, Offline) Overview: DiffusionBee is a fantastic free AI art generator app that runs locally on your Mac. It brings Stable Diffusion (an open-source image generation model) to macOS in a user-friendly package. We love DiffusionBee for quick offline image generation – no internet needed and everything stays on your device. With DiffusionBee, you can create AI art, enhance or modify images, and even generate videos, all on your Mac’s hardware. It’s perfect for those who want to experiment with AI art privately or have unlimited generations without a subscription. macOS Compatibility: DiffusionBee is built exclusively for macOS and is optimized for Apple Silicon chips. In fact, the app was designed with M1/M2 Macs in mind – it runs much faster on Apple Neural Engine and GPU. (It does work on Intel Macs too, but much more slowly.) You’ll need macOS 13.1 or later to run DiffusionBee. In our testing on an M1 Pro Mac, DiffusionBee installed easily (just a drag-and-drop app) and ran completely offline. Generating a typical 512x512 image took around 10–20 seconds on our machine, which is impressive for local AI. It uses about 4–6 GB of RAM when running. No extra drivers or command-line work needed – it’s a one-click installer. Core AI Features: DiffusionBee provides a suite of creative AI tools: Text-to-Image: Type a prompt to generate an image (using Stable Diffusion models). Image-to-Image: Supply an input image and a prompt to transform the image in various ways. Generative Fill: Select part of an image and have the AI fill it (similar to content-aware fill, but AI-driven – great for adding/removing objects). Image Upscaler: Enhance and upsize images using AI to preserve quality. Variants and Control: Generate variations of an image, and use “control images” to guide the AI on composition. Video Tools: It even has experimental features to generate short AI animation or apply AI on video frames. Train Models: Advanced users can train custom Stable Diffusion models on their own data directly in the app. All these features run locally. The AI model runs fully on your Mac, no cloud involved, so your images and prompts stay private. DiffusionBee essentially turns your Mac into a creative AI studio. Pros and Cons: Pros: 100% free and offline – no credits or fees, generate as much art as you want. Great performance on M1/M2 Macs thanks to Apple Silicon optimization. Wide range of features (it’s not just text-to-image, but also editing and upscaling). Privacy and control – everything stays on your Mac. Ideal for artists who want to use AI but not be cloud-dependent. Cons: Stable Diffusion’s image quality, while good, is generally a notch below Midjourney’s latest – so results may require more prompt tweaking. The app’s interface, while straightforward, can be a bit basic and occasionally buggy since it’s evolving. It also eats up disk space because the AI models are large (each model can be a few GB). Generation is slower compared to cloud services with powerful GPUs – e.g., an image might take ~30 seconds on a MacBook Air M1 (still, that’s not bad!). Also, if you have an older Intel Mac without a strong GPU, expect very slow generation times. Pricing: DiffusionBee is completely free. It’s open-source, and there are no premium tiers. You can download it from the official site or GitHub and start using without any sign-up. This makes it a compelling choice for hobbyists or students who don’t want to pay for Midjourney or DALL-E credits. Just remember to have sufficient storage and a relatively recent Mac to get the best experience. 7. Pixelmator Pro Overview: Pixelmator Pro is a powerful image editing and graphic design app for Mac that has embraced AI to simplify complex edits. If you need Photoshop-like capabilities on Mac with some AI magic, Pixelmator Pro is for you. We’ve been impressed by its machine learning tools for tasks like automatically removing backgrounds, upscaling images, enhancing photos, and even a new feature that generates imagery and text using AI. The app feels fully at home on macOS (it’s Mac-only) and is known for being user-friendly. With Pixelmator Pro, even non-designers can achieve pro-looking results quickly, thanks to AI assistance. macOS Compatibility: Pixelmator Pro was designed exclusively for Mac and it shows. It runs natively on Apple Silicon and is highly optimized for Metal and Core ML, leveraging the Neural Engine for speed. In fact, it was one of the first apps to update for M1 support. Whether you’re on an M2 MacBook or an older Intel iMac, Pixelmator Pro runs smoothly (though AI features are faster on M1/M2). It supports the latest macOS features like Dark Mode, Split View, AppleScript, and even has Shortcuts integration. You can download it from the Mac App Store. We appreciate that it’s a native app – it launches fast and doesn’t require an internet connection for most features (except the new AI Compose which uses ChatGPT for text generation). Core AI Features: Pixelmator Pro has a suite of “ML” tools (machine learning) built-in: ML Enhance: One-click automatic enhancement of photos (adjusts colors, exposure, etc. using trained models). ML Super Resolution: Upscales images intelligently to increase resolution without losing detail. Great for making a low-res image sharper. ML Denoise and Deband: Cleans up noise or color banding artifacts in photos. ML Match Colors: Can make one image adopt the color palette of another. Background Removal: With a click, remove the background from an image (e.g., isolate the subject) using AI object recognition. Repair Tool: Magically remove unwanted objects or blemishes from photos – the AI fills in the area naturally. Image Playground (New): An AI image generator integrated into Pixelmator (released in 2025) that lets you create new images from a prompt or transform layers in various art styles. This uses on-device “Apple Intelligence” for image generation. Writing Tools (New): AI-powered text assistant that can proofread, summarize, or rewrite text in your designs, and even generate original text via ChatGPT integration – useful for things like creating lorem ipsum or getting copy ideas for a poster. Beyond AI features, Pixelmator Pro is a full-fledged editor with layering, vector tools, painting, effects, etc., so you can fine-tune the AI results. Pros and Cons: Pros: Fully native Mac app with smooth performance; one-time purchase (no subscription); a wide range of AI features that drastically cut down editing time (background removal and upscaling work impressively well). It’s beginner-friendly with templates and an intuitive interface, yet powerful enough for advanced edits. Integrates well with macOS (e.g., you can use it in Photos app extensions). And because most features run locally with Core ML, no internet or uploading images needed. Cons: It’s Mac-only (not a con for us, but Windows users can’t use it). Advanced Photoshop users might find some specific pro features missing (though Pixelmator Pro covers most needs). The AI-generated content features are newer – for example, the Image Playground generation may not be as advanced as Midjourney, and it requires a newer MacOS (Sequoia) and specific hardware support. Also, while the interface is clean, it can take a little time for completely new users to learn all the tools available. Pricing: Pixelmator Pro is a paid app but very affordable compared to Adobe apps. It costs a one-time fee of $49.99 on the Mac App Store, and you own it forever (all the major updates for the past few years have been free). There’s a free 15-day trial available on their website if you want to test it. No subscription required, which is a big plus in our book. Considering it packs in photo editing, graphic design, and AI tools in one, it’s great value. 8. Descript Overview: Descript is an AI-powered audio and video editing application that’s incredibly popular among podcasters, video creators, and anyone who works with voice recordings. We included Descript because it uses AI in unique ways: it can transcribe audio to text with high accuracy, allow you to edit the audio by editing the text transcript, remove filler words and noise automatically, and even clone your voice for overdubs. On Mac, Descript provided us a revolutionary way to edit videos – it’s like editing a Word document. If you create content (like YouTube videos, podcasts, tutorials) on your Mac, Descript can streamline your workflow big time with its AI features. macOS Compatibility: Descript has a native Mac app (downloadable from their site) and it runs on macOS 13 (Ventura) or later. It fully supports Apple Silicon Macs – in fact, Descript added native M1 support which made it much faster for exporting and processing. We’ve run it on an M2 MacBook Pro and it’s smooth, especially for transcription and basic edits. Some heavy AI tasks (like voice synthesis) might take a little processing time, but nothing too bad. The UI is very Mac-like and they update it frequently. It does require an internet connection for some AI features (e.g., the transcript is done via cloud AI, and the voice cloning uses their server), but basic editing can be done offline once media is transcribed. Core AI Features: Descript’s headline feature is text-based editing: it will automatically transcribe your audio/video into text with AI (pretty accurate, thanks to their use of a powerful transcription model). You can then edit the transcript – delete a sentence or word – and it will cut the corresponding audio/video. It’s mind-blowing to cut out “ums” and tangents just by editing text. Key AI features include: Overdub (AI Voice Cloning): Descript can create a clone of your voice (you provide a training recording) and then you can generate new voiceover just by typing text. If you forgot to say a word in a recording, just type it in – Descript will produce that word in your voice seamlessly. Studio Sound: An AI noise reduction and enhancement that makes your audio sound like it was recorded in a studio. It removes background noise and evens out voices. Remove Filler Words: With one click, find and remove all “um”, “uh”, and similar fillers from the audio. Dialogue Editing and Speaker Detection: It identifies different speakers in your recording and labels them. You can easily delete or tighten gaps in conversation. AI Video Tools: New features like AI green screen (remove or blur background without a physical green screen), AI eye contact (make it look like the speaker is looking at camera), and even generate short video clips or social posts from a longer video using AI. Transcription & Search: All transcripts are searchable, so you can search your recordings for a word and instantly find the spot in the video. Descript basically combines transcription, audio editing, and some video editing, with AI at the core. Pros and Cons: Pros: Hugely simplifies the editing process – edit videos by editing text! Overdub is amazingly useful for quick fixes or adding narration. The transcription is fast and pretty accurate, turning hours of audio into text in minutes. Great for collaboration as well (you can share projects and text scripts). Descript’s interface is friendly even for non-editors. They also have a free tier to get started. Cons: Descript does a lot, so it can feel a bit heavy compared to a simple editor. The free plan has limitations (like transcript hours per month, watermark on videos). For long-form or highly precise video editing, you might still need to round-trip to Premiere or Final Cut for polish. AI voice cloning requires clear training audio and, ethically, you should only clone your own voice. Some features like video generation or fancy AI avatars are newer and can be hit-or-miss. Also, processing long recordings can tax your Mac (it’s doing AI work, after all), though cloud offloading helps. Pricing: Descript has a Free plan with limited usage (e.g. 1 hour of transcription per month, 720p video export with watermark, and limited use of some AI tools). Paid plans remove these limits: the Hobbyist plan is $16 per month (billed annually), which gives 10 hours transcription, 1080p export, some AI usage like filler removal and basic Overdub. The Creator plan is $24/month (annual) with 30 hours transcription and unlimited use of most AI features. There’s also a Pro plan ($30/mo) and Enterprise. Essentially, for most individual creators, ~$16-24 a month unlocks the really useful stuff, and we’ve found that to be a good value given how much time it saves in editing and cleanup. 9. Notion AI Overview: Notion AI adds a powerful generative AI assistant into Notion, the popular all-in-one workspace app. We love Notion on Mac for organizing notes, documents, tasks, and wikis – and with Notion’s AI features, it can now help brainstorm ideas, summarize long notes, draft content, and even answer questions from your notes. Imagine having a research assistant and copywriter inside your notes app. Using Notion AI on our Mac, we were able to outline articles, generate meeting agendas, and get summaries of meeting notes with ease. It’s a huge productivity booster for knowledge work. macOS Compatibility: Notion runs on Mac either via the Notion desktop app (which is an optimized Electron app) or in a web browser. The desktop app works fine on Apple Silicon Macs; it’s not a heavy app. Notion AI features are integrated into the app – just hit Space or click the “Ask AI” button in any page. Performance is good, though responses take a second since it’s querying their cloud AI (needs internet). As of 2025, ensure your Notion app is updated to access the AI features. We did find that you need a certain plan (Business plan or AI add-on) for full access, which is a consideration (more on pricing below). Core AI Features: Notion AI is like an AI assistant that understands the context of your Notion pages and databases. Key capabilities include: Text Generation & Brainstorming: In any Notion page, you can ask the AI to generate content – for example, “Draft a blog post about Mac productivity” and it will create an outline or even paragraphs. Great for overcoming writer’s block. Brainstorm ideas, get list of pros/cons, or ask for suggestions right within your notes. Summarization: You can have Notion AI summarize a long page of notes or extract action items. We used this on meeting notes to get the key points quickly. It can summarize highlights of a research doc, or give you a TL;DR of a lengthy article you paste in. Translation & Tone Rewrite: It can translate text between languages or rewrite text in a different tone (e.g., make a paragraph more casual or more professional). Useful for polishing writing. Q&A on Your Notes: Perhaps the most powerful – you can ask questions about your content. For example, “What is the status of Project X?” and if you have that info in your workspace, it will try to answer from your pages. It’s like a personal knowledge base query. Automating Databases: Notion AI can fill in fields or generate content for database entries (like writing a task description from a title, etc.). And Notion is adding AI properties that can automatically update. Coding and Diagrams: It can generate snippets of code or even Mermaid diagrams if you ask (though it’s not as specialized as Copilot or a real IDE for code). All these features are invoked through a simple command prompt in Notion. It uses a combination of OpenAI GPT-4 and Anthropic Claude under the hood, with Notion’s own context awareness (it knows your workspace structure for better answers). Pros and Cons: Pros: Native part of your note-taking workflow – no need to switch to ChatGPT for many tasks. Saves time in writing and summarizing content – extremely handy for meeting notes, documentation, and ideation. Contextual awareness means it can be more relevant to your info (e.g., summarizing your notes rather than generic). Notion itself is a great Mac app for organization, and AI makes it even better. Cons: Notion AI is no longer available on the free or cheap plans – they moved it to higher-tier plans, which is a downside. That means to use it extensively, you might need a Business plan ($15-20/month user) or an add-on fee. Also, for very recent info outside your notes, it won’t know (it’s not connected to the internet like Bing; it only knows what’s in its training or in your workspace). Some generated content can be generic, so you’ll usually refine it. Finally, heavy users might hit limits (Notion AI originally had a cap of responses per member, which can be extended on business plans). Pricing: Notion AI used to be an add-on ($10/month) for Plus plans, but as of 2025 it’s included only in Business and Enterprise plans. Essentially, new Free or Plus users do not have access to Notion AI beyond maybe a trial.The Business plan is about $15 per user per month (annual billing) which includes Notion AI and other advanced features. This is a bit of a bummer for personal users on a budget. However, if you’re already using Notion for work or a team, upgrading for AI might be justified. We hope Notion brings back a personal AI plan, but for now, budget-conscious users might stick to copying text into ChatGPT as a workaround. For those who do opt in, Notion AI can genuinely save hours of work each week in summarizing and content creation. 10. Raycast (with AI Assistant) Overview: Raycast is a productivity booster for Mac – essentially a supercharged app launcher and automation tool – and its latest addition is Raycast AI, an AI assistant integrated right into macOS. We included Raycast because it uniquely combines system-level automation with AI: you can open Raycast with a hotkey and ask the AI anything (like you would with ChatGPT), or use it to control your Mac with natural language. For example, we can hit Cmd+Space (Raycast’s shortcut), ask “Search my files for budget report” or “Summarize the text in my clipboard”, and the AI will do it. Raycast AI brings the power of GPT-4 (and many other models) to your fingertips without even opening a browser. It truly makes your Mac feel smarter and more personalized. macOS Compatibility: Raycast is a native Mac application (built as a replacement for Spotlight/Alfred). It runs on macOS 11 Big Sur and above. It’s optimized for Apple Silicon, so it’s fast and low on resource usage. We tested the AI features on an M1 MacBook and they worked flawlessly – responses appear in the Raycast window in seconds. Raycast integrates deeply: it can use Mac’s clipboard, launch apps, run scripts, etc., so the AI can interact with your OS. Note: To use Raycast’s AI, you need to log in to a Raycast account and have the Pro subscription enabled. It requires internet to query the AI models. Core AI Features: Raycast’s AI is essentially an AI chatbot plus Mac automation: AI Command Bar: Hit the hotkey and just start asking anything – it’s like a Spotlight search, but for AI answers. It can do general knowledge Q&A, draft text, or even write code snippets, just like ChatGPT. The twist is it’s always one keyboard shortcut away, anywhere on your Mac. Contextual Actions: Raycast can feed in context such as your clipboard content. For example, copy some text from a document, then trigger Raycast AI and ask “Summarize the clipboard text” – it will know to summarize what you copied. Or select a file and use a Raycast command to have the AI analyze it (for example, summarize a PDF’s text). Multiple AI Models: Raycast supports various models and providers. By default, it gives you a certain number of GPT-4 or other advanced model queries on Pro, and you can also plug in your own API keys if you want. This means you can access models like Claude, or even community models, through the same interface. Natural Language Mac Actions: You can type commands like “Toggle Dark Mode” or “Play some music” and if you have scripts/commands set up, Raycast can execute them. With AI, Raycast can understand more complex natural language to trigger these. (This feature is evolving, but it’s bridging Siri-like control with GPT understanding.) Translation and Other Utilities: Raycast AI includes quick translate functions (type a phrase and it can translate on the fly), and things like explaining code or regex you type, etc., as part of its default prompts. Think of Raycast as both a Spotlight replacement and now a mini ChatGPT on demand. It truly increases productivity because you don’t need to switch context to get AI help. Pros and Cons: Pros: Incredible convenience – AI is just a keystroke away, integrated with what you’re doing. Great for power users who live on the keyboard. Can incorporate live context (clipboard, selected text) easily, which web ChatGPT can’t do without extensions. Because it’s an app, you avoid the clutter of opening browser tabs for quick questions. Also, Raycast itself has many extensions and automations, and the AI can be combined with those (for example, you could have an extension that pipes AI output to a note). The base Raycast app is free and extremely useful even without AI. Cons: Raycast AI is a paid feature (Pro plan subscription) after the free messages quota. So while Raycast core is free, the AI assistant will cost (though you can alternatively use your own OpenAI API key in some capacity). Some users might already use Spotlight or Alfred and be reluctant to switch. And compared to a full ChatGPT interface, Raycast’s responses are in a small window – fine for short answers, but not for heavy chat conversations (you’d still use a full app for that). Additionally, since it can hook into system, one should be mindful of privacy (Raycast doesn’t log your data and the AI providers are external, but always good to review settings). Pricing: The Raycast app is free for core usage. Raycast AI is part of Raycast Pro, which is $8 per month (billed annually) for individuals. The Pro plan gives you a set number of AI messages (they mention 50 free AI queries on the free tier, then unlimited on Pro with some advanced model access). There’s also a higher “Advanced AI” tier (which was about $16/month) that unlocks access to the most advanced models like GPT-4 with longer context, Claude, etc. They do offer a short trial of Pro. If you’re an avid Raycast user, the subscription might be worth it for the integration; if not, you could stick to using the free tier or an alt like just using the ChatGPT Mac app. For many of us, having that AI in-line has proven worth the cost. Frequently Asked Questions (FAQ) Can you use AI software on a Mac? Absolutely – Macs are great for AI software. Many popular AI tools have Mac versions or work via the web on macOS. In fact, Apple’s newer Macs with M1/M2 chips are very AI-friendly, as they have neural engines that some apps (like Pixelmator Pro and DiffusionBee) use for machine learning tasks. Whether it’s a native app or a cloud service, you can run everything from AI chatbots to art generators on a Mac. Our list above showcases a variety of AI applications confirmed to run well on macOS. What is the best AI writing software for Mac? It depends on your needs. For general-purpose writing and brainstorming, ChatGPT (with the official Mac app) is the most versatile – it can help with articles, emails, coding, you name it. If you’re looking for marketing copy or long-form blog content, Jasper AI is a top choice with templates for content creation, albeit with a higher price tag. For improving and editing your own writing, Grammarly is excellent as it integrates with Mac apps to catch errors and even offers AI rewrites (GrammarlyGO). Notion AI is fantastic if you already organize notes in Notion – it can draft and refine content right where your notes live. All these run great on Mac (either natively or in web browsers). Many writers actually use a combo (for example, drafting ideas in ChatGPT, then polishing language with Grammarly on Mac). What’s the best AI art generator for Mac users? Midjourney is currently one of the best AI image generators in terms of output quality. Mac users can access Midjourney easily through Discord or a browser – it’s not Mac-specific, but it works fine on macOS since it’s cloud-based. If you prefer a native Mac app or want a free option, DiffusionBee is an excellent choice for running Stable Diffusion locally on Apple Silicon Macs. It’s not as artistically powerful as Midjourney, but it gives you a lot of flexibility and privacy. Additionally, Pixelmator Pro has integrated some generative AI (Image Playground) for creating images on-device, which is great if you want an all-in-one editor. So for highest quality and variety – go Midjourney; for free offline generation – DiffusionBee; and for integrated editing + AI – Pixelmator Pro is superb on Mac. Do I need an M1/M2 Mac for these AI apps? While you can run most of these AI applications on Intel-based Macs, having an M1 or M2 Mac greatly enhances performance for many of them. Apps like Pixelmator Pro and DiffusionBee are fully optimized for Apple Silicon chips, meaning they run significantly faster on M1/M2 machines (e.g., AI image generation or upscaling might be 5-10× faster than on an Intel Mac). That said, cloud-based AI services (ChatGPT, Jasper, Midjourney, etc.) will work fine on any Mac since the heavy lifting is done on servers. If you plan to do local AI tasks (like local Stable Diffusion or local transcription with MacWhisper), an Apple Silicon Mac with plenty of RAM will give the best experience. But you don’t need the latest Mac – we’ve even used some of these tools on older Macs via web with no problem. Are AI apps for Mac free? There are some great free AI tools for Mac, but many of the most powerful ones have a cost (often subscription-based). For instance, ChatGPT has a free version, but the advanced GPT-4 access is behind a $20/mo subscription. DiffusionBee is totally free and open-source for image generation. Grammarly has a free tier, while Jasper is paid-only. Descript offers a free plan with limited transcription and exports, and you pay for higher usage. Raycast app is free, but the AI assistant in it comes with the paid Pro plan. Notion AI used to be an add-on; now it’s included only in higher paid plans. The benefit is many paid AI services offer trials or free quotas, so you can often try them on your Mac without upfront cost. In our list above, we made sure to note which are free, freemium, or paid so you can pick according to your budget. How does Siri compare to these AI tools? Apple’s Siri (built into macOS and iOS) is an earlier generation voice assistant and is quite limited compared to modern AI like ChatGPT. Siri can do basic Mac commands, dictate messages, and answer very simple queries, but it often can’t engage in complex conversations or generate creative content. The AI apps we discuss (ChatGPT, Notion AI, Raycast AI, etc.) use advanced language models that produce far more detailed and context-aware responses. In fact, Apple has recognized this gap – the latest macOS (Sequoia) introduces Apple Intelligence features (like Writing Tools and web page summaries) to boost what Siri and the system can do. But as of 2025, Siri itself still can’t write your essay or debug your code. We recommend using the specialized AI apps for heavy-duty tasks and treating Siri as a hands-free helper for simple commands. Some tools like Raycast AI even aim to replace Siri on Mac with a much smarter GPT-based assistant. Is my data safe with these AI applications? It’s wise to be cautious. For any cloud-based AI (ChatGPT, Jasper, Notion AI, etc.), your prompts and content are sent to servers for processing. Reputable companies have policies to not misuse your data – for instance, OpenAI lets you opt-out of data usage, and Notion AI only accesses data in your workspace. Still, you shouldn’t input highly sensitive personal or confidential information into a third-party AI service unless you trust their privacy measures or have an enterprise agreement. For local apps like DiffusionBee or MacWhisper, everything stays on your Mac, so those are safer for privacy by design. Apple’s built-in AI (Apple Intelligence) also does a lot on-device for privacy. In short: check each app’s privacy policy. For example, Grammarly states it encrypts your texts and doesn’t sell data, but it is cloud-based. Descript’s voice clone requires your permission and training data. If privacy is a top concern, using offline tools or self-hosted models on Mac might be preferable. Do I need to know how to code to use AI software on Mac? Not at all. The beauty of these modern AI apps is that they have user-friendly interfaces or integrate into tools you already use. Our list contains apps aimed at general users (writers, artists, professionals) with no coding required. For instance, using ChatGPT or Notion AI is as easy as typing questions in plain English. DiffusionBee has a simple GUI – you enter text prompts and click a button to generate images. No coding needed. That said, if you are a coder, there are some more technical things you can do on a Mac (like running AI models via Terminal, or integrating AI with AppleScript/Shortcuts). But those are optional advanced uses. The average Mac user can absolutely leverage AI apps with zero programming knowledge – just be ready to experiment and describe what you want to the AI in natural language. Comparison Table of Top Mac AI Software Below is a quick comparison of all the AI tools we discussed, including their pricing models, compatibility, and key features at a glance: AI SoftwarePricingmacOS CompatibilityKey FeaturesChatGPT (OpenAI)Free basic use; Plus $20/moNative Mac app (10.15+); Web (all browsers); Apple Silicon optimizedConversational AI chatbot; writing & coding assistance; GPT-4 access with subscription; Mac app offers global shortcutJasper AIPaid only – Pro ~$69/mo (no free tier)Web-based (Safari/Chrome on Mac); no native app neededAI content generator for marketing & writing; 50+ templates (blogs, ads, etc.); team collaboration; uses GPT-4 for high-quality outputsGrammarlyFree basic plan; Premium from ~$12/moNative Mac app, plus browser extensions; works on M1/M2Real-time grammar and spell checking; style and tone suggestions; GrammarlyGO AI writing assistance for rewrites & drafts; integrates with most Mac appsGitHub Copilot$10/mo (individual Pro); free trial availableIDE extensions (VS Code, JetBrains, Xcode) on macOS; Apple Silicon support in editorsAI code autocomplete and chat; supports many programming languages; suggests code snippets and entire functions; context-aware coding help in your editorMidjourneySubscription – Basic $10/mo, Standard $30/mo, etc.Web & Discord app (runs via cloud); works on any Mac with internetAI image generation from text prompts; produces high-quality art and graphics; various styles and photorealism; no local resources required (cloud GPU)DiffusionBeeFree (open-source)macOS app (13.1+); Apple Silicon recommended (runs on Intel slowly)Local Stable Diffusion image generator; works offline 100%; text-to-image, image-to-image, upscaling, and more tools; privacy-focused (data never leaves device)Pixelmator ProPaid app, one-time $49.99 (15-day free trial)macOS app (10.14+); Apple Silicon nativeAdvanced image editor with ML Enhance, ML Super Resolution upscaling, background removal, and smart object removal; integrates macOS features; now includes AI image generation and text assist toolsDescriptFree plan (1 hr transcript, etc.); Creator plan $24/momacOS app (13+); Apple Silicon native; also available on WindowsAI-driven audio/video editor; transcribes audio to text; edit by editing text; Overdub voice cloning; removes filler words & noise; great for podcasts and videosNotion AIIncluded in Notion Business plan ($15–$20/user/mo) (no longer on free plans)Notion Mac app (Electron, runs on Intel & M1); also via any browserAI assistant inside Notion; generates content, brainstorms, summarizes notes; answers questions using your notes’ context; integrates with tasks & docs in Notion workspaceRaycast + AICore Raycast is free; AI Pro $8/mo (annual) (Advanced $16/mo)macOS app (11+); Apple Silicon optimized; needs internet for AI queriesSpotlight-like launcher with built-in GPT assistant; instant Q&A or text generation via hotkey; integrates with Mac clipboard and commands for contextual actions; supports multiple AI models; boosts Mac automation with natural language Each of these AI tools brings something unique to macOS. Whether you’re aiming to write smarter, code faster, create art, or automate tasks, there’s an AI app on Mac tailored to that purpose. By combining the strengths of a few of them (as we often do), you can transform your Mac into an intelligent productivity hub. Happy experimenting with AI on your Mac!

Developer Snapshots: Kleinere News der Woche

Sat, 09 Aug 2025 09:15:42 +0200

Die Übersicht enthält kleine, aber interessante Meldungen zu Node.js, VS Code, PyCharm, PSF, Qt, Stackable, CUDA, Microsoft und cmake.

Pycharm vs VSCode: Welches Tool eignet sich besser für Programmierprojekte?

Fri, 27 Jun 2025 15:20:28 +0200

Pycharm vs VSCode sind zwei der beliebtesten integrierten Entwicklungsumgebungen (IDEs) auf dem Markt. Doch welches Tool eignet sich besser für Ihre Programmierprojekte? Wir geben Entscheidungshilfen. … ... mehr

CVE-2025-42921 | JetBrains Toolbox App up to 2.5 SSH Plugin certificate validation (Nessus ID 234844)

Sat, 26 Apr 2025 04:54:08 +0200

A vulnerability, which was classified as problematic, was found in JetBrains Toolbox App up to 2.5. Affected is an unknown function of the component SSH Plugin. The manipulation leads to certificate with host mismatch. This vulnerability is traded as CVE-2025-42921. It is possible to launch the attack remotely. There is no exploit available. It is recommended to upgrade the affected component.

KI generiertes Nachrichten Update

Hier ist eine erweiterte Version des Nachrichtenartikels mit zusätzlichen Informationen, die thematisch passen, und entferntem unnötigen Inhalt. Ich habe versucht, den Artikel informativer und nützlicher zu gestalten:

CVE-2025-42921 | JetBrains Toolbox App up to 2.5: Schwere Schwachstelle in der SSH-Plugin-Zertifikatsvalidierung

Zusammenfassung:

Eine schwerwiegende Sicherheitslücke (CVE-2025-42921) wurde in der JetBrains Toolbox App bis zur Version 2.5 entdeckt. Die Schwachstelle betrifft das SSH-Plugin und erlaubt Angreifern, Zertifikate mit fehlerhaftem Host-Matching zu verwenden. Dies könnte es einem Angreifer ermöglichen, sich unbefugt mit Systemen zu verbinden, die durch das SSH-Plugin der Toolbox App verwaltet werden.

Details zur Schwachstelle:

CVE-ID: CVE-2025-42921
Betroffene Software: JetBrains Toolbox App bis Version 2.5
Betroffene Komponente: SSH-Plugin
Art der Schwachstelle: Fehlerhafte Zertifikatsvalidierung (Host-Mismatch)
Risikoeinschätzung: Von VulDB als "problematic" (problematisch) eingestuft.
Angriffsvektor: Remote (Fernzugriff)
Exploit-Status: Derzeit ist kein öffentlich verfügbarer Exploit bekannt. Dies bedeutet jedoch nicht, dass kein Exploit in Zukunft entwickelt werden kann.

Was bedeutet das?

Die Toolbox App wird von vielen Entwicklern verwendet, um verschiedene JetBrains IDEs (wie IntelliJ IDEA, PyCharm, WebStorm usw.) zu verwalten und zu starten. Das SSH-Plugin ermöglicht es, IDEs über SSH zu starten und zu verwalten, was insbesondere in CI/CD-Umgebungen oder bei Remote-Entwicklung nützlich ist. Eine erfolgreiche Ausnutzung dieser Schwachstelle könnte einem Angreifer die Kontrolle über die betroffenen IDE-Instanzen oder sogar die zugrunde liegenden Systeme ermöglichen.

Empfohlene Maßnahmen:

Update: JetBrains hat die Schwachstelle erkannt und wird voraussichtlich in Kürze ein Update veröffentlichen. Es wird dringend empfohlen, die JetBrains Toolbox App so schnell wie möglich auf die neueste verfügbare Version zu aktualisieren. Überprüfen Sie die JetBrains-Sicherheitsseite (https://www.jetbrains.com/security/) für die neuesten Informationen und Updates.
Überprüfen Sie Ihre SSH-Konfiguration: Sichern Sie sich, dass Ihre SSH-Konfigurationen korrekt sind und dass keine unsicheren Zertifikate verwendet werden.
Monitoring: Überwachen Sie Ihre Systeme auf verdächtige Aktivitäten, die mit SSH-Verbindungen in Verbindung stehen.

Weitere Informationen:

VulDB: https://vuldb.com/?id.305508
Tsecurity.de: https://tsecurity.de/de/2743797/IT+Reverse+Engineering/Sicherheitsl%C3%BCcken/CVE-2025-42921+%7C+JetBrains+Toolbox+App+up+to+2.5+SSH+Plugin+certificate+validation+%28Nessus+ID+234844%29/
Nessus ID: 234844

Haftungsausschluss: Dieser Artikel dient nur zu Informationszwecken und stellt keine professionelle Sicherheitsberatung dar.

Änderungen und Ergänzungen:

Ausführlichere Beschreibung der Schwachstelle: Erklärung, was ein "Host-Mismatch" bedeutet und welche Auswirkungen dies haben kann.
Kontextualisierung: Erklärung der Rolle der JetBrains Toolbox App und des SSH-Plugins.
Risikobewertung: Hervorhebung der potenziellen Auswirkungen einer erfolgreichen Ausnutzung.
Detailliertere Empfehlungen: Konkrete Schritte zur Behebung der Schwachstelle (Update, Konfigurationsprüfung, Monitoring).
Link zur JetBrains-Sicherheitsseite: Direkter Link zur offiziellen Quelle für Sicherheitsinformationen.
Haftungsausschluss: Standardmäßiger Haftungsausschluss.
Formatierung: Bessere Lesbarkeit durch Verwendung von Überschriften, Listen und Fettschrift.

Ich hoffe, diese erweiterte Version ist hilfreich! Bitte beachte, dass dies nur eine Zusammenfassung ist und weitere Informationen in den verlinkten Artikeln zu finden sind.

Making the swap from Windows to Linux is harder than I imagined.

Sun, 06 Apr 2025 21:21:43 +0200

This might just as well be a rant post, but recently I got really tired of Microshit Binbows and decided maybe it's time to swap over. Windows, OneDrive, Copilot and the whole Microsoft ecosystem just never seem to function how they should and it feels like with each new update Microsoft breaks more than they fix.

Finally, I decided today that enough is enough. I am making the switch. I have had experience with Linux before so this shouldn't the hardest thing to do, right?

First thing's first: A distro. What to pick, what to pick. The distros that I have been working with in the past were Ubuntu and Debian, but those seemed boring. I have heard of all the wonderful things about the extreme customizability of KDE Plasma, so maybe give something in that direction a try. After having a chat with chatgpt on my interests and doing some reading, the best distro I came up with "drum roll"... is KDE Neon.

KDE Neon seemed so fresh I had to try it out. Now I have no experience with the Power of KDE Plasma, but I figured I might as well learn some new tricks. So I grabbed the ISO started rufus, booted into my USB drive and installed it. Only took 10 minutes!

My first impressions of this OS and KDE Plasma: Phenomenal! Neon looks so sleek and the possibilities for customization is endless, I could sit for days and try to figure out all the fine details. I was really excited.

Now to install all my favorite programs and software. What to do from here? Let's start with my favorite web browser: Opera GX. No native support, no matter let me just use wine. It's a buggy mess. I really disliked the fact that I had to switch browsers, but because I am on new frontiers I might as well just suck it up and install chrome (I am gonna use Google One so using chrome over Firefox seemed natural). Time to download the software to enhance my peripherals. No native support for GHUB for my mouse and no native support steelseries gg. Ok ok, I can still use some other software to tweak my peripherals, albeit a workaround.

I use my computer mainly to code so let's setup my dev environment. I will shamefully admit that I rely on cracked jetbrains software like PyCharm and IntelliJ Idea to streamline my personal projects. It's just easier this way. Jetbrains community edition software lacks the useful functionality that I need, but since I don't code for enterprise reasons and only for myself I am not justifying the price. So back from the tangent, let me setup my dev enviroment. No cracks for Jetbrains software for linux. I need to use VSCode if I want to go through the trouble of mimicking the functionality of this software. Bummer, but I can make it work.

Time to install some games. Since most of the games I play require kernel level anti-cheat NONE of them are available on Linux.

OK.. I tried switching over but nothing is working out.
No Opera GX
No GHUB
No Steelseries GG
No PyCharm
No League of Legends
No Destiny 2

These are some of the only things I really turn my computer on for so wtf. Something's gotta give right?

So now I am stuck using this godforsaken operating system that Microsoft just continues to make worse update after update.

I am going to keep KDE Neon for a while and I will encourage myself to use it everyday such that I can maybe force myself to swap over, but that seems like a longshot. I would really like to know from the Linux community if these frustrations I am facing have ever been with you? And how did you guys manage just to swap over if you had this great dependance on the suckyiest software on the face of the earth (Windows 11)?

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Designing, Building & Deploying an AI Chat App from Scratch (Part 2)

Mon, 20 Jan 2025 11:04:37 +0100

Cloud Deployment and Scaling

Photo by Alex wong on Unsplash

1. Introduction

In the previous post, we built an AI-powered chat application on our local computer using microservices. Our stack included FastAPI, Docker, Postgres, Nginx and llama.cpp. The goal of this post is to learn more about the fundamentals of cloud deployment and scaling by deploying our app to Azure, making it available to real users. We’ll use Azure because they offer a free education account, but the process is similar for other platforms like AWS and GCP.

You can check a live demo of the app at chat.jorisbaan.nl. Now, obviously, this demo isn’t very large-scale, because the costs ramp up very quickly. With the tight scaling limits I configured I reckon it can handle about 10–40 concurrent users until I run out of Azure credits. However, I do hope it demonstrates the principles behind a scalable production system. We could easily configure it to scale to many more users with a higher budget.

I give a complete breakdown of our infrastructure and the costs at the end. The codebase is at https://github.com/jsbaan/ai-app-from-scratch.

A quick demo of the app at chat.jorisbaan.nl. We start a new chat, come back to that same chat, and start another chat.

1.1. Recap: local application

Let’s recap how we built our local app: A user can start or continue a chat with a language model by sending an HTTP request to http://localhost. An Nginx reverse proxy receives and forwards the request to a UI over a private Docker network. The UI stores a session cookie to identify the user, and sends requests to the backend: the language model API that generates text, and the database API that queries the database server.

Local architecture of the app. See part 1 for more details. Made by author in draw.io.

Introduction
1.1 Recap: local application
Cloud architecture
2.1 Scaling
2.2 Kubernetes Concepts
2.3 Azure Container Apps
2.4 Azure architecture: putting it all together
Deployment
3.1 Setting up
3.2 PostgreSQL server deployment
3.3 Azure Container App Environment deployment
3.4 Azure Container Apps deployment
3.5 Scaling our Container Apps
3.6 Custom domain name & HTTPS
Resources & costs overview
Roadmap
Final thoughts
Acknowledgements
AI usage

2. Cloud architecture

Conceptually, our cloud architecture will not be too different from our local application: a bunch of containers in a private network with a gateway to the outside world, our users.

However, instead of running containers on our local computer with Docker Compose, we will deploy them to a computing environment that automatically scales across virtual or psychical machines to many concurrent users.

2.1 Scaling

Scaling is a central concept in cloud architectures. It means being able to dynamically handle varying numbers of users (i.e., HTTP requests). Uvicorn, the web server running our UI and database API, can already handle about 40 concurrent requests. It’s even possible to use another web server called Gunicorn as a process manager that employs multiple Uvicorn workers in the same container, further increasing concurrency.

Now, if we want to support even more concurrent request, we could give each container more resources, like CPUs or memory (vertical scaling). However, a more reliable approach is to dynamically create copies (replicas) of a container based on the number of incoming HTTP requests or memory/CPU usage, and distribute the incoming traffic across replicas (horizontal scaling). Each replica container will be assigned an IP address, so we also need to think about networking: how to centrally receive all requests and distribute them over the container replicas.

This “prism” pattern is important: requests arrive centrally in some server (a load balancer) and fan out for parallel processing to multiple other servers (e.g., several identical UI containers).

Photo of two prisms by Fernando @cferdophotography on Unsplash

2.2 Kubernetes Concepts

Kubernetes is the industry standard system for automating deployment, scaling and management of containerized applications. Its core concepts are crucial to understand modern cloud architectures, including ours, so let’s quickly review the basics.

Node: A physical or virtual machine to run containerized app or manage the cluster.
Cluster: A set of Nodes managed by Kubernetes.
Pod: The smallest deployable unit in Kubernetes. Runs one main app container with optional secondary containers that share storage and networking.
Deployment: An abstraction that manages the desired state of a set of Pod replicas by deploying, scaling and updating them.
Service: An abstraction that manages a stable entrypoint (the service’s DNS name) to expose a set of Pods by distributing incoming traffic over the various dynamic Pod IP addresses. A Service has multiple types:
- A ClusterIP Service exposes Pods within the Cluster
- A LoadBalancer Service exposes Pods to outside the Cluster. It triggers the cloud provider to provision an external public IP and load balancer outside the cluster that can be used to reach the cluster. These external requests are then routed via the Service to individual Pods.
Ingress: An abstraction that defines more complex rules for a cluster’s entrypoint. It can route traffic to multiple Services; give Services externally-reachable URLs; load balance traffic; and handle secure HTTPS.
Ingress Controller: Implements the Ingress rules. For example, an Nginx-based controller runs an Nginx server (like in our local app) under the hood that is dynamically configured to route traffic according to Ingress rules. To expose the Ingress Controller itself to the outside world, you can use a LoadBalancer Service. This architecture is often used.

2.3 Azure Container Apps

Armed with these concepts, instead of deploying our app with Kubernetes directly, I wanted to experiment a little by using Azure Container Apps (ACA). This is a serverless platform built on top of Kubernetes that abstracts away some of its complexity.

With a single command, we can create a Container App Environment, which, under the hood, is an invisible Kubernetes Cluster managed by Azure. Within this Environment, we can run a container as a Container App that Azure internally manages as Kubernetes Deployments, Services, and Pods. See article 1 and article 2 for detailed comparisons.

A Container App Environment also auto-creates:

An invisible Envoy Ingress Controller that routes requests to internal Apps and handles HTTPS and App auto-scaling based on request volume.
An external Public IP address and Azure Load Balancer that routes external traffic to the Ingress Controller that in turn routes it to Apps (sounds similar to a Kubernetes LoadBalancer Service, eh?).
An Azure-generated URL for each Container App that is publicly accessible over the internet or internal, based on its Ingress config.

This gives us everything we need to run our containers at scale. The only thing missing is a database. We will use an Azure-managed PostgreSQL server instead of deploying our own container, because it’s easier, more reliable and scalable. Our local Nginx reverse proxy container is also obsolete because ACA automatically deploys an Envoy Ingress Controller.

It’s interesting to note that we literally don’t have to change a single line of code in our local application, we can just treat it as a bunch of containers!

2.4 Azure architecture: putting it all together

Here is a diagram of the full cloud architecture for our chat application that contains all our Azure resources. Let’s take a high level look at how a user request flows through the system.

Azure architecture diagram. Made by author in draw.io.

User sends HTTPS request to chat.jorisbaan.nl.
A Public DNS server like Google DNS resolves this domain name to an Azure Public IP address.
The Azure Load Balancer on this IP address routes the request to the (for us invisible) Envoy Ingress Controller.
The Ingress Controller routes the request to UI Container App, who routes it to one of its Replicas where a UI web server is running.
The UI web server makes requests to the database API and language model API Apps, who both route it to one of their Replicas.
A database API replica queries the PostgreSQL server hostname. The Azure Private DNS Zone resolves the hostname to the PostgreSQL server’s IP address.

3. Deployment

So, how do we actually create all this? Rather than clicking around in the Azure Portal, infrastructure-as-code tools like Terraform are best to create and manage cloud resources. However, for simplicity, I will instead use the Azure CLI to create a bash script that deploys our entire application step by step. You can find the full deployment script including environment variables here 🤖. We will go through it step by step now.

3.1 Setting up

We need an Azure account (I’m using a free education account), a clone of the https://github.com/jsbaan/ai-app-from-scratch repo, Docker to build and push the container images, the downloaded model, and the Azure CLI to start creating cloud resources.

We first create a resource group so our resources are easier to find, manage and delete. The --location parameter refers to the physical datacenter we’ll use to deploy our app’s infrastructure. Ideally, it is close to our users. We then create a private virtual network with 256 IP addresses to isolate, secure and connect our database server and Container Apps.

brew update && brew install azure-cli # for macos

echo "Create resource group"
az group create \
  --name $RESOURCE_GROUP \
  --location "$LOCATION"
  
echo "Create VNET with 256 IP addresses"
az network vnet create \
  --resource-group $RESOURCE_GROUP \
  --name $VNET \
  --address-prefix 10.0.0.0/24 \
  --location $LOCATION

3.2 PostgreSQL server deployment

Depending on the hardware, an Azure-managed PostgreSQL database server costs about $13 to $7000 a month. To communicate with Container Apps, we put the DB server within the same private virtual network but in its own subnet. A subnet is a dedicated range of IP addresses that can have its own security and routing rules.

We create the Azure PostgreSQL Flexible Server with private access. This means only resources within the same virtual network can reach it. Azure automatically creates a Private DNS Zone that manages a hostname for the database that resolves to its IP address. The database API will later use this hostname to connect to the database server.

We will randomly generate the database credentials and store them in a secure place: Azure KeyVault.

echo "Create subnet for DB with 128 IP addresses"
az network vnet subnet create \
  --resource-group $RESOURCE_GROUP \
  --name $DB_SUBNET \
  --vnet-name $VNET \
  --address-prefix 10.0.0.128/25

echo "Create a key vault to securely store and retrieve secrets, \
like the db password"
az keyvault create \
  --name $KEYVAULT \
  --resource-group $RESOURCE_GROUP \
  --location $LOCATION

echo "Give myself access to the key vault so I can store and retrieve \
the db password"
az role assignment create \
  --role "Key Vault Secrets Officer" \
  --assignee $EMAIL \
  --scope "/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.KeyVault/vaults/$KEYVAULT"

echo "Store random db username and password in the key vault"
az keyvault secret set \
  --name postgres-username \
  --vault-name $KEYVAULT  \
  --value $(openssl rand -base64 12 | tr -dc 'a-zA-Z' | head -c 12)
az keyvault secret set \
  --name postgres-password \
  --vault-name $KEYVAULT  \
  --value $(openssl rand -base64 16)

echo "While we're at it, let's already store a secret session key for the UI"
az keyvault secret set \
  --name session-key \
  --vault-name $KEYVAULT  \
  --value $(openssl rand -base64 16)
 
echo "Create PostgreSQL flexible server in our VNET in its own subnet. \
Auto-creates Private DS Zone."
POSTGRES_USERNAME=$(az keyvault secret show --name postgres-username --vault-name $KEYVAULT --query "value" --output tsv)
POSTGRES_PASSWORD=$(az keyvault secret show --name postgres-password --vault-name $KEYVAULT --query "value" --output tsv)
az postgres flexible-server create \
  --resource-group $RESOURCE_GROUP \
  --name $DB_SERVER \
  --vnet $VNET \
  --subnet $DB_SUBNET \
  --location $LOCATION \
  --admin-user $POSTGRES_USERNAME \
  --admin-password $POSTGRES_PASSWORD \
  --sku-name Standard_B1ms \
  --tier Burstable \
  --storage-size 32 \
  --version 16 \
  --yes

3.3 Azure Container App Environment deployment

With the network and database in place, let’s deploy the infrastructure to run containers — the Container App Environment (recall, this is a Kubernetes cluster under the hood).

We create another subnet with 128 IP addresses and delegate its management to the Container App Environment. The subnet should be big enough for every ten new replicas to get a new IP address in the subrange. We can then create the Environment. This is just a single command without much configuration.

echo "Create subnet for ACA with 128 IP addresses."
az network vnet subnet create \
  --resource-group $RESOURCE_GROUP \
  --name $ACA_SUBNET \
  --vnet-name $VNET \
  --address-prefix 10.0.0.0/25

echo "Delegate the subnet to ACA"
az network vnet subnet update \
  --resource-group $RESOURCE_GROUP \
  --vnet-name $VNET \
  --name $ACA_SUBNET \
  --delegations Microsoft.App/environments
  
echo "Obtain the ID of our subnet"
ACA_SUBNET_ID=$(az network vnet subnet show \
  --resource-group $RESOURCE_GROUP \
  --name $ACA_SUBNET \
  --vnet-name $VNET \
  --query id --output tsv)
  
echo "Create Container Apps Environment in our custom subnet.\\
By default, it has a Workload profile with Consumption plan."
az containerapp env create \
  --resource-group $RESOURCE_GROUP \
  --name $ACA_ENVIRONMENT \
  --infrastructure-subnet-resource-id $ACA_SUBNET_ID \
  --location $LOCATION

3.4 Azure Container Apps deployment

Each Container App needs a Docker image to run. Let’s first setup a Container Registry, and then build all our images locally and push them to the registry. Note that we simply copied the model file into the language model image using its Dockerfile, so we don’t need to mount external storage like we did for local deployment in part 1.

echo "Create container registry (ACR)"
az acr create \\
  --resource-group $RESOURCE_GROUP \\
  --name $ACR \\
  --sku Standard \\
  --admin-enabled true
  
echo "Login to ACR and push local images"
az acr login --name $ACR
docker build --tag $ACR.azurecr.io/$DB_API $DB_API
docker push $ACR.azurecr.io/$DB_API
docker build --tag $ACR.azurecr.io/$LM_API $LM_API
docker push $ACR.azurecr.io/$LM_API
docker build --tag $ACR.azurecr.io/$UI $UI
docker push $ACR.azurecr.io/$UI

Now, onto deployment. To create Container Apps we specify their Environment, container registry, image, and the port they will listen to for requests. The ingress parameter regulates whether Container Apps can be reached from the outside world. Our two APIs are internal and therefore completely isolated, with no public URL and no traffic ever routed from the Envoy Ingress Controller. The UI is external and has a public URL, but sends internal HTTP requests over the virtual network to our APIs. We pass these internal hostnames and db credentials as environment variables.

echo "Deploy DB API on Container Apps with the db credentials from the key \
vault as env vars. More secure is to use a managed identity that allows the \
container itself to retrieve them from the key vault. But for simplicity we \
simply fetch it ourselves using the CLI."
POSTGRES_USERNAME=$(az keyvault secret show --name postgres-username --vault-name $KEYVAULT --query "value" --output tsv)
POSTGRES_PASSWORD=$(az keyvault secret show --name postgres-password --vault-name $KEYVAULT --query "value" --output tsv)
az containerapp create --name $DB_API \
  --resource-group $RESOURCE_GROUP \
  --environment $ACA_ENVIRONMENT \
  --registry-server $ACR.azurecr.io \
  --image $ACR.azurecr.io/$DB_API \
  --target-port 80 \
  --ingress internal \
  --env-vars "POSTGRES_HOST=$DB_SERVER.postgres.database.azure.com" "POSTGRES_USERNAME=$POSTGRES_USERNAME" "POSTGRES_PASSWORD=$POSTGRES_PASSWORD" \
  --min-replicas 1 \
  --max-replicas 5 \
  --cpu 0.5 \
  --memory 1

echo "Deploy UI on Container Apps, and retrieve the secret random session \
key the UI uses to encrypt session cookies"
SESSION_KEY=$(az keyvault secret show --name session-key --vault-name $KEYVAULT --query "value" --output tsv)
az containerapp create --name $UI \
  --resource-group $RESOURCE_GROUP \
  --environment $ACA_ENVIRONMENT \
  --registry-server $ACR.azurecr.io \
  --image $ACR.azurecr.io/$UI \
  --target-port 80 \
  --ingress external \
  --env-vars "db_api_url=http://$DB_API" "lm_api_url=http://$LM_API" "session_key=$SESSION_KEY" \
  --min-replicas 1 \
  --max-replicas 5 \
  --cpu 0.5 \
  --memory 1 
  
echo "Deploy LM API on Container Apps"
az containerapp create --name $LM_API \
  --resource-group $RESOURCE_GROUP \
  --environment $ACA_ENVIRONMENT \
  --registry-server $ACR.azurecr.io \
  --image $ACR.azurecr.io/$LM_API \
  --target-port 80 \
  --ingress internal \
  --min-replicas 1 \
  --max-replicas 5 \
  --cpu 2 \
  --memory 4 \
  --scale-rule-name my-http-rule \
  --scale-rule-http-concurrency 2

3.5 Scaling our Container Apps

Let’s take a look at how our Container Apps they scale. Container Apps can scale to zero, which means they have zero replicas and stop running (and stop incurring costs). This is a feature of the serverless paradigm, where infrastructure is provisioned on demand. The invisible Envoy proxy handles scaling based on triggers, like concurrent HTTP requests. Spawning new replicas may take some time, which is called cold-start. We set the minimum number of replicas to 1 to avoid cold starts and the resulting timeout errors for first requests.

The default scaling rule creates a new replica whenever an existing replica receives 10 concurrent HTTP requests. This applies to the UI and the database API. To test whether this scaling rule makes sense, we would have to perform load testing to simulate real user traffic and see what each Container App replica can handle individually. My guess is that they can handle a lot more concurrent request than 10, and we could relax the rule.

3.5.1 Scaling language model inference.

Even with our small, quantized language model, inference requires much more compute than a simple FastAPI app. The inference server handles incoming requests sequentially, and the default Container App resources of 0.5 virtual CPU cores and 1GB memory result in very slow response times: up to 30 seconds for generating 128 tokens with a context window of 1024 (these parameters are defined in the LM API’s Dockerfile).

Increasing vCPU to 2 and memory to 4GB gives much better inference speed, and handles about 10 requests within 30 seconds. I configured the http scaling rule very tightly at 2 concurrent requests, so whenever 2 users chat at the same time, the LM API will scale out.

With 5 maximum replicas, I think this will allow for roughly 10–40 concurrent users, depending on the length of the chat histories. Now, obviously, this isn’t very large-scale, but with a higher budget, we could increase vCPUs, memory and the number of replicas. Ultimately we would need to move to GPU-based inference. More on that later.

3.6 Custom domain name & HTTPS

The automatically generated URL from the UI App looks like https://chat-ui.purplepebble-ac46ada4.germanywestcentral.azurecontainerapps.io/. This isn’t very memorable, so I want to make our app available as subdomain on my website: chat.jorisbaan.nl.

I simply add two DNS records on my domain registrar portal (like GoDaddy). A CNAME record that links my chat subdomain to the UI’s URL, and TXT record to prove ownership of the subdomain to Azure and obtain a TLS certificate.

# Obtain UI URL and verification code
URL=$(az containerapp show -n $UI -g $RESOURCE_GROUP -o tsv --query "properties.configuration.ingress.fqdn")
VERIFICATION_CODE=$(az containerapp show -n $UI -g $RESOURCE_GROUP -o tsv --query "properties.customDomainVerificationId")

# Add a CNAME record with the URL and a TXT record with the verification code to domain registrar
# (Do this manually)

# Add custom domain name to UI App
az containerapp hostname add --hostname chat.jorisbaan.nl -g $RESOURCE_GROUP -n $UI
# Configure managed certificate for HTTPS
az containerapp hostname bind --hostname chat.jorisbaan.nl -g $RESOURCE_GROUP -n $UI --environment $ACA_ENVIRONMENT --validation-method CNAME

Container Apps manages a free TLS certificate for my subdomain as long as the CNAME record points directly to the container’s domain name.

The public URL for the UI changes whenever I tear down and redeploy an Environment. We could use a fancier service like Azure Front Door or Application Gateway to get a stable URL and act as reverse proxy with additional security, global availability, and edge caching.

4. Resources & costs overview

Now that the app is deployed, let’s look at an overview of all the Azure resources it app uses. We created most of them ourselves, but Azure also automatically created a Load balancer, Public IP, Private DNS Zone, Network Watcher and Log Analytics workspace.

Screenshot of all resources from Azure Portal.

Some resources are free, others are free up to a certain time or compute budget, which is part of the reason I chose them. The following resources incur the highest costs:

Load Balancer (standard Tier): free for 1 month, then $18/month.
Container Registry (standard Tier): free for 12 months, then $19/month.
PostgreSQL Flexible Server (Burstable B1MS Compute Tier): free for 12 months, then at least $13/month.
Container App: Free for 50 CPU hours/month or 2M requests/month, then $10/month for an App with a single replica, 0.5 vCPUs and 1GB memory. The LM API with 2vCPUs, 4GB memory costs about $50 per month for a single replica.

You can see that the costs of this small (but scalable) app can quickly add up to hundreds of dollars per month, even without a GPU server to run a stronger language model! That’s the reason why the app probably won’t be up when you’re reading this.

It also becomes clear that Azure Container Apps is more expensive then I initially thought: it requires a standard-Tier Load balancer for automatic external ingress, HTTPS and auto-scaling. We could get around this by disabling external ingress and deploying a cheaper alternative — like a VM with a custom reverse proxy, or a basic-Tier Load balancer. Still, a standard-tier Kubernetes cluster would have cost at least $150/month, so ACA can be cheaper at small scale.

5. Roadmap

Now, before we wrap up, let’s look at just a few of the many directions to improve this deployment.

Continuous Integration & Continuous Deployment. I would set up a CI/CD pipeline that runs unit and integration tests and redeploys the app upon code changes. It might be triggered by a new git commit or merged pull request. This will also make it easier to see when a service isn’t deployed properly. I would also set up monitoring and alerting to be aware of issues quickly (like a crashing Container App instance).

Lower latency: the language model server. I would load test the whole app — simulating real-world user traffic — with something like Locust or Azure Load Testing. Even without load testing, we have an obvious bottleneck: the LM server. Small and quantized as it is, it can still take up quite a while for lengthy answers, with no concurrency. For more users it would be faster and more efficient to run a GPU inference server with a batching mechanism that collects multiple generation requests in a queue — perhaps with Kafka — and runs batch inference on chunks.

With even more users, we might want several GPU-based LM servers that consume from the same queue. For GPU infrastructure I’d look into Azure Virtual Machines or something more fancy like Azure Machine Learning.

The llama.cpp inference engine is good for single-user CPU-based inference. When moving to a GPU-server, I would look into inference engines more suitable to batch inference, like vLLM or Huggingface TGI. And, obviously, a better (bigger) model for increased response quality — depending on the use case.

6. Final thoughts

I hope this project offers a glimpse of what an AI-powered web app in production may look like. I tried to balance realistic engineering with cutting about every corner to keep it simple, cheap, understandable, and limit my time and compute budget. Sadly, I cannot keep the app live for long since it would quickly cost hundreds of dollars per month. If someone can help with Azure credits to keep the app running, let me know!

Some closing thoughts about using managed services: Although Azure Container Apps abstracts away some of the Kubernetes complexity, it’s still extremely useful to have an understanding of the lower-level Kubernetes concepts. The automatically created invisible infrastructure like Public IPs, Load balancers and ingress controllers add unforeseen costs and make it difficult to understand what’s going on. Also, ACA documentation is limited compared to Kubernetes. However, if you know what you’re doing, you can set something up very quickly.

Acknowledgements

I heavily relied on the Azure docs, and the ACA docs in particular. Thanks to Dennis Ulmer for proofreading and Lucas de Haas for useful discussion.

AI usage

I experimented a bit more with AI tools compared to part 1. I used Pycharm’s CoPilot plugin for code completion and had quite some back-and-forth with ChatGPT to learn about the Azure or Kubernetes ecosystem, and to spar about bugs. I double-checked everything in the docs and most of the information was solid. Like part 1, I did not use AI to write this post, though I did use ChatGPT to paraphrase some bad-running sentences.

Designing, Building & Deploying an AI Chat App from Scratch (Part 2) was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

Designing, Building & Deploying an AI Chat App from Scratch (Part 1)

Mon, 20 Jan 2025 10:19:39 +0100

Microservices Architecture and Local Development

Photo by Danist Soh on Unsplash

Introduction

The aim of this project is to learn about the fundamentals of modern, scalable web applications by designing, building and deploying an AI-powered chat app from scratch. We won’t use fancy frameworks or commercial platforms like ChatGPT. This will provide a better understanding of how real-world systems may work under the hood, and give us full control over the language model, infrastructure, data and costs. The focus will be on engineering, backend and cloud deployment, rather than the language model or a fancy frontend.

This is part 1. We will design and build a cloud-native app with several APIs, a database, private network, reverse proxy, and simple user interface with sessions. Everything runs on our local computer. In part 2, we will deploy our application to a cloud platform like AWS, GCP or Azure with a focus on scalability so actual users can reach it over the internet.

A quick demo of the app. We start a new chat, come back to that same chat, and start another chat. We will now build this app locally and make it available at localhost.

You can find the codebase at https://github.com/jsbaan/ai-app-from-scratch. Throughout this post I will link to specific lines of code with this hyperlink robot 🤖 (try it!)

Microservices and APIs

Modern web applications are often built using microservices — small, independent software components with a specific role. Each service runs in its own Docker container — an isolated environment independent of the underlying operating system and hardware. Services communicate with each other over a network using REST APIs.

You can think of a REST API as the interface that defines how to interact with a service by defining endpoints — specific URLs that represent the possible resources or actions, formatted like http://hostname:port/endpoint-name Endpoints, also called paths or routes, are accessed with HTTP requests that can have various types like GET to retrieve data or POST to create data. Parameters can be passed in the URL itself or in the request body or header.

Architecture

Let’s make this more concrete. We want a web page where users can chat with a language model and come back to their previous chats. Our architecture will look like this:

Local architecture of the app. Each service runs in its own Docker container and communicates over a private network. Made by author in draw.io.

The above architecture diagram shows how a user’s HTTP request to localhost on the left flows through the system. We will discuss and set up each individual service, starting with the backend services on the right. Finally, we discuss communication, networking and container orchestration.

The structure of this post follows the components in our architecture (click to jump to the section):

Language model API. A llama.cpp language model inference server running the quantized Qwen2.5–0.5B-Instruct model 🤖.
PostgreSQL database server. A database that stores chats and messages 🤖.
Database API. A FastAPI and Uvicorn Python server that queries the PostgreSQL database 🤖.
User interface. A FastAPI and Uvicorn Python server that serves HTML and support session-based authentication 🤖.
Private Docker network. For communication between microservices 🤖.
Nginx reverse proxy. A gateway between the outside world and network-isolated services 🤖.
Docker Compose. A container orchestration tool to easily run manage our services together 🤖.

1. Language model API

Setting up the actual language model is pretty easy, nicely demonstrating that ML engineering is usually more about engineering than ML. Since I want our app to run on a laptop, model inference should be fast and CPU-based with low memory.

I looked at several inference engines, like Fastchat with vLLM or Huggingface TGI, but went with llama.cpp because it’s popular, fast, lightweight and supports CPU-based inference. Llama.cpp is written in C/C++ and conveniently provides a Docker image with its inference engine and a simple web server that implements the popular OpenAI API specification. It comes with a basic UI for experimenting, but we’ll build our own UI shortly.

As for the actual language model, I chose the quantized Qwen2.5–0.5B-Instruct model from Alibaba Cloud, whose responses are surprisingly coherent given how small it is.

1.1 Running the language model API

The beauty of containerized applications is that, given a Docker image, we can have it running in seconds without installing any packages. The docker run command below pulls the llama.cpp server image, mounts the model file that we downloaded earlier to the container’s filesystem, and runs a container with the llama.cpp server listening for HTTP requests at port 80. It uses flash attention and has max generation length of 512 tokens.

docker run
	--name lm-api \
	--volume $PROJECT_PATH/lm-api/gguf_models:/models \
	--publish 8000:80 \ # add this to make the API accessible on localhost
	ghcr.io/ggerganov/llama.cpp:server 
		-m /models/qwen2-0_5b-instruct-q5_k_m.gguf --port 80 --host 0.0.0.0 --predict 512 --flash-attn

Ultimately we will use Docker Compose to run this container together with the others 🤖.

1.2 Accessing the container

Since Docker containers are completely isolated from everything else on their host machine, i.e., our computer, we can’t reach our language model API yet.

However, we can break through a bit of networking isolation by publishing the container’s port 80 to our host machine’s port 8000 with --publish 8000:80 in the docker run command. This makes the llama.cpp server available at http://localhost:8000.

The hostname localhost resolves to the loopback IP address 127.0.0.1 and is part of the loopback network interface that allows a computer to communicate with itself. When we visit http://localhost:8000, our browser sends an HTTP GET request to our own computer on port 8000, which gets forwarded to the llama.cpp container listening at port 80.

1.3 Testing the language model API

Let’s test the language model server by sending a POST request with a short chat history.

curl -X POST  \
-H "Content-Type: application/json" \
-d '{
	"messages": [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "assistant", "content": "Hello, how can I assist you today?"},
    {"role": "user", "content": "Hi, what is an API?"}
	],
	"max_tokens": 10
	}'

The response is JSON and the generated text is under choices.message.content: “An API (Application Programming Interface) is a specification…”.

Perfect! Ultimately, our UI service will be the one to send requests to the language model API, and define the system prompt and opening message 🤖.

2. PostgreSQL database server

Next, let’s look into storing chats and messages. PostgreSQL is a powerful, open-source relational database and running a PostgreSQL server locally is just another another docker run command using its official image. We’ll pass some extra environment variables to configure the database name, username, and password.

docker run --name db --publish 5432:5432 --env POSTGRES_USER=myuser --env POSTGRES_PASSWORD=mypassword postgres

After publishing port 5432, the database server is available on localhost:5432. PostgreSQL uses its own protocol for communication and doesn’t understand HTTP requests. We can use a database client like psql to test the connection.

pg_isready -U joris -h localhost -d postgres
> localhost:5432 - accepting connections

When we deploy our application in part 2, we will use a database managed by a cloud provider to make our lives easier and add more security, reliability and scalability. However, setting one up locally like this is useful for local development and, perhaps later on, integration tests.

3. Database API

Databases often have a separate API server sitting in front to control access, enforce extra security, and provide a simple, standardized interface that abstracts away the database’s complexity.

We will build this API from scratch with FastAPI, a modern framework for building fast, production-ready Python APIs. We will run the API with Uvicorn, a high-performance Python web server that handles things like network communication and simultaneous requests.

3.1 Quick FastAPI example

Let’s quickly get a feeling for FastAPI and look at a minimal example app with a single GET endpoint /hello.

from fastapi import FastAPI

# FastAPI app object that the Uvicorn web server will load and serve
my_app = FastAPI()

# Decorator telling FastAPI that function below handles GET requests to /hello
@my_app.get("/hello") 
def read_hello():
  # Define this endpoint's response
    return {"Hello": "World"}

We can serve our app at http://localhost:8080 by running the Uvicorn server.

uvicorn main.py:my_app --host 0.0.0.0 --port 8080

If we now send a GET request to our endpoint by visiting http://localhost:8080/hello in our browser, we receive the JSON response {"Hello": "World"} !

3.2 Connecting to the database

On to the actual database API. We define four endpoints in main.py 🤖 for creating or fetching chats and messages. You get a nice visual summary of these in the auto-generated docs, see below. The UI will call these endpoints to process user data.

A cool feature of FastAPI is that it automatically generates interactive documentation according to the OpenAPI specification with Swagger. If the Uvicorn server is running we can find it at http://hostname:port/docs. This is a screenshot of the doc web page.

The first thing we need to do is to connect the database API to the database server. We use SQLAlchemy, a popular Python SQL toolkit and Object-Relational Mapper (ORM) that abstracts away writing manual SQL queries.

We establish this connection in database.py 🤖 by creating the SQLAlchemy engine with a connection URL that includes the database hostname, username and password (remember, we configured these by passing them as environment variables to the PostgreSQL server). We also create a session factory that creates a new database session for each request to the database API.

3.3 Interacting with the database

Now let’s design our database. We define two SQLAlchemy data models in models.py 🤖 that will be mapped to actual database tables. The first is a Message model 🤖 with an id, content, speaker role, owner_id, and session_id (more on this later). The second is a Chat model 🤖, which I’ll show here to get a better feeling for SQLAlchemy models:

class Chat(Base):
  __tablename__ = "chats"

  # Unique identifier for each chat that will be generated automatically.
  id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)

  # Username associated with the chat. Index is created for faster lookups.
  username = Column(String, index=True)

  # Session ID associated with the chat. 
  # Used to "scope" chats, i.e., users can only access chats from their session.
  session_id = Column(String, index=True)

  # The relationship function links the Chat model to the Message model.
  # The back_populates flag creates a bidirectional relationship.
  messages = relationship("Message", back_populates="owner")

Database tables are typically created using migration tools like Alembic, but we’ll simply ask SQLAlchemy to create them in main.py 🤖.

Next, we define the CRUD (Create, Read, Update, Delete) methods in crud.py 🤖. These methods use a fresh database session from our factory to query the database and create new rows in our tables. The endpoints in main.py will import and use these CRUD methods 🤖.

3.4 Endpoint request and response validation

FastAPI is heavily based on Python’s type annotations and the data validation library Pydantic. For each endpoint, we can define a request and response schema that defines the input/output format we expect. Each request to or response from an endpoint is automatically validated and converted to the right data type and included in our API’s automatically generated documentation. If something about a request or response is missing or wrong, an informative error is thrown.

We define the Pydantic schemas for the database-api in schemas.py 🤖 and use them in the endpoint definitions in main.py 🤖, too. For example, this is the endpoint to create a new chat:

@app.post("/chats", response_model=schemas.Chat)
async def create_chat(chat: schemas.ChatCreate, db: Session = Depends(get_db)):
    db_chat = crud.create_chat(db, chat)
    return db_chat

We can see that it expects a ChatCreate request body and Chat response body. FastAPI verifies and converts the request and response bodies according to these schemas 🤖:

class ChatCreate(BaseModel):
    username: str
    messages: List[MessageCreate] = []
    session_id: str

class Chat(ChatCreate):
    id: UUID
    messages: List[Message] = []

Note: our SQLAlchemy models for the database should not be confused with these Pydantic schemas for endpoint input/output validation.

3.5 Running the database API

We can serve the database API using Uvicorn, making it available at http://localhost:8001.

cd $PROJECT_PATH/db-api
uvicorn app.main.py:app --host 0.0.0.0 --port 8001

To run the Uvicorn server in its own Docker container, we create a Dockerfile 🤖 that specifies how to incrementally build the Docker image. We can then build the image and run the container, again making the database API available at http://localhost:8001 after publishing the container’s port 80 to host port 8001. We pass the database credentials and hostname as environment variables.

docker build --tag db-api-image $PROJECT_PATH/db-api
docker run --name db-api --publish 8001:80 --env POSTGRES_USERNAME= --env POSTGRES_PASSWORD= --env POSTGRES_HOST= db-api-image

4. User interface

With the backend in place, let’s build the frontend. A web interface typically consists of HTML for structure, CSS for styling and Javascript for interactivity. Frameworks like React, Vue, and Angular use higher-level abstractions like JSX that can ultimately be transformed into HTML, CSS, and JS files to be bundled and served by a web server like Nginx.

Since I want to focus on the backend, I hacked together a simple UI with FastAPI. Instead of JSON responses, its endpoints now return HTML based on template files that are rendered by Jinja, a templating engine that replaces variables in the template with real data like chat messages.

To handle user input and interact with the backend (e.g., retrieve chat history from the database API or generate a reply via the language model API), I’ve avoided JavaScript altogether by using HTML forms 🤖 that trigger internal POST endpoints. These endpoints then simply use Python’s httpx library to make HTTP requests 🤖.

Endpoints are defined in main.py 🤖, HTML templates are in the app/templates directory 🤖, and the static CSS file for styling the pages is in the app/static directory 🤖. FastAPI serves the CSS file at http://hostname/static/style.css so the browser can find it.

Screenshot of the UI’s interactive documentation.

4.1 Homepage

The homepage allows users to enter their name to start or return to a chat 🤖. The submit button triggers a POST request to the internal /chats endpoint with username as form parameter, which calls the database API to create a new chat and then redirects to the Chat Page 🤖.

4.2 Chat Page

The chat page calls the database API to retrieve the chat history 🤖. Users can then enter a message that triggers a POST request to the internal /generate/{chat_id} endpoint with the message as form parameter 🤖.

The generate endpoint calls the database API to add the user’s message to the chat history, and then the language model API with the full chat history to generate a reply 🤖. After adding the reply to the chat history, the endpoint redirects to the chat page, that again retrieves and displays the latest chat history. We send POST request to the LM API using httpx, but we could use a more standardized LM API package like langchain to invoke its completion endpoint.

4.3 Authentication & user sessions

So far, all users can access all endpoints and all data. This means anyone can see your chat given your username or chat id. To remedy that, we will use session-based authentication and authorization.

We will store a first party & GDRP compliant signed session cookie in the user’s browser 🤖. This is just an encrypted dict-like object in the request/response header. The user’s browser will send that session cookie with each request to our hostname, so that we can identify and verify a user user and show them their own chats only.

As an extra layer of security, we “scope” the database API such that each chat row and each message row in the database contains a session id. For each request to the database API, we include the current user’s session id in the request header and query the database with both the chat id (or username) AND that session id. This way, the database can only ever return chats for the current user with its unique session id 🤖.

4.4 Running the UI

To run the UI in a Docker container, we follow the same recipe as the database API, adding the hostnames of the database API and language model API as environment variables.

docker build --tag chat-ui-image $PROJECT_PATH/chat-ui
docker run --name chat-ui --publish 8002:80 --env LM_API_URL= --env DB_API_URL= chat-ui-image

How do we know the hostnames of the two APIs? We will look networking and communication next.

5. Private Docker network

Let’s zoom out and take a look at our architecture again. By now, we have four containers: the UI, DB API, LM API, and PostgreSQL database. What’s missing is the network, reverse proxy and container orchestration.

Our app’s microservices architecture. Made by author in draw.io.

Until now, we used our computer’s localhost loopback network to send requests to an individual container. This was possible because we published their ports to our localhost. However, for containers to communicate with each other, they must be connected to the same network and know each others hostname/IP address and port.

We will create a user-defined bridge Docker network that provides automatic DNS resolution. This means that container names are resolved to their dynamic container’s IP address. The network also provides isolation, and therefore security: you have to be on the same network to be able to reach our containers.

docker network create --driver bridge chat-net

We connect all containers to it by adding --network chat-net to their docker run command. Now, the database API can reach the database at db:5432 and the UI can reach the database API at http://db-api and the language model API at http://lm-api. Port 80 is default for HTTP requests so we can omit it.

6. Nginx reverse proxy

Now, how do we — the user — reach our network-isolated containers? During development we published the UI container port to our localhost, but in a realistic scenario you typically use a reverse proxy. This is another web server that acts like a gateway, forwarding HTTP requests to containers in their private network, enforcing security and isolation.

Nginx is a web server often used as reverse proxy. We can easily run it using its official Docker image. We also mount a configuration file 🤖 in which we specify how Nginx should route incoming requests. As an example, the simplest possible configuration forwards all requests (location / ) from Nginx container’s port 80 to the UI container at http://chat-ui.

http { server { listen 80; location / { proxy_pass http://chat-ui } } }

Since the Nginx container is in same private network, we can’t reach it either. However, we can publish its port so it becomes the only access point of our entire app 🤖. A request to localhost now goes to the Nginx container, who forwards it to the UI and the UI’s response back to us.

docker run --network chat-net --publish 80:80 --volume $PROJECT_PATH/nginx.conf:/etc/nginx/nginx.conf nginx

In part 2 we will see that these gateway servers can also distribute incoming requests over copies of the same containers (load balancing) for scalability; enable secure HTTPS traffic; and do advanced routing and caching. We will use an Azure-managed reverse proxy rather this Nginx container, but I think it’s very useful to understand how they work and how to set one up yourself. It can also be significantly cheaper compared to a managed reverse proxy.

7. Docker Compose

Let’s put everything together. Throughout this post we manually pulled or built each image and ran its container. However, in the codebase I’m actually using Docker Compose: a tool designed to define, run and stop multi-container applications on a single host like our computer.

To use Docker Compose, we simply specify a compose.yml file 🤖 with build and run instructions for each service. A cool feature is that it automatically creates a user-defined bridge network to connect our services. Docker DNS will resolve the service names to container IP addresses.

Inside the project directory we can start all services with a single command:

docker compose up --build

Final thoughts

That wraps it up! We built an AI-powered chat web application that runs on our local computer, learning about microservices, REST APIs, FastAPI, Docker (Compose), reverse proxies, PostgreSQL databases, SQLAlchemy, and llama.cpp. We’ve built it with a cloud-native architecture in mind so we can deploy our app without changing a single line of code.

We will discuss deployment in part 2 and cover Kubernetes, the industry-standard container orchestration tool for large-scale applications across multiple hosts; Azure Container Apps, a serverless platform that abstracts away some of Kubernetes’ complexities; and concepts like load balancing, horizontal scaling, HTTPS, etc.

Roadmap

There is a lot we could do to improve this app. Here are some things I would work on given more time.

Language model. We now use a very general instruction-tuned language model as virtual assistant. I originally started this project to have a “virtual representation of me” on my website for visitors to discuss my research with, based on my scientific publications. For such a use case, an important direction is to improve and tweak the language model output. Perhaps that’ll become a part 3 of this series in the future.

Frontend. Instead of a quick FastAPI UI, I’d build a proper frontend using something like React, Angular or Vue to allow things like steaming LM responses and dynamic views rather than reloading the page every time. A more lightweight alternative that I’d like to experiment with is htmx, a library that provides modern browser features directly from HTML rather than javascript. It would be pretty straightforward to implement LM response streaming, for example.

Reliability. To make the system more mature, I’d add unit and integration tests and a better database setup like Alembic allowing for migrations.

Acknowledgements

Thanks to Dennis Ulmer, Bryan Eikema and David Stap for initial feedback or proofreading.

AI usage

I used Pycharm’s CoPilot plugin for code completion, and ChatGPT for a first version of the HTML and CSS template files. Towards the end, I started experimenting more with debugging and sparring too, which proved surprisingly useful. For example, I used it to learn about Nginx configurations and session cookies in FastAPI. I did not use AI to write this post, though I did use ChatGPT to paraphrase a few bad-running sentences.

Here are some additional resources that I found useful during this project.

Django vs Flask vs FastAPI YouTube video by Patrick Loeber.
The FastAPI tutorial was by far most helpful.
Docker documentation, especially the networking overview, bridge network intro, docker-compose quickstart and networks in docker-compose.
SQLAlchemy docs and their Object-Relational Mapper (ORM) tutorial.
PostgreSQL Cheat Sheet.

Designing, Building & Deploying an AI Chat App from Scratch (Part 1) was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

Designing, Building & Deploying an AI Chat App from Scratch (Part 1)

Mon, 20 Jan 2025 10:19:38 +0100

Microservices Architecture and Local Development

Photo by Danist Soh on Unsplash

Introduction

A quick demo of the app. We start a new chat, come back to that same chat, and start another chat. We will now build this app locally and make it available at localhost.

You can find the codebase at https://github.com/jsbaan/ai-app-from-scratch. Throughout this post I will link to specific lines of code with this hyperlink robot 🤖 (try it!)

Microservices and APIs

Architecture

Let’s make this more concrete. We want a web page where users can chat with a language model and come back to their previous chats. Our architecture will look like this:

Local architecture of the app. Each service runs in its own Docker container and communicates over a private network. Made by author in draw.io.

The structure of this post follows the components in our architecture (click to jump to the section):

Language model API. A llama.cpp language model inference server running the quantized Qwen2.5–0.5B-Instruct model 🤖.
PostgreSQL database server. A database that stores chats and messages 🤖.
Database API. A FastAPI and Uvicorn Python server that queries the PostgreSQL database 🤖.
User interface. A FastAPI and Uvicorn Python server that serves HTML and support session-based authentication 🤖.
Private Docker network. For communication between microservices 🤖.
Nginx reverse proxy. A gateway between the outside world and network-isolated services 🤖.
Docker Compose. A container orchestration tool to easily run manage our services together 🤖.

1. Language model API

As for the actual language model, I chose the quantized Qwen2.5–0.5B-Instruct model from Alibaba Cloud, whose responses are surprisingly coherent given how small it is.

1.1 Running the language model API

docker run
	--name lm-api \
	--volume $PROJECT_PATH/lm-api/gguf_models:/models \
	--publish 8000:80 \ # add this to make the API accessible on localhost
	ghcr.io/ggerganov/llama.cpp:server 
		-m /models/qwen2-0_5b-instruct-q5_k_m.gguf --port 80 --host 0.0.0.0 --predict 512 --flash-attn

Ultimately we will use Docker Compose to run this container together with the others 🤖.

1.2 Accessing the container

Since Docker containers are completely isolated from everything else on their host machine, i.e., our computer, we can’t reach our language model API yet.

1.3 Testing the language model API

Let’s test the language model server by sending a POST request with a short chat history.

curl -X POST  \
-H "Content-Type: application/json" \
-d '{
	"messages": [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "assistant", "content": "Hello, how can I assist you today?"},
    {"role": "user", "content": "Hi, what is an API?"}
	],
	"max_tokens": 10
	}'

The response is JSON and the generated text is under choices.message.content: “An API (Application Programming Interface) is a specification…”.

Perfect! Ultimately, our UI service will be the one to send requests to the language model API, and define the system prompt and opening message 🤖.

2. PostgreSQL database server

docker run --name db --publish 5432:5432 --env POSTGRES_USER=myuser --env POSTGRES_PASSWORD=mypassword postgres

pg_isready -U joris -h localhost -d postgres
> localhost:5432 - accepting connections

3. Database API

Databases often have a separate API server sitting in front to control access, enforce extra security, and provide a simple, standardized interface that abstracts away the database’s complexity.

3.1 Quick FastAPI example

Let’s quickly get a feeling for FastAPI and look at a minimal example app with a single GET endpoint /hello.

from fastapi import FastAPI

# FastAPI app object that the Uvicorn web server will load and serve
my_app = FastAPI()

# Decorator telling FastAPI that function below handles GET requests to /hello
@my_app.get("/hello") 
def read_hello():
  # Define this endpoint's response
    return {"Hello": "World"}

We can serve our app at http://localhost:8080 by running the Uvicorn server.

uvicorn main.py:my_app --host 0.0.0.0 --port 8080

If we now send a GET request to our endpoint by visiting http://localhost:8080/hello in our browser, we receive the JSON response {"Hello": "World"} !

3.2 Connecting to the database

3.3 Interacting with the database

class Chat(Base):
  __tablename__ = "chats"

  # Unique identifier for each chat that will be generated automatically.
  id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)

  # Username associated with the chat. Index is created for faster lookups.
  username = Column(String, index=True)

  # Session ID associated with the chat. 
  # Used to "scope" chats, i.e., users can only access chats from their session.
  session_id = Column(String, index=True)

  # The relationship function links the Chat model to the Message model.
  # The back_populates flag creates a bidirectional relationship.
  messages = relationship("Message", back_populates="owner")

Database tables are typically created using migration tools like Alembic, but we’ll simply ask SQLAlchemy to create them in main.py 🤖.

3.4 Endpoint request and response validation

We define the Pydantic schemas for the database-api in schemas.py 🤖 and use them in the endpoint definitions in main.py 🤖, too. For example, this is the endpoint to create a new chat:

@app.post("/chats", response_model=schemas.Chat)
async def create_chat(chat: schemas.ChatCreate, db: Session = Depends(get_db)):
    db_chat = crud.create_chat(db, chat)
    return db_chat

We can see that it expects a ChatCreate request body and Chat response body. FastAPI verifies and converts the request and response bodies according to these schemas 🤖:

class ChatCreate(BaseModel):
    username: str
    messages: List[MessageCreate] = []
    session_id: str

class Chat(ChatCreate):
    id: UUID
    messages: List[Message] = []

Note: our SQLAlchemy models for the database should not be confused with these Pydantic schemas for endpoint input/output validation.

3.5 Running the database API

We can serve the database API using Uvicorn, making it available at http://localhost:8001.

cd $PROJECT_PATH/db-api
uvicorn app.main.py:app --host 0.0.0.0 --port 8001

docker build --tag db-api-image $PROJECT_PATH/db-api
docker run --name db-api --publish 8001:80 --env POSTGRES_USERNAME= --env POSTGRES_PASSWORD= --env POSTGRES_HOST= db-api-image

4. User interface

Screenshot of the UI’s interactive documentation.

4.1 Homepage

4.2 Chat Page

4.3 Authentication & user sessions

4.4 Running the UI

To run the UI in a Docker container, we follow the same recipe as the database API, adding the hostnames of the database API and language model API as environment variables.

docker build --tag chat-ui-image $PROJECT_PATH/chat-ui
docker run --name chat-ui --publish 8002:80 --env LM_API_URL= --env DB_API_URL= chat-ui-image

How do we know the hostnames of the two APIs? We will look networking and communication next.

5. Private Docker network

Our app’s microservices architecture. Made by author in draw.io.

docker network create --driver bridge chat-net

6. Nginx reverse proxy

http { server { listen 80; location / { proxy_pass http://chat-ui } } }

docker run --network chat-net --publish 80:80 --volume $PROJECT_PATH/nginx.conf:/etc/nginx/nginx.conf nginx

7. Docker Compose

Inside the project directory we can start all services with a single command:

docker compose up --build

Final thoughts

Roadmap

There is a lot we could do to improve this app. Here are some things I would work on given more time.

Reliability. To make the system more mature, I’d add unit and integration tests and a better database setup like Alembic allowing for migrations.

Acknowledgements

Thanks to Dennis Ulmer, Bryan Eikema and David Stap for initial feedback or proofreading.

AI usage

Here are some additional resources that I found useful during this project.

Django vs Flask vs FastAPI YouTube video by Patrick Loeber.
The FastAPI tutorial was by far most helpful.
Docker documentation, especially the networking overview, bridge network intro, docker-compose quickstart and networks in docker-compose.
SQLAlchemy docs and their Object-Relational Mapper (ORM) tutorial.
PostgreSQL Cheat Sheet.

Should I make the swap?

Thu, 02 Jan 2025 02:05:51 +0100

I installed a Windows security update today and am less than pleased with its changes. I now have a permanent desktop icon titled "learn more about this picture" that takes me to Bing when I have a wallpaper engine covering up whatever garbage it's trying to show me. The search bar is now permanently affixed to my taskbar, which I cannot remove without Windows Pro. Copilot is now a crucial part of Windows, so I can't uninstall it. To top it all off, however, the update is a part of the Windows security line, so if I rollback, I am at a greater risk of having security vulnerabilities on my machine since I can't skip out on the 'features' of this update that I would rather not be forced into.

I have been looking at Linux Mint Cinnamon for a long time and might finally be ready to jump. My biggest concern, however, is that I use this computer for a lot of stuff that I worry won't have Linux support. I was hoping you all could quell some of my worries and give me the confidence to finally make the swap.

First of all, I use Steam a lot on this computer. It's actually the biggest reason I haven't moved to Linux yet. I have A LOT of games on here that I am worried I will no longer be able to play if I am on cinnamon. I know there are some compatibility options for Windows software, such as Wine and Proton, but I haven't messed with them and worry they aren't as 'perfect' as I have been told.

Additionally, I do a lot of 3d modeling and game development in my free time. Most of what I do is on Autocad, Fusion, Revit, Maya, and Blender. Much of this software doesn't have native Linux support. I am not concerned with running VMs, but I worry that this kind of software will have a lot of trouble in a VM as they tend to be pretty resource-intensive.

For game development, I often jump between Godot, Gamemaker Studio 2, and Unity. Godot has native Linux support, but GmS2 and Unity are both developed specifically for Ubuntu. I worry that they won't run smoothly on Linux Mint. I would rather jump through the hoops of uninstalling all this Windows crap than run Ubuntu. How true to Ubuntu is Linux Mint? I know it's a branch of Ubuntu, but is it pretty guaranteed that if something runs on Ubuntu, it will run on Mint?

Finally, I do a lot of software development as well. I use VSCode, Eclipse, IntelliJ, and less often PyCharm. I use all of these instead of sticking to just one because I personally prefer VSCode, but my work requires the other stuff for security reasons, so I have and regularly run them all. I am not worried about these so much, as they all have native Debian support.

So what do you guys think? Is it just anxiety and unfounded worry getting the better of me, or am I right to be apprehensive about the stability of my tools and data if I make the jump? I do have over a terabyte of data I would like to preserve on this computer (I am still working on adding a personal NAS to my home network), so the fear of losing some or all of that is also very real to me. What do you guys think? Any words of wisdom for a chronic worrier?

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Should I make the swap?

Thu, 02 Jan 2025 02:05:50 +0100

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heise+ | Python-Entwicklung: PyCharm und VS Code im Vergleich

Wed, 20 Nov 2024 12:15:43 +0100

Tiefe Integration bei PyCharm, und ein ganzer Zoo von Plug-ins bei VS Code – trotz unterschiedlicher Konzepte liegen beide Werkzeuge dicht beieinander.

A Shout Out to MX Linux for Casual Nerd Users

Tue, 19 Nov 2024 14:36:20 +0100

I switched over to MX-linux because I had some fairly old laptop that I was too attached to to exchange for something newer. Since, I have fallen so in love with the system, that I use it for every computer in my possession. I have enjoyed it so much that I just had to post something about it and I would hate if such a great system would become unused and eventually fall into decay.

I am using the latest version of MX linux with the XFCE desktop environment. The speed up from switching from ubuntu 22 to MX is extremely noticeable on some of my older devices. What I love the most about it is that it cuts down a lot of the excessive stuff in ubuntu, but keeps what I feel are the essential features. Theres support for multiple workspaces, there's a full set of basic programs for editing files, viewing PDFs etc, there's the usual GUI-based tools for configuring stuff like ethernet connections, disk partitions, mouse options and keyboard layout. And also, every software that I have used for ubuntu and tried on MX -has worked. This includes steam, inkscape, blender, pycharm, spyder, VS code and fiji.

Great system, super happy that this project exists. Writing this on a dell M4800 on MX, still going strong after more than 10 years of service. I run MX on most of my old <2009 mac pros which would basically melt when running ubuntu.

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JetBrains Offers Free Use of WebStorm and Rider IDEs

Sat, 26 Oct 2024 01:33:52 +0200

An anonymous reader quotes a report from InfoWorld: Select developers now are getting free access to JetBrains' WebStorm and Rider IDEs. The company on October 24 announced it has launched non-commercial licenses for its WebStorm JavaScript and TypeScript IDE and the Rider cross-platform .NET and game development IDE. As of now, developers using these IDEs for non-commercial purposes, such as open source project development or content creation, can use them for free. JetBrains views the move as expanding the availability of these IDEs to a broader swath of developer roles. More than two-thirds of developers code outside of work as a hobby and nearly 40% code for educational and learning purposes outside of work, the company said."Previously this year, JetBrains released other products under the same terms for non-commercial use, including RustRover, an IDE for Rust development, and Aqua, an IDE designed for test automation," notes InfoWorld. "JetBrains also provides community editions of IntelliJ and PyCharm, IDEs for Java and Python, respectively, which can be used to build proprietary and commercial software." JetBrains has an FAQ section with additional details about the change.

Read more of this story at Slashdot.

Two New IDE’s get Veracode Scan

Mon, 30 Sep 2024 20:04:28 +0200

We're happy to announce two new Veracode Scan products: Veracode Scan for Eclipse and Veracode Scan for Visual Studio. Building on the success and adoption of Veracode Scan in Visual Studio Code, IntelliJ, PyCharm, and Rider, we're releasing versions for Eclipse and Visual Studio. Now the power of Veracode’s outstandingly accurate Static Application Scanning is avaialble two of the most widely used and customer-requested IDE’s. Veracode Scan for Eclipse includes Veracode Static, Veracode SCA and Veracode Fix. Veracode Scan for Visual Studio launches with Veracode Static, with Fix and SCA following shortly. Veracode Scan IDE extensions cut developer toil by minimizing the time between coding and feedback. Developers can scan code before pushing it into source management tools (where it can and probably should be rescanned using one of Veracode’s popular CI/CD integrations), get fast feedback and then use Veracode Fix - our AI code security remediation…

Python Developer Survey: 55% Use Linux, 6% Use Python 2

Sun, 01 Sep 2024 05:17:39 +0200

More than 25,000 Python developers from nearly 200 countries took the 7th annual Python Developers Survey between November 2023 and February 2024, with 85% saying Python was their main language. Some interesting findings: Though Python 2 reached "end-of-life" status in April of 2020, last year's survey found 7% of respondents were still using Python 2. This year's survey found that number has finally dropped... to 6%. "Almost half of Python 2 holdouts are under 21 years old," the survey results point out, "and a third are students. Perhaps courses are still using Python 2?" Meanwhile, 73% are using one of the last three versions of Python (3.10, 3.11, or 3.12) "The share of developers using Linux as their development environment has decreased through the years: compared with 2021, it's dropped by 8 percentage points." [The graphic is a little confusing, showing 55% using Linux, 55% using Windows, 29% on MacOS, 2% on BSD, and 1% on "Other."] Visual Studio Code is the most popular IDE (22%), followed by Jupyter Notebook (20%) and Vim (17%). The next-most popular IDEs were PyCharm Community Edition (13%), JupyterLab (12%), NotePad++ (11%) and Sublime Text (9%). Interestingly, just 23% of the 25,000 respondents said they only used one IDE, with 38% saying they used two, 21% using three, and 19% using four or more. [The annual survey is a collaboration between the Python Software Foundation and JetBrains.] 37% said they'd contributed to open-source projects within the last year. (77% of those contributed code, while 38% contributed documentation, 35% contributed governance/leadership/maintainer duties, and 33% contributed tests...) For "age range," nearly one-third (32%) said 21-29 (with another 8% choosing 18-20). Another 33% said 30-39, while 16% said 40-49, 7% said 50-59, and 3% chose "60 or older." 49% of respondents said they had less than two years of programming experience, with 33% saying "less than 1 year" and 16% saying "1-2 years." (34% of developers also said they practiced collaborative development.) And here's how the 25,000 developers answered the question: how long have you been programming in Python? Less than 1 year: 25% 1-2 years: 16% 3-5 years: 26% 6-10 years: 19% 11+ years: 13% So what are they doing with Python? Among those who'd said Python was their main language: Data analysis: 44% Web development: 44% Machine learning: 34% Data engineering: 28% Academic research: 26% DevOps / Systems administration / Writing automation scripts 26% Programming of web parsers / scrapers / crawlers: 25% 62% were "fully employed by a company," while the next-largest category was "student" (12%) with another 5% in "working student". There were also categories for "self-employed" (6%), "freelancer" (another 6%), and "partially employed by a company" (4%). Another 4% said they were unemployed. In other news, the Python Software Foundation board has also "decided to invest more in connecting and serving the global Python community" by hosting monthly "office hours" on their Discord channel.

Read more of this story at Slashdot.

Developer Snapshots: Kleinere News der letzten Woche

Sat, 24 Aug 2024 08:32:58 +0200

Die Übersicht enthält kleine, aber interessante Meldungen zu Cloud Hypervisor, Linux.org, PyCharm, OpenAPI-Tools, Cequence, W3C, Aider, Rust, pgmq und Qrisp.

An Introduction to Quantum Computers and Quantum Coding

Fri, 23 Aug 2024 20:51:47 +0200

Demystifying the novel world of quantum computing, quantum programming, and quantum algorithms.

Photo by Manuel on Unsplash

Preface:

This is an adaptation of something I wrote for one of my physics courses, so it assumes a level of knowledge in mathematics and science. The topics referenced in the article include some linear algebra, superposition, basic algorithm concepts, and a bit of modular arithmetic when discussing algorithms. However, since you’re reading an article on quantum computing you’re likely savvy enough to look up and understand all the ideas referenced. Furthermore, all sources are cited, so you can explore all of those for deeper learning. Also, all images and figures used were generated by me, using tools like Microsoft Word, PyCharm, and diagrams.net unless otherwise noted.

Why Does This Matter?

Before committing to a somewhat lengthy and dense read, you might be wondering why this matters to you, even if you’ve never touched a quantum computer. The reality is that breakthroughs are happening all the time, and quantum computing holds real relevance in different computational fields, especially machine learning. For starters, the quantum analogs of classical algorithms have potential to be much more efficient.

One example of this is the Quantum Support Vector Machine. Notably, classical SVMs often use the kernel trick to transform data into a higher dimensional space so that they can locate a separating hyperplane. However, quantum SVMs would have a significant advantage as they naturally represent data in exponentially higher dimensional spaces without the computational strain that classical computers face. This allows quantum SVMs to handle more complex datasets more efficiently.

Another example is in the realm of neural network training. The basic unit of quantum computation, the qubit, can be entangled with other qubits, creating correlations that classical systems can’t replicate. While entanglement offers possibilities for correlated updates across a quantum neural network, it’s important to note that the concept is still under research.

Part 1: Introduction to Quantum Computing

Quantum computers function very differently from classical computers, leveraging quantum properties and phenomena to greatly increase computational power. At a high level, there are a few tenets of quantum computing that differentiate it from classical computation: qubits versus bits, quantum versus classical logic gates, the presence of quantum phenomena, and the opportunities offered by quantum computing’s enhanced computational capabilities.

At the core of quantum computing is the qubit, which serves as the fundamental unit of computation in a quantum computer– taking the place of a classical computer’s bit. While the bit can occupy either the 0 or 1 state exclusively, the qubit can be in a superposition of the 0 and 1 states (Microsoft, n.d.). It can be very hard to conceptualize the qubit; where the classical bit is simply an electric current or absence of electric current, the qubit can take many different physical forms.

These include “spin” qubits, which is the most straightforward example. This type of qubit uses the spin property of a particle (generally an electron) to complete computations. To initialize a spin qubit, an electron is trapped using a quantum dot, for example, then manipulated using magnetic fields that interact with their spin state (Harvey, 2024). The computational difference between a bit and qubit is significant, and stems from the qubit’s ability to be affected by quantum phenomena like superposition between the 0 and 1 states, and entanglement with other qubits (Microsoft, n.d.).

One tool that is very helpful in visualizing the state of a qubit is the Bloch sphere; it is effectively just a sphere with north and south poles representing |0⟩ and |1⟩ respectively, and all other points along the sphere representing linear combinations of the poles’ values (Microsoft, 2024). Since this representation of the qubit uses a complex vector space, the state of the qubit will be described in Dirac notation hereafter. This visualization of the superposition state of a qubit aids in the understanding of quantum logic gates especially because it allows for a geometric understanding of the operation being performed. Generally, when a qubit is initialized it is in the z-basis |0⟩ state, which is analogous to the classical 0 state (Quantum-Inspire by QuTech, 2024).

Bloch Sphere illustration, Wikipedia. (n.d.) https://en.wikipedia.org/wiki/Bloch_sphere. (GFDL License)

Another key difference between the classical and quantum computer is the logic gates: while classical computers use AND, OR, NOT, etc. to perform basic logic operations, quantum computers use quantum logic gates such as X, Hadamard, Toffoli, and CNOT (Wikipedia, 2024). These quantum gates are used to perform logical operations on a single qubit or a very small number of qubits, and can be combined with others to perform more complex operations and manipulations.

First, the X gate is very similar to the classical NOT gate: it inverts the phase of a qubit– if a qubit is in the |0⟩ state, it inverts to the |1⟩ state, and vice versa.
Next, the Hadamard gate is used to put a qubit in the |0⟩ state into an equal superposition between |1⟩ and |0⟩. Third, the Toffoli gate is an example of a multi-qubit gate.
The Toffoli gate operates with three qubits, two of them are “control” and one is the “target.” In the Toffoli gate it will invert the target qubit only if the two control qubits are in the |1⟩ state (Roy & Chakrabarti, 2024).
Finally, the CNOT gate is a very common gate used in quantum computing, and we will examine a use case later on. The CNOT is also a multiple qubit gate, as it has one target qubit and one control qubit; when the control qubit is in the |1⟩ state, it inverts the phase of the target qubit.

These are just a few examples of many interesting quantum logic gates, and it is important to note that unlike classical logic gates, there is not necessarily a physical “gate” that the qubits pass through, but rather these are just operations that are performed on the qubit which take different forms depending on many factors.

A third major difference between classical and quantum computing is the presence of quantum phenomena such as superposition, superconduction, entanglement and interference. These properties are used in different ways depending on the methods used to perform quantum computations (Microsoft Azure, 2024). Another property that is present is quantum decoherence, which poses a serious problem to the development of useful or widespread quantum computing. Quantum decoherence is when a particle in superposition interacts with its environment and becomes entangled with the environment, ultimately interfering with the computational outcome (Brandt, 1999).

The computational advances of a quantum computer are great: take, for example, the algorithm used for finding the prime factors of an integer. In classical computing, one of the leading prime factorization algorithms is General Number Field Sieve (Wikipedia, 2024). The program runs at a quasi-polynomial time complexity, and it shows how hard it can be to factor a very large number. Compared to the leading quantum algorithm, Shor’s Algorithm, which runs in logarithmic space complexity, and a polylogarithmic time complexity, which is once again a complicated expression, but boils down to the fact that it is vastly more efficient (Li et al., 2022). Obviously this is just one example, but it serves as a testament to the power of quantum computing– the power to turn a program which runs in exponential time into a program which runs in logarithmic time is truly remarkable.

Part 2: Quantum Programming: Languages, Compilers and Algorithms

Though their hardware is fundamentally different from classical computers, quantum computers are programmed using languages often similar in syntax to classical languages. These include QCL, Qiskit, and Q#, who are based around the syntax of C, Python, and C#/F# respectively. Furthermore, their compilers are built with C++, Python and C++, and C# respectively. (IonQ, 2024). Thus, classical and quantum languages can be very similar syntactically– the main difference comes from the content of the programs, and how quantum algorithms are structured.

Before examining different languages, their syntaxes, and how they compare to the classical languages that they’re based around, it’s important to understand the content of a quantum program and why no matter how similar the syntax is, there is an unbridgeable gap between a classical and quantum program.

This stems from the mechanics of a quantum computer– as discussed before, quantum computation is based around holding qubits in superposition, and applying different “gates” to them– effectively transformations along the Bloch sphere that they are represented by. What that boils down to is the fact that unlike a classical computer, where you write a program which will utilize a pre-made circuit to perform computations, quantum programming is the act of actually encoding the circuit. Let’s examine some pseudo code and its associated quantum circuit to better understand this. Maybe the simplest possible quantum program/circuit, the following program simply initializes a qubit, applies a Hadamard gate to put it into a superposition, then measures the state of the qubit.

Image by author.

The associated quantum circuit for this program is:

The “H” represents a Hadamrd gate, and the meter represents a measurement being taken. Image by author.

The double line following the measurement symbol indicates that the qubit is no longer in a superposition, but rather one of two discrete states (0 or 1) since its wave function was collapsed during the measurement.

To get a better feel for the syntax of different quantum languages, let’s look at programs in the three aforementioned languages that all serve identical purposes. All three programs are made to create a Bell state, which is an entangled state of two qubits. The gates (operations) applied to the two qubits are: Hadamard on the first qubit, 0, then on the second qubit, 1, with the first qubit as the control. The function of the CNOT gate is effectively just to entangle two qubits (Rioux, 2023).

#Qiskit (Python Basd)
#Create a quantum circuit with two qubits
qc = QuantumCircuit(2)

#Apply a Hadamard gate on the first qubit
qc.h(0)

#Apply a CNOT gate with the first qubit as control and the second qubit as target
qc.cx(0, 1)

//Q# (C#/F# based)
namespace BellState{
  operation PrepareBellState() : Unit{
    using (qubits = Qubit[2]) {
      //Apply a Hadamard gate on the first Qubit
      H(qubits[0]);
      //Apply a CNOT gate with the first qubit as control and the second qbit as target
      CNOT(qubits[0], qubits[1]);
    }
  }
}

//QCL (C based)
init {
  qubits q[2]
  //Apply a Hadamard gate on the first qubit
  H(q[0]);
  //Apply a CNOT gate with the first qubit as control and the second as target
  CNOT(q[0], q[1]);
}

Unsurprisingly, the quantum programs look very similar in syntax to the languages each is based on– for example the Pythonic program uses a couple built-in methods and doesn’t have much else going on and the C# based program is full of curly brackets. Reviewing the syntax of a few quantum languages is helpful to understand what a quantum program looks like, but the reality is that the hardware being used is so different that the actual code in a quantum program would be useless to a classical computer, and vice versa. Because of that, it would be much more interesting to analyze two algorithms made for the same purpose, one classical and one quantum, and dissect the different steps taken in each case to achieve the result.

Recall the example presented in Part 1 (GNFS and Shor’s algorithm), where we looked at the time complexities of two prime factorization algorithms. As both algorithms are rather abstract and complex, it may be easier to understand their respective theories in paragraph format instead of examining their pseudo code.

The classical algorithm, General Number Field Sieve, can be summarized into five main algorithmic steps (Case, n.d.). Throughout the explanation, “N” refers to the number being factored.

The first step is polynomial selection: this step involves selecting two polynomials such that they multiply to smooth numbers when evaluated at certain points modulo N.
The next step is the “sieve” step: the goal is to find sets of integers (a, b) such that 𝑓(𝑎)⋅𝑔(𝑏) ≡ ℎ2(mod N) where h is a smooth number, and store all values (a, b, and h).
The third step is the matrix step: a large matrix, A, is constructed from the relations found in the sieve step.
Next use Gaussian elimination to reduce A to a simpler form while preserving its properties. This process will identify a set of linearly independent relations.
Use linnear algebra methods such as Lanczos algorithm to find the null space of the matrix– this will give vectors that correspond to dependencies among the relations.
Combining the relations found before will produce squares in modulo N, which after further mathematical manipulation give two integers X and Y.
These two integers are used to find the non trivial factors of N by computing the GCD of X — Y and X + Y with respect to N (Case, n.d.). That method is described by quasi-polynomial complexity, which, while it does run in sub-polynomial time, is much slower than the quantum method, Shor’s algorithm.

The process of calculating an integer N’s prime factors using Shor’s algorithm is entirely different from using GNFS. Shor’s algorithm can be broken down into a few main steps.

The first step uses classical computing: pick a random integer r such that 1 < r < N, calculate their GCD’s and if it does not equal 1, it is a non-trivial factor of N.
The next step is to prepare the needed qubits– we do this with two quantum registers, which function just like classical registers. In the first register there are enough qubits to represent integers from 0 to q–1 where q is a power of 2 that is at least N². The second register has enough qubits to represent integers from 0 to N–1.
The next step deviates from classical computing heavily: to put the entire first register into a superposition, apply a Hadamard transform to each qubit.
Next use a quantum circuit to compute the function f(x) = r^x mod(N) and store the result in the second register; this will entangle the first and second registers.
Next measure the second register– this will collapse it into a state |k⟩ (where k = r^x mod(N)) which leaves the first register in a superposition of values x that map to |k⟩.Now the period of the function f(x)=r^x mod(N) can be expressed as T.
The penultimate step of the algorithm is to apply a quantum fourier transform (QFT) to the first register, which will yield a series of peaks in the frequency domain corresponding to values of 1/T.
The final step in the quantum computation is to measure the first register– the result will be an integer, B, such that B is q/T, recall q from when we defined the first register. Having completed the quantum computation, you then move onto the classical post-processing step to get the final result.

The post-processing involves manipulating the measured result B to get the period, T. If T is even, compute the GCD of N with r^(T/2) + 1 and r^(T/2) - 1, which will yield non-trivial factors of N. If T is odd, repeat algorithm with a different r value. This program’s polylogarithmic time complexity is very efficient, especially compared to the GNFS algorithm (Pavlidis & Gizopoulos, 2022).

Here is a visual representation of the flow of both algorithms to aid understanding, where red is the beginning step, blue is the GNFS algorithm, and green is Shor’s algorithm:

Blue steps correspond to GNFS, and green steps correspond to Shor’s Algorithm. Image by author.

What enables Shor’s algorithm to run so much faster than the GNFS is the fundamentally different computational concepts being used: Shor’s algorithm leverages quantum mechanics to achieve polynomial time complexity. This speedup is primarily due to quantum parallelism (the ability to perform many quantum operations at the same time) and the efficient execution of the quantum Fourier transform, which are impossible in classical computing. By utilizing superposition and entanglement, Shor’s algorithm reduces factoring to a period-finding problem, solved exponentially faster than classical methods (Brandt, 1999).

Obviously both algorithms are very complex, but they serve as an excellent example since the problem of factoring a large integer is something a quantum computer can do much faster than a classical computer. A much simpler example that we can analyze the quantum code for is a quantum take on rock-paper-scissors (or a coin toss if that’s easier to think about). Two players each initialize a qubit (one each) to the |0⟩ state and apply a Hadamard gate which puts it into an equal superposition between |0⟩ and |1⟩. Finally, both qubits are measured– if both qubits collapse to the |0⟩ or |1⟩ state, it is a draw. Otherwise, whoever’s qubit collapsed to the |0⟩ state loses, and the one who’s qubit collapsed to the |1⟩ state wins. Let’s write the code to run this program in Qiskit:

qc = QuantumCircuit(2, 2)  # initialize a quantum circuit with 2 qubits and 2 classical bits

qc.h(0)  # apply Hadamrd gate to qubit 0, this is Bob's qubit
qc.h(1)  # apply Hadamard gate to qubit 1, this is Alice's qubit

qc.measure(0, 0) # measure Bob's qubit and map it to classical bit 0
qc.measure(1, 1) # measure Alice's qubit and map it to classical bit 1

print(qc) # prints the quantum circuit accociated with this program

The output of that code is simply the quantum circuit associated with the program, since it never actually runs the circuit on a quantum computer. However, that is the general format used when defining a very basic quantum circuit– a number of qubits and bits are allocated to it, then stating– in order– the operations to be performed on each qubit. The output of this code, which is just a visual representation of the circuit is:

The boxes with “H” represent Hadamard gates, those with an “X” represent CNOT gates, and those with an “M” represent measurements being taken. Image by author.

Before we can run this program on a quantum computer, there are a few steps we need to take. The most important is optimizing the circuit; not all quantum computers have the same ability to operate on qubits with certain gates, and they don’t always have the same connectivity of qubits. We need to add this circuit optimization into our code to prepare it to run on a real quantum computer. To do this we use the following code which defines our access to the IBM Quantum Backend using an IBM API key, then runs an optimization of the circuit, printing the optimized circuit.

print(qc) # prints the quantum circuit accociated with this program

service = QiskitRuntimeService(channel="ibm_quantum", token="your_token")

backend = service.least_busy(simulator=False, operational=True)

pm = generate_preset_pass_manager(backend=backend, optimization_level=1)

isa_circuit = pm.run(qc)

print(isa_circuit)

The output of this program is less important since it is just a more complex version of the same circuit, but it results in a circuit that is optimized for an IBM Quantum computer and while it looks much different and more complicated, it will function the same as the circuit from earlier.

In conclusion, while the topic of quantum programming can be daunting due to its many languages and contrasting algorithms, as well as the background in math, physics, and computing needed to understand it, when broken down right it’s not so bad. Through incremental learning it’s very achievable to understand quantum computing. Furthermore, quantum computing has fascinating aspects in many STEM fields– number theory, linear algebra, calculus, and discrete mathematics all apply to the theoretical side of quantum algorithms; engineering, physics, computer science, and logic all apply to the actual design of quantum algorithms. Then again, the more you learn about the fascinating realm of quantum computing, the more you may find yourself feeling like Richard Feynman’s famous quote: “I’m smart enough to know that I’m dumb.” (Goodreads, 2024)

References

Adedoyin, A., & et. al. (2022, January 8). Quantum Algorithm Implementations for Beginners. ACM Digital Library. Retrieved May 27, 2024, from https://dl.acm.org/doi/10.1145/3517340#d1e3003

Brandt, H. E. (1999, November). Qubit devices and the issue of quantum decoherence. Science Direct. Retrieved May 20, 2024, from https://www.sciencedirect.com/science/article/pii/S0079672799000038

Brubaker, B. (2023, October 17). Thirty Years Later, a Speed Boost for Quantum Factoring. Quanta Magazine. Retrieved May 27, 2024, from https://www.quantamagazine.org/thirty-years-later-a-speed-boost-for-quantum-factoring-20231017/

Case, M. (n.d.). A Beginner’s Guide To The General Number Field Sieve. UMD Computer Science. Retrieved May 26, 2024, from https://www.cs.umd.edu/~gasarch/TOPICS/factoring/NFSmadeeasy.pdf

Goodreads. (2024). Quotes by Richard P. Feynman (Author of Surely You’re Joking, Mr. Feynman!). Goodreads. Retrieved May 27, 2024, from https://www.goodreads.com/author/quotes/1429989.Richard_P_Feynman

Harvey, S. P. (2024, March 5). Quantum Dots/Spin Qubits. Oxford University Press and The American Institute of Physics. Retrieved May 19, 2024, from https://oxfordre.com/physics/display/10.1093/acrefore/9780190871994.001.0001/acrefore-9780190871994-e-83

IBM. (2024). IBM Qiskit Docs. IBM Quantum Documentation. Retrieved May 26, 2024, from https://docs.quantum.ibm.com/

IonQ. (2024, March 14). Hello Many Worlds in Seven Quantum Languages. IonQ. Retrieved May 26, 2024, from https://ionq.com/docs/hello-many-worlds-seven-quantum-languages

Li, J., Peng, X., Du, J., & Suter, D. (2022, January 8). An Efficient Exact Quantum Algorithm for the Integer Square-free Decomposition Problem. Nature. Retrieved May 26, 2024, from https://www.nature.com/articles/srep00260

Microsoft. (n.d.). What is a Qubit? Microsoft Azure. Retrieved May 19, 2024, from https://azure.microsoft.com/en-us/resources/cloud-computing-dictionary/what-is-a-qubit

Microsoft. (2024). Azure Quantum | Single-qubit gates. Azure Quantum. Retrieved May 20, 2024, from https://quantum.microsoft.com/en-us/explore/concepts/single-qubit-gates

Microsoft Azure. (2024, January 12). Understanding quantum computing — Azure Quantum. Microsoft Learn. Retrieved May 20, 2024, from https://learn.microsoft.com/en-us/azure/quantum/overview-understanding-quantum-computing

Pavlidis, A., & Gizopoulos, D. (2022, July 19). Quantum Cryptography — Shor’s Algorithm Explained. Classiq. Retrieved May 27, 2024, from https://www.classiq.io/insights/shors-algorithm-explained

Quantum-Inspire by QuTech. (2024). Qubit basis states. Quantum Inspire. Retrieved May 20, 2024, from https://www.quantum-inspire.com/kbase/qubit-basis-states/

Rioux, F. (2023, January 10). 8.53: Bell State Exercises. Chemistry LibreTexts. Retrieved May 26, 2024, from https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Quantum_Tutorials_(Rioux)/08%3A_Quantum_Teleportation/8.53%3A_Bell_State_Exercises

Roy, S. G., & Chakrabarti, A. (2024, March 5). Toffoli Gate. Science Direct. Retrieved May 20, 2024, from https://www.sciencedirect.com/topics/computer-science/toffoli-gate

Wikipedia. (2024). General number field sieve. Wikipedia. Retrieved May 24, 2024, from https://en.wikipedia.org/wiki/General_number_field_sieve

Wikipedia. (2024, May 15). Quantum logic gate. Wikipedia. Retrieved May 19, 2024, from https://en.wikipedia.org/wiki/Quantum_logic_gate

Wikipedia. (n.d.). Bloch sphere. Wikipedia. Retrieved August 20, 2024, from https://en.wikipedia.org/wiki/Bloch_sphere

An Introduction to Quantum Computers and Quantum Coding was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

I installed PyCharm CE using tarball archive, help me add it to the overview menu as an iconed .desktop shortcut or simply an app icon that I can just click and run just like any other app.

Mon, 22 Jul 2024 10:46:10 +0200

https://preview.redd.it/k9c55q9y61ed1.png?width=706&format=png&auto=webp&s=fe13c499c62db82c0d57be144db4ab4fe476333a

I'm using Fedora Linux 40 (Gnome) and I installed PyCharm Community using tar.gz file from the official website but everytime I wanna open it I have to go to the extracted folder and run PyCharm CE using the terminal but I wanna add it to the overview so that I can just click and run it. I created this .desktop file using text editor and I thought it would work, (as it usually does, but I'm still mostly a noob so idk what went wrong), but after creating the file and making it executable and giving it all the neccesary permissions it just didn't work, so I tried to update the Desktop Database and then it said "Key File does not start with a group" and I have no idea what to do next.

Can any of you please help me anyhow add PyCharm to the overview menu, I'd be really gratefull.I'm using Fedora Linux 40 (Gnome) and I installed PyCharm Community using tar.gz file from the official website but everytime I wanna open it I have to go to the extracted folder and run PyCharm CE using the terminal but I wanna add it to the overview so that can I just click and run it. I created this .desktop file using text editor and I thought it would work, (as it usually does, but I'm still mostly a noob so idk what went wrong), but after creating the file and making it executable and giving it all the neccesary permissions it just didn't work, so I tried to update the Desktop Database and then it said "Key File does not start with a group" and I have no idea what to do next.

Can any of you please help me anyhow add PyCharm to the overview menu, I'd be really gratefull.

submitted by /u/GunSmith_XX7
[link] [comments]

Available Now: Veracode Scan for JetBrains IDEs

Mon, 24 Jun 2024 19:21:55 +0200

Veracode Scan for VS Code was one of the big hits on the expo floor at the RSA Security conference in May this year. People liked the integration of Veracode Static, Veracode SCA, and Veracode Fix into a single extension, giving developers the tools to scan their code and resolve problems with AI assistance while they are actively developing code. What they asked for was more IDE support, and so we’re pleased to announce the availability of Veracode SAST, Veracode SCA, and Veracode Fix in three IDEs from JetBrains: IntelliJ Pycharm Ryder Installation is simple, simply search for Veracode Scan from the Plugins dialog and install. If you don’t have Veracode API credentials, you will need to generate them and configure a credentials file or set environment variables. Once you’ve done that, you will be ready to start scanning your code for flaws, analyzing your third-party software for vulnerabilities, and then remediating problems with Veracode Fix. Let’s take a quick look at…

Now Avaialble: Veracode Scan for JetBrains IDEs

Thu, 20 Jun 2024 20:21:43 +0200

Veracode Scan for VS Code was one of the big hits on the expo floor at the RSA Security conference in May this year. People liked the integration of Veracode Static Scan, Veracode SCA, and Veracode Fix into a single extension. What they asked for was more IDE’s and so we’re pleased to announce the availability of Veracode SAST, Veracode SCA, and Veracode Fix in three IDEs from JetBrains: IntelliJ Pycharm Ryder Installation is simple, simply search for Veracode Scan from the Plugins dialog and install. If you don’t have Veracode API credentials, you will need to generate them and configure a credentials file or set environment variables. Once you’ve done that, you will be ready to start scanning your code for flaws, analyzing your third-party software for vulnerabilities, then remediating problems with Veracode Fix. Let’s take a quick look at the plugin interface:

CVE-2024-37051 | JetBrains IntelliJ IDEA Access Token insufficiently protected credentials

Thu, 13 Jun 2024 09:40:35 +0200

A vulnerability classified as problematic was found in JetBrains IntelliJ IDEA, Aqua, CLion, DataGrip, DataSpell, GoLand, MPS, PhpStorm, PyCharm, Rider, RubyMine, RustRover and WebStorm. Affected by this vulnerability is an unknown functionality of the component Access Token Handler. The manipulation leads to insufficiently protected credentials. This vulnerability is known as CVE-2024-37051. The attack can be launched remotely. There is no exploit available. It is recommended to upgrade the affected component.

JetBrains Urges Urgent Patching for Critical IntelliJ Vulnerability Exposing GitHub Tokens

Wed, 12 Jun 2024 08:18:35 +0200

JetBrains Urges Urgent Patching for Critical IntelliJ Vulnerability Exposing GitHub Tokens

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JetBrains Warns of Critical Vulnerability in IntelliJ IDEs Exposing GitHub Tokens

JetBrains has issued an urgent advisory for users of its IntelliJ integrated development environment (IDE) applications, highlighting a critical vulnerability that could expose GitHub access tokens. This flaw, tracked as CVE-2024-37051, affects all IntelliJ-based IDEs from version 2023.1 onwards where the JetBrains GitHub plugin is enabled and configured.

The vulnerability was first reported on May 29, 2024, by an external security researcher. Ilya Pleskunin, JetBrains’ security support team lead, explained that the issue involves handling pull requests within the IDE, potentially allowing malicious content in pull requests to expose access tokens to unauthorized third parties.

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In response, JetBrains has released security updates addressing this critical flaw in all affected IDE versions from 2023.1 onwards. The company has also patched the vulnerable GitHub plugin and removed all impacted versions from its official plugin marketplace.

The fixed versions for IntelliJ IDEs include:

Aqua: 2024.1.2
CLion: 2023.1.7, 2023.2.4, 2023.3.5, 2024.1.3, 2024.2 EAP2
DataGrip: 2024.1.4
DataSpell: 2023.1.6, 2023.2.7, 2023.3.6, 2024.1.2
GoLand: 2023.1.6, 2023.2.7, 2023.3.7, 2024.1.3, 2024.2 EAP3
IntelliJ IDEA: 2023.1.7, 2023.2.7, 2023.3.7, 2024.1.3, 2024.2 EAP3
MPS: 2023.2.1, 2023.3.1, 2024.1 EAP2
PhpStorm: 2023.1.6, 2023.2.6, 2023.3.7, 2024.1.3, 2024.2 EAP3
PyCharm: 2023.1.6, 2023.2.7, 2023.3.6, 2024.1.3, 2024.2 EAP2
Rider: 2023.1.7, 2023.2.5, 2023.3.6, 2024.1.3
RubyMine: 2023.1.7, 2023.2.7, 2023.3.7, 2024.1.3, 2024.2 EAP4
RustRover: 2024.1.1
WebStorm: 2023.1.6, 2023.2.7, 2023.3.7, 2024.1.4

JetBrains has urged administrators to patch their systems immediately and revoke any GitHub tokens used by the affected plugin to prevent potential unauthorized access.

“In addition to working on a security fix, we contacted GitHub to help minimize the impact,” Pleskunin stated. “Due to the measures implemented during the mitigation process, the JetBrains GitHub plugin may not function as expected in older versions of JetBrains IDEs.”

Trending: Offensive Security Tool: PingRAT

Patch and Revoke Github tokens

JetBrains also advises customers who have used GitHub pull request functionality in IntelliJ IDEs to revoke any GitHub tokens linked to the vulnerable plugin. This includes tokens used with OAuth integration or Personal Access Tokens (PATs), and to delete the IntelliJ IDEA GitHub integration plugin token.

“Please note that after the token has been revoked, you will need to set up the plugin again as all plugin features, including Git operations, will stop working,” Pleskunin added.

Earlier this year, JetBrains warned of another critical vulnerability in its TeamCity On-Premises servers, which allowed attackers to gain admin privileges. Public exploit code for this vulnerability has been available since March.

Users are strongly advised to update their IntelliJ IDEs to the latest versions to ensure the security of their development environments and protect their GitHub accounts from potential exploitation.

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The post JetBrains Urges Urgent Patching for Critical IntelliJ Vulnerability Exposing GitHub Tokens first appeared on Black Hat Ethical Hacking.

[PSA] JetBrains appears to be slowing removing support for functionality on Linux

Wed, 12 Jun 2024 00:01:19 +0200

Hey r/linux

I have something I feel inclined, almost obligated to share. I do not post anywhere on the internet really. Its very rare, but I felt this was worth sharing.

For anyone that does not know JetBrains makes a bunch of different products. IntelliJ, Rubymine, PyCharm, GoLand, WebStorm, PhpStorm, and so on.

I'm going to backtrack initially and get to the most recent stuff so bare with me.

About 4 years ago all JetBrains products dropped GTK compliance with no notice. The issue being that they removed the ability for Linux window managers to detect different window types on all JetBrains products. Meaning its impossible for a window manager to determine if its an application window, a dialog/modal and or a menu.

I do not think I need to elaborate on what issues that causes on Linux. However, this was not a huge deal as most of us know you can ignore applications, windows, etc via the window manager. SO not a big issue since you could work around it with Linux itself.

3 years go by and a new major issue crops up as they effectively disabled the window manager on Linux altogether. Currently there is a 2 part workaround to get the native window manager back. This currently still works but there is no permanent fix and no activity on the ticket.

This is "kinda" writing on the wall, but given they still provide a way around the issue natively in all JetBrains products and it is officially documented on the website you can give it a "pass" as Linux is still supported.

However, as of earlier this year it is no longer possible to navigate between two or more open editor windows within the application. I have been stuck on a version of Intellij that is just over a year old because of this issue. If you have two or more editor windows open the IDE/Application will go into a state that you can not see all open windows.

_THIS_ is the writing on the wall for all JetBrains users on Linux.

I also want to mention this is not even scratching the surface of all the issues on Linux that have been stagnate or ignored. These are just the major issues that completely break usability on Linux.

I asked for a refund as my renewal date was very recent. I provided the information why and links to the tickets. NO refund yet, but within 2 hours one of my tickets was updated with another ticket as reference. In the referenced ticket I see that as of 14 days ago they will be dropping global menu support altogether for Wayland and X.

I do not want to post links to the tickets as I don't want to create a situation. But I will provide links if you DM me to look at the issues. Though all mine, theirs and others tickets can be found on youtrack with a bit of effort.

Anyway, I am a software engineer for 20 years now and have been using JetBrains products for most of my career. Now a long journey ahead to get off IntelliJ/JetBrains and for anyone that works on the JVM, if you know, you know.

submitted by /u/k3mist
[link] [comments]

problem with jetbrains program windows

Mon, 06 May 2024 13:45:56 +0200

https://pixeldrain.com/u/4S76zwCk

Could this be related to kde 6?

The same thing happened in arch linux and now it also happens in opensuse.

I have this problem that is making me extremely frustrated, has anyone experienced this and knows how to solve it?

installation via snap

operating system: opensuse

PyCharm 2024.1.1 (Community Edition) Build #PC-241.15989.155, built on April 29, 2024 Runtime version: 17.0.10+1-b1207.14 amd64 VM: OpenJDK 64-Bit Server VM by JetBrains s.r.o. Linux 6.8.9-1-default GC: G1 Young Generation, G1 Old Generation Memory: 2994M Colors: 12 Registration: project.tree.structure.show.url=false ide.experimental.ui=true Current Desktop: KDE

DataGrip 2024.1.3 Build #DB-241.17011.41, built on May 14, 2024 Licensed to Phelipe Alves Fagundes Subscription is active until September 26, 2024. For educational use only. Runtime version: 17.0.11+1-b1207.23 amd64 VM: OpenJDK 64-Bit Server VM by JetBrains s.r.o. Linux 6.8.9-1-default GC: G1 Young Generation, G1 Old Generation Memory: 2994M Colors: 12 Registration: ide.experimental.ui=true Current Desktop: KDE

submitted by /u/yurifontella
[link] [comments]

HPR4117: JAMBOREE !

Fri, 03 May 2024 03:24:41 +0200

https://github.com/freeload101/Java-Android-Magisk-Burp-Objection-Root-Emulator-Easy

Java Android Magisk Burp Objection Root Emulator Easy (JAMBOREE)
Get a working portable Python/Git/Java environment on Windows in SECONDS without having local administrator, regardless of your broken Python or other environment variables. Our open-source script downloads directly from proper sources without any binaries. While the code may not be perfect, it includes many useful PowerShell tricks.

Run Android apps and pentest without the adware and malware of BlueStacks or NOX.

Features / Request
Core        Status
RMS:Runtime Mobile Security ✔️
Brida, Burp to Frida bridge ❌
SaftyNet+ Bypass    ❌
Burp Suite Pro / CloudFlare UserAgent Workaround-ish    ✔️
ZAP Using Burp  ✔️
Google Play ✔️
Java    ✔️
Android 11 API 30   ✔️
Magisk  ✔️
Burp    ✔️
Objection   ✔️
Root    ✔️
Python  ✔️
Frida   ✔️
Certs   ✔️
AUTOMATIC1111   ✔️
AutoGPT ✔️
Bloodhound  ✔️
PyCharm ✔️
OracleLinux WSL ✔️
Ubuntu/Olamma WSL   ✔️
Postgres No admin   ✔️
SillyTavern ✔️
Volatility 3    ✔️
Arduino IDE / Duck2Spark    ✔️
Youtube Downloader Yt-dlp   ✔️

How it works:
Temporarily resets your windows $PATH environment variable to fix any issues with existing python/java installation
Build a working Python environment in seconds using a tiny 16 meg nuget.org Python binary and portable PortableGit. Our solution doesn't require a package manager like Anaconda. I would like to make it even easier to use but I don't want to spend more time developing it if nobody is going to use it! Please let me know if you like it and open bugs/suggestions/feature request etc! You can contact me at https://rmccurdy.com !

Installation/Requirements ( For Android AVD Emulator) :
Local admin just to install Android AVD Driver:
HAXM Intel driver ( https://github.com/intel/haxm )

AMD ( https://github.com/google/android-emulator-hypervisor-driver-for-amd-processors )

Usage:
Put ps1 file in a folder
Rightclick Run with PowerShell

From command prompt

powershell -ExecutionPolicy Bypass -Command "[scriptblock]::Create((Invoke-WebRequest "https://raw.githubusercontent.com/freeload101/Java-Android-Magisk-Burp-Objection-Root-Emulator-Easy/main/JAMBOREE.ps1").Content).Invoke();" More infomation on bypass Root Detection and SafeNet https://www.droidwin.com/how-to-hide-root-from-apps-via-magisk-denylist/

( Watch the Video Tutorial below it's a 3-5 min process. You only have to setup once. After that it's start burp then start AVD )

Burp/Android Emulator (Video Tutorial )
Update Video with 7minsec Podcast!

https://youtu.be/XdXleap0BiM

name

(Video Tutorial)

https://youtu.be/pYv4UwP3BaU

name

USB Rubber Ducky Scripts & Payloads Python 3 Arduino DigiSpark

https://youtu.be/e8tKhFS0Tow

name

Old payloads: https://github.com/hak5/usbrubberducky-payloads/tree/1d3e9be7ba3f80cdb008885fac49be2ba926649d/payloads

PhreakNIC 24: Java Android Magisk Burp Objection Root Emulator Easy (JAMBOREE)

https://www.youtube.com/watch?v=R1eu2Ui1ZLU

name

how do i go with this? new linux user

Fri, 29 Mar 2024 00:31:06 +0100

i'm a new user of linux btw and have chosen linuxmint as my first distros. feel free to crrect if i ecer used a term incorrectly. so here it goes. my wifi driver is broken way back pre-installed linux. was using windows10 back then. my technician contacted me that the cost effective way to solve my wifi problem (wifi not showing in my network settings) is to buy a wifi usb adapter/tor so that i can use wifi again.

so i bought it and it works without issue. but then due to my another issue, wherein my win10 kept always popping a prompt about "license" etc. i've decided to search whether i would upgrade to win11 or not. personally i don't wanna. i've read somesay about linux. the more i search about it, the more i'm liking it. so i did the installation. it was fine until as i turn off and on my laptop as i changed my set-up from store to home. i was surprised that my wifi usb adapter/tor wasn't working/blinking. i tried finding a solution in YT and have come across using terminal and i use

sudo apt install bcmwl-kernel-source (enter) data... data...data... that i don't understand (then i choose Y for yes) then at 95% of the progress, there was a prompt that says about MOK (machine owner key) that i need to do something about it since it (my wifi adapter/tor) is considered a third party thing as i understand it. also it needs to create a password for the next step so that after rebooting, i will then type it in. and then i was assuming that that was the end of it and my wifi usb adapter/tor will be workinng again. but it was not the case.

at 95%, there were no additional information or an option to input the password that i need to create in order to proceed. i feel like it hang'ed on me. and that there was only an OK and i can't do something about it. kept waiting for what seems like forever so i decided to close it, and restart it and maybe i would then proceed to the nexy step, maybe? as it restarted, there was no next step happening so i tried to do it again... the "sudo apt install bcmwl-kernel-source"

but there was an error... i tried searching how to fix it and found this solution 'sudo killall apt apt-get' then 'sudo dpkg --configure -a'

and yada yada yada. im sorry as at this point i was too tired and my back hurts already, lol. i'm sorry, i was not used to all this. to all the terminal or coded² thing, yet. i don't mind learning it but in my first day of linux installation i got to operate this without a proper video to follow stepbystep had me exhausted (in the wifi usb adapter/tor issue part)

i was able to get back to the prompt where it's stating about the MOK and an option to create a password. so i did. and then close and restarted it. HOWEVER, i was coming of without reference at that point and pair it with my exhaustion i click and click and click. i inputed my created password. before it i remembered choosing install a MOK or something... after all that and it rebooted. my wifi usb adapter/tor is still not working :(

i tried again the 'sudo apt install bcmwl-kernel-source' to only find with this:

bcmwl-kernel-source is already the newest version (6.30.223.271+bdcom-0ubuntu10~22.04.1). 0 upgraded, 0 newly installed, 0 to remove and 104 not upgraded.

what am i gonna do next? huhu

submitted by /u/jjustbecause
[link] [comments]

GitHub: Copilot Chat steht jetzt auch für JetBrains-Kunden zur Verfügung

Fri, 08 Mar 2024 15:47:05 +0100

Nachdem GitHub seinen KI-Assistenten bereits unter anderem in Visual Studio und Visual Studio Code zur Verfügung gestellt hat, können nun auch Kunden des tschechischen Unternehmens JetBrains, die mit den dortigen Entwicklungsumgebungen wie PyCharm, Rider, WebStorm oder IntelliJ arbeiten, auf Copilot Chat zugreifen. Die Integration hat offiziell die private Beta verlassen. Wer den Assistenten bereits in […]

GitHub Copilot Chat now generally available in all JetBrains IDEs

Fri, 08 Mar 2024 13:17:01 +0100

GitHub Copilot Chat, aka the AI-powered coding assistant, is now out of beta and available to all Copilot subscribers. This integration brings the power of Copilot Chat directly into JetBrains IDEs, including PyCharm, IntelliJ IDEA, WebStorm, and Rider. IDE stands for Integrated Development Environment, which means that it’s a single application that combines various tools […]

[Testing Updates] 2024-03-01 - Gnome Builder, Lazarus, Signal, XFCE, Python

Fri, 01 Mar 2024 08:37:41 +0100

Hello community,

here we have another set of package updates! This is rather a small one …

Current promotions

We currently have a flashsale with our partner MINISFORUM on the UM790Pro featuring the Manjaro Linux GamingEdition. Use the device either as a MiniPC or Gaming Console! Use our link to get yours. Note: US Market only!
Find out all about our current Gaming Laptop the Hero with Manjaro pre-installed from Spain!
Protect your personal data, keep yourself safe with Surfshark VPN: 79% OFF + 2 mo. FREE

Notable Package Updates

Gnome builder got updated to focus more on flatpaks separately
lazarus IDE got renewed to 3.2
Signal is now at 7.0.0.
- more about the new option to use user names can be found here
Updates to XFCE and Python

Additional Info

Info about AUR packages (click for more details)

Get our latest daily developer images now from Github: Plasma, GNOME, XFCE. You can get the latest stable releases of Manjaro from CDN77.

Our current supported kernels

linux419 4.19.307
linux54 5.4.269
linux510 5.10.210
linux515 5.15.149
linux61 6.1.79
linux66 6.6.18
linux67 6.7.6
linux68 6.8.0-rc6
linux61-rt 6.1.77_rt24
linux66-rt 6.6.15_rt22
linux67-rt 6.7_rt6

Package Changes (Fri Mar 1 06:08:37 CET 2024)

testing extra x86_64: 270 new and 274 removed package(s)
testing kde-unstable x86_64: 49 new and 49 removed package(s)
testing multilib x86_64: 3 new and 3 removed package(s)

:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2024-02-28           2024-03-01
-------------------------------------------------------------------------------
                              arkdep         2024.02.25-1         2024.02.29-1
                            chromium      122.0.6261.94-1                    -
              manjaro-pacnew-checker              0.5.4-3              0.6.0-1
                   opengamepadui-git0.30.2.r1.g94f966b8-10.30.2.r2.g7323c1c5-1
                 tuxedo-drivers-dkms              4.2.2-1              4.3.0-1
               vivaldi-ffmpeg-codecs      122.0.6261.84-1                    -


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2024-02-28           2024-03-01
-------------------------------------------------------------------------------
                       android-tools             34.0.4-3             34.0.4-4
                             ansible              9.2.0-1              9.3.0-1
                        ansible-core             2.16.3-1             2.16.4-1
                              awxkit             23.8.0-1             23.9.0-1
                       bbswitch-dkms              0.8-654              0.8-655
                                 bcc             0.28.0-2             0.29.1-1
                           bcc-tools             0.28.0-2             0.29.1-1
                            binaryen              1:116-1              1:117-1
                            birdfont             2.32.3-1             2.33.4-1
                             blender          17:4.0.2-14          17:4.0.2-15
                            bpftrace             0.19.1-1             0.20.1-1
                             buildah             1.34.0-2             1.34.1-1
                            calligra             3.2.1-55             3.2.1-56
                          cargo-deny            0.14.14-1            0.14.15-1
                             cfitsio            1:4.3.1-1            1:4.4.0-1
                            chromium      122.0.6261.69-1      122.0.6261.94-1
                                crun             1.14.3-1             1.14.4-1
                         dark-reader             4.9.77-1             4.9.78-1
                           darkhttpd               1.15-1               1.16-1
                              docker           1:25.0.2-1           1:25.0.3-1
                                dolt             1.34.3-1             1.35.0-1
                      doublecmd-gtk2             1.1.10-1             1.1.10-2
                       doublecmd-qt5             1.1.10-1             1.1.10-2
                       doublecmd-qt6             1.1.10-1             1.1.10-2
                                dpkg             1.22.0-1             1.22.5-1
                              dqlite             1.16.2-1             1.16.4-1
                               dunst              1.9.2-1             1.10.0-1
                             dvisvgm                3.2-1              3.2.1-1
                       dwarffortress              50.11-1              50.11-2
                          electron27             27.3.3-1             27.3.4-1
                          electron28             28.2.4-1             28.2.5-1
                          electron29             29.0.1-1             29.1.1-1
                            epiphany               45.2-1               45.3-1
                                 eza             0.18.4-1             0.18.5-1
                           fcitx5-qt              5.1.4-4              5.1.4-5
                 firefox-dark-reader             4.9.77-1             4.9.78-1
           firefox-developer-edition            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-ach            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-af            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-an            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ar            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-ast            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-az            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-be            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-bg            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-bn            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-br            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-bs            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ca            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-ca-valencia      124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-cak            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-cs            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-cy            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-da            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-de            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-dsb            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-el            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-en-ca            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-en-gb            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-en-us            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-eo            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-es-ar            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-es-cl            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-es-es            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-es-mx            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-et            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-eu            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-fa            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ff            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-fi            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-fr            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-fur            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-fy-nl            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-ga-ie            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-gd            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-gl            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-gn            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-gu-in            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-he            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-hi-in            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-hr            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-hsb            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-hu            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-hy-am            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ia            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-id            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-is            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-it            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ja            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ka            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-kab            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-kk            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-km            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-kn            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ko            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-lij            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-lt            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-lv            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-mk            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-mr            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ms            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-my            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-nb-no            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-ne-np            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-nl            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-nn-no            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-oc            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-pa-in            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-pl            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-pt-br            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-pt-pt            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-rm            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ro            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ru            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-sat            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-sc            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-sco            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-si            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-sk            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-sl            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-son            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-sq            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-sr            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-sv-se            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-szl            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ta            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-te            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-tg            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-th            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-tl            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-tr            124.0b4-1            124.0b5-1
  firefox-developer-edition-i18n-trs            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-uk            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-ur            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-uz            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-vi            124.0b4-1            124.0b5-1
   firefox-developer-edition-i18n-xh            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-zh-cn            124.0b4-1            124.0b5-1
firefox-developer-edition-i18n-zh-tw            124.0b4-1            124.0b5-1
                     flatpak-builder              1.4.0-1              1.4.2-1
                   gentium-plus-font              6.200-1                    -
                             git-lfs              3.4.1-1              3.5.0-1
                          github-cli             2.43.1-1             2.44.1-1
                       gitlab-runner             16.9.0-1             16.9.1-1
                        gitlab-shell          3:14.33.0-1          3:14.34.0-1
                            glfw-doc             3.3.10-1                    -
                        glfw-wayland             3.3.10-1                    -
                            glfw-x11             3.3.10-1                    -
                     glib-networking           1:2.78.0-1           1:2.78.1-1
                       gnome-builder               45.0-3               45.0-4
                      gnome-contacts               45.0-1               45.1-1
                         gnome-panel             3.50.0-3             3.50.0-4
                               gopls             0.14.2-1             0.15.1-1
                             gparted              1.5.0-1              1.6.0-1
                       grafana-agent             0.40.0-1             0.40.1-1
                    grafana-agentctl             0.40.0-1             0.40.1-1
                             haproxy              2.9.5-1              2.9.6-1
                                hugo            0.123.4-1            0.123.6-1
                            hyprlang              0.4.0-1              0.4.1-1
                               imath             3.1.10-1             3.1.11-1
                               kafka              3.6.1-1              3.7.0-1
                             krename              5.0.2-9             5.0.2-10
                             lazarus                3.0-2                3.2-1
                        lazarus-gtk2                3.0-2                3.2-1
                        lazarus-gtk3                3.0-2                3.2-1
                         lazarus-qt5                3.0-2                3.2-1
                         lazarus-qt6                3.0-2                3.2-1
                              libbsd             0.12.0-1             0.12.1-1
                              libluv           1.48.0_0-1           1.48.0_1-1
                             libsrtp            1:2.5.0-1            1:2.6.0-1
                        libsrtp-docs            1:2.5.0-1            1:2.6.0-1
                            libunrar           1:6.2.12-1            1:7.0.7-1
                   libxfce4windowing             4.19.2-1             4.19.3-2
                         liquidshell              1.9.0-2              1.9.0-3
                          lua-dkjson                2.6-1                2.7-1
                             lua-luv           1.48.0_0-1           1.48.0_1-1
                        lua51-dkjson                2.6-1                2.7-1
                           lua51-luv           1.48.0_0-1           1.48.0_1-1
                        lua52-dkjson                2.6-1                2.7-1
                           lua52-luv           1.48.0_0-1           1.48.0_1-1
                        lua53-dkjson                2.6-1                2.7-1
                           lua53-luv           1.48.0_0-1           1.48.0_1-1
                            luarocks             3.10.0-1             3.10.0-2
                                mame              0.262-1              0.263-1
                          mame-tools              0.262-1              0.263-1
                              mandoc             1.14.6-2             1.14.6-3
                           materialx             1.38.8-8             1.38.9-1
                             melange              0.6.4-1              0.6.5-1
               netfilter-fullconenat      r73.0cf3b48-351      r73.0cf3b48-352
                 networkmanager-l2tp            1.20.10-1            1.20.12-1
                  nextcloud-app-mail              3.5.6-1              3.5.7-1
                                 nix             2.19.1-2             2.20.3-1
                            nix-docs             2.19.1-2             2.20.3-1
                                 npm             10.4.0-2             10.5.0-1
                                 orc             0.4.37-1             0.4.38-1
                             osbuild                109-1                111-1
                               pango           1:1.51.2-1           1:1.52.0-1
                          pango-docs           1:1.51.2-1           1:1.52.0-1
                       piping-server             0.17.0-1             0.18.0-1
                                pixi             0.15.1-1             0.15.2-1
                              pixman             0.43.2-1             0.43.4-1
     plasma5-applets-thermal-monitor              1.3.0-2                    -
                            polymake               4.11-6               4.11-7
                        prusa-slicer              2.7.1-1              2.7.2-1
                            pstoedit               3.78-1               4.00-1
                            pstotext                1.9-7                    -
           pycharm-community-edition           2023.3.3-1           2023.3.4-1
                             pyright            1.1.351-1            1.1.352-1
                      python-astroid             2.15.6-1              3.1.0-2
                          python-bcc             0.28.0-2             0.29.1-1
                        python-build              1.0.3-1              1.1.1-1
                       python-crc32c          2.3.post0-1                2.4-1
                python-flask-htmlmin              2.2.1-3                    -
                   python-hypothesis            6.98.13-1            6.98.15-1
                    python-inflate64              0.3.1-2              1.0.0-1
                       python-openai             1.13.2-1             1.13.3-1
                       python-poetry              1.7.1-1              1.8.1-1
                  python-poetry-core              1.9.0-2              1.9.0-3
                       python-pylint             2.17.7-1              3.1.0-1
                    python-pyscipopt              4.4.0-1              4.4.0-2
                         python-rich             13.7.0-1             13.7.1-1
                         python-ruff              0.2.2-1              0.3.0-2
              python-setuptools-rust              1.8.1-1              1.9.0-1
            python-trove-classifiers          2024.1.31-1          2024.2.22-1
                           python-uv             0.1.11-1             0.1.13-1
                                   r              4.3.2-4              4.3.3-1
                          rapidcheck      r1056.ff6af6f-1      r1056.ff6af6f-2
                              rasqal           1:0.9.33-6           1:0.9.33-7
                                rauc             1.11.1-1             1.11.2-1
                                 rcs             5.10.1-1             5.10.1-2
                              recoll             1.37.4-1             1.37.4-2
                         release-plz             0.3.48-1             0.3.49-1
                           repro-env              0.3.3-1              0.4.0-1
                                ruff              0.2.2-1              0.3.0-2
                            ruff-lsp             0.0.52-1             0.0.53-1
                                sane              1.2.1-6              1.3.0-1
                                scip              8.1.0-2              9.0.0-1
                         sequoia-wot             0.10.0-1             0.11.0-1
                      signal-desktop             6.48.1-1              7.0.0-1
                                sile            0.14.17-1            0.14.17-2
                         slicer-udev              2.7.1-1              2.7.2-1
                    ssh-openpgp-auth              0.2.1-1              0.2.2-1
                   sshd-openpgp-auth              0.2.1-1              0.3.0-1
              svelte-language-server             0.16.3-1             0.16.5-1
                           tailscale             1.60.0-1             1.60.1-1
             thunderbird-dark-reader             4.9.77-1             4.9.78-1
                              tinygo             0.31.0-1             0.31.1-1
                                 tor           0.4.8.10-1           0.4.8.10-2
                ttf-scheherazade-new              4.000-1              4.000-3
                               unrar           1:6.2.12-1            1:7.0.7-1
                                 usd             23.11-12             23.11-13
                          usd-extras             23.11-12             23.11-13
                                  uv             0.1.11-1             0.1.13-1
                               vault             1.15.5-1             1.15.6-1
                    vhba-module-dkms           20240202-3           20240202-4
               vivaldi-ffmpeg-codecs      120.0.6099.80-1      122.0.6261.84-1
           vscode-css-languageserver             1.86.0-1             1.87.0-1
          vscode-html-languageserver             1.86.0-1             1.87.0-1
          vscode-json-languageserver             1.86.0-1             1.87.0-1
      vscode-markdown-languageserver             1.86.0-1             1.87.0-1
                            wasmtime             18.0.1-1             18.0.2-1
                            waycheck              1.1.0-1              1.1.1-1
                            wrangler             3.30.0-1             3.30.1-1
              xf86-input-elographics              1.4.3-1              1.4.4-1
                xfce4-clipman-plugin              1.6.5-1              1.6.6-1
                         xfce4-panel             4.18.5-1             4.18.6-1
                   xfce4-taskmanager              1.5.6-2              1.5.7-1
                      xfce4-terminal              1.1.2-2              1.1.3-1
                                 znc              1.9.0-1              1.9.0-3
                             zziplib            0.13.72-2            0.13.73-1
                                glfw                    -                3.4-2
                 gnome-builder-clang                    -               45.0-4
               gnome-builder-flatpak                    -               45.0-4
                      python-joserfc                    -              0.9.0-1
                    ttf-gentium-plus                    -              6.200-5


:: Different overlay package(s) in repository kde-unstable x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2024-02-28           2024-03-01
-------------------------------------------------------------------------------
                    akonadi-contacts23.08.5.r3700.g8ec4c2fb-123.08.5.r3701.gb122e972-1
                        akonadi-mime23.08.5.r1998.g16e9fa7-123.08.5.r2000.g1a94ad3-1
                      akonadi-search23.08.5.r1600.g436bae6-123.08.5.r1606.g60857d7-1
                               baloo5.114.0.r3417.gc334530b-15.114.0.r3421.gc6ce8eb9-1
                       baloo-widgets23.08.5.r960.gb1a3f60-123.08.5.r962.gd9c9de7-1
                           calindori23.08.1.r831.gaa8d656-123.08.1.r832.g3a287b0-1
                             dolphin23.08.5.r7867.gf13f3c7a2-123.08.5.r7871.g992272f8c-1
                               elisa23.08.4.r3715.g707bfbe2-123.08.5.r3724.gdc125b06-1
                          elisa-qtmm23.08.4.r3715.g707bfbe2-123.08.5.r3724.gdc125b06-1
                           granatier23.08.5.r1144.gdac423a-123.08.5.r1145.gfce1eb6-1
                                 k3b1:23.08.5.r7147.g6810d711c-11:23.08.5.r7150.gaf0743069-1
                        kaddressbook23.08.5.r6659.g2fbdb2bf-123.08.5.r6661.gc913e17e-1
                            kcmutils5.114.0.r1094.g80db4e37-15.114.0.r1095.gd52a573d-1
                      kconfigwidgets5.114.0.r1051.g1ed5434e-15.114.0.r1053.g3cfbbeab-1
                       kde-cli-tools5.27.10.r2319.ga28aa659-15.27.10.r2320.gcb94a787-1
                            kdenlive23.08.5.r19607.g9c51caa25-123.08.5.r19616.g0791d4462-1
                            keysmith23.08.1.r588.ge49900e-123.08.1.r590.gef70642-1
                       kfilemetadata5.114.0.r1089.gb3643aa-15.114.0.r1091.g49aa1f8-1
                         kfourinline23.08.5.r1224.g2da8f64-123.08.5.r1225.g5a5e57d-1
                               ki18n5.114.0.r720.g7e987c1-15.114.0.r722.g7e6e758-1
                 kidentitymanagement23.08.5.r4288.gcd421c05-123.08.5.r4289.gb2c611ee-1
                         kinfocenter5.27.10.r2674.g89ff2977-15.27.10.r2677.g5e441188-1
                                 kio5.114.0.r6892.g67207a96e-15.114.0.r6894.gac50baa8f-1
                     kirigami-addons1:1.0.0.r4.g2d5904d-11:1.0.1.r0.ga1a67ea-1
                           kirigami25.114.0.r4404.g4500d6b1-15.114.0.r4405.gef4aeb77-1
                          kitinerary23.08.5.r3553.gafe59512-123.08.5.r3557.g46cc76b4-1
                      kmailtransport23.08.5.r2123.gededc00-123.08.5.r2124.gc1eb9eb-1
                           kmenuedit5.27.10.r1296.g554d40a-15.27.10.r1298.ge5b6c48-1
                           knewstuff5.114.0.r1803.ga6a02162-15.114.0.r1804.gdbf0f45b-1
                       kopeninghours23.08.5.r438.g95a9e0f-123.08.5.r439.g3eb449e-1
                         ktextaddons23.08.5.r1253.gcd85505-123.08.5.r1254.g1f7d373-1
                         ktexteditor5.114.0.r4412.g28e37d1c2-15.114.0.r4413.g8a74e8efd-1
                     kunitconversion5.114.0.r595.g793b415-15.114.0.r596.g583284a-1
                       kuserfeedback5.249.0.r10.ge1be745-1  6.0.0.r4.g5cb5a96-1
                                kwin5.27.10.r26232.g4d6f6223bc-15.27.10.r26275.g86ede0ecf2-1
                         libkdegames23.08.5.r2475.g6e67dda6-123.08.5.r2476.g94487c36-1
                  libkeduvocdocument23.08.2.r1872.gd6afb08-123.08.5.r1895.gd05366b-1
                             libkleo23.08.5.r1990.g4c86cf41-123.08.5.r1991.g5a7a63a0-1
                        libkmahjongg23.08.5.r638.g3960d8c-123.08.5.r639.g30f12d0-1
                          messagelib23.08.5.r7775.gb7d0cb363-123.08.5.r7782.gc2fbefd5a-1
                             neochat23.08.1.r4178.g628de5608-123.08.1.r4183.g0c24996b4-1
                           pimcommon23.08.5.r2341.g0e1f4c2d-123.08.5.r2343.g7bde8d58-1
                       plasma-camera  1.0.r237.ga972ea0-1  1.0.r238.gc183b28-1
                     plasma-firewall5.27.10.r877.g0bb4426-15.27.10.r880.g1f6bf95-1
                     plasma-settings23.08.1.r1378.gffc96a1-123.08.1.r1381.gf0c24b1-1
                  plasma-thunderbolt5.27.10.r334.gb204d86-15.27.10.r335.gc4ff615-1
                                sddm0.19.0.r262.g63780fcd-10.19.0.r273.gcc03fabf-1
                            spacebar23.08.1.r882.ga4231c0-123.08.1.r884.g9ea6caa-1
                         vakzination23.08.1.r405.gdbdc46b-123.08.1.r406.gd456830-1


:: Different sync package(s) in repository multilib x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2024-02-28           2024-03-01
-------------------------------------------------------------------------------
               lib32-glib-networking           1:2.78.0-1           1:2.78.1-1
                           lib32-orc             0.4.37-1             0.4.38-1
                         lib32-pango           1:1.51.2-1           1:1.52.0-1

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I just installed KDE Neon on my Surface Laptop Go which struggled to run Windows 11 and constantly overheated. KDE Neon is actually amazing.

Sun, 14 Jan 2024 17:16:12 +0100

Okay full disclosure, I'm a software engineer and I'm relatively experienced with Unix environments so perhaps (or definitely) the transition for me into using this on my personal laptop has been easier than the average user. There have been a bunch of things which I needed the command line for initial fix up.

But god damn, now that it's all running I cannot believe THAT MY LAPTOP DOES NOT HEAT UP ANYMORE and the FANS DON'T RUN LIKE CRAZY and IT DOESN'T LAG LIKE A HYENA.

I really like the UI of KDE and as someone who's a lifelong Windows user, this feels very familiar without any of the bloated bullshit you get with using a OS with bloated code from the 1990s. Battery life is still crap but such is this laptop but I am SO HAPPY IT RUNS FAST :)))

Pycharm runs like butter, Chrome doesn't slow everything down, file explorer is decent but Windows Explorer IMO is far superior, but overall just awesome for my needs. Wallpapers are really cool too. Oh yeah, CPU usage is constantly at 100%, half the RAM isn't used by the OS, and updates aren't forced up my rectal entrance which is much appreciated.

submitted by /u/Pythagosaurus69
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PyCharm for Linux Users: A Comprehensive Python IDE Guide

Sat, 06 Jan 2024 02:16:06 +0100

PyCharm is a leading Python IDE for Linux, known for its robust set of features that cater to both beginners and seasoned developers. This guide explores PyCharm's capabilities, from intelligent code assistance to debugging tools, making it an indispensable tool for Python development on Linux systems.

Debugging and Tuning Amazon SageMaker Training Jobs with SageMaker SSH Helper

Thu, 28 Dec 2023 21:36:31 +0100

A new tool that increases the debuggability of managed training workloads

Photo by James Wainscoat on Unsplash

Considering all the new Amazon SageMaker features announced over the past year (2023), including at the most recent AWS re:invent, it would have been easy to have overlooked SageMaker SSH Helper — a new utility for connecting to remote SageMaker training environments. But sometimes it is the quiet enhancements that have the potential to make the greatest impact on your daily development. In this post we will review SageMaker SSH Helper and demonstrate how it can increase your ability to 1) investigate and solve errors that arise in your training applications and 2) optimize their runtime performance.

In previous posts, we discussed at length the benefits of training in the cloud. Cloud-based managed training services, such as Amazon SageMaker, have simplified many of the complexities surrounding AI model development and greatly increased accessibility to both AI-specific machinery and pretrained AI models. To train in Amazon SageMaker, all you need to do is define a training environment (including an instance type) and point to the code you wish to run, and the training service will 1) set up the requested environment, 2) deliver your code to the training machine, 3) run your training script, 4) copy the training output to persistent storage, and 5) tear everything down when the training completes (so that you pay only for what you need). Sounds easy… right? However, managed training is not without its flaws, one of which — the limited access it enables to the training environment — will be discussed in this post.

Disclaimers

Please do not interpret our use of Amazon SageMaker, SageMaker SSH Helper, or any other framework or utility we should mention as an endorsement for their use. There are many different methodologies for developing AI models. The best solution for you will depend on the details of your project.
Please be sure to verify the contents of this post, particularly the code samples, against the most up to date SW and documentation available at the time that you read this. The landscape of AI development tools is in constant flux and it is likely that some of the APIs we refer to will change over time.

Disadvantage of Managed Training — Inaccessibility of the Training Environment

As seasoned developers are well aware, a significant chunk of the application development-time is actually spent on debugging. Rarely do our programs work “out of the box”; More often than not, they require hours of laborious debugging to get them to run as desired. Of course, to be able to debug effectively, you need to have direct access to your application environment. Trying to debug an application without access to its environment is like trying to fix a faucet without a wrench.

Another important step in AI model development is to tune the runtime performance of the training application. Training AI models can be expensive and our ability to maximize the utilization of our compute resources can have a decisive cost on training. In a previous post we described the iterative process of analyzing and optimizing training performance. Similar to debugging, direct access to the runtime environment will greatly increase and accelerate our ability to reach the best results.

Unfortunately, one of the side-effects of the “fire and forget” nature of training in SageMaker, is the lack of ability to freely connect to the training environment. Of course, you could always debug and optimize performance using the training job output logs and debug prints (i.e., add prints, study the output logs, modify your code, and repeat until you’ve solved all your bugs and reached the desired performance) but this would be a very primitive and time-consuming solution.

There are a number of best practices that address the problem of debugging managed training workloads, each with its own advantages and disadvantages. We will review three of these, discuss their limitations, and then demonstrate how the new SageMaker SSH Helper completely alters the playing field.

Debug in Your Local Environment

It is recommended that you run a few training steps in your local environment before launching your job to the cloud. Although this may require a few modifications to your code (e.g., to enable training on a CPU device), it is usually worth the effort as it enables you to identify and fix silly coding errors. It is certainly more cost effective than discovering them on an expensive GPU machine in the cloud. Ideally, your local environment would be as similar to the SageMaker training environment (e.g., using the same versions of Python and Python packages) but in most cases there is a limit to the extent that this is possible.

Debug Locally within the SageMaker Docker Container

The second option is to pull the deep learning container (DLC) image that SageMaker uses and run your training script within the container on your local PC. This method allows you to get a good understanding of the SageMaker training environment including the packages (and package versions) that are installed. It is extremely useful in identifying missing dependencies and addressing dependency conflicts. Please see the documentation for details on how to login and pull the appropriate image. Note that the SageMaker APIs support pulling and training within a DLC via its local mode feature. However, running the image on your own will enable you to explore and study the image more freely.

Debug in the Cloud on an Unmanaged Instance

Another option is to train on an unmanaged Amazon EC2 instance in the cloud. The advantage to this option is the ability to run on the same instance type that you use in SageMaker. This will enable you to reproduce issues that you may not be able to reproduce in your local environment, e.g., issues related to your use of the GPU resources. The easiest way to do this would be to run your instance with a machine image that is most similar to your SageMaker environment (e.g., the same OS, Python, and Python package versions). Alternatively, you could pull the SageMaker DLC and run it on the remote instance. However, keep in mind that although this also runs in the cloud, the runtime environment may still be significantly different than SageMaker’s environment. SageMaker configures a whole bunch of system settings during initialization. Trying to reproduce the same environment may require quite a bit of effort. Given that debugging in the cloud is more costly than the previous two methods, our goal should be to try to clean up our code as much as possible before resorting to this option.

Debugging Limitations

Although each of the above options are useful for solving for certain types of bugs, none of them offer a way to perfectly replicate the SageMaker environment. Consequently, you may run into issues when running in SageMaker that you are not able to reproduce, and thus not able to correct, when using these methods. In particular, there are a number of features that are supported only when running in the SageMaker environment (e.g., SageMaker’s Pipe input and Fast File modes for accessing data from Amazon S3). If your issue is related to one of those features, you will not be able to reproduce it outside of SageMaker.

Tuning Limitations

In addition, the options above do not provide an effective solution for performance tuning. Runtime performance can be extremely susceptible to even the slightest changes in the environment. While a simulated environment might provide some general optimization hints (e.g., the comparative performance overhead of different data augmentations), an accurate profiling analysis can be performed only in the SageMaker runtime environment.

SageMaker SSH Helper

SageMaker SSH Helper introduces that ability to connect to the remote SageMaker training environment. This is enabled via an SSH connection over AWS SSM. As we will demonstrate, the steps required to set this up are quite simple and very well worth the effort. The official documentation includes comprehensive details on the value of this utility and how it can be used.

Example

In the code block below we demonstrate how to enable remote connection to a SageMaker training job using sagemaker-ssh-helper (version 2.1.0). We pass in our full code source directory but replace our usual entry_point (train.py) with a new run_ssh.py script that we place in the root of the source_dir. Note that we add the SSHEstimatorWrapper to the list of project dependencies since our start_ssh.py script will require it. Alternatively, we could have added sagemaker-ssh-helper to our requirements.txt file. Here we have set the connection_wait_time_seconds setting to two minutes. As we will see, this will impact the behavior of our training script.

from sagemaker.pytorch import PyTorch
from sagemaker_ssh_helper.wrapper import SSHEstimatorWrapper
MINUTE = 60

estimator = PyTorch(
    role='',
    entry_point='run_ssh.py',
    source_dir='',
    instance_type='ml.g5.xlarge',
    instance_count=1,
    framework_version='2.0.1',
    py_version='py310',
    dependencies=[SSHEstimatorWrapper.dependency_dir()]
)


# configure the SSH wrapper. Set the wait time for the connection.
ssh_wrapper = SSHEstimatorWrapper.create(estimator.framework, 
                                    connection_wait_time_seconds=2*MINUTE)

# start job
estimator.fit()

# wait to receive an instance id for the connection over SSM
instance_ids = ssh_wrapper.get_instance_ids()

print(f'To connect run: aws ssm start-session --target {instance_ids[0]}')

As usual, the SageMaker service will allocate a machine instance, build the requested environment, download and unpack our source code, and install the requested dependencies. At that point, the runtime environment will be identical to the one in which we usually run our training script. Only now, instead of training we will run our start_ssh.py script:

import sagemaker_ssh_helper
from time import sleep

# setup SSH and wait for connection_wait_time_seconds seconds
# (to give opportunity for the user to connect before script resumes)
sagemaker_ssh_helper.setup_and_start_ssh()

# place any code here... e.g. your training code
# we choose to sleep for two hours to enable connecting in an SSH window
# and running trials there
HOUR = 60*60
sleep(2*HOUR)

The setup_and_start_ssh function will start the SSH service, then block for the allotted time we defined above (connection_wait_time_seconds) to allow an SSH client to connect, and then proceed with the rest of the script. In our case it will sleep for two hours and then exit the training job. During that time we can connect to the machine using the aws ssm start-session command and the instance-id that was returned by the ssh_wrapper (which typically starts with an “mi-” prefix for “managed instance”) and play to our hearts desire. In particular, we can explicitly run our original training script (which was uploaded as part of the source_dir) and monitor the training behavior.

The method we have described, enables us to run our training script iteratively while we identify and fix bugs. It also provides an ideal setting for optimizing performance — one in which we can 1) run a few training steps, 2) identify performance bottlenecks (e.g., using PyTorch Profiler), 3) tune our code to address them, and 4) repeat, until we achieve the desired runtime performance.

Importantly, keep in mind that the instance will be terminated as soon as the start_ssh.py script completes. Make sure to copy all important files (e.g., code modifications, profile traces, etc.) to persistent storage before it is too late.

Port Forwarding Over AWS SSM

We can extend our aws ssm start-session command to enable port forwarding. This allows you to securely connect to server applications running on your cloud instance. This is particularly exciting for developers who are accustomed to using the TensorBoard Profiler plugin for analyzing runtime performance (as we are). The command below demonstrates how to set up port forwarding over AWS SSM:

aws ssm start-session \
  --target mi-0748ce18cf28fb51b \
  --document-name AWS-StartPortForwardingSession
  --parameters '{"portNumber":["6006"],"localPortNumber":["9999"]}'

Additional Modes of Use

The SageMaker SSH Helper documentation describes several different ways of using the SSH functionality. In the basic example the setup_and_start_ssh command is added to the top of the existing training script (instead of defining a dedicated script). This allows you time (as defined by the connection_wait_time_seconds setting) to connect to the machine before the training begins so that you can monitor its behavior (from a separate process) as it runs.

The more advanced examples include different methods for using SageMaker SSH Helper to debug the training script running in the SageMaker environment from an IDE running in our local environment. The setup is more complicated but may very well be worth the reward of being able to perform line-by-line debugging from a local IDE.

Additional use cases cover training in a VPC, integration with SageMaker Studio, connecting to SageMaker inference endpoints, and more. Please be sure to see the documentation for details.

When to Use SageMaker SSH Helper

Given the advantages of debugging with SageMaker SSH Helper, you might wonder if there is any reason to use the three debugging methods we described above. We would argue that, despite the fact that you could perform all of your debugging in the cloud, it is still highly recommended that you perform your initial development and experimentation phase — to the extent possible — in your local environment (using the first two methods we described). Only once you have exhausted your ability to debug locally, should you move to debugging in the cloud using SageMaker SSH Helper. The last thing you would want would be to spend hours cleaning up silly syntax errors on a super expensive cloud-based GPU machine.

Contrary to debugging, analyzing and optimizing performance has little value unless it is performed directly on the target training environment. Thus, it would be advised to perform your optimization efforts on the SageMaker instance using SageMaker SSH Helper.

Summary

Until now, one of the most painful side effects of training on Amazon SageMaker has been the loss of direct access to the training environment. This restricted our ability to debug and tune our training workloads in an effective manner. The recent release of SageMaker SSH Helper and its support for unmediated access to the training environment opens up a wealth of new opportunities for developing, debugging, and tuning. These can have a distinctive impact on the efficiency and speed of your ML development life cycle. It is for this reason that SageMaker SSH Helper is one of our favorite new cloud-ML features of 2023.

Debugging and Tuning Amazon SageMaker Training Jobs with SageMaker SSH Helper was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

HPR3997: The Oh No! News.

Tue, 28 Nov 2023 02:06:39 +0100

The Oh No! news.

Oh No! News is Good News.

TAGS: Oh No, News, Threat analysis, InfoSec, Google Dynamic Search Ads

Threat analysis; your attack surface.

Source: Former NHS secretary found guilty of illegally accessing medical records
- A former NHS employee has been found guilty and fined for illegally accessing the medical records of over 150 people.
- Loretta Alborghetti, from Redditch, worked as a medical secretary within the Ophthalmology department at Worcestershire Acute Hospitals NHS Trust when she illegally accessed the records.
Supporting Source: Open Street Map link to Redditch Worcestershire.
Source: NetSupport RAT Infections on the Rise. Targeting Government and Business Sectors
- While NetSupport Manager started off as a legitimate remote administration tool for technical assistance and support, malicious actors have misappropriated the tool to their own advantage, using it as a beachhead for subsequent attacks.
Source: Beware: Malicious Google Ads Trick WinSCP Users into Installing Malware
- The threat actors are believed to leverage Google's Dynamic Search Ads (DSAs), which automatically generates ads based on a site's content to serve the malicious ads that take the victims to the infected site.
Source: Trojanized PyCharm Software Version Delivered via Google Search Ads.
- Victims who clicked on the ad were taken to a hacked web page with a link to download the application, which turned out to install over a dozen different pieces of malware instead.

InfoSec; the language of security.

Source: Why Defenders Should Embrace a Hacker Mindset

Additional Information.
- What is a "Data Breach"? A data breach is a security violation, in which sensitive, protected or confidential data is copied, transmitted, viewed, stolen, altered or used by an individual unauthorized to do so.
- What is "Malware"? Malware (a portmanteau for malicious software) is any software intentionally designed to cause disruption to a computer, server, client, or computer network, leak private information, gain unauthorized access to information or systems, deprive access to information, or which unknowingly interferes with the user's computer security and privacy.
- What is a "Payload"? In the context of a computer virus or worm, the payload is the portion of the malware which performs malicious action; deleting data, sending spam or encrypting data. In addition to the payload, such malware also typically has overhead code aimed at simply spreading itself, or avoiding detection.
- What is "Phishing"? Phishing is a form of social engineering where attackers deceive people into revealing sensitive information or installing malware such as ransomware. Phishing attacks have become increasingly sophisticated and often transparently mirror the site being targeted, allowing the attacker to observe everything while the victim is navigating the site, and transverse any additional security boundaries with the victim.
- Social engineering (security) In the context of information security, social engineering is the psychological manipulation of people into performing actions or divulging confidential information. A type of confidence trick for the purpose of information gathering, fraud, or system access, it differs from a traditional "con" in that it is often one of many steps in a more complex fraud scheme.
- What is "Information Security" (InfoSec)? Information security, sometimes shortened to InfoSec, is the practice of protecting information by mitigating information risks. It is part of information risk management.
  - Information Security Attributes: Confidentiality, Integrity and Availability (C.I.A.). Information Systems are composed in three main portions, hardware, software and communications with the purpose to help identify and apply information security industry standards, as mechanisms of protection and prevention, at three levels or layers: physical, personal and organizational. Essentially, procedures or policies are implemented to tell administrators, users and operators how to use products to ensure information security within the organizations.
- What is "Risk management"? Risk management is the identification, evaluation, and prioritization of risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events or to maximize the realization of opportunities.
- What is a "Vulnerability" (computing)? Vulnerabilities are flaws in a computer system that weaken the overall security of the device/system. Vulnerabilities can be weaknesses in either the hardware itself, or the software that runs on the hardware.
- What is an "Attack Surface"? The attack surface of a software environment is the sum of the different points (for "attack vectors") where an unauthorized user (the "attacker") can try to enter data to or extract data from an environment. Keeping the attack surface as small as possible is a basic security measure.
- What is an "Attack Vector"? In computer security, an attack vector is a specific path, method, or scenario that can be exploited to break into an IT system, thus compromising its security. The term was derived from the corresponding notion of vector in biology. An attack vector may be exploited manually, automatically, or through a combination of manual and automatic activity.
- What is "Standardization"? Standardization is the process of implementing and developing technical standards based on the consensus of different parties that include firms, users, interest groups, standards organizations and governments. Standardization can help maximize compatibility, interoperability, safety, repeatability, or quality. It can also facilitate a normalization of formerly custom processes.
  - List of computer standards.
  - List of technical standard organizations.
- What is a "Replay attack"? A replay attack is a form of network attack in which valid data transmission is maliciously or fraudulently repeated or delayed. Another way of describing such an attack is: "an attack on a security protocol using a replay of messages from a different context into the intended (or original and expected) context, thereby fooling the honest participant(s) into thinking they have successfully completed the protocol run."
- What is a "Man-in-the-middle attack"? In cryptography and computer security, a man-in-the-middle, ..., attack is a cyberattack where the attacker secretly relays and possibly alters the communications between two parties who believe that they are directly communicating with each other, as the attacker has inserted themselves between the two parties.
- What is "Transport Layer Security" (TLS)? Transport Layer Security (TLS) is a cryptographic protocol designed to provide communications security over a computer network. The protocol is widely used in applications such as email, instant messaging, and voice over IP, but its use in securing HTTPS remains the most publicly visible.
- What is a "Handshake" (computing)?. In computing, a handshake is a signal between two devices or programs, used to, e.g., authenticate, coordinate. An example is the handshaking between a hypervisor and an application in a guest virtual machine.
- What is Security theater? The practice of taking security measures that are considered to provide the feeling of improved security while doing little or nothing to achieve it.

License: Creative Commons Attribution-ShareAlike 4.0 International

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Python Community Announces Podcast, Developer's Survey, PyCharm Discount

Sat, 18 Nov 2023 16:49:48 +0100

The Python community is staying busy. Three weeks ago a new podcast launched with Python core developer/steering council member Pablo Galindo and Python developer-in-residence Åukasz Langa. This month the Python Sofware Foundation announced its seventh Python Developers Survey. And for the fifth year in a row the foundation partnered with JetBrains to offer a 30% discount on JetBrains' dedicated Python Integrated Development Environment "PyCharm" — with all proceeds benefitting the Python Software Foundation ("The discount will be automatically applied when you check out. The promotion will only be available through November 27th...") A PSF blog post about the fundraiser notes you can also just make a direct donation to the Python Software Foundation, or sign up to become a foundation member to "help us sustain what we do."

Read more of this story at Slashdot.

Looking for your positive experiences with convertibles that work well with Linux

Sat, 11 Nov 2023 14:16:12 +0100

Hey guys,

i just started my Masters in Bioinformatics and want to upgrade my Loptop (5 y/o ideapad 330S, that runs okish under Windows, but i had to disable RST to install any Linux distro and its just soooo slow now, even closing open programs, when i have an IDE and Mozilla open at the same time...).

So jeah, because i have lots of notes i have to take in classes i was looking for a convertible, but the reviews i found were only ones that are not really favourable for the specific convertibles.

It should be strong enough that it can run an IDE (like IntelliJ or PyCharm) + some googling + and a program to take notes on smoothly, has a good feeling on the touchscreen, especially to take notes and draw and the screen should be optimised for reading and spending extended times working on it (so good for the eyes).

Would be very grateful for any personal experiences or some good pointers, because i cant find quality resources right now.

thanks :)

submitted by /u/Groghnash
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Trojanized PyCharm Software Version Delivered via Google Search Ads

Tue, 31 Oct 2023 12:04:23 +0100

A new malvertising campaign has been observed capitalizing on a compromised website to promote spurious versions of PyCharm on Google search results by leveraging Dynamic Search Ads. "Unbeknownst to the site owner, one of their ads was automatically created to promote a popular program for Python developers, and visible to people doing a Google search for it," Jérôme Segura, director of threat

Ubuntu touch on samsung tablet

Mon, 23 Oct 2023 12:15:41 +0200

Guys, I'm thinking about buying a Samsung Galaxy Tab S7 or S8 and I would like to know if Ubuntu Touch runs smoothly on the tablet. I'm going to buy it to make drawings and I would like it to run a program to program like Pycharm on Ubuntu.

submitted by /u/Gb-R
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Dumpulator - An Easy-To-Use Library For Emulating Memory Dumps. Useful For Malware Analysis (Config Extraction, Unpacking) And Dynamic Analysis In General (Sandboxing)

Wed, 24 May 2023 16:20:10 +0200

Note: This is a work-in-progress prototype, please treat it as such. Pull requests are welcome! You can get your feet wet with good first issues

An easy-to-use library for emulating code in minidump files. Here are some links to posts/videos using dumpulator:

Introduction video with OALabs: Dumpulator - Using Binary Emulation To Automate Reverse Engineering
Emulating malware with Dumpulator
Emotet x64 Stack Strings Config Emulation | OALABS Research
Native function and Assembly Code Invocation
Guloader string decryption (VEH)

Examples

Calling a function

The example below opens StringEncryptionFun_x64.dmp (download a copy here), allocates some memory and calls the decryption function at 0x140001000 to decrypt the string at 0x140017000:

from dumpulator import Dumpulator

dp = Dumpulator("StringEncryptionFun_x64.dmp")
temp_addr = dp.allocate(256)
dp.call(0x140001000, [temp_addr, 0x140017000])
decrypted = dp.read_str(temp_addr)
print(f"decrypted: '{decrypted}'")

The StringEncryptionFun_x64.dmp is collected at the entry point of the tests/StringEncryptionFun example. You can get the compiled binaries for StringEncryptionFun here

Tracing execution

from dumpulator import Dumpulator

dp = Dumpulator("StringEncryptionFun_x64.dmp", trace=True)
dp.start(dp.regs.rip)

This will create StringEncryptionFun_x64.dmp.trace with a list of instructions executed and some helpful indications when switching modules etc. Note that tracing significantly slows down emulation and it's mostly meant for debugging.

Reading utf-16 strings

from dumpulator import Dumpulator

dp = Dumpulator("my.dmp")
buf = dp.call(0x140001000)
dp.read_str(buf, encoding='utf-16')

Running a snippet of code

Say you have the following function:

00007FFFC81C06C0 | mov qword ptr [rsp+0x10],rbx       ; prolog_start
00007FFFC81C06C5 | mov qword ptr [rsp+0x18],rsi
00007FFFC81C06CA | push rbp
00007FFFC81C06CB | push rdi
00007FFFC81C06CC | push r14
00007FFFC81C06CE | lea rbp,qword ptr [rsp-0x100]
00007FFFC81C06D6 | sub rsp,0x200                      ; prolog_end
00007FFFC81C06DD | mov rax,qword ptr [0x7FFFC8272510]

You only want to execute the prolog and set up some registers:

from dumpulator import Dumpulator

prolog_start = 0x00007FFFC81C06C0
# we want to stop the instruction after the prolog
prolog_end = 0x00007FFFC81C06D6 + 7

dp = Dumpulator("my.dmp", quiet=True)
dp.regs.rcx = 0x1337
dp.start(start=prolog_start, end=prolog_end)
print(f"rsp: {hex(dp.regs.rsp)}")

The quiet flag suppresses the logs about DLLs loaded and memory regions set up (for use in scripts where you want to reduce log spam).

Custom syscall implementation

You can (re)implement syscalls by using the @syscall decorator:

from dumpulator import *
from dumpulator.native import *
from dumpulator.handles import *
from dumpulator.memory import *

@syscall
def ZwQueryVolumeInformationFile(dp: Dumpulator,
                                 FileHandle: HANDLE,
                                 IoStatusBlock: P[IO_STATUS_BLOCK],
                                 FsInformation: PVOID,
                                 Length: ULONG,
                                 FsInformationClass: FSINFOCLASS
                                 ):
    return STATUS_NOT_IMPLEMENTED

All the syscall function prototypes can be found in ntsyscalls.py. There are also a lot of examples there on how to use the API.

To hook an existing syscall implementation you can do the following:

import dumpulator.ntsyscalls as ntsyscalls

@syscall
def ZwOpenProcess(dp: Dumpulator,
                  ProcessHandle: Annotated[P[HANDLE], SAL("_Out_")],
                  DesiredAccess: Annotated[ACCESS_MASK, SAL("_In_")],
                  ObjectAttributes: Annotated[P[OBJECT_ATTRIBUTES], SAL("_In_")],
                  ClientId: Annotated[P[CLIENT_ID], SAL("_In_opt_")]
                  ):
    process_id = ClientId.read_ptr()
    assert process_id == dp.parent_process_id
    ProcessHandle.write_ptr(0x1337)
    return STATUS_SUCCESS

@syscall
def ZwQueryInformationProcess(dp: Dumpulator,
                              ProcessHandle: Annotated[HANDLE, SAL("_In_")],
                              ProcessInformationClass: Annotated[PROCESSINFOCLASS, SAL("_In_")],
                              ProcessInformation: Annotated[PVOID, SAL("_Out_wri   tes_bytes_(ProcessInformationLength)")],
                              ProcessInformationLength: Annotated[ULONG, SAL("_In_")],
                              ReturnLength: Annotated[P[ULONG], SAL("_Out_opt_")]
                              ):
    if ProcessInformationClass == PROCESSINFOCLASS.ProcessImageFileNameWin32:
        if ProcessHandle == dp.NtCurrentProcess():
            main_module = dp.modules[dp.modules.main]
            image_path = main_module.path
        elif ProcessHandle == 0x1337:
            image_path = R"C:\Windows\explorer.exe"
        else:
            raise NotImplementedError()
        buffer = UNICODE_STRING.create_buffer(image_path, ProcessInformation)
        assert ProcessInformationLength >= len(buffer)
        if ReturnLength.ptr:
            dp.write_ulong(ReturnLength.ptr, len(buffer))
        ProcessInformation.write(buffer)
        return STATUS_SUCCESS
    return ntsyscal   ls.ZwQueryInformationProcess(dp,
                                                ProcessHandle,
                                                ProcessInformationClass,
                                                ProcessInformation,
                                                ProcessInformationLength,
                                                ReturnLength
                                                )

Custom structures

Since v0.2.0 there is support for easily declaring your own structures:

from dumpulator.native import *

class PROCESS_BASIC_INFORMATION(Struct):
    ExitStatus: ULONG
    PebBaseAddress: PVOID
    AffinityMask: KAFFINITY
    BasePriority: KPRIORITY
    UniqueProcessId: ULONG_PTR
    InheritedFromUniqueProcessId: ULONG_PTR

To instantiate these structures you have to use a Dumpulator instance:

pbi = PROCESS_BASIC_INFORMATION(dp)
assert ProcessInformationLength == Struct.sizeof(pbi)
pbi.ExitStatus = 259  # STILL_ACTIVE
pbi.PebBaseAddress = dp.peb
pbi.AffinityMask = 0xFFFF
pbi.BasePriority = 8
pbi.UniqueProcessId = dp.process_id
pbi.InheritedFromUniqueProcessId = dp.parent_process_id
ProcessInformation.write(bytes(pbi))
if ReturnLength.ptr:
    dp.write_ulong(ReturnLength.ptr, Struct.sizeof(pbi))
return STATUS_SUCCESS

If you pass a pointer value as a second argument the structure will be read from memory. You can declare pointers with myptr: P[MY_STRUCT] and dereferences them with myptr[0].

Collecting the dump

~~There is a simple x64dbg plugin available called MiniDumpPlugin~~ The minidump command has been integrated into x64dbg since 2022-10-10. To create a dump, pause execution and execute the command MiniDump my.dmp.

Installation

From PyPI (latest release):

python -m pip install dumpulator

To install from source:

python setup.py install

Install for a development environment:

python setup.py develop

Related work

Dumpulator-IDA: This project is a small POC plugin for launching dumpulator emulation within IDA, passing it addresses from your IDA view using the context menu.
wtf: Distributed, code-coverage guided, customizable, cross-platform snapshot-based fuzzer designed for attacking user and / or kernel-mode targets running on Microsoft Windows
speakeasy: Windows sandbox on top of unicorn.
qiling: Binary emulation framework on top of unicorn.
Simpleator: User-mode application emulator based on the Hyper-V Platform API.

What sets dumpulator apart from sandboxes like speakeasy and qiling is that the full process memory is available. This improves performance because you can emulate large parts of malware without ever leaving unicorn. Additionally only syscalls have to be emulated to provide a realistic Windows environment (since everything actually is a legitimate process environment).

Credits

herrcore for inspiring me to make this
secret club
JetBrains for free PyCharm license!
Image by GraphiqaStock on Freepik

Download Dumpulator

Dumpulator - An Easy-To-Use Library For Emulating Memory Dumps. Useful For Malware Analysis (Config Extraction, Unpacking) And Dynamic Analysis In General (Sandboxing)

Wed, 24 May 2023 09:54:24 +0200

Note: This is a work-in-progress prototype, please treat it as such. Pull requests are welcome! You can get your feet wet with good first issues

An easy-to-use library for emulating code in minidump files. Here are some links to posts/videos using dumpulator:

Introduction video with OALabs: Dumpulator - Using Binary Emulation To Automate Reverse Engineering
Emulating malware with Dumpulator
Emotet x64 Stack Strings Config Emulation | OALABS Research
Native function and Assembly Code Invocation
Guloader string decryption (VEH)

Examples

Calling a function

The example below opens StringEncryptionFun_x64.dmp (download a copy here), allocates some memory and calls the decryption function at 0x140001000 to decrypt the string at 0x140017000:

from dumpulator import Dumpulator

dp = Dumpulator("StringEncryptionFun_x64.dmp")
temp_addr = dp.allocate(256)
dp.call(0x140001000, [temp_addr, 0x140017000])
decrypted = dp.read_str(temp_addr)
print(f"decrypted: '{decrypted}'")

The StringEncryptionFun_x64.dmp is collected at the entry point of the tests/StringEncryptionFun example. You can get the compiled binaries for StringEncryptionFun here

Tracing execution

from dumpulator import Dumpulator

dp = Dumpulator("StringEncryptionFun_x64.dmp", trace=True)
dp.start(dp.regs.rip)

Reading utf-16 strings

from dumpulator import Dumpulator

dp = Dumpulator("my.dmp")
buf = dp.call(0x140001000)
dp.read_str(buf, encoding='utf-16')

Running a snippet of code

Say you have the following function:

00007FFFC81C06C0 | mov qword ptr [rsp+0x10],rbx       ; prolog_start
00007FFFC81C06C5 | mov qword ptr [rsp+0x18],rsi
00007FFFC81C06CA | push rbp
00007FFFC81C06CB | push rdi
00007FFFC81C06CC | push r14
00007FFFC81C06CE | lea rbp,qword ptr [rsp-0x100]
00007FFFC81C06D6 | sub rsp,0x200                      ; prolog_end
00007FFFC81C06DD | mov rax,qword ptr [0x7FFFC8272510]

You only want to execute the prolog and set up some registers:

from dumpulator import Dumpulator

prolog_start = 0x00007FFFC81C06C0
# we want to stop the instruction after the prolog
prolog_end = 0x00007FFFC81C06D6 + 7

dp = Dumpulator("my.dmp", quiet=True)
dp.regs.rcx = 0x1337
dp.start(start=prolog_start, end=prolog_end)
print(f"rsp: {hex(dp.regs.rsp)}")

The quiet flag suppresses the logs about DLLs loaded and memory regions set up (for use in scripts where you want to reduce log spam).

Custom syscall implementation

You can (re)implement syscalls by using the @syscall decorator:

from dumpulator import *
from dumpulator.native import *
from dumpulator.handles import *
from dumpulator.memory import *

@syscall
def ZwQueryVolumeInformationFile(dp: Dumpulator,
                                 FileHandle: HANDLE,
                                 IoStatusBlock: P[IO_STATUS_BLOCK],
                                 FsInformation: PVOID,
                                 Length: ULONG,
                                 FsInformationClass: FSINFOCLASS
                                 ):
    return STATUS_NOT_IMPLEMENTED

All the syscall function prototypes can be found in ntsyscalls.py. There are also a lot of examples there on how to use the API.

To hook an existing syscall implementation you can do the following:

import dumpulator.ntsyscalls as ntsyscalls

@syscall
def ZwOpenProcess(dp: Dumpulator,
                  ProcessHandle: Annotated[P[HANDLE], SAL("_Out_")],
                  DesiredAccess: Annotated[ACCESS_MASK, SAL("_In_")],
                  ObjectAttributes: Annotated[P[OBJECT_ATTRIBUTES], SAL("_In_")],
                  ClientId: Annotated[P[CLIENT_ID], SAL("_In_opt_")]
                  ):
    process_id = ClientId.read_ptr()
    assert process_id == dp.parent_process_id
    ProcessHandle.write_ptr(0x1337)
    return STATUS_SUCCESS

@syscall
def ZwQueryInformationProcess(dp: Dumpulator,
                              ProcessHandle: Annotated[HANDLE, SAL("_In_")],
                              ProcessInformationClass: Annotated[PROCESSINFOCLASS, SAL("_In_")],
                              ProcessInformation: Annotated[PVOID, SAL("_Out_wri   tes_bytes_(ProcessInformationLength)")],
                              ProcessInformationLength: Annotated[ULONG, SAL("_In_")],
                              ReturnLength: Annotated[P[ULONG], SAL("_Out_opt_")]
                              ):
    if ProcessInformationClass == PROCESSINFOCLASS.ProcessImageFileNameWin32:
        if ProcessHandle == dp.NtCurrentProcess():
            main_module = dp.modules[dp.modules.main]
            image_path = main_module.path
        elif ProcessHandle == 0x1337:
            image_path = R"C:\Windows\explorer.exe"
        else:
            raise NotImplementedError()
        buffer = UNICODE_STRING.create_buffer(image_path, ProcessInformation)
        assert ProcessInformationLength >= len(buffer)
        if ReturnLength.ptr:
            dp.write_ulong(ReturnLength.ptr, len(buffer))
        ProcessInformation.write(buffer)
        return STATUS_SUCCESS
    return ntsyscal   ls.ZwQueryInformationProcess(dp,
                                                ProcessHandle,
                                                ProcessInformationClass,
                                                ProcessInformation,
                                                ProcessInformationLength,
                                                ReturnLength
                                                )

Custom structures

Since v0.2.0 there is support for easily declaring your own structures:

from dumpulator.native import *

class PROCESS_BASIC_INFORMATION(Struct):
    ExitStatus: ULONG
    PebBaseAddress: PVOID
    AffinityMask: KAFFINITY
    BasePriority: KPRIORITY
    UniqueProcessId: ULONG_PTR
    InheritedFromUniqueProcessId: ULONG_PTR

To instantiate these structures you have to use a Dumpulator instance:

pbi = PROCESS_BASIC_INFORMATION(dp)
assert ProcessInformationLength == Struct.sizeof(pbi)
pbi.ExitStatus = 259  # STILL_ACTIVE
pbi.PebBaseAddress = dp.peb
pbi.AffinityMask = 0xFFFF
pbi.BasePriority = 8
pbi.UniqueProcessId = dp.process_id
pbi.InheritedFromUniqueProcessId = dp.parent_process_id
ProcessInformation.write(bytes(pbi))
if ReturnLength.ptr:
    dp.write_ulong(ReturnLength.ptr, Struct.sizeof(pbi))
return STATUS_SUCCESS

If you pass a pointer value as a second argument the structure will be read from memory. You can declare pointers with myptr: P[MY_STRUCT] and dereferences them with myptr[0].

Collecting the dump

Installation

From PyPI (latest release):

python -m pip install dumpulator

To install from source:

python setup.py install

Install for a development environment:

python setup.py develop

Related work

Dumpulator-IDA: This project is a small POC plugin for launching dumpulator emulation within IDA, passing it addresses from your IDA view using the context menu.
wtf: Distributed, code-coverage guided, customizable, cross-platform snapshot-based fuzzer designed for attacking user and / or kernel-mode targets running on Microsoft Windows
speakeasy: Windows sandbox on top of unicorn.
qiling: Binary emulation framework on top of unicorn.
Simpleator: User-mode application emulator based on the Hyper-V Platform API.

Credits

herrcore for inspiring me to make this
secret club
JetBrains for free PyCharm license!
Image by GraphiqaStock on Freepik

Download Dumpulator

Building Better ML Systems. Chapter 1: Every project must start with a plan.

Thu, 20 Apr 2023 17:35:48 +0200

Building Better ML Systems —
Chapter 1: Every Project Must Start with a Plan

About ML project lifecycle, designs doc, business value, and requirements. About starting small and failing fast.

Photo by charlesdeluvio on Unsplash

A lot of data scientists and ML engineers, after graduating from universities, have a false image of how their day-to-day work will look like — they expect it to be similar to their studies:

Trying cool state-of-the-art algorithms on fixed relatively clean datasets and selecting the best one in terms of accuracy (Expectations).

You don’t need:

To think about the business value and a never-ending list of requirements.
(Most likely) to collect, label, and clean the dataset. In some cases, even the train/validation/test split is already done for you.
To thoroughly evaluate your model, check for biases, and conduct A/B tests.
To deploy the model to thousands (or millions) of users and ensure it is up and running 99.9% of the time.
To monitor the model, catch any drops in accuracy, and retrain it as needed.
To collect new data immediately after deploying a previous version and start working on a new, hopefully, better model.

Yes, you don’t need to think about all this during the research/study project. But in real-life projects it becomes crucial.

The main difference between research and a real-life project is that:

In real life, there are many users who use your model in all imaginable and unimaginable ways and expect it to always work quickly, accurately, and fairly without bias. Users’ behaviors continuously change, and epidemics and wars may happen, while your company tries to earn a profit by delivering what users want and building a competitive advantage by applying Machine Learning in ways that no one else has ever tried or succeeded before (Reality).

Throughout this series, you will learn that building better Machine Learning systems requires thinking of it as a system — paying enough attention to each component and their relationships.

This tutorial will be beneficial for Data Scientists, Machine Learning Engineers, Team, and Tech Leads (or those who aspire to be one). Do not expect this series to be comprehensive, although it will help you lay a strong foundation in ML system design, fill any gaps, and allow you to explore topics that are less familiar to you. Along the way, I will provide links to numerous excellent posts, papers, and books.

Without further ado, let’s begin!

Every project must start with a plan.

Below is the Machine Learning project lifecycle. Make yourself comfortable. First, you understand the task and determine what needs to be done. Then, you collect, label, and clean the data. Next, you move on to modeling. After that, you evaluate the models and select the best one. Finally, you deploy the model and monitor its performance.

Image 1. Life Cycle of a Machine Learning Project. Image by Author.

Is this the end? No, it is only the beginning.

While monitoring, you may discover that the model is not working well for some subset of users, or its accuracy is deteriorating over time, so you start again: understand the problem -> get data -> model and evaluate -> deploy.

Or during model evaluation, you may find that the model is not good enough to deploy, and so you start again: understand what is not working and how to improve it -> collect more data -> do more modeling -> evaluate to (hopefully) get better results this time.

(If this is your first time learning about the Machine Learning project lifecycle, I recommend checking out Anton Morgunov’s post: The Life Cycle of a Machine Learning Project: What Are the Stages?)

So there are two important things to understand:

Building a Machine Learning system is an iterative process that continues forever until the model is removed from production. (No rest for the wicked)
Image 1 provides a simplified version of how a Machine Learning system is developed, but in reality, you do not move smoothly and sequentially from stage to stage. Something can go wrong (and usually does) at each stage, which can set you back one or more steps, or even throw you to the beginning. (Welcome to the real world)

Image 2. Realistic Life Cycle of a Machine Learning Project. Image by Author.

Those with engineering backgrounds may wonder: What is the difference between Machine Learning projects and traditional software development? Where are the tests, builds, and releases? Thank you for asking.

The truth is that the Machine Learning project is a subclass of a software engineering project. So all the best practices you may think of in software engineering are highly welcomed in ML projects. With that said, let me introduce you to a truly realistic life cycle of a software project with a Machine Learning component:

Image 3. Truly Realistic Life Cycle of a Software project with a Machine Learning component. Image by Author.

And to take control over this chaos, each project must start with a plan.

(Read MLOps: Machine Learning Life Cycle by Satish Chandra Gupta to learn more about the ML software development lifecycle.)

Before spending thousands of dollars on data annotation and weeks and weeks on Machine Learning model development, there are four things you need to do. Let’s call it the “pre-coding” stage. So, close your PyCharm for now, as all you need is a Google document, your brain, and Zoom.

1. Estimate the business value of the ML project.

Any commercial company’s goal is to earn more money or provide a better customer experience… in order to earn more money. With this simple axiom in mind, convince your boss, C-level management, and stakeholders that the current ML project is a good investment.

Ideally, you need to provide some rough numbers on how the ML model increases the company’s revenue, user engagement, or decreases request processing time, etc. Be creative here, turn off your perfectionism, and do not hesitate to ask your colleagues from the financial and marketing departments for help.

(Keep in mind, later this metric will be used to access the project, so be realistic with what you promise to deliver.)

2. Collect the requirements.

Once no one has doubts that the ML model is necessary, start collecting requirements.

Each domain is specific and each project is unique, so there is no exhaustive list of requirements to refer to. So trust your experience and collaborate with your colleagues.

Here’s a helpful tip: Come up with a list of generic questions (I’ll share mine below) and just ask. Start the conversation, and as you discuss, more project-specific questions will naturally arise.

How much data do we have? How are we going to label it?
What should model latency be?
Where will the model be deployed — cloud or on-premises? What are the instance specifications?
Are there any requirements for data privacy and model explainability?

If a task can be solved with machine learning, it does not mean it should be. At this point, I suggest that you reconsider whether a pure software engineering approach or a basic rule-based approach may be a suitable solution. Here are the posts that can help you with that:
- When to Use Machine Learning by Amazon
- Four Situations Where you Should Not use Machine Learning by Svenja Szillat

There is no Machine Learning without data. It may seem obvious, but unfortunately, in my career, I’ve seen too many companies making the same mistake: they want AI, but their datasets are small, lacking important features, or dirty. A great post “The AI Hierarchy of Needs” by Monica Rogati encourages to think of AI as the top of a pyramid of needs, while data collection, storage, and cleaning are at the foundation.

Image 4. The AI Hierarchy of Needs. Adapted from an image by Monica Rogati in “The AI Hierarchy of Needs”.

3. Start small and fail fast.

Even if your goal is to create an ML system that serves millions of users per day, it’s wise to start with something much much smaller:

PoC (Proof of Concept). Manually retrieve data from data storages, quickly iterate through a couple of algorithms in a Jupyter Notebook, and finally, proof (or reject) the hypothesis that you can train a machine learning model with satisfactory accuracy on the data you have. During the PoC stage, you’ll also understand what is needed to deploy and scale the model.
MVP (Minimal Viable Product). Assuming the PoC stage was successful and now you are creating a product with only the main functionality and releasing it to users. In a Machine Learning project, this means rolling out the model to a segment of the users and accessing whether it brings the expected business value.

Once you realize that an idea is not working out — abandon it with a clear conscience and move to the next one. This is much easier to do when you haven’t already spent years of work or hundreds of thousands of dollars. Keeping the cost of failure low is a key factor in the success of a project.

(To explore this topic further, read POC vs MVP: What to Choose to Build a Great Product by Dmitry Chekalin.)

4. Write a design document.

A design document in software engineering is a description of the software system’s architecture — its overall structure, its individual components, and the interactions between them. It can take an arbitrary form and structure, be formal or informal, high-level or detailed (it is up to a team to decide). During the implementation phase of software development, the design document serves as a blueprint for developers to follow.

This is a best practice in software engineering, and as I mentioned earlier, all software engineering best practices are highly welcomed in ML projects.

My personal reasons to love design docs are:

Writing triggers the thought process. Writing a design doc is like implementing the project on a high level — you do not actually code but still make decisions on data, algorithms, and infrastructure. You consider all scenarios and evaluate trade-offs, which means that you’ll save time and money in the future by avoiding dead ends.
Design docs simplify the synchronization and collaboration within a team. The document is shared among team members so that they can review it, familiarize themselves with the system design, and launch discussions if needed. No one is left out, and everyone is encouraged to contribute.

If you are ready to start writing a design doc, here is a template for machine learning systems proposed by Eugene Yan. Feel free to modify it and adapt it to your project needs.

If you would like to learn more about design documents as a concept, check out these posts:
- How to Write Design Docs for Machine Learning Systems by Eugene Yan
- Design Docs at Google by Malte Ubl

Conclusion

In this chapter, we learned that every project must start with a plan because ML systems are too complex to implement in an ad-hoc manner. We reviewed the ML project lifecycle, discussed why and how to estimate project business value, how to collect the requirements, and then reevaluate with a cold mind whether ML is truly needed. We learned how to start small and fail fast using concepts like “PoC” and “MVP”. And finally, we talked about the importance of design documents during the planning stage.

In the next posts, you will learn about data collection and labeling, model development, experiment tracking, online and offline evaluation, deployment, monitoring, retraining, and much much more — all this will help you build better Machine Learning systems.

The next chapter will be available soon. Subscribe to stay tuned.

Building Better ML Systems. Chapter 1: Every project must start with a plan. was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

Visual Studio Vs PyCharm: Which One Should You Use?

Fri, 07 Apr 2023 14:16:56 +0200

When developing software, choosing the right Integrated Development Environment (IDE) is important. The environment should be easy to use and must integrate well with the languages you are using. The two most popular IDEs for developing software are Visual Studio and PyCharm. Both software have their distinctive features and advantages, which makes them appropriate for […]

The post Visual Studio Vs PyCharm: Which One Should You Use? appeared first on Windows Report - Error-free Tech Life.

snap vs flatpak

Mon, 13 Feb 2023 09:30:57 +0100

I've just noticed that both VScode and PyCharm offer snaps but not flatpaks, according to their websites.

Since these are quite important software packages, does this indicate that snap gets closer to becoming the "industry standard" instead of the more free/open flatpak system? I've always been a bigger fan of flatpak, if I had to choose something outside the repos.

submitted by /u/trivialBetaState
[link] [comments]

PyCharm Professional 2022.3.1 - Python IDE with complete set of tools.

Thu, 29 Dec 2022 21:00:33 +0100

PyCharm is a Python IDE with complete set of tools for productive development with the Python programming language. In addition, the IDE provides high-class capabilities for professional Web development with the Django framework.

Following the release of version 3, PyCharm forked into two paths: a free, Open-Source Community Edition; and the commercial, full-featured Professional Edition. Here are a few highlights of the different forks:

Professional Edition

Full-featured IDE for Python & Web development
Supports Django, Flask, Google App Engine, Pyramid, web2py
JavaScript, CoffeeScript, TypeScript, CSS, Cython, Template languages and more
Remote development, Databases and SQL support, UML, and SQLAlchemy Diagrams

Community Edition

Lightweight IDE for Python development only
Free, open-source, Apache 2 license
Intelligent Editor, Debugger, Refactorings, Inspections, VCS integration
Project Navigation, Testing support, Customizable UI, Vim key bindings

You can compare the forks here.

The quoted price is that for individual customers, paid annually. PyCharm is available at several price points. Above price reflects one year subscription for individual user; see this page for more information.

The option to display editor tabs on multiple rows is available in the new UI.
Actions on Save work as expected again.
Excessive CPU usage and IDE freezes that occurred for certain tool window sizes have been fixed.
Packaging: PyCharm no longer uses excessive disk space when caching PyPI.
Running a script on the Python Debug Server with pydevd-pycharm works as expected again.
Quick documentation popup: Markup used in docstrings is now rendered in Quick documentation.
HTTP client: Setting a proxy no longer breaks package inspection.
Python console: Code that is run with the Emulate terminal in output console option enabled now has the correct indentation level.
Inspections: The Loose punctuation mark inspection now works correctly for reStructuredText fields in docstrings.
Inspections: We fixed an SOE exception where processing generic types broke error highlighting in the editor.
Debugger: We fixed several issues with the debugger.
Code insight: Code insight for IntEnum properties is now correct.
Code insight: Code insight has been improved for data class arguments when wildcard or custom module import is involved.

Version for Apple Silicon

Download Now]]>

PyCharm Community 2022.3.1 - Lightweight IDE for Python development only.

Thu, 29 Dec 2022 19:45:34 +0100

PyCharm's smart code editor provides first-class support for Python, JavaScript, CoffeeScript, TypeScript, CSS, popular template languages and more. Take advantage of language-aware code completion, error detection, and on-the-fly code fixes!

Intelligent Python Support Enjoy outstanding coding assistance with smart code completion, code inspections, on-the-fly error highlighting, auto-fixes, along with automated code refactorings and rich navigation capabilities for all major Python implementations.
Smart Cross-technology Support In addition to Python, Pycharm supports JavaScript, CoffeeScript, TypeScript, HTML/CSS, Cython, template languages, AngularJS, Node.js, and more.
Web Development Frameworks PyCharm offers great framework-specific support for modern web development frameworks such as Django, Flask, Google App Engine, Pyramid, and web2py.
Remote Development Capabilities Run, debug, test, and deploy applications on remote hosts or virtual machines, with remote interpreters, integrated ssh terminal, and Vagrant integration.
Built-in Developer Tools An amazing suite of tools right out of the box: an integrated debugger and graphical test runner; a built-in terminal; integration with Git, SVN, and Mercurial; built-in Database Tools & SQL support.
Customizable and Cross-platform IDE PyCharm works on Windows, Mac OS or Linux with a single license key. Enjoy a fine-tuned workspace with customizable color schemes and key-bindings, with VIM emulation available.

Packaging: PyCharm no longer uses excessive disk space caching PyPI.
HTTP client: Setting a proxy no longer breaks package inspection.
Python console: Code that is run with the Emulate terminal in output console option enabled now has the correct indentation level.
Inspections: The Loose punctuation mark inspection now works correctly for reStructuredText fields in docstrings.
Inspections: Fixed an SOE exception where processing generic types broke error highlighting in the editor.
Debugger: We fixed several issues for the debugger.
Code insight: Code insight for IntEnum properties is now correct.
Code insight: Code insight has been improved for dataclass arguments when wildcard import is used.

Version for Apple Silicon

Download Now]]>

Start Using Python to Automate PLAXIS

Fri, 09 Dec 2022 22:31:18 +0100

PLAXIS AUTOMATION SERIES

Step-by-step guide toward automation

Photo by Hitesh Choudhary on Unsplash

PLAXIS is a Finite Element modelling software that geotechnical engineers will definitely come across at a certain point in their careers. Modelling complex geotechnical problems in a PLAXIS can be challenging and represents time-consuming modelling work often involving repetitive tasks.

As an engineer, we always want to automate the boring and engineer the awesome.

In this context, programming, more specifically Python, is the best available tool to automate repetitive tasks.

Python has been around for many years but only recently get recognised by the larger community because of its ease of use, large extent of applications and support by huge open-source communities. It is a great programming language for data science, workflow automation and web development.

PLAXIS has a well-developed Application Programming Interface (API) which allows users to operate PLAXIS through programming. More details can be seen on the official Bentley website.

API / Python scripting - PLAXIS

Goal

Although the PLAXIS Python API has been developed for a long time, there is still a lack of thorough guidelines to introduce this technique to geotechnical engineers.

This tutorial assumes readers have zero experience in programming so I will show how to set up the programming environment from scratch.

Disclaimer

There have been a lot of paid courses which teach engineers to use the built-in Python editor in PLAXIS which I agree is quite well-developed. But I personally prefer to use my own programming environment to write scripts because of the following three reasons:

A well-developed Integrated Development Environment (IDE) is more user-friendly for coding as it picks up wrong syntaxes and identifies bugs, which is crucial for beginners.
Built-in Python editor has less flexibility to import user-developed modules. In the future when you have more programming experience, you will find that a lot of time we need to separate out the functions we write as a module which makes our script less busy. This can be well managed in IDE.
We don’t want to keep the scripts to ourselves but to share among colleagues. IDE provides perfect integration with code-sharing platforms such as GitHub, GitLab etc.

The ultimate goal of this tutorial is to show you how to use Python script to create your first structural element in PLAXIS 2D. This can be done with the following four steps.

Install Integrated Development Environment (IDE)
Activate PLAXIS Environment
Connect to PLAXIS API
Create first plate element

Lastly, this tutorial assumes readers are using Windows OS and have PLAXIS 2D V22 installed. So let’s get started!

Step 1: Install Integrated Development Environment (IDE)

IDE is a software application which provides comprehensive facilities for programming, usually consisting of source code editor, build automation tools and debugger.

There are various options for IDE, such as Visual Studio Code (VS Code), PyCharm, Jupyter Notebook etc, which have no difference in functionality and are completely up to users’ preference for the choice of IDE. This instruction demonstrates the installation of VS Code.

Install Visual Studio Code (VS Code) with the following instruction:

Download the latest VS code for Windows: https://code.visualstudio.com/download

Screenshot by the author

Follow the installation wizard, and check the options as shown below.

Screenshot by the author

Once installed, open VS Code on Desktop. You will see the following interface.

Screenshot from VS Code by the author

Add your work folder in Explorer by right clicking Explorer -> Add Folder to Workplace…

Screenshot from VS Code by the author

You have now got VS code set-up and is ready to start coding!

Step 2: Activate PLAXIS Environment

Once your virtual environment and IDE are set up, you can start writing Python script within IDE.

To write a Python script, you should follow the process below:

Open IDE terminal
Direct to your preferred work folder (in terminal)
Activate PLAXIS Python Environment
Create .py file in the folder

Open IDE terminal

Click the “warning” icons in the bottom menu bar:

Screenshot from VS Code by the author

You will see the Shell window comes up:

Screenshot from VS Code by the author

Head to “Terminal” tab in the top menu bar as indicated. You should see that you are in the work folder.

Screenshot from VS Code by the author

Direct to your preferred work folder

If it is not the correct work folder. You can type:

For example, I am currently at Current Projects folder and I want to locate to 00_Digitalisation->01_Python-FE. The folder path is:

C:\Users\phtsang\Desktop\Current_Projects\00_Digitalisation\01_Python-FE

In IDE terminal:

Screenshot from VS Code by the author

It should show the correct folder name as shown above.

Activate PLAXIS Python Environment

To activate the PLAXIS Python environment, we will need to select PLAXIS built-in python interpreter which contains all the functionalities required to operate PLAXIS. The python interpreter is automatically installed when PLAXIS is installed.

Location of the Python interpreter:

C:\ProgramData\Bentley\Geotechnical\PLAXIS Python Distribution V2\python\python.exe

To select a specific environment, use the Python: Select Interpreter command from the Command Palette (Ctrl+Shift+P). Click “Enter interpreter path…”, then browse the python.exe in the location mentioned above.

Screenshot from VS Code by the author

In the Terminal tab, select Command Prompt in the drop down list as highlighted below.

Screenshot from VS Code by the author

You should see (PLAXIS) in front of the working directory if the environment is activated successfully.

Screenshot from VS Code by the author

Create .py file in the folder

Click the New file icon:

Screenshot from VS Code by the author

Create .py file as below:

Screenshot from VS Code by the author

Next section we will start connecting to the PLAXIS API.

Step 3: Connect PLAXIS API

I will first create an empty python script and call it “create_plate.py” as shown below.

Screenshot from VS Code by the author

After that, we write the code below to the python file. Three things are doing here:

Import modules from PLAXIS Python environment. In order to operate PLAXIS with Python script, we need to use the functions (more commonly known as methods in terms of programming) developed by PLAXIS. The module we import is called “plxscripting.east”
Open PLAXIS 2D desktop application. The path of the Plaxis2DXInput.exe should be the same as listed below if default installation path is adopted. If that’s not the case, simply change the path to the correct directory. Port number and Password can stay as default but you can select any values you want.
Start the PLAXIS scripting server with the pre-defined port number and password.

from plxscripting.easy import *
import subprocess, time

PLAXIS_PATH = r'C:\Program Files\Bentley\Geotechnical\PLAXIS 2D CONNECT Edition V22\\Plaxis2DXInput.exe'  # Specify PLAXIS path on server.

PORT_i = 10000  # Define a port number.
PORT_o = 10001

PASSWORD = 'SxDBR
subprocess.Popen([PLAXIS_PATH, f'--AppServerPassword={PASSWORD}', f'--AppServerPort={PORT_i}'], shell=False)  # Start the PLAXIS remote scripting service.

time.sleep(5)  # Wait for PLAXIS to boot before sending commands to the scripting service.


# Start the scripting server.

s_i, g_i = new_server('localhost', PORT_i, password=PASSWORD)
s_o, g_o = new_server('localhost', PORT_o, password=PASSWORD)


s_i.new()

g_i.gotostructures()

Screenshot from VS Code by the author

To test that the code above is working properly, we will run “create_plate.py” in the terminal as shown below. Type “python create_plate.py” and click Enter.

(PLAXIS) C:\Users\phtsang\Desktop\PLAXIS_V22\Script>python create_plate.py

Screenshot from VS Code by the author

The PLAXIS 2D app should be opened automatically. If the server is configured correctly, you should see “SERVER ACTIVE” as shown below.

Screenshot from PLAXIS by the author

Now that we connect to the PLAXIS API server, we can then create a plate element in PLAXIS using Python script.

Step 4: Create First Plate Element

In this part of tutorial, we aim to create a plate element with positive and negative interfaces. Then we assign “Concrete” material to the element.

First, we define the material name and geometry. I plan to create a line from (-10,0) to (10,0). The square bracket [ ] is called list in python, which is a very common data type to store values. To access the values stored in a list, it is called in the following syntax:

If I want to access the coordinates of first point, I use

x coordinate = -10 = first_point[0]

y coordinate = 10 = first_point[1]

0 and 1 here called index which always starts from 0.

Then we create the material and assign it to the plate material list. To create plate material, the command “g_i.platemat()” is used. The code underneath is to assign the plate object to a list.

material=['Concrete']
first_point=[-10,0]
second_point=[10,0]

# Create material
for i in range(len(material)):
    g_i.platemat('Identification',material[i])


platematerials = [mat for mat in g_i.Materials[:] if mat.TypeName.value == 'PlateMat']

After that, we create plate element with “g_i.plate()” based on the pre-defined coordinates.

plate=g_i.plate(
    (first_point[0],first_point[1]),
    (second_point[0],second_point[1]),
    )
plate1=plate[-1]

Then, create interfaces using “g_i.posinterface()” and “g_i.neginterface()”.

plate2=plate[-2]
g_i.posinterface(plate2)
g_i.neginterface(plate2)

Finally, set “Concrete” to the plate element.

plate1.setmaterial(platematerials[0])

If you rerun the script, you will see the following is created in PLAXIS. As you see, the “Concrete” material is created and assigned to the plate element we created.

Screenshot from PLAXIS by the author

Congratulations! You have just created your first plate element in PLAXIS using Python!

Bonus

Of course, we often need to create more than one structural element in PLAXIS. In this section, we aim to create four plate elements which form a rectangle with the following coordinates:

(-10,0)
(-10,10)
(10,10)
(10,0)

We need to first create a list (call it ‘df_plate’) which specifies the coordinates of each plate element. The first and second points are stored as (x1,y1) and (x2,y2) respectively. Within the list, I used a new data type called Dictionary which is very commonly used in Python. More on that in the next tutorial.

df_plate=[{'x1':-10,'y1':0,'x2':10,'y2':0},{'x1':-10,'y1':10,'x2':-10,'y2':0},{'x1':-10,'y1':10,'x2':10,'y2':10},{'x1':10,'y1':10,'x2':10,'y2':0}]

Since this time we need to access multiple elements in a list, we will utilise a concept called for loop. It allows us to loop through the elements and create points in PLAXIS accordingly. This can be done with the following code:

for i in range(len(df_plate)):
    plate=g_i.plate(
        (df_plate[i]['x1'],df_plate[i]['y1']),
        (df_plate[i]['x2'],df_plate[i]['y2']),
        )
    plate1=plate[-1]

Your final script should look like:

# Plate
#Material name and geometry
material=['Concrete']

df_plate=[{'x1':-10,'y1':0,'x2':10,'y2':0},{'x1':-10,'y1':10,'x2':-10,'y2':0},{'x1':-10,'y1':10,'x2':10,'y2':10},{'x1':10,'y1':10,'x2':10,'y2':0}]

# Create material
for i in range(len(material)):
    g_i.platemat('Identification',material[i])

platematerials = [mat for mat in g_i.Materials[:] if mat.TypeName.value == 'PlateMat']

#Create Plate
for i in range(len(df_plate)):
    plate=g_i.plate(
        (df_plate[i]['x1'],df_plate[i]['y1']),
        (df_plate[i]['x2'],df_plate[i]['y2']),
        )
    plate1=plate[-1]

#Create Interface

    plate2=plate[-2]
    g_i.posinterface(plate2)
    g_i.neginterface(plate2)
#Set Material

    plate1.setmaterial(platematerials[0])

If you rerun the script, you will see the following is created in PLAXIS. Now, you are able to create multiple elements using Python script.

Screenshot from PLAXIS by the author

Conclusion

That’s the end of the first tutorial on automating PLAXIS with Python. By now, you should be able to create structural elements in PLAXIS using Python script. In the future, I will keep posting tutorials on using Python in PLAXIS. More than that, I’m also keen to share knowledge on how to use Python to automate boring workflow in engineering.

If you’re interested in hearing more about Python, PLAXIS and workflow automation, feel free to follow my page.

Start Using Python to Automate PLAXIS was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

Stop using Print, and start Debugging

Mon, 05 Dec 2022 21:49:19 +0100

Photo by Fotis Fotopoulos onÂ Unsplash

Learn how to debug your Python program with Visual StudioÂ Code

Introduction

I once read that in programming an error in code is called bug for a very specific reason. When computers were still huge mainframes (a long, long time ago) it happened that a bug got stuck in the gears and thatâ€™s why the program wouldnâ€™t runÂ anymore!

Today by bugs we mean a very different thing. Everyone, even the most experienced and paid programmers in the world write code that contains bugs, but the skill lies in finding them. In this article, we find outÂ how!

Print and Jupyter Notebooks

It is common for data scientists to write code using Jupyter Notebooks or Google Colab. I too find that they are super convenient to use, unfortunately, though debugging is not as convenient.

In these notebooks, we can split our code into cells, that way at the end of the execution of a cell, we can print out all the values of the variables we are interested in, and see if anything has gone wrong. Or at least we can get an idea of whatâ€™s going on inside theÂ code.

Even in cases where we do not use notebooks, we often use print() to figure out the value of variables and thus understand why the code behaved a certain way and fixÂ it.

For example, suppose we want to execute the following code.

admin = get_user_input() #returns user input

if admin == 'admin':
  print(f'welcome {admin}')

With the previous code, we know we have the variable admin. When this variable takes the value â€˜adminâ€™ we want to greet ourÂ admin.

We find, however, that this condition never occurs, even when it should occur, since it is our admin who is using theÂ program.

Then what novice programmers generally do is go and print out the admin variable and figure out whatâ€™sÂ wrong.

admin = get_user_input() #returns user input
print('The value of admin is : ' , admin)

if admin == 'admin':
  print(f'welcome {admin} ')

We note that the result of this print is asÂ follows.

The value of admin is : admin\n

And we find that our get_user_input function returns one \n extra and that is why the condition never occurs. We are then ready to fix our code and run everything. BugÂ found!

But is this the best way to find the bug? Not really. In such simple cases where we have 4 lines of code maybe it is okay, but in more complex projects you have to prefer the debugger tool that is provided by variousÂ IDEs.

Debug withÂ VSCode

IDE stands for Integrated Development Environment and is a tool that allows you to write code by providing very useful tools such as a debugger.

In this article, we will look at the VSCode debugger but they all work pretty much the same, so even if you use PyCharm or any other IDE donâ€™tÂ worry.

Letâ€™s start by writing a simple code in Python in VSCode. The example code is asÂ follows.

from random import random, randint
import time 

class User:
    def __init__(self, name , psw) -> None:
        self.name = name
        self.psw = psw

    def say_hello(self):
        print(f'Hello {self.name}') 
        self.get_name_len()

    def get_name_len(self):
        print(len(self.name))

    def __str__(self) -> str:
        return f"{self.name} , {self.psw}"


if __name__ == '__main__':

    for _  in range(3):
        i = int(randint(0,10))

        name = f'user_ {i}' 
        psw = f'psw_ {i}' 
        user = User(name, psw) 
        user.say_hello()

In this code, we created a User class, where each user is described by name and password.

Plus a user has two methods, such as say_hello which greets the user, get_name_len which returns the length of the userâ€™s name, and the __str__ method which defines how a user should beÂ printed.

Finally in the main we go to create three random users and have them use the say_hello method.

Letâ€™s now go to introduce an error. For example in the get_name_len method, we only print the length of self instead of self.name.

from random import random, randint
import time 

class User:
    def __init__(self, name , psw) -> None:
        self.name = name
        self.psw = psw

    def say_hello(self):
        print(f'Hello {self.name}') 
        self.get_name_len()

    def get_name_len(self):
        print(len(self))

    def __str__(self) -> str:
        return f"{self.name} , {self.psw}"

if __name__ == '__main__':

    for _  in range(3):
        i = int(randint(0,10))

        name = f'user_ {i}' 
        psw = f'psw_ {i}' 
        user = User(name, psw) 
        user.say_hello()

Now if we go to execute the code we will get the following error.

Error (Image ByÂ Author)

Our purpose now is to try to find the error using the VSCode debugger.

The first thing to do is to insert a Breakpoint at a certain point in your code. With the Breakpoint, you tell your compiler to pause the run at that point so that you can inspect the various variables in your code, and then continue the run only when you want itÂ to.

To enter a Breakpoint click to the far left of your code and a red dot willÂ appear.

Breakpoint (Image ByÂ Author)

Now letâ€™s run the code in debug mode by clicking on the following icon.

Debug (Image ByÂ Author)

Once you click you will see that your code will start the run but stop almost immediately.

You should now have a screen likeÂ this.

Debug (Image ByÂ Author)

So, the yellow line with that symbol next to it, tells you where the code stopped, right where you put the Breakpoint.

In the upper left corner, on the other hand, you can see the contents of your variables within the code. Many of these variables seem meaningless since they are pointers to functions you have in the code. But if you see well there should be a User variable since before the Breakpoint we have already created a user. In my case, I can see the content which is asÂ follows.

Variables (Image ByÂ Author)

This way I know what the content of my user variable is and I have already saved myself from writing aÂ print().

Now we can start using the main debugger commands found at the top of the bar made likeÂ this.

Commands (Image ByÂ Author)

The main commands are those highlighted in red. The first allows us to go forward one line of code to see what happens. The second allows us to go inside a function and see what happens. And the last one allows us to go outside the scope of a function.

Since our program is now stuck on the user.say_hello() function let's click on the down arrow to see what happens inside this function.

Once clicked you will see that the execution will continue within this function.

say_hello (Image ByÂ Author)

Now we need to understand what the stack is for. The stack tells you basically how many functions you are in. In fact, if you see in the lower left-hand corner now a line has beenÂ added.

Stack (Image ByÂ Author)

This tells us that we are now in the scope of the say_hello function so if we exit this function by clicking the up arrow, we will be back in theÂ main.

Now letâ€™s move forward one line of code with the forwardÂ command.

Forward Command (Image ByÂ Author)

Now that we are over another function, we click the down arrow to go inside the functionÂ itself.

Stack (Image ByÂ Author)

You see that because we have entered inside another function the stack has increased, so we are in a function inside a function (no, this isnâ€™t Inception).

Obviously, we can enter more than one unique Breakpoint. So letâ€™s stop the debug and relaunch it by entering 2 Breakpoints thisÂ time.

Two Breakpoints (Image ByÂ Author)

So in this case by clicking on forward, we are going to stop at the second Breakpoint.

If we now click forward again, the code will go to stop, but this time because we found theÂ error!

Error Found (Image ByÂ Author)

We succeeded in our intent. Error found, and we did not dirty our code with uselessÂ prints!

Only one thing remains to be said. What is the watch section for? Well, to look at variables.

Suppose we save all our users in aÂ list.

from random import random, randint
import time 

class User:
    def __init__(self, name , psw) -> None:
        self.name = name
        self.psw = psw

    def say_hello(self):
        print(f'Hello {self.name}') 
        self.get_name_len()

    def get_name_len(self):
        print('ciao')
        print(len(self.name))

    def __str__(self) -> str:
        return f"{self.name} , {self.psw}"


if __name__ == '__main__':

    users = []
    for _  in range(3):
        i = int(randint(0,10))

        name = f'user_ {i}' 
        psw = f'psw_ {i}' 
        user = User(name, psw) 
        user.say_hello()
        users.append(user)

    print('end of this tutorial')

Now we want to see what happens to this list as we go through the code.
So letâ€™s click on the plus button and add the viable users under watch. In fact, letâ€™s add len(users) asÂ well.

Watch (Image ByÂ Author)

Now as you move forward with your code with the forward command, you will see the list fills up and you will be able to inspect the objects withinÂ it.

After some iterations (Image ByÂ Author)

Final Thoughts

Well, these are the basics of using the debugger. It is a very useful and easy tool to use. Of course like all things, you have to get used to it. So the next time you have problems with your code, force yourself to use the debugger instead of using prints and you will see that in no time you will be automatically using it all theÂ time!

The End

Marcello Politi

Linkedin, Twitter,Â CV

Stop using Print, and start Debugging was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

Step by Step Identity Resolution With Python And Zingg

Mon, 28 Nov 2022 21:43:16 +0100

An open source, machine learning based approach to resolve identities at scale

One of the main challenges in generating useful insights from data is siloed and disjointed datasets having poor data quality. Data inconsistencies and duplicate records are often introduced due to multiple sources of information in enterprise data pipelines. This is a huge problem for data scientists working on fraud detection, personalization and recommendations. For data analysts, it is hard to report accurate customer lifetime value, most valuable customers, new customers added and other metrics as the underlying data is inconsistent.

For example, take a look at the customer data below

Customer Data with multiple records belonging to the same customer and no unique identifier. Image by Author

We can see that there are multiple rows for the same customer, such as the following

Different records for the same customer. Image by Author

We have an ssn column, however, there is no guarantee that it would always be unique. In the example above, the ssn of the second record is not consistent with the other records. A quick human verification however confirms that these 3 records belong to the same customer.

Here’s another example of different records belonging to the same customer.

Image By Author

Defining rules across attributes and combining them all to assess matching records is time consuming and prone to errors. Building such a system can easily take months and delay the actual analysis. Trying to perform identity resolution at scale utilizing data columns is not easy either.

Overall, building an identity resolution system has the following challenges

The total number of comparisons required to find duplicates becomes unmanageable with an increase in the number of records. The total number of comparisons we would make on N records for one attribute is given by

Image By Author

As our dataset size N increases, the number of comparisons shoot up

Scaling Identity Resolution. Image by Author

2. Understanding which attributes to use for identifying duplicates and deciding the matching criteria for large datasets with many attributes and variations is tough.

While building an identity resolution system, the following steps are generally involved

Preprocessing: normalizing the data as much as possible such as getting rid of common occurring words, removing leading and trailing spaces, making attributes in lowercase or same case, cleaning punctuation etc. This is done so that we can define the attribute specific matching rules.
Indexing: Since comparing each record with every other record shows scalability issues we segregate the dataset into smaller blocks and then perform comparisons within the block. This reduces the processing and it becomes much easier to scale the system to a larger volume of data.
Attribute level rule definition: Relevant attributes are compared based on criteria, such as we will consider two records to be similar for email attribute if and only if the emails match exactly.
Record level rule definition: Attribute level comparison defined above is rolled up to a combined definition of similarity at the record level. For example first name and last name match but email does not match completely.
Group similarity: If two records match individually to a third record but do not match each other, maybe due to a missing attribute, how do we handle this?

Building this ourselves is certainly doable but is it worth our time? Let us explore an open source option — Zingg. We will use Zingg’s Python api and build an identity resolution pipeline for our customer data.

As an ML based tool, Zingg takes care of the above steps so that we can perform identity resolution at scale.

In order to perform entity resolution, Zingg defines five phases — findTrainingData, label, train, match and link.

findTrainingData: As a supervised machine learning system, Zingg learns matching from training data. The findTrainingData phase selects sample pairs from our data through which the user can build a training set.
label: This phase pulls up the interactive labeler that shows the pairs selected in findTrainingData. The labeler prompts the user to mark them as matches or non matches. If the user is not sure or unable to decide, the user can choose not sure as an option.
train: Using the labeled data, Zingg learns similarity rules to identify potential duplicates. Zingg does not compare each record in the dataset with every other record in the dataset which would result in scalability issues for large datasets. Instead, Zingg first learns how to group similar records together into blocks. It also learns suitable similarity rules per the training set, thus cutting down the total number of comparisons required. Models are persisted to the disk for use with newer data.
match: The trained models are applied to predict match scores that can be used to resolve identities.
link: Finds matches across datasets

findTrainingData and label phase are usually run a few times and samples are marked by the user. Non matching, obvious matches and edge case samples are chosen carefully by Zingg through findTrainingData to build a robust training set with sufficient variations to train the models.

Once we have about 30–40 matching samples we can train and save the models by running the train phase. Once the model is trained, the match or the link phase can be performed as new datasets with the same attributes come in.

Let us use Zingg on the customer data and resolve identities.

Step 1: Install Zingg

The fastest way to get started with Zingg is to use the Zingg docker image. Let us get the docker image and start working with it.

docker pull zingg/zingg:0.3.4
docker run -u  -it zingg/zingg:0.3.4 bash

For additional information regarding using Zingg docker, check out the official documentation linked here.

We will use the febrl example loaded into a table named customers in Postgres.

Step 2: Define the input location and match criteria

Zingg python package is already installed in the docker container, so we will use it directly.

Let us define the input for our customers table. We create a Python script named FebrlExamplePostgresql.py and import the necessary packages

from zingg.client import *
from zingg.pipes import *

For each column that we want to use as part of our output, we create a FieldDefinition object. The FieldDefinition takes the name of the attribute, its data type, and the match type. For example, we can define the first name column like this

fname = FieldDefinition("fname", "string", MatchType.FUZZY)

Match types configure Zingg on how we want the matching to be performed for each field. Zingg provides different matching criteria, some of which are

FUZZY: Generalized matching with abbreviations, typos and other variations, applicable for fields like names
EXACT: No variations allowed, applicable for fields like country codes
DONT_USE: Fields with this match type are ignored during processing but will appear in the output

There are many more match types that we can use as per our column data documentation here.

The following Python program builds the arguments for Zingg and adds all the field definitions to it.

#build the arguments for zingg
args = Arguments()

#set field definitions
fname = FieldDefinition("fname", "string", MatchType.FUZZY)
lname = FieldDefinition("lname", "string", MatchType.FUZZY)
streetnumber = FieldDefinition("streetnumber", "string", MatchType.FUZZY)
street = FieldDefinition("street","string", MatchType.FUZZY)
address = FieldDefinition("address", "string", MatchType.FUZZY)
locality = FieldDefinition("locality", "string", MatchType.FUZZY)
areacode = FieldDefinition("areacode", "string", MatchType.FUZZY)
state = FieldDefinition("state", "string", MatchType.FUZZY)
dateofbirth = FieldDefinition("dateofbirth", "string", MatchType.FUZZY)
ssn = FieldDefinition("ssn", "string", MatchType.FUZZY)

fieldDefs = [fname, lname, streetnumber, street, address, locality, areacode
state, dateofbirth, ssn]

args.setFieldDefinition(fieldDefs)

Step 3: Connect Zingg with Postgres

Zingg lets us connect to various data sources and sinks using relevant configurations for each type of data platform as described in the documentation. Zingg’s Python API provides a generic Pipe through which we can define the data sources and sinks for our pipeline.

To connect Zingg with our customers table in Postgres, we create a Pipe object and name it customerDataStaging. We set the format as jdbc.

customerDataStaging = Pipe("customerDataStaging", "jdbc")

We specify the properties for the Pipe to connect with our Postgres database.

customerDataStaging.addProperty("url","jdbc:postgresql://localhost:5432/postgres")
customerDataStaging.addProperty("dbtable", "customers")
customerDataStaging.addProperty("driver", "org.postgresql.Driver")
customerDataStaging.addProperty("user","suchandra")
customerDataStaging.addProperty("password","1234")

To write our output to the customers_unified table, we create another Pipe object with relevant properties.

customerIdentitiesResolved = Pipe("customerIdentitiesResolved", "jdbc")
customerIdentitiesResolved.addProperty("url","jdbc:postgresql://localhost:5432/postgres")
customerIdentitiesResolved.addProperty("dbtable", "customers_unified")
customerIdentitiesResolved.addProperty("driver", "org.postgresql.Driver")
customerIdentitiesResolved.addProperty("user","suchandra")
customerIdentitiesResolved.addProperty("password","1234")

We also need the JDBC driver for Zingg to connect with Postgres. Let us download the Postgres JDBC driver and add the path of the driver to spark.jars property of zingg.conf as described here.

Step 4: Find pairs to label — findTrainingData

We have defined our input schema as well as input and output data source and sink. Let us now specify the directory to store the models and the model identifier. We also specify the fraction of the dataset to be used to select data for labeling so that our training data can be created fast.

args.setZinggDir("models")
args.setModelId("customer360")
args.setNumPartitions(4)
args.setLabelDataSampleSize(0.5)

Next, we invoke Zingg client and specify the appropriate which could be findTrainingData, label, train or match. We will take the phase name as an input on the command line.

options = ClientOptions([ClientOptions.PHASE,])
#Zingg execution for the given phase
zingg = Zingg(args, options)
zingg.initAndExecute()

Here is the complete code

from zingg.client import *
from zingg.pipes import *
import sys
#build the arguments for zingg
args = Arguments()
#phase name to be passed as a command line argument
phase_name = sys.argv[1]
#set field definitions
fname = FieldDefinition("fname", "string", MatchType.FUZZY)
lname = FieldDefinition("lname", "string", MatchType.FUZZY)
streetnumber = FieldDefinition("streetnumber", "string", MatchType.FUZZY)
street = FieldDefinition("street","string", MatchType.FUZZY)
address = FieldDefinition("address", "string", MatchType.FUZZY)
locality = FieldDefinition("locality", "string", MatchType.FUZZY)
areacode = FieldDefinition("areacode", "string", MatchType.FUZZY)
state = FieldDefinition("state", "string", MatchType.FUZZY)
dateofbirth = FieldDefinition("dateofbirth", "string", MatchType.FUZZY)
ssn = FieldDefinition("ssn", "string", MatchType.FUZZY)
fieldDefs = [fname, lname, streetnumber, street, address, locality, areacode
state, dateofbirth, ssn]
#add field definitions to Zingg Client arguments
args.setFieldDefinition(fieldDefs)
#defining input pipe
customerDataStaging = Pipe("customerDataStaging", "jdbc")
customerDataStaging.addProperty("url","jdbc:postgresql://localhost:5432/postgres")
customerDataStaging.addProperty("dbtable", "customers")
customerDataStaging.addProperty("driver", "org.postgresql.Driver")
customerDataStaging.addProperty("user","suchandra")
customerDataStaging.addProperty("password","1234")
#add input pipe to arguments for Zingg client
args.setData(customerDataStaging)
#defining output pipe
customerIdentitiesResolved = Pipe("customerIdentitiesResolved", "jdbc")
customerIdentitiesResolved.addProperty("url","jdbc:postgresql://localhost:5432/postgres")
customerIdentitiesResolved.addProperty("dbtable", "customers_unified")
customerIdentitiesResolved.addProperty("driver", "org.postgresql.Driver")
customerIdentitiesResolved.addProperty("user","suchandra")
customerIdentitiesResolved.addProperty("password","1234")
#add output pipe to arguments for Zingg client
args.setOutput(customerIdentitiesResolved)
#save latest model in directory models/599
args.setModelId("customer360")
#store all models in directory models/
args.setZinggDir("models")
#sample size for selecting data for labelling
args.setNumPartitions(4)
#fraction of total dataset to select data for labelling
args.setLabelDataSampleSize(0.5)
options = ClientOptions([ClientOptions.PHASE,phase_name])
#Zingg execution for the given phase
zingg = Zingg(args, options)
zingg.initAndExecute()

We will run our customer identity resolution Python program using the Zingg command line.

zingg.sh 
--properties-file /zingg-0.3.4-SNAPSHOT/config/zingg.conf
--run /zingg-0.3.4-SNAPSHOT/examples/febrl/CustomerIdentityResolution.py findTrainingData

Here are some of the output logs during the findTrainingData phase.

Sampling customer data to find potential pairs to show to the user. Image By Author

Step 5: Label records as matches or non matches to build the training set

We can now run the Zingg label phase and mark the records selected by the program earlier.

zingg.sh 
--properties-file /zingg-0.3.4-SNAPSHOT/config/zingg.conf
--run /zingg-0.3.4-SNAPSHOT/examples/febrl/CustomerIdentityResolution.py label

We are shown pairs of records

Building training set for identity resolution through user feedback on select samples. Image By Author

We need to specify whether they match, do not match or we are not sure whether they match or not. The above records do not look like they match so we mark them as 0

Training Zingg for Identity Resolution. Image By Author

These records on the other hand look very similar hence we label them as 1

What should we do with this pair?

Fuzzy Matching with Zingg. Image By Author

It is a little unlikely that there are two different people living in the same locality, same area with same date of birth and ssn number, these two records could be for the same person with incorrect entry for last name, however it could be for different persons as well. For such cases where we are unsure, we mark them as 2.

Step 6: Run Zingg Python phase — train

As our dataset was small, one round of findTrainingData and label was enough. So now, we can build our models by running

zingg.sh 
--properties-file /zingg-0.3.4-SNAPSHOT/config/zingg.conf
--run /zingg-0.3.4-SNAPSHOT/examples/febrl/CustomerIdentityResolution.py train

Training and cross validation parameters are printed on the screen.

Training machine learning models for identity resolution. Image By Author

Step 7: Ready to resolve identities!

Zingg models are ready, so let’s match

zingg.sh 
--properties-file /zingg-0.3.4-SNAPSHOT/config/zingg.conf
--run /zingg-0.3.4-SNAPSHOT/examples/febrl/CustomerIdentityResolution.py match

On completion, Zingg writes the output to the table we specified in our Python program.

Customer Identity Resolution by Zingg. Image By Author

Zingg adds 3 new columns

Z_CLUSTER — unique ID assigned by Zingg, all records with the same cluster are matching or duplicated.
Z_MINSCORE — it indicates the least the record matched with any other record in that cluster
Z_MAXSCORE — it indicates the maximum the record matched with any other record in that cluster

Using these columns and applying suitable thresholds, we can resolve identities. We can also get human review from annotators.

Let’s see how Zingg interpreted the duplicate records for eglinton and jaiden rollins we had see earlier.

Consider cluster 15

Customer record matches. Image By Author

It has 3 records which are clear matches and should be resolved to the same customer. Each record shows a max and min score greater than 0.95, which means each record has a maximum match greater than 0.95 as well as the least match within the same cluster is also greater than 0.95. We can set a threshold of 0.95 and automatically mark records above this threshold as being sure matches requiring no human intervention.

Similarly, cluster 37 shows obvious matching records

Matching customers with Zingg. Image By Author

Let’s look at cluster 20

Human review and data stewardship for identity resolution. Image By Author

This shows scores lesser than our selected threshold so we will pass it on to humans for review.

Identity Resolution is a critical step while building our data platforms and products. It enables us to understand who our core business entities are. As a custom tool for identity resolution, Zingg abstracts away the complexity and effort in building a fuzzy record matching system. Zingg takes care of data preprocessing, attribute and record level similarity definition and scalability. Thus we can use our customer, supplier, supplies, product, and parts data for critical business analytics and operations without worrying about missing or incomplete information.

Step by Step Identity Resolution With Python And Zingg was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.

Is starting snaps directly from their installation folder fine when you don't care about sandboxing? (e.g starting chromium snap directly from /snap/chromium/current/usr/lib/chromium-browser/chrome)

Fri, 30 Sep 2022 14:15:08 +0200

Hey all,

first a bit of background info why I want to discuss this (just scroll down to the last paragraph if you don't care). I recently switched from using the chromium flatpak on my Ubuntu 22.04 to using the chromium snap. The reason I'm doing this is that don't like one thing about flathub: I don't really know who is maintaining/taking care of the flatpak I'm using. I don't know if anyone is slipping malicious stuff into it or if it's updated properly. At least I'm not aware of any curation. Unfortunately there is no official PPA or flatpak for chromium that I can use so I fall back to the snap.

One thing that I like about the snapcraft store is the publisher verification. That little check mark that tells me that chromium is from Canonical or that pycharm is from JetBrains gives me some trust.

Don't get me wrong. From a technical point of view I really love flatpaks and I wasn't a fan of snaps in the past for the several well known reasons (always uninstalled snapd and installed flatpak) but the curation is a killer feature for me.

So I tried the chromium snap from Canonical and ran into two issues:

I have to replug my yubikey for u2f to work when using the snap. Everytime I restart the browser I have to do this. Super annoying as I have a yubikey nano. Here is a link to the bug tracker: https://bugs.launchpad.net/ubuntu/+source/chromium-browser/+bug/1884759
The "Create shortcut" or PWA function in the chromium snap not really work as there are two issues with it:
1. The .desktop files generated are not correct: https://bugs.launchpad.net/ubuntu/+source/chromium-browser/+bug/1732482 (can be fixed manually not a big deal)
2. Separate icons for the PWAs/Desktop Shortcuts and for different profiles (I do this using --user-data-dir and --class) in Gnome doesn't work. The reason why I use PWAs is that I like to have dedicated icons for several web applications like MS Teams or Outlook for example. I also have separate task bar icons using different profiles for each of my bigger customers. Here is the bug tracker link about this and from here I got the following workaround that I want to discuss: https://bugs.launchpad.net/ubuntu/+source/chromium-browser/+bug/1891649

From the this bug tracker link I got the workaround to just start chromium directly from the snap installation directory "/snap/chromium/current/usr/lib/chromium-browser/chrome". When I do this, all of the issues described above are not existent. As far as I understand, directly starting chromium from the snap installation folder will start chromium without any sandboxing (at least it then creates its config directly in ~/.config/chromium). Now I want to ask you: Do you see any problems doing this when I don't care about sandboxing? For me it seems fine as I would be also fine with using a official PPA over the snap for chromium and there I would also not have any sandboxing. For me this looks like a good thing: I can use snapcraft as I trusted source for installing/updating the application binaries and if I have any problems caused by the snap sandbox I just start it like a usual application.

Any opinions on this?

submitted by /u/st0n1e
[link] [comments]

Entwicklungsumgebung: PhpStorm, GoLand und PyCharm erreichen Version 2022.2

Tue, 02 Aug 2022 13:47:37 +0200

PhpStorm lässt sich nun mit Rector nutzen, einem Tool für automatische Aktualisierung von PHP-Code. PyCharm bringt Support für Python 3.11, GoLand für Go 1.19.

[Testing Update] 2022-07-23 - Kernels, Cinnamon, Virtualbox 6.4.36, KDE-Git, Haskell, Python

Sat, 23 Jul 2022 10:02:13 +0200

Hello community,

Another testing branch update with some usual updates for you.

Checkout the store. From 21st till 24th we offer free standard shipping!

Most of our Kernels got updated
Some more Cinnamon updates got added
Virtualbox is now at 6.1.36
Regular KDE-git, Haskell and Python updates

Additional Info

Info about AUR packages (click for more details)

Get our latest daily developer images now from Github: Plasma, GNOME, XFCE. You get the latest stable releases of Manjaro from CDN77.

Our current supported kernels

linux419 4.19.253
linux54 5.4.207
linux510 5.10.132
linux515 5.15.56
linux517 5.17.15 (EOL)
linux518 5.18.13
linux519 5.19-rc7
linux515-rt 5.15.49_rt47
linux518-rt 5.18.0_rt11

Package Changes (Sat Jul 23 08:03:59 CEST 2022)

testing core x86_64: 2 new and 2 removed package(s)
testing multilib x86_64: 1 new and 1 removed package(s)
testing extra x86_64: 44 new and 44 removed package(s)
testing community x86_64: 263 new and 255 removed package(s)

Overlay Package Changes

testing core x86_64: 10 new and 10 removed package(s)
testing kde-unstable x86_64: 70 new and 70 removed package(s)
testing extra x86_64: 66 new and 66 removed package(s)

:: Different overlay package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                            cinnamon              5.4.3-1              5.4.5-1
                      discord-canary            0.0.136-1                    -
 linux515-rt-virtualbox-host-modules             6.1.34-7           6.1.36-0.1
 linux518-rt-virtualbox-host-modules             6.1.34-1             6.1.36-1
                         mint-themes            1:2.0.2-1            1:2.0.3-1
                                pnpm              7.5.2-1              7.6.0-1
                               tlpui            1.5.0.1-1            1.5.0.2-1
                             xviewer              3.2.7-1              3.2.8-1
                     xviewer-plugins              1.4.2-1              1.4.3-1


:: Different sync package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                          abseil-cpp         20211102.0-2         20220623.0-1
                               acorn            1:8.7.1-1            1:8.8.0-1
                              adios2              2.8.1-1              2.8.2-1
                                agda            2.6.2.1-3            2.6.2.2-1
                            agordejo              0.4.0-1              0.4.1-1
                             amsynth             1.12.4-1             1.13.0-1
                           apptainer              1.0.1-2              1.0.3-1
                               arrow              8.0.0-3              8.0.1-1
                                bear             3.0.19-6             3.0.19-7
                           borgmatic              1.6.5-1              1.6.6-1
                       cabal-install          3.4.0.0-165            3.4.1.0-1
                            cardinal              22.06-1              22.07-1
                       cardinal-data              22.06-1              22.07-1
                       cardinal-jack              22.06-1              22.07-1
                        cardinal-lv2              22.06-1              22.07-1
                        cardinal-vst              22.06-1              22.07-1
                       cardinal-vst3              22.06-1              22.07-1
                          cargo-edit             0.10.1-1             0.10.2-1
                       cargo-nextest             0.9.26-1             0.9.28-1
                         cargo-tauri              1.0.4-1              1.0.5-1
                      cargo-zigbuild             0.11.1-1             0.11.2-1
                               carla              2.4.3-1              2.5.0-1
                    cinnamon-desktop              5.4.1-1              5.4.2-1
                           clash-ghc              1.6.2-5              1.6.3-1
                             cockpit                272-1                273-1
                    cockpit-machines                271-1                272-1
                         cockpit-pcp                272-1                273-1
                      cockpit-podman                 50-1               51.1-1
                                crun              1.4.5-1                1.5-1
                             crystal              1.5.0-1              1.5.0-2
                              dagger             0.2.24-1             0.2.25-1
                               darcs            2.16.5-43            2.16.5-44
                           dart-sass             1.53.0-1             1.54.0-1
                                deno             1.23.4-1             1.24.0-1
                               dhall            1.41.1-51            1.41.1-53
                          dhall-bash            1.0.40-62            1.0.40-64
                          dhall-docs             1.0.9-60             1.0.9-62
                          dhall-json            1.7.10-55            1.7.10-57
                    dhall-lsp-server              1.1.0-5              1.1.1-1
                          dhall-yaml            1.2.10-56            1.2.10-58
                          displaycal              3.9.6-1              3.9.6-2
                       distrobuilder                2.1-1                2.1-2
                            electron             19.0.8-1             19.0.9-1
                             element             0.46.5-1             0.46.6-1
                fcitx5-pinyin-zhwiki   1:0.2.4.20220529-1   1:0.2.4.20220722-1
                           filezilla             3.60.1-2             3.60.2-1
                             fluajho              1.7.2-1              1.7.3-1
                               fwupd              1.8.2-2              1.8.3-1
                                gdal              3.4.3-3              3.5.0-4
                           git-annex       10.20220624-14       10.20220624-15
                               gitea             1.16.8-1             1.16.9-1
                       gitlab-runner             15.1.0-1             15.2.0-1
                            glfw-doc              3.3.7-1              3.3.8-1
                        glfw-wayland              3.3.7-1              3.3.8-1
                            glfw-x11              3.3.7-1              3.3.8-1
                                 gmt              6.3.0-2              6.4.0-1
                             gmt-doc              6.3.0-2              6.4.0-1
                             go-ipfs             0.13.1-1                    -
                                grpc             1.47.1-1             1.48.0-1
                            grpc-cli             1.47.1-1             1.48.0-1
         haskell-aeson-better-errors          0.9.1.0-392            0.9.1.1-1
                  haskell-bower-json          1.0.0.1-390          1.0.0.1-391
                       haskell-brick             0.69.1-1               0.70-1
                          haskell-ci           0.12.1-263           0.12.1-264
                   haskell-clash-lib              1.6.2-5              1.6.3-1
               haskell-clash-prelude              1.6.2-5              1.6.3-1
                      haskell-ghcide            1.4.2.3-3            1.4.2.3-5
                          haskell-gi            0.26.0-32            0.26.0-33
                    haskell-gi-cairo            1.0.26-32            1.0.26-33
                      haskell-hakyll          4.15.1.1-82          4.15.1.1-83
                 haskell-hledger-lib              1.25-43              1.25-44
   haskell-hls-call-hierarchy-plugin          1.0.0.0-195          1.0.0.0-198
             haskell-hls-eval-plugin          1.1.2.0-198          1.1.2.0-201
 haskell-hls-explicit-imports-plugin          1.0.1.0-195          1.0.1.0-197
         haskell-hls-floskell-plugin          1.0.0.1-197          1.0.0.1-200
         haskell-hls-fourmolu-plugin          1.0.0.2-204          1.0.0.2-207
 haskell-hls-haddock-comments-plugin          1.0.0.3-195          1.0.0.3-198
            haskell-hls-hlint-plugin          1.0.1.1-195          1.0.1.1-197
      haskell-hls-module-name-plugin          1.0.0.1-195          1.0.0.1-198
           haskell-hls-ormolu-plugin          1.0.1.0-201          1.0.1.0-204
              haskell-hls-plugin-api          1.2.0.0-148            1.2.0.1-1
          haskell-hls-pragmas-plugin          1.0.1.0-195          1.0.1.0-198
           haskell-hls-retrie-plugin          1.0.1.1-195          1.0.1.1-197
  haskell-hls-stylish-haskell-plugin          1.0.0.2-198          1.0.0.2-200
              haskell-hls-test-utils          1.1.0.0-196          1.1.0.0-198
             haskell-language-server          1.3.0.0-231          1.3.0.0-233
            haskell-lens-family-core              2.1.0-9              2.1.2-1
           haskell-regex-compat-tdfa          0.95.1.4-98          0.95.1.4-99
                  haskell-regex-tdfa           1.3.1.2-26            1.3.1.3-1
                haskell-summoner-tui          2.0.1.1-375          2.0.1.1-376
                haskell-tasty-silver           3.3.1.1-11           3.3.1.1-12
                   haskell-unixutils            1.54.2-68            1.54.2-69
                        hdf5-openmpi             1.12.2-2             1.12.2-3
                           hedgewars            1.0.0-303            1.0.0-304
                          hexer-hobu              1.4.0-7              1.4.0-8
                             hledger              1.25-66              1.25-67
                        hledger-iadd            1.3.17-60            1.3.17-62
                          hledger-ui              1.25-86              1.25-88
                         hledger-web             1.25-104             1.25-105
                               idris              1.3.4-3              1.3.4-4
               intel-compute-runtime        22.27.23681-1        22.29.23750-1
             intel-graphics-compiler        1:1.0.11485-7        1:1.0.11485-8
                             jenkins              2.359-1              2.360-1
                          jupyterlab              3.4.3-1              3.4.4-1
                               kubie             0.17.0-1             0.17.1-1
                            laborejo              2.0.3-1              2.1.0-1
                             lazygit               0.34-2               0.35-1
                      libcalfbox-lss              1.0.0-2              1.1.0-1
                        libfilezilla           1:0.37.2-1           1:0.38.1-1
                          libgeotiff              1.6.0-4              1.7.1-1
                          liblas 1.8.1.r127+ge6a1aaed-2 1.8.1.r128+gded46373-1
                       libspatialite              5.0.1-2              5.0.1-3
                           libtg_owt    0.git14.10d5f4b-1    0.git14.10d5f4b-2
                       libtraceevent            1:1.6.1-1            1:1.6.2-1
                  libtraceevent-docs            1:1.6.1-1            1:1.6.2-1
                          libtracefs              1.4.1-1              1.4.2-1
                     libtracefs-docs              1.4.1-1              1.4.2-1
                             libvips             8.12.2-1             8.13.0-1
                             libvirt            1:8.5.0-2            1:8.5.0-3
             libvirt-storage-gluster            1:8.5.0-2            1:8.5.0-3
        libvirt-storage-iscsi-direct            1:8.5.0-2            1:8.5.0-3
                 libvirt-storage-rbd            1:8.5.0-2            1:8.5.0-3
                           liquidsfz              0.2.3-1              0.3.0-1
                        lua-penlight             1.12.0-2             1.13.1-1
                      lua51-penlight             1.12.0-2             1.13.1-1
                      lua52-penlight             1.12.0-2             1.13.1-1
                      lua53-penlight             1.12.0-2             1.13.1-1
              luajit 2.1.0.beta3.r422.g4c2441c1-1 2.1.0.beta3.r431.g5677985d-1
                                 lxd                5.3-1                5.4-1
                     maliit-keyboard              2.3.0-1              2.3.1-1
                              mapnik             3.1.0-11             3.1.0-12
                          mattermost              7.1.1-1              7.1.2-1
                              mdbook             0.4.20-1             0.4.21-1
                       mediathekview             13.9.0-1             13.9.1-1
                          merkaartor             0.19.0-2             0.19.0-3
                               mimir              2.1.0-4              2.2.0-1
                               minio         2022.06.30-1         2022.07.17-1
                        minio-client         2022.06.26-1         2022.07.15-1
                           mktorrent                1.1-4                1.1-5
                               mmctl              7.1.0-1              7.1.2-1
                            molecule              4.0.0-1              4.0.1-1
                     molecule-podman              2.0.0-1              2.0.1-1
                              monero           0.17.3.2-3           0.18.0.0-1
                          monero-gui           0.17.3.2-3           0.18.0.0-1
                              muffin              5.4.2-1              5.4.3-1
                              mumble           1.4.230-11           1.4.230-13
                              murmur           1.4.230-11           1.4.230-13
                     mysql-workbench             8.0.29-1             8.0.29-2
                                naev              0.9.3-1              0.9.4-1
                                nemo              5.4.1-1              5.4.2-1
               netfilter-fullconenat      r73.0cf3b48-219      r73.0cf3b48-220
              nextcloud-app-contacts              4.1.1-1              4.2.0-1
              nginx-mod-headers-more              0.33-13               0.34-1
                       nginx-mod-njs              0.7.5-1              0.7.6-1
                            obsidian             0.15.6-1             0.15.8-1
                                 oha              0.4.7-1              0.5.3-1
                             opendht          1:2.4.7.2-1            1:2.4.9-1
                      openscenegraph             3.6.5-13             3.6.5-14
                             osbuild                 59-1                 60-1
                            paraview             5.10.1-8             5.10.1-9
                                pdal              2.4.2-2              2.4.2-3
                            php-grpc             1.47.1-1             1.48.0-1
                           php7-grpc             1.47.1-1             1.48.0-1
                            plantuml           1.2022.4-2           1.2022.6-1
                                poco             1.11.3-1             1.12.1-1
                             postgis              3.2.1-1              3.2.1-2
                           postgrest              9.0.0-5              9.0.0-6
                           primus_vk              1.6.1-1              1.6.2-1
                                proj              8.2.0-1              9.0.1-1
                        prusa-slicer              2.4.2-6              2.4.2-7
                               pueue              2.0.4-1              2.1.0-1
           pycharm-community-edition           2022.1.3-1           2022.1.4-1
                             pyright            1.1.261-1            1.1.262-1
                  python-aiobotocore              2.2.0-1              2.3.4-1
               python-ansible-compat              2.1.0-1              2.2.0-1
                     python-cfn-lint             0.61.2-1             0.61.3-1
                   python-cloudflare             2.9.10-1             2.9.11-1
                         python-cmd2              2.3.3-1              2.4.0-1
                     python-daiquiri              3.0.1-3              3.1.0-1
                python-dogpile.cache              1.1.6-1              1.1.7-1
                  python-elementpath              2.5.1-1              2.5.2-1
              python-email-validator              1.1.3-3              1.2.0-1
                      python-fastapi             0.78.0-1             0.79.0-1
                        python-fiona             1.8.21-1             1.8.21-2
                   python-frozendict            1:2.3.2-1            1:2.3.3-1
                python-funcparserlib            1.0.0a0-1              1.0.0-1
                         python-gdal              3.4.3-3              3.5.0-4
                       python-geoip2              4.4.0-1              4.5.0-1
     python-googleapis-common-protos             1.56.2-1             1.56.3-1
                       python-grpcio             1.47.1-1             1.48.0-1
                     python-identify              2.5.1-1              2.5.2-1
               python-keystoneclient              4.5.0-1              5.0.0-1
                   python-lsp-server              1.4.1-1              1.5.0-1
                     python-pydrive2             1.12.1-1             1.14.0-1
                       python-pyface              7.3.0-4              7.4.2-1
                python-pylink-square             0.13.0-1             0.14.0-1
                      python-pyogrio              0.4.0-1              0.4.0-2
                       python-pyproj              3.0.1-3              3.3.1-1
              python-pytest-metadata              2.0.1-1              2.0.2-1
           python-pytest-subtesthack              0.1.2-3              0.2.0-1
                 python-pytest-sugar              0.9.4-5              0.9.5-1
                      python-pytools           2022.1.6-1           2022.1.7-1
                          python-rsa                4.8-3                4.9-1
               python-spyder-kernels              2.3.1-1              2.3.2-1
                       python-traits              6.2.0-3              6.3.2-1
                     python-traitsui              7.2.1-3              7.4.0-1
                  python-uritemplate              3.0.1-6              4.1.1-1
                                qgis             3.26.0-1             3.26.0-2
                           qmapshack             1.16.1-2             1.16.1-3
                                repo               2.27-1               2.28-1
                            restinio             0.6.15-1             0.6.16-1
                  rime-pinyin-zhwiki   1:0.2.4.20220529-1   1:0.2.4.20220722-1
                          rubberband              2.0.2-1              3.0.0-2
                        ruby-bundler             2.3.17-1             2.3.18-1
                           ruby-i18n             1.10.0-1             1.12.0-1
                ruby-rack-protection              2.1.0-2              2.2.0-1
                         ruby-tzinfo              2.0.4-1              2.0.5-1
                       selene-linter             0.19.1-1             0.20.0-1
                         sequoia-sop             0.27.0-1             0.27.1-1
                               sfizz              1.2.0-1              1.2.0-2
                          shellcheck            0.8.0-142            0.8.0-143
                      signal-desktop             5.50.1-1             5.51.0-1
                         slicer-udev              2.4.2-6              2.4.2-7
                              spyder              5.3.1-1              5.3.2-1
                              stylua             0.14.0-1             0.14.1-1
                              sysdig             0.29.2-5             0.29.2-6
                         sysdig-dkms             0.29.2-5             0.29.2-6
                             taskell           1.11.4-189           1.11.4-190
                    telegram-desktop              4.0.2-2              4.0.2-4
                              tembro              0.5.0-1              0.5.1-1
                            thermald              2.4.9-1                2.5-1
                           trace-cmd              3.1.1-1              3.1.2-1
                               trivy             0.30.0-1             0.30.2-1
                             ts-node             10.9.0-1             10.9.1-1
                                tuna             1:0.17-1             1:0.18-1
         v2ray-domain-list-community     20220719055203-1     20220721123730-1
                         v2ray-geoip       202207140057-1       202207210057-1
                               vault             1.11.0-1             1.11.1-1
                          virtualbox             6.1.34-4             6.1.36-1
                  virtualbox-ext-vnc             6.1.34-4             6.1.36-1
                virtualbox-guest-iso             6.1.34-1             6.1.36-1
              virtualbox-guest-utils             6.1.34-4             6.1.36-1
          virtualbox-guest-utils-nox             6.1.34-4             6.1.36-1
                virtualbox-host-dkms             6.1.34-4             6.1.36-1
                      virtualbox-sdk             6.1.34-4             6.1.36-1
                            visidata                2.8-2              2.9.1-1
                             vivaldi        5.3.2679.68-1        5.3.2679.70-1
                                 vtk             9.1.0-18             9.1.0-19
                            wasmtime             0.37.0-1             0.39.1-1
                  webp-pixbuf-loader              0.0.5-1              0.0.6-1
                         x42-plugins           20220605-1           20220714-1
                                xapp             2.2.13-1             2.2.14-1
                                 xed              3.2.4-1              3.2.6-1
                             xreader              3.4.1-1              3.4.2-1
                     zsh-completions             0.33.0-1             0.34.0-1
                  haskell-witherable                    -              0.4.2-1
                                kubo                    -             0.14.0-1
                   libretro-mame2016                    -              44430-1
                                ncnn                    -           20220721-1
                           openslide                    -              3.4.1-3
        python-requests-wsgi-adapter                    -              0.4.1-1
             python-sphinx-lv2-theme                    -              1.2.0-1
                 python-whatthepatch                    -              1.0.2-1
                 waifu2x-ncnn-vulkan                    -           20220419-2


:: Different overlay package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                            linux419           4.19.252-3           4.19.253-1
                    linux419-headers           4.19.252-3           4.19.253-1
                            linux510           5.10.131-1           5.10.132-1
                    linux510-headers           5.10.131-1           5.10.132-1
                            linux515            5.15.55-1            5.15.56-1
                    linux515-headers            5.15.55-1            5.15.56-1
                            linux518            5.18.12-3            5.18.13-1
                    linux518-headers            5.18.12-3            5.18.13-1
                             linux54            5.4.206-1            5.4.207-1
                     linux54-headers            5.4.206-1            5.4.207-1


:: Different sync package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                              libbpf              0.8.0-1              0.8.1-1


:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                  linux419-acpi_call             1.2.2-39             1.2.2-40
                   linux419-bbswitch              0.8-252              0.8-253
                linux419-broadcom-wl     6.30.223.271-252     6.30.223.271-253
                linux419-ndiswrapper             1.63-142             1.63-143
               linux419-nvidia-390xx           390.151-15           390.151-16
               linux419-nvidia-470xx        470.129.06-13        470.129.06-14
                     linux419-nvidia             515.57-6             515.57-7
                   linux419-nvidiabl             0.88-251             0.88-252
                      linux419-r8168          8.049.02-63          8.049.02-64
                  linux419-rtl8723bu          20220114-34          20220114-35
                   linux419-tp_smapi             0.43-201             0.43-202
                linux419-vhba-module          20211218-35          20211218-36
    linux419-virtualbox-host-modules            6.1.34-21             6.1.36-1
                        linux419-zfs              2.1.5-7              2.1.5-8
                  linux510-acpi_call             1.2.2-49             1.2.2-50
                   linux510-bbswitch              0.8-150              0.8-151
                linux510-broadcom-wl     6.30.223.271-152     6.30.223.271-153
               linux510-nvidia-390xx           390.151-18           390.151-19
               linux510-nvidia-470xx        470.129.06-17        470.129.06-18
                     linux510-nvidia             515.57-6             515.57-7
                      linux510-r8168          8.049.02-87          8.049.02-88
                  linux510-rtl8723bu          20220114-43          20220114-44
                   linux510-tp_smapi             0.43-150             0.43-151
                linux510-vhba-module          20211218-45          20211218-46
    linux510-virtualbox-host-modules            6.1.34-23             6.1.36-1
                        linux510-zfs              2.1.5-7              2.1.5-8
                  linux515-acpi_call             1.2.2-51             1.2.2-52
                   linux515-bbswitch               0.8-66               0.8-67
                linux515-broadcom-wl      6.30.223.271-66      6.30.223.271-67
               linux515-nvidia-390xx           390.151-51           390.151-52
               linux515-nvidia-470xx        470.129.06-18        470.129.06-19
                     linux515-nvidia             515.57-6             515.57-7
                      linux515-r8168          8.049.02-66          8.049.02-67
                  linux515-rtl8723bu          20220114-45          20220114-46
                   linux515-tp_smapi              0.43-66              0.43-67
                linux515-vhba-module          20211218-47          20211218-48
    linux515-virtualbox-host-modules            6.1.34-24             6.1.36-1
                        linux515-zfs              2.1.5-7              2.1.5-8
    linux517-virtualbox-host-modules            6.1.34-16             6.1.36-1
                  linux518-acpi_call             1.2.2-16             1.2.2-17
                   linux518-bbswitch               0.8-16               0.8-17
                linux518-broadcom-wl      6.30.223.271-15      6.30.223.271-16
               linux518-nvidia-390xx           390.151-17           390.151-18
               linux518-nvidia-470xx        470.129.06-17        470.129.06-18
                     linux518-nvidia             515.57-8             515.57-9
                      linux518-r8168          8.049.02-16          8.049.02-17
                  linux518-rtl8723bu          20220522-16          20220522-17
                   linux518-tp_smapi              0.43-16              0.43-17
                linux518-vhba-module          20211218-16          20211218-17
    linux518-virtualbox-host-modules            6.1.34-17             6.1.36-1
                        linux518-zfs              2.1.5-9             2.1.5-10
    linux519-virtualbox-host-modules           6.1.34-0.9           6.1.36-0.1
                   linux54-acpi_call             1.2.2-45             1.2.2-46
                    linux54-bbswitch              0.8-219              0.8-220
                 linux54-broadcom-wl     6.30.223.271-220     6.30.223.271-221
                 linux54-ndiswrapper             1.63-175             1.63-176
                linux54-nvidia-390xx           390.151-15           390.151-16
                linux54-nvidia-470xx        470.129.06-15        470.129.06-16
                      linux54-nvidia             515.57-6             515.57-7
                    linux54-nvidiabl             0.88-219             0.88-220
                       linux54-r8168          8.049.02-81          8.049.02-82
                   linux54-rtl8723bu          20220114-39          20220114-40
                    linux54-tp_smapi             0.43-219             0.43-220
                 linux54-vhba-module          20211218-41          20211218-42
     linux54-virtualbox-host-modules            6.1.34-19             6.1.36-1
                         linux54-zfs              2.1.5-7              2.1.5-8


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                         389-ds-base              2.2.1-1              2.2.2-1
                               atkmm             2.28.2-2             2.28.3-1
                          atkmm-2.36             2.36.1-2             2.36.2-1
                     atkmm-2.36-docs             2.36.1-2             2.36.2-1
                          atkmm-docs             2.28.2-2             2.28.3-1
                        avogadrolibs             1.96.0-2             1.97.0-1
                    avogadrolibs-qt5             1.96.0-2             1.97.0-1
                            chromium     103.0.5060.114-1     103.0.5060.134-1
                        java-openjfx          18.0.1.u2-1          18.0.2.u2-1
                    java-openjfx-doc          18.0.1.u2-1          18.0.2.u2-1
                    java-openjfx-src          18.0.1.u2-1          18.0.2.u2-1
                      java11-openjfx         11.0.15.u2-1         11.0.16.u2-1
                  java11-openjfx-doc         11.0.15.u2-1         11.0.16.u2-1
                  java11-openjfx-src         11.0.15.u2-1         11.0.16.u2-1
                      java17-openjfx          17.0.3.u2-1          17.0.4.u2-1
                  java17-openjfx-doc          17.0.3.u2-1          17.0.4.u2-1
                  java17-openjfx-src          17.0.3.u2-1          17.0.4.u2-1
                         jdk-openjdk        18.0.1.1.u2-1          18.0.2.u9-1
                       jdk11-openjdk        11.0.15.u10-2         11.0.16.u8-2
                       jdk17-openjdk          17.0.3.u7-2          17.0.4.u8-2
                         jre-openjdk        18.0.1.1.u2-1          18.0.2.u9-1
                jre-openjdk-headless        18.0.1.1.u2-1          18.0.2.u9-1
                       jre11-openjdk        11.0.15.u10-2         11.0.16.u8-2
              jre11-openjdk-headless        11.0.15.u10-2         11.0.16.u8-2
                       jre17-openjdk          17.0.3.u7-2          17.0.4.u8-2
              jre17-openjdk-headless          17.0.3.u7-2          17.0.4.u8-2
                          kitinerary            22.04.3-1            22.04.3-2
                      libphonenumber          1:8.12.50-2          1:8.12.52-1
                         openjdk-doc        18.0.1.1.u2-1          18.0.2.u9-1
                         openjdk-src        18.0.1.1.u2-1          18.0.2.u9-1
                       openjdk11-doc        11.0.15.u10-2         11.0.16.u8-2
                       openjdk11-src        11.0.15.u10-2         11.0.16.u8-2
                       openjdk17-doc          17.0.3.u7-2          17.0.4.u8-2
                       openjdk17-src          17.0.3.u7-2          17.0.4.u8-2
                              ostree             2022.4-1             2022.5-1
                              prison             5.96.0-1             5.96.0-2
                        python-evdev              1.5.0-1              1.6.0-1
            python-trove-classifiers          2022.6.26-1          2022.7.22-1
                                 qbs             1.22.1-1             1.23.0-1
                            qt5-base    5.15.5+kde+r170-1    5.15.5+kde+r172-1
                             qt5-svg     5.15.5+kde+r10-1     5.15.5+kde+r11-1
             qt5-xcb-private-headers    5.15.5+kde+r170-1    5.15.5+kde+r172-1
                           qtcreator              7.0.2-4              8.0.0-1
                     qtcreator-devel              7.0.2-4              8.0.0-1

:: Different overlay package(s) in repository kde-unstable x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                         audiocd-kio22.04.3.r1092.g5818940-122.04.3.r1094.g8f766a9-1
                              bomber22.04.3.r569.g56cdf3c-122.04.3.r570.gbe88435-1
                              breeze5.25.3.r2431.gd012df4e-15.25.3.r2433.g5caf82c3-1
                        breeze-icons5.96.0.r1908.ge6ae2ea7-15.96.0.r1909.gacc75ff7-1
                              cantor22.04.3.r3368.g4efa9889-122.04.3.r3371.gf5f8319b-1
                            discover5.25.3.r8730.g45170af19-15.25.3.r8742.gcd2b9b05a-1
                             dolphin22.04.3.r7046.gd4ed58f6a-122.04.3.r7050.gd0c3e373a-1
                             drkonqi5.25.3.r803.gba2a47e0-15.25.3.r809.g80efd753-1
                           filelight22.04.3.r1154.g97fbbd4-122.04.3.r1155.g7d2f734-1
                           itinerary22.04.3.r1956.g302bdf8-122.04.3.r1961.gd2cf370-1
                                kate22.04.3.r19242.gf6743520d-122.04.3.r19252.g5b2f39986-1
                            kcmutils5.96.0.r650.g03804c1-15.96.0.r651.g85097f0-1
                      kconfigwidgets5.96.0.r750.geb393b1-15.96.0.r752.g89d04a1-1
                         kcoreaddons5.96.0.r1531.gd1f29806-15.96.0.r1532.gdf8a2f6b-1
                      kdebugsettings22.04.3.r946.g5f5c562-122.04.3.r949.g5890609-1
                          kdeconnect22.04.3.r3491.g182fd5f2-122.04.3.r3494.geefdf0c5-1
                       kdepim-addons22.04.3.r4721.g5eedfcb9c-122.04.3.r4723.g779bae66b-1
                    kdeplasma-addons5.25.3.r8931.g7be911900-15.25.3.r8938.g4f6891294-1
                            keysmith  22.06.r8.gb74e529-1  22.06.r9.gab97a00-1
                       kfilemetadata5.96.0.r866.gcb95bf6-15.96.0.r868.g138880a-1
                                kget22.04.3.r3215.g827824c6-122.04.3.r3216.g3682529a-1
                        kglobalaccel5.96.0.r536.gca47aad-15.96.0.r537.g5683e03-1
                         khelpcenter22.04.3.r2758.g1cfa9d78-122.04.3.r2759.g1bfabb70-1
                                 kio5.96.0.r5588.g125977a27-15.96.0.r5595.gc6207ee11-1
                          kio-extras22.04.3.r7299.g850d9af0-122.04.3.r7302.g2b4ec3a8-1
                     kirigami-addons  1:0.3.r5.g1468d70-1  1:0.3.r6.gbd7741e-1
                    kirigami-gallery22.04.3.r255.gca484dc-122.04.3.r256.g09384d4-1
                           kirigami25.96.0.r3182.gb6e57d84-15.96.0.r3184.g1b19825b-1
                          kitinerary22.04.3.r2306.gaf30845-122.04.3.r2328.gf19e8f4-1
                           kleopatra22.04.3.r6677.ga9a3f23b-122.04.3.r6697.ga71ac7b3-1
                              kmines22.04.3.r1771.gd14a074-122.04.3.r1772.ga4000b6-1
                           knewstuff5.96.0.r1366.g39c74671-15.96.0.r1367.g6b941efe-1
                                koko  22.06.r7.g7152f6c-1  22.06.r9.gc8e4141-1
                             kompare22.04.3.r1145.gf7b472b-122.04.3.r1146.g3d27211-1
                            kongress  22.06.r6.gd325480-1 22.06.r10.ge9b588f-1
                           konqueror22.04.3.r15130.g90807e9fa-122.04.3.r15131.g1d7ed315e-1
                             konsole22.04.3.r8551.gf7a05efa-122.04.3.r8554.g05a4d489-1
                           kpipewire5.25.3.r134.gca8fbdb-15.25.3.r135.g3bc932e-1
                                krdc22.04.3.r1609.g194d0c5-122.04.3.r1610.g6b9f4c1-1
                             kscreen5.25.3.r1484.gbcc0353-15.25.3.r1491.g387fda6-1
                             ksudoku22.04.3.r1122.g5057715-122.04.3.r1123.g61a004a-1
                            ktorrent22.04.3.r2867.gcb0986aa-122.04.3.r2868.gce4aef3c-1
                                kwin5.25.3.r22771.ga0c8d4b24-15.25.3.r22827.gb6cf576ef-1
                              kwrite22.04.3.r19242.gf6743520d-122.04.3.r19252.g5b2f39986-1
                             libkleo22.04.3.r1206.g121ed86-122.04.3.r1221.g1be06ea-1
                          libkscreen5.25.3.r1632.g6c3140b-15.25.3.r1633.gf6c8db3-1
                        libksysguard5.25.3.r2419.gabe0012-15.25.3.r2421.g2d64af6-1
                            lokalize22.04.3.r1840.gdab52c0c-122.04.3.r1841.g167df143-1
                     maliit-keyboard 2.3.0.r0.gdcde37d3-1 2.3.1.r0.g9673c8e8-1
                             mauikit2.1.2.r49.g82274116-12.1.2.r50.g8ad10f4d-1
                             mauiman        r22.f42eb96-1        r23.6ccbef3-1
                             neochat22.06.r47.ga7504876-122.06.r51.g94f32560-1
                              parley22.04.3.r4531.g5d76d7d5-122.04.3.r4533.g767fa241-1
                    plasma-bigscreen      r487.g95c8e34-1      r489.gee83ea0-1
                      plasma-desktop5.25.3.r9437.g292b5c635-15.25.3.r9454.g0fc8d0316-1
                     plasma-firewall5.25.3.r642.gbbdfe7b-15.25.3.r643.g0c9bbb3-1
            plasma-remotecontrollers       r93.g0ab8e75-1       r94.ge952261-1
                          plasma-sdk5.25.3.r2377.g29f3ee38-15.25.3.r2378.g811d92d1-1
                     plasma-settings 22.06.r30.g1e6d45b-1 22.06.r32.g0a02044-1
                plasma-systemmonitor5.25.3.r595.ga6b72e0-15.25.3.r597.g43f1a12-1
            plasma-wayland-protocols1.4.0.r1054.g0469915-11.4.0.r1055.gbcb428f-1
              plasma-wayland-session5.25.3.r12087.g6ec7a9f0a-15.25.3.r12094.g502430d76-1
                    plasma-workspace5.25.3.r12087.g6ec7a9f0a-15.25.3.r12094.g502430d76-1
                  qqc2-desktop-style5.96.0.r639.gf804b45-15.96.0.r643.g299748e-1
                            sddm-kcm5.25.3.r670.g08ecf2b-15.25.3.r671.gea131ce-1
                      systemsettings5.25.3.r2693.g682b604c-15.25.3.r2695.g270c9d2b-1
                             tokodon 22.06.r14.g565052f-1 22.06.r17.gb30ed83-1
                            umbrello22.04.3.r8486.g4f81aaa82-122.04.3.r8487.g908b3425f-1
              xdg-desktop-portal-kde5.25.3.r509.g3b31623-15.25.3.r512.g57f17b2-1
                             yakuake22.04.3.r802.g10be48c-122.04.3.r803.g7bd2d68-1


:: Different sync package(s) in repository multilib x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2022-07-20           2022-07-23
-------------------------------------------------------------------------------
                     lib32-primus_vk              1.6.1-1              1.6.2-1

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Amazon Launches CodeWhisperer, a GitHub Copilot-like AI Pair Programming Tool

Thu, 23 Jun 2022 18:48:58 +0200

At its re:Mars conference, Amazon today announced the launch of CodeWhisperer, an AI pair programming tool similar to GitHub's Copilot that can autocomplete entire functions based on only a comment or a few keystrokes. From a report: The company trained the system, which currently supports Java, JavaScript and Python, on billions of lines of publicly available open-source code and its own codebase, as well as publicly available documentation and code on public forums. It's now available in preview as part of the AWS IDE Toolkit, which means developers can immediately use it right inside their preferred IDEs, including Visual Studio Code, IntelliJ IDEA, PyCharm, WebStorm and Amazon's own AWS Cloud 9. Support for the AWS Lambda Console is also coming soon. Ahead of today's announcement, Vasi Philomin, Amazon's VP in charge of its AI services, stressed that the company didn't simply create this in order to offer a copy of Copilot. He noted that with CodeGuru, its AI code reviewer and performance profiler, and DevOps Guru, its tool for finding operation issues, the company laid the groundwork for today's launch quite a few years ago.

Read more of this story at Slashdot.

Security updates for Tuesday

Tue, 20 Jul 2021 17:30:11 +0200

Security updates have been issued by Debian (kernel, libjdom1-java, rabbitmq-server, and systemd), Fedora (glibc), Gentoo (libpano13, libslirp, mpv, pjproject, pycharm-community, and rpm), Mageia (glibc, libuv, mbedtls, rvxt-unicode, mxrvt, eterm, tomcat, and zziplib), openSUSE (dbus-1, firefox, go1.15, lasso, nodejs10, nodejs12, nodejs14, and sqlite3), SUSE (go1.15), and Ubuntu (containerd).

I am a hobby gamedev using Windows and I want to switch to Linux. What should I know?

Thu, 15 Jul 2021 11:00:16 +0200

I am a hobby gamedev. I use windows on daily basis. In terms of gamedev, i usually just use C++, but sometimes I will also create a side project (not necessarily gamedev related) in Python, Lua or even HTML/CSS, because why not. For C++ i use visual studio, for Python pycharm community and for everything else vscode.

I want to switch to Linux. And there comes my question: what should I know before?

First of all, I have nothing against learning new things. As most programmers, I have experience in bashing my head against the wall in search of solution. I understand that learning Linux will be a challenge to face. I also don't feel the urge to use GUIs for everything.

What editor(s) would you recommend? I'm aiming for free editors. Once again, I have nothing against using the terminal for coding, so it might be a GUI, might be terminal based. I'd like to know what you guys think it's better.

What overall useful software should I first install (cmake, git etc.)?

And probably most importantly: what should I know about developing games supporting windows on Linux? Most players use windows (statistically). So how does gamedev differ on Linux in comparison to windows? Is save management (AppData, etc. ) going to be a problem?

Thank you all in advance.

submitted by /u/sherlock-holmes221b
[link] [comments]

heise+ | Python-Programmierung: Git mit Pycharm unter Windows nutzen

Tue, 22 Jun 2021 15:01:41 +0200

Wer mit Pycharm an Python-Projekten arbeitet, kann Git direkt über die IDE als Versionskontrollsystem verwenden. Wir zeigen, wie das mit Gitlab funktioniert.

Does linux have a trashcan and regardless of if it does or not. how does restoring old files work?

Fri, 18 Jun 2021 06:00:14 +0200

So the context to this is. I just deleted pycharm (Python IDE) to switch to visual studio but it doesnt have a linux option and got it back just by pressing Ctrl Z. How does this work? Where was pycharm "saved" for a lack of a better word for that what i estimate to be 30 second. What exactly happened

submitted by /u/Tuke333
[link] [comments]

JetBrains PyCharm up to 2020.3.3 Project Local Privilege Escalation

Sat, 15 May 2021 17:31:44 +0200

A vulnerability was found in JetBrains PyCharm up to 2020.3.3 and classified as problematic. This issue affects some unknown functionality of the component Project Handler. Upgrading to version 2020.3.4 eliminates this vulnerability.

CVE-2021-30005

Tue, 11 May 2021 17:46:39 +0200

In JetBrains PyCharm before 2020.3.4, local code execution was possible because of insufficient checks when getting the project from VCS.

Entwicklungsumgebungen: JetBrains zielt mit IntelliJ IDEA und Co auf Teamarbeit

Thu, 08 Apr 2021 11:01:05 +0200

Die 2021.1-Releases von IntelliJ IDEA, PyCharm, RubyMine und CLion bringen eine Integration der JetBrains-Tools Code With Me und Space.

Recommend me DE or Window Manager

Sun, 07 Feb 2021 11:30:14 +0100

Hello, folks! I'm looking for new Desktop Environment or a Window manager, currently I'm using i3wm with polybar, however there are plenty of small bugs that bother me. When someone is calling me on slack/Skype I don't see the dialog box to answer unless I have the application opened on my screen, having dialog boxes from IDE's like Pycharm, IntelliJ and so on is pain in the ass. I'm a programmer / systems administrator and have tons of terminals open And IDE's, I don't want to spend time debugging my own machine. Most of the features from i3 that I use are: toggle full screen, having split screen, moving apps to different deaktop (page whatever is called), resizing windows, having specific apps to open to specific desktop also using single 4k monitor.

submitted by /u/toorhax
[link] [comments]

Sarenka - OSINT Tool - Data From Services Like Shodan, Censys Etc. In One Place

Thu, 07 Jan 2021 12:02:15 +0100

SARENKA is an Open Source Intelligence (OSINT) tool which helps you obtaining and understanding Attack Surface.

The main goal is to gathering infromation from search engines for Internet-connected devices (https://censys.io/, https://www.shodan.io/). It scraps data about Common Vulnerabilities and Exposures (CVE), Common Weakness Enumeration (CWE) and also has database where CVEs are mapped to CWE.

It returns data about local machine - local installed softwares (from Windows Registry), local network information (python libraries, popular cmd commads).

For now application has also simple tools like hash calcualtor, shannon entropy calculator and very simple port scanner. More cryptography-math tools and reconnaissance scripts are planned.

Realtion beetwen CWE and CVE - sarenka data feeder

Generating this file takes a long time e.g: 702.5641514

all CWE Ids with description

https://raw.githubusercontent.com/pawlaczyk/sarenka_tools/master/cwe_all.json

all CVE Ids with description

In progress

get all CVE Ids by CWE Id

In progress

Installation

Description in progress

Getting started

Description in progress Sarenka is local web application for Windows.

Config

Rirst release gathers data from two search engines. example sarenka/backend/connectors/credentials.json

{   
    "censys": {
        "base_url": "https://censys.io/",
        "API_ID": "",
        "Secret": "",
        "API_URL": "https://censys.io/api/v1"
    },
    "shodan": {
        "base_url": "https://www.shodan.io/",
        "user": "",
        "api_key": ""
    }
}

Features

gets data from https://censys.io/ by ip
get data from https://www.shodan.io/ by ip
get DNS data
get WHOIS data
banner grabbing
find CVEs by CWE
generatre pdf report

You can also:

calculate hashes based on user string
calculate shannon entropy based on user string
check is port open|closed (instead always use nmap if you can - it's slow)

Database

This is tricki part, because we have 863 sqlite3 database files: default, CWE-NONE (some CVE hasn't cwe_id eg.: CVE-2013-3621) and 861 individual for CWEs

Tech

Description in progress.

SARENKA uses a number of open source projects to work properly on:

Renderforest - logo generator
gawk - python manage.py migrate --database CWE_ID
chocolatey
PyCharm - Community Edition
Technology - description
Technology - description
Technology - description
Technology - description
Technology - description
Technology - description
Technology - description
Technology - description
Technology - description
Technology - description

And of course SARENKA itself is open source with a public repository on GitHub.

Planned features

Rewrite documentation in English (end of 2021)
trello/ github instead of Jira
Cover 100% code by tests
typing backend
document all functions and class
Docker
online demo
Jenkins
GraphQL
Selenium Scrapers
More pentesting tools
Google Dorks
Abstract Algebra calculator
Number Theory calculator
Server certificate validator
tests on Linux
NLP
d3js visualizations
alterntive pure version in command lineS

CI/CD Tools

Tests

Tested on Windows 10
Tested on Kali Linux kali-rolling 2020.2

Documentation

Till end of March, 2021 documentation will be available only in Polish! The documentation is availabe here.

Download Sarenka

42Crunch unveils new IDE OpenAPI editing plugins for Eclipse, IntelliJ, PyCharm

Wed, 16 Dec 2020 03:01:03 +0100

42Crunch announced the release of new IDE OpenAPI (Swagger) editing plugins for both Eclipse and JetBrains family of IDEs including IntelliJ and PyCharm. 42Crunch’s free OpenAPI security audit plugins simplify REST API development by delivering features such as OpenAPI navigation, code snippets, intellisense, and HTML preview. More importantly, the plugins help developers take their API security to the next level by delivering audit reports right to the developer’s IDE. Thus, engineers discover and address security … More →

The post 42Crunch unveils new IDE OpenAPI editing plugins for Eclipse, IntelliJ, PyCharm appeared first on Help Net Security.

Beginner programer self learner // Rainmeter

Mon, 07 Dec 2020 07:45:11 +0100

Hello lovely Linux people. I am here to ask for some tips and tricks You could give me. Internet has spoken and said: "if You learning programming start with project you will use".

So: in python I want to create my own journal/diary app. I know there are some programs like that but I want to create my own and what are Your tips about:

What GUI framework you would recommend to create something modern metro like app that doesn't look like windows 95 style.
I want to create something light that uses stuff what is already in the system like calendar.
How to do it according to a new trends to be able to upload it to git and allow someone to use it ( for beginning with same configuration as mine.
PyGObject or Kivy or PySimpleGUI or Tk
PyCharm or something else?

My setup: Arch + GNOME 3.38

submitted by /u/FoxRandomer
[link] [comments]

I created an app to show the shortcuts of the current application

Sat, 05 Dec 2020 16:15:15 +0100

Looking up shortcuts on the web takes you out of the current context and breaks your workflow. That's why, as a Linux user, I have always been a bit envious of macOS users, who had access to tools that could instantly show the current application's shortcuts (CheatSheet, Pretzel, ...).

Thanks to KeyCombiner, my side project for the past 10 months, I can now do the same on Linux. Via pressing a global shortcut (Super+Alt+C by default), I can trigger an overlay that lets me search through the current application's shortcuts, without taking me away from the current context. While testing the app, I have grown dependent on it and miss it whenever I work on another machine without KeyCombiner installed. I think you might like it, too ;)

The AppImage is free to use and can be downloaded from this page: https://keycombiner.com/desktop/
Direct download link: https://keycombiner.com/download/KeyCombiner-0.0.9.AppImage

This Gif shows how it looks like:

Demo for VSCode, Chrome, and PyCharm

The data is provided by an offline version of KeyCombiner's public shortcut collections: https://keycombiner.com/collections/

So it works for the applications listed there. In particular, it should work for all apps that an average software developer uses (VSCode, JetBrains IDEs, Vim, Eclipse, Chrome, Nautilus, Terminal, Obsidian,...). This list is growing fast, and I am happy to take suggestions ;)

To use the app, you will need to create a free account. This is needed because KeyCombiner not only shows the current application's shortcuts but, in addition, also those from your personal shortcut collections. These personal collections are also accessible from a web interface and associated with your user account. You can also create collections of short text snippets, such as commands and programming language syntax. These will then also be available via the instant lookup on the desktop. Personally, I use this a lot for looking up Regex syntax, that I keep forgetting.

(KeyCombiner has a lot of additional features, but this one has a Linux-specific implementation and can be used by itself)

I'd be thrilled to receive some feedback and answer your questions!

submitted by /u/tkainrad
[link] [comments]

Entwicklungsumgebung: PyCharm 2020.3 räumt die Benutzeroberfläche auf

Thu, 03 Dec 2020 12:47:45 +0100

Die aktuelle Version der Python-IDE von JetBrains bringt neben Neuerungen für die Oberfläche ein Plug-in für kollaboratives Arbeiten.

heise+ | Programmieren mit Python: Schnittstellen entwickeln mit Pycharm und FastAPI

Thu, 29 Oct 2020 08:17:49 +0100

IDEs wie Pycharm machen das Leben für Programmierer einfacher. Wir zeigen, wie Sie in Pycharm mit FastAPI eine Python-REST-Schnittstelle erstellen.

JetBrains PyCharm 2019.2.5/2019.3 on Windows Apple Notarization Service Credentials insufficiently protected credentials

Fri, 09 Oct 2020 15:33:31 +0200

A vulnerability, which was classified as problematic, was found in JetBrains PyCharm 2019.2.5/2019.3 on Windows. This affects an unknown code block of the component Apple Notarization Service. There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

JetBrains PyCharm up to 2019.1 Connection memory corruption

Sun, 20 Sep 2020 10:33:02 +0200

A vulnerability classified as critical was found in JetBrains PyCharm up to 2019.1. This vulnerability affects some unknown processing of the component Connection Handler. Upgrading to version 2019.2 eliminates this vulnerability.

[Testing Update] 2020-07-25 - Kernels, Deepin, Mesa, AMDVLK, Python

Sat, 25 Jul 2020 10:33:28 +0200

Hello community,

Another testing branch update with some interesting updates for you!

Get the latest #PinePhone images! Phosh, Plasma-Mobile #stayhome, #staysafe, #stayhealthy

We all our Kernels
Most Deepin packages got updated
Mesa is now at 20.1.4
AMDVLK updated to 2020.Q3.2
Usual Python package updates and rebuilds

If you like following latest Plasma development you may also like to check out our current version of manjaro-kde-dev, which we build on a regular basis against kde-git master packages. Also check out our latest RC of Manjaro Mikah 20.1! XFCE, KDE and Gnome

Upstream notice

Arch updated their default compression to zstd. We adopted to the same standard. More and more packages will have the zst extension from now on. If you get for what ever reason an error with ZSTD not supported as archive format you can do this:

sudo pacman -Syy
sudo pacman -S pacman-static
sudo pacman-static -Syyu

Our current supported kernels

linux44 4.4.231
linux49 4.9.231
linux414 4.14.189
linux419 4.19.134
linux54 5.4.53
linux56 5.6.19 [EOL]
linux57 5.7.10
linux58 5.8-rc5
linux54-rt 5.4.52_rt31
linux56-rt 5.6.17_rt9

Package Changes (Wed Jul 22 09:07:28 CEST 2020)

testing community x86_64: 467 new and 465 removed package(s)
testing core x86_64: 16 new and 15 removed package(s)
testing extra x86_64: 134 new and 132 removed package(s)
testing multilib x86_64: 7 new and 7 removed package(s)

:: Different overlay package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
  gnome-shell-extension-dash-to-dock                 67-7                 68-1
                                 gwe             0.15.1-1             0.15.1-2
                    telegram-desktop        2.1.18pre-0.1          2.1.22pre-1
                               tlpui    1.2.r6.g945ff46-1              1.3.1-1
                            topgrade              5.2.0-1              5.3.0-1
                              ventoy             1.0.15-1             1.0.16-1


:: Different sync package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
                             alembic             1.7.12-4             1.7.13-1
                            ammonite              2.1.4-1              2.2.0-1
                           arrayfire              3.7.1-1              3.7.2-1
                       aws-checksums              0.1.5-1              0.1.7-1
                             aws-cli           1.18.100-1           1.18.104-1
                            binaryen               1:94-1               1:95-1
                             blender          17:2.83.2-1          17:2.83.3-2
                           borgmatic              1.5.8-1              1.5.9-1
                              ccache             3.7.10-1             3.7.11-1
                              cobalt            0.15.11-1             0.16.0-1
                             cockpit                223-1                224-1
                   cockpit-dashboard                223-1                224-1
                      cockpit-docker                223-1                224-1
                    cockpit-machines                223-1                224-1
                         cockpit-pcp                223-1                224-1
                      cockpit-podman                 18-1                 20-1
                                cuda            10.2.89-5             11.0.2-1
                               cudnn           7.6.5.32-4          8.0.0.180-2
                   deepin-calculator             5.5.22-1             5.5.24-1
                   deepin-compressor            5.8.0.3-1            5.8.0.4-1
              deepin-desktop-schemas           5.6.0.13-1           5.6.0.14-1
                       deepin-editor             5.6.23-1             5.6.24-1
                   deepin-icon-theme         2020.06.30-1         2020.07.24-1
                 deepin-image-viewer            5.6.3.2-2            5.6.3.2-3
                     deepin-launcher           5.2.0.13-1           5.2.0.14-1
              deepin-qt-dbus-factory          5.2.0.3.1-1            5.2.0.4-1
                       deepin-reader            5.7.0.2-1            5.7.0.6-1
                deepin-session-shell           5.1.0.10-1           5.1.0.12-1
                   deepin-session-ui           5.2.0.11-1           5.2.0.12-1
                     deepin-terminal             5.2.11-1             5.2.13-1
                             distorm              3.4.1-2                3.5-1
                               doctl             1.45.1-2             1.46.0-1
                          emscripten            1.39.18-3            1.39.20-2
                              fcitx5     0.0.0.20200626-1     0.0.0.20200722-1
               fcitx5-chinese-addons     0.0.0.20200716-1     0.0.0.20200722-1
                           fcitx5-qt     0.0.0.20200616-2     0.0.0.20200723-1
                           findomain              1.7.0-1              2.1.1-1
                firefox-adblock-plus              3.9.1-1              3.9.3-1
     firefox-extension-privacybadger          2020.6.29-1          2020.7.21-1
               firefox-ublock-origin             1.28.2-1             1.28.4-1
                               flint              2.6.0-1              2.6.1-1
                           freeimage             3.18.0-5             3.18.0-6
                            geonkick              2.2.3-1              2.3.1-1
                         ghostwriter              1.8.1-3              1.8.1-4
                           git-annex        8.20200617-19       8.20200720.1-1
                              gitlab             13.1.4-1             13.2.0-1
                       gitlab-gitaly             13.1.2-1             13.2.0-1
                       gitlab-runner             13.1.0-1             13.2.1-1
                        gitlab-shell           2:13.3.0-1           2:13.4.0-1
                    gitlab-workhorse             8.36.0-1             8.37.0-1
                                grpc             1.30.1-2             1.30.2-1
                            grpc-cli             1.30.1-2             1.30.2-1
                                gxkb              0.8.1-2              0.8.2-1
                             haproxy              2.2.0-2              2.2.1-1
                    haskell-hopenpgp            2.9.4-111            2.9.4-112
          haskell-incremental-parser           0.4.0.2-11                0.5-1
                      hopenpgp-tools            0.23.1-73            0.23.1-74
                           hypercorn             0.10.1-1             0.10.2-1
                           intel-mkl         2020.1.217-6         2020.2.254-1
                    intel-mkl-static         2020.1.217-6         2020.2.254-1
     intellij-idea-community-edition         2:2020.1.3-2         2:2020.1.4-1
                                 k9s             0.21.2-1             0.21.4-1
                          kcm-fcitx5     0.0.0.20200615-1     0.0.0.20200722-1
                              kstars            1:3.4.3-1            1:3.4.3-2
                             kubeone        1.0.0beta.2-1        1.0.0beta.3-1
                            kylin-nm              1.2.4-1              1.2.5-1
                                 ldc           2:1.22.0-1           2:1.22.0-2
                          liblphobos           2:1.22.0-1           2:1.22.0-2
                            liburing                0.6-1                0.7-1
                        luminancehdr              2.6.0-8              2.6.0-9
                              lutris              0.5.7-1            0.5.7.1-1
                               lxcfs              4.0.3-1              4.0.4-1
                               magma              2.5.3-1              2.5.3-3
                             mbedtls             2.16.5-1             2.16.6-1
                                nccl              2.6.4-1              2.7.3-1
               netfilter-fullconenat       r73.0cf3b48-32       r73.0cf3b48-33
             nextcloud-app-bookmarks            1:3.2.4-1            1:3.2.5-1
                              nodejs             14.5.0-1             14.6.0-1
                              nomacs         1:3.16.224-1         1:3.16.224-2
                         openimageio           2.1.16.0-1           2.1.16.0-2
                          opensubdiv              3.4.3-1              3.4.3-2
                     pantheon-photos              2.7.0-1              2.7.0-2
                            php-grpc             1.30.1-2             1.30.2-1
                              podman              2.0.2-1              2.0.3-1
                       podman-docker              2.0.2-1              2.0.3-1
                   powerdns-recursor              4.3.2-1              4.3.3-1
           pycharm-community-edition           2020.1.3-1           2020.1.4-1
                      pycuda-headers           2019.1.2-5           2019.1.2-6
                               pyenv             1.2.19-1             1.2.20-1
                   python-bitcoinlib             0.10.2-1             0.11.0-1
                        python-boto3            1.14.23-1            1.14.27-1
                     python-botocore            1.17.23-1            1.17.27-1
                      python-distorm              3.4.1-2                3.5-1
                         python-docs              3.8.4-1              3.8.5-1
                python-dogpile.cache              0.9.1-1              0.9.2-1
                     python-engineio             3.11.2-1             3.13.1-1
                     python-eventlet             0.25.1-4             0.25.2-1
                      python-fastapi             0.55.1-2             0.60.1-1
               python-flask-compress              1.4.0-2              1.5.0-1
               python-flask-socketio              4.2.1-1              4.3.1-1
                       python-fpylll           0.5.1dev-2           0.5.2dev-1
                  python-google-auth             1.19.0-1             1.19.2-1
                       python-grpcio             1.30.1-2             1.30.2-1
                      python-hacking              3.1.0-1              3.2.0-1
                   python-hypothesis             5.20.3-1             5.21.0-1
                       python-libcst              0.3.7-1              0.3.8-1
                   python-matplotlib              3.3.0-1              3.3.0-2
                   python-novaclient             17.1.0-1             17.2.0-1
                       python-orjson              3.2.2-1              3.3.0-1
                  python-oslo-config              8.2.0-1              8.3.0-1
                   python-oslo-utils              4.2.2-1              4.3.0-1
                   python-osprofiler              3.2.2-1              3.3.0-1
                        python-pasta              0.1.7-2              0.2.0-1
                        python-paste              3.4.2-1              3.4.3-1
                       python-poetry              1.0.9-1             1.0.10-1
                 python-pycryptodome              3.9.8-1              3.9.8-2
                       python-pycuda           2019.1.2-5           2019.1.2-6
                     python-pygments              2.6.1-2              2.6.1-3
                      python-pytorch              1.5.0-2           1.6.0rc6-1
                 python-pytorch-cuda              1.5.0-2           1.6.0rc6-1
                  python-pytorch-opt              1.5.0-2           1.6.0rc6-1
             python-pytorch-opt-cuda              1.5.0-2           1.6.0rc6-1
                    python-reportlab             3.5.44-1             3.5.46-1
                        python-scipy              1.5.1-1              1.5.2-1
                     python-socketio              4.4.0-1              4.6.0-1
                    python-starlette             0.13.4-1             0.13.6-1
                   python-tensorflow              2.2.0-1           2.3.0rc2-2
              python-tensorflow-cuda              2.2.0-1           2.3.0rc2-2
               python-tensorflow-opt              2.2.0-1           2.3.0rc2-2
          python-tensorflow-opt-cuda              2.2.0-1           2.3.0rc2-2
                          python-tox             3.17.1-1             3.18.0-1
                        python-ujson              2.0.3-1              3.0.0-1
                      python-webargs              6.0.0-1              6.1.0-1
                    python-webcolors             1.11.1-1             1.11.1-2
                       python-xcffib             0.10.0-1             0.10.1-1
                         python-yaml              5.3.1-1              5.3.1-2
                     python2-distorm              3.4.1-2                3.5-1
                python2-pycryptodome              3.9.8-1              3.9.8-2
                         python2-tox             3.17.1-1             3.18.0-1
                        python2-yaml              5.3.1-1              5.3.1-2
              qt5-ukui-platformtheme              1.0.2-2              1.0.4-1
                             redkite              1.0.0-1              1.0.1-1
                               rgbds              0.4.0-3              0.4.1-1
                      rime-cantonese     0.0.0.20200717-1     0.0.0.20200725-1
                          rime-essay     0.0.0.20200709-1     0.0.0.20200724-1
                                root            6.20.06-1            6.22.00-2
                           root-cuda            6.20.06-1            6.22.00-2
                          ruby-cairo             1.16.5-1             1.16.6-1
                       ruby-diff-lcs                1.3-4              1.4.4-1
                               scrot                1.3-1                1.4-1
                            shotwell          2:0.30.10-1          2:0.30.10-2
                             snapper             0.8.11-1             0.8.12-1
                            solidity             0.6.11-1             0.6.12-1
                             svt-vp9              0.2.1-1              0.2.2-1
                            sysbench             1.0.18-1             1.0.20-1
                          tensorflow              2.2.0-1           2.3.0rc2-2
                     tensorflow-cuda              2.2.0-1           2.3.0rc2-2
                      tensorflow-opt              2.2.0-1           2.3.0rc2-2
                 tensorflow-opt-cuda              2.2.0-1           2.3.0rc2-2
                             toolbox             0.0.92-1             0.0.93-1
         v2ray-domain-list-community     20200721225648-1     20200723214519-1
                             vim-ale              2.6.0-1              2.7.0-1
                          virtualbox             6.1.12-2             6.1.12-3
                  virtualbox-ext-vnc             6.1.12-2             6.1.12-3
               virtualbox-guest-dkms             6.1.12-2             6.1.12-3
              virtualbox-guest-utils             6.1.12-2             6.1.12-3
          virtualbox-guest-utils-nox             6.1.12-2             6.1.12-3
                virtualbox-host-dkms             6.1.12-2             6.1.12-3
                      virtualbox-sdk             6.1.12-2             6.1.12-3
                              wpscan            1:3.8.2-1            1:3.8.3-1
                         x42-plugins           20200714-1           20200714-2
                             xalan-c             1:1.11-3             1:1.12-1
            xfce4-whiskermenu-plugin              2.4.5-1              2.4.6-1
                           xlockmore               5.64-1               5.65-1
                              xrootd             4.12.3-2              5.0.0-2
                               bless                    -              0.6.2-4
                                gcc9                    -              9.3.0-3
                        gcc9-fortran                    -              9.3.0-3
                           gcc9-libs                    -              9.3.0-3
                     haskell-git-lfs                    -              1.1.0-1
      haskell-http-client-restricted                    -              0.0.3-1
                              marker                    -       2020.04.04.2-3
                            qxmledit                    -             0.9.15-2
                         tree-sitter                    -             0.16.9-1
                             xrootd4                    -             4.12.3-4


:: Different overlay package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
                       libutil-linux           2.35.2-1.1                    -
                            linux414           4.14.188-1           4.14.189-1
                    linux414-headers           4.14.188-1           4.14.189-1
                            linux419           4.19.133-2           4.19.134-1
                    linux419-headers           4.19.133-2           4.19.134-1
                             linux44            4.4.230-1            4.4.231-1
                     linux44-headers            4.4.230-1            4.4.231-1
                             linux49            4.9.230-1            4.9.231-1
                     linux49-headers            4.9.230-1            4.9.231-1
                             linux54             5.4.52-2             5.4.53-1
                     linux54-headers             5.4.52-2             5.4.53-1
                             linux57              5.7.9-1             5.7.10-1
                     linux57-headers              5.7.9-1             5.7.10-1
                      manjaro-system           20200427-1           20200723-1
                          util-linux           2.35.2-1.1                    -


:: Different sync package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
                           amd-ucode   20200519.8ba6fa6-1   20200619.e96c121-1
                       libutil-linux             2.35.2-1               2.36-1
                      linux-firmware   20200519.8ba6fa6-1   20200619.e96c121-1
                           logrotate             3.16.0-1             3.17.0-1
                                sudo              1.9.1-1              1.9.2-1
                          util-linux             2.35.2-1               2.36-1


:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
                                gvim           8.2.1260-0           8.2.1272-0
                  linux414-acpi_call            1.1.0-160            1.1.0-161
                   linux414-bbswitch              0.8-160              0.8-161
                linux414-broadcom-wl     6.30.223.271-160     6.30.223.271-161
                linux414-ndiswrapper              1.63-10              1.63-11
               linux414-nvidia-340xx           340.108-29           340.108-30
               linux414-nvidia-390xx           390.132-37           390.132-38
               linux414-nvidia-418xx           418.113-34           418.113-35
               linux414-nvidia-430xx            430.64-35            430.64-36
               linux414-nvidia-435xx            435.21-45            435.21-46
               linux414-nvidia-440xx            440.100-3            440.100-4
                   linux414-nvidiabl             0.88-160             0.88-161
                      linux414-r8168           8.048.03-7           8.048.03-8
                  linux414-rt3562sta       2.4.1.1_r4-158       2.4.1.1_r4-159
                   linux414-tp_smapi              0.43-52              0.43-53
                linux414-vhba-module          20200106-23          20200106-24
    linux414-virtualbox-host-modules             6.1.12-1             6.1.12-2
                        linux414-zfs              0.8.4-9             0.8.4-10
                  linux419-acpi_call            1.1.0-124            1.1.0-125
                   linux419-bbswitch              0.8-124              0.8-125
                linux419-broadcom-wl     6.30.223.271-123     6.30.223.271-124
                linux419-ndiswrapper              1.63-14              1.63-15
               linux419-nvidia-340xx           340.108-44           340.108-45
               linux419-nvidia-390xx           390.132-53           390.132-54
               linux419-nvidia-418xx           418.113-52           418.113-53
               linux419-nvidia-430xx            430.64-52            430.64-53
               linux419-nvidia-435xx            435.21-63            435.21-64
               linux419-nvidia-440xx            440.100-5            440.100-6
                   linux419-nvidiabl             0.88-123             0.88-124
                      linux419-r8168          8.048.03-10          8.048.03-11
                  linux419-rtl8723bu          20200405-20          20200405-21
                   linux419-tp_smapi              0.43-73              0.43-74
                linux419-vhba-module          20200106-38          20200106-39
   linux419-virtualbox-guest-modules             6.1.12-1             6.1.12-2
    linux419-virtualbox-host-modules             6.1.12-1             6.1.12-2
                        linux419-zfs             0.8.4-13             0.8.4-14
                   linux44-acpi_call            1.1.0-161            1.1.0-162
                    linux44-bbswitch              0.8-161              0.8-162
                 linux44-broadcom-wl     6.30.223.271-131     6.30.223.271-132
                 linux44-ndiswrapper               1.63-9              1.63-10
                linux44-nvidia-340xx           340.108-25           340.108-26
                linux44-nvidia-390xx           390.132-31           390.132-32
                linux44-nvidia-418xx           418.113-30           418.113-31
                linux44-nvidia-430xx            430.64-29            430.64-30
                linux44-nvidia-435xx            435.21-31            435.21-32
                linux44-nvidia-440xx            440.100-3            440.100-4
                    linux44-nvidiabl             0.88-161             0.88-162
                       linux44-r8168           8.048.03-6           8.048.03-7
                   linux44-rt3562sta       2.4.1.1_r4-118       2.4.1.1_r4-119
                    linux44-tp_smapi              0.43-40              0.43-41
                 linux44-vhba-module          20200106-22          20200106-23
     linux44-virtualbox-host-modules             6.1.12-1             6.1.12-2
                         linux44-zfs              0.8.4-8              0.8.4-9
                   linux49-acpi_call            1.1.0-175            1.1.0-176
                    linux49-bbswitch              0.8-175              0.8-176
                 linux49-broadcom-wl     6.30.223.271-175     6.30.223.271-176
                 linux49-ndiswrapper               1.63-9              1.63-10
                linux49-nvidia-340xx           340.108-25           340.108-26
                linux49-nvidia-390xx           390.132-32           390.132-33
                linux49-nvidia-418xx           418.113-31           418.113-32
                linux49-nvidia-430xx            430.64-30            430.64-31
                linux49-nvidia-435xx            435.21-37            435.21-38
                linux49-nvidia-440xx            440.100-3            440.100-4
                    linux49-nvidiabl             0.88-175             0.88-176
                       linux49-r8168           8.048.03-6           8.048.03-7
                   linux49-rt3562sta       2.4.1.1_r4-159       2.4.1.1_r4-160
                    linux49-tp_smapi              0.43-43              0.43-44
                 linux49-vhba-module          20200106-22          20200106-23
     linux49-virtualbox-host-modules             6.1.12-1             6.1.12-2
                         linux49-zfs              0.8.4-8              0.8.4-9
                   linux54-acpi_call             1.1.0-59             1.1.0-60
                    linux54-bbswitch               0.8-59               0.8-60
                 linux54-broadcom-wl      6.30.223.271-59      6.30.223.271-60
                 linux54-ndiswrapper              1.63-15              1.63-16
                linux54-nvidia-340xx           340.108-51           340.108-52
                linux54-nvidia-390xx           390.132-59           390.132-60
                linux54-nvidia-418xx           418.113-59           418.113-60
                linux54-nvidia-430xx            430.64-59            430.64-60
                linux54-nvidia-435xx            435.21-59            435.21-60
                linux54-nvidia-440xx            440.100-5            440.100-6
                    linux54-nvidiabl              0.88-59              0.88-60
                       linux54-r8168          8.048.03-11          8.048.03-12
                   linux54-rtl8723bu          20200405-23          20200405-24
                    linux54-tp_smapi              0.43-59              0.43-60
                 linux54-vhba-module          20200106-44          20200106-45
    linux54-virtualbox-guest-modules             6.1.12-1             6.1.12-2
     linux54-virtualbox-host-modules             6.1.12-1             6.1.12-2
                         linux54-zfs             0.8.4-14             0.8.4-15
                   linux57-acpi_call             1.1.0-15             1.1.0-16
                    linux57-bbswitch               0.8-15               0.8-16
                 linux57-broadcom-wl      6.30.223.271-15      6.30.223.271-16
                 linux57-ndiswrapper              1.63-15              1.63-16
                linux57-nvidia-340xx           340.108-15           340.108-16
                linux57-nvidia-390xx           390.132-15           390.132-16
                linux57-nvidia-418xx           418.113-15           418.113-16
                linux57-nvidia-430xx            430.64-15            430.64-16
                linux57-nvidia-435xx            435.21-15            435.21-16
                linux57-nvidia-440xx            440.100-6            440.100-7
                       linux57-r8168          8.048.03-15          8.048.03-16
                   linux57-rtl8723bu          20200405-15          20200405-16
                    linux57-tp_smapi              0.43-15              0.43-16
                 linux57-vhba-module          20200106-15          20200106-16
    linux57-virtualbox-guest-modules            6.1.10-11             6.1.12-2
     linux57-virtualbox-host-modules             6.1.12-1             6.1.12-2
                         linux57-zfs             0.8.4-15             0.8.4-16
               manjaro-arm-tools-git  2.8.6.r4.g3f2e271-1 2.8.6.r10.g5060eb8-1
                                 vim           8.2.1260-0           8.2.1272-0
                         vim-runtime           8.2.1260-0           8.2.1272-0
                   libva-mesa-driver                    -             20.1.4-1
                                mesa                    -             20.1.4-1
                          mesa-vdpau                    -             20.1.4-1
                         opencl-mesa                    -             20.1.4-1
                        vulkan-intel                    -             20.1.4-1
                  vulkan-mesa-layers                    -             20.1.4-1
                       vulkan-radeon                    -             20.1.4-1


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
                              amdvlk          2020.Q3.1-2          2020.Q3.2-1
                              clamav            0.102.3-1            0.102.4-1
                               clang             10.0.0-3             10.0.1-1
                         compiler-rt             10.0.0-1             10.0.1-1
                                 efl             1.24.3-1             1.24.3-2
                            efl-docs             1.24.3-1             1.24.3-2
                               fping                4.2-2                4.3-1
                     freecell-solver             5.24.0-1              6.0.1-1
                                gegl             0.4.24-1             0.4.24-2
                              gthumb             3.10.0-1             3.10.0-2
                         imagemagick          7.0.10.24-1          7.0.10.24-2
                     imagemagick-doc          7.0.10.24-1          7.0.10.24-2
                              jasper             2.0.16-2             2.0.17-1
                          jasper-doc             2.0.16-2             2.0.17-1
                            kdevelop              5.5.2-2              5.5.2-3
                               krita              4.3.0-1              4.3.0-2
                              libidn               1.35-3               1.36-1
                           libkdcraw            20.04.3-1            20.04.3-2
                          libmagick6          6.9.11.23-1          6.9.11.24-1
                              libraw             0.19.5-3             0.20.0-1
                                 lld             10.0.0-3             10.0.1-1
                                lldb             10.0.0-2             10.0.1-1
                                llvm             10.0.0-2             10.0.1-1
                           llvm-libs             10.0.0-2             10.0.1-1
                          llvm-ocaml             10.0.0-2             10.0.1-1
                               ndctl                 68-2                 69-1
                              openmp             10.0.0-1             10.0.1-1
            plasma-wayland-protocols                1.0-1              1.1.0-1
                          prometheus             2.19.2-1             2.20.0-1
       prometheus-memcached-exporter              0.6.0-2              0.7.0-1
            python-lazy-object-proxy              1.5.0-2              1.5.1-1
                    python-shiboken2             5.15.0-1             5.15.0-2
                      python-urllib3             1.25.9-1            1.25.10-1
                  python-urllib3-doc             1.25.9-1            1.25.10-1
           python2-lazy-object-proxy              1.5.0-1                    -
                     python2-urllib3             1.25.9-1            1.25.10-1
                                qemu              5.0.0-7              5.0.0-8
                     qemu-arch-extra              5.0.0-7              5.0.0-8
                  qemu-block-gluster              5.0.0-7              5.0.0-8
                    qemu-block-iscsi              5.0.0-7              5.0.0-8
                      qemu-block-rbd              5.0.0-7              5.0.0-8
                    qemu-guest-agent              5.0.0-7              5.0.0-8
                       qemu-headless              5.0.0-7              5.0.0-8
            qemu-headless-arch-extra              5.0.0-7              5.0.0-8
                           qt5-tools             5.15.0-2             5.15.0-3
                           qtcreator             4.12.4-1             4.12.4-2
                                re2c                1.3-2                2.0-1
                            rubygems              3.1.3-1              3.1.4-1
                           shiboken2             5.15.0-1             5.15.0-2
                      spice-protocol             0.14.1-1             0.14.2-1
                            valgrind 3.15.0+269+gd772e2599-1          3.16.1-1
                      vulkan-headers          1:1.2.147-1          1:1.2.148-1
                    vulkan-html-docs          1:1.2.147-1          1:1.2.148-1
                  xfce4-timer-plugin              1.7.0-2              1.7.1-1


:: Different overlay package(s) in repository multilib x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
             lib32-libva-mesa-driver                    -             20.1.4-1
                          lib32-mesa                    -             20.1.4-1
                    lib32-mesa-vdpau                    -             20.1.4-1
                   lib32-opencl-mesa                    -             20.1.4-1
                  lib32-vulkan-intel                    -             20.1.4-1
            lib32-vulkan-mesa-layers                    -             20.1.4-1
                 lib32-vulkan-radeon                    -             20.1.4-1


:: Different sync package(s) in repository multilib x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-22           2020-07-25
-------------------------------------------------------------------------------
                        lib32-amdvlk          2020.Q3.1-2          2020.Q3.2-1
                         lib32-clang             10.0.0-1             10.0.1-1
                          lib32-llvm             10.0.0-1             10.0.1-1
                     lib32-llvm-libs             10.0.0-1             10.0.1-1

No issue, everything went smoothly
Yes there was an issue. I was able to resolve it myself.(Please post your solution)
Yes i am currently experiencing an issue due to the update. (Please post about it)

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[Testing Update] 2020-07-22 - Kernels, VirtualBox, NextCloud, Deepin, OpenJDK

Wed, 22 Jul 2020 10:18:42 +0200

Hello community,

Another testing branch update with some interesting updates for you!

The #PineBookPro is again available for pre-order! #stayhome, #staysafe, #stayhealthy

We updated the real-time Kernel
Virtualbox is 6.1.12
Nextcloud got its first point-release to its 19 series
More Deepin packages
OpenJDK is updated
Firefox 79 series got another beta release
Riot is renamed to Element
Regular Python updates

Upstream notice

sudo pacman -Syy
sudo pacman -S pacman-static
sudo pacman-static -Syyu

Our current supported kernels

linux44 4.4.230
linux49 4.9.230
linux414 4.14.188
linux419 4.19.133
linux54 5.4.52
linux56 5.6.19 [EOL]
linux57 5.7.9
linux58 5.8-rc5
linux54-rt 5.4.52_rt31
linux56-rt 5.6.17_rt9

Package Changes (Wed Jul 22 09:07:28 CEST 2020)

testing community x86_64: 467 new and 465 removed package(s)
testing core x86_64: 16 new and 15 removed package(s)
testing extra x86_64: 134 new and 132 removed package(s)
testing multilib x86_64: 7 new and 7 removed package(s)

:: Different overlay package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-17           2020-07-22
-------------------------------------------------------------------------------
                               cpu-x 4.0.1.r22.ge567ff7-1 4.0.1.r27.gb32f893-1
                     diffuse-manjaro          0.5.0.rc2-10.5.0.rev7.gb7eb43f-1
                         edid-decode       r450.4ee445e-1       r451.56dd103-1
                      gnome-firmware 3.34.0+36+g4147a76-1                    -
                        grub-vanilla               2.04-4               2.04-5
                          guayadeque0.4.6.r2149.ed0b3ca4-10.4.6.r2150.3c54f64b-1
                            hw-probe1.6+beta.20.g6b59310d48-11.6+beta.21.g791646fa2b-1
                           limepanel 0.48.r133.g3366074-1 0.48.r133.g3366074-2
                          linux54-rt        5.4.47_rt28-1        5.4.52_rt31-1
                linux54-rt-acpi_call             1.1.0-17             1.1.0-18
                 linux54-rt-bbswitch               0.8-17               0.8-18
              linux54-rt-broadcom-wl      6.30.223.271-17      6.30.223.271-18
                  linux54-rt-headers        5.4.47_rt28-1        5.4.52_rt31-1
              linux54-rt-ndiswrapper               1.63-7               1.63-8
             linux54-rt-nvidia-340xx           340.108-16           340.108-17
             linux54-rt-nvidia-390xx           390.132-17           390.132-18
             linux54-rt-nvidia-418xx           418.113-17           418.113-18
             linux54-rt-nvidia-430xx            430.64-17            430.64-18
             linux54-rt-nvidia-435xx            435.21-16            435.21-17
             linux54-rt-nvidia-440xx            440.100-1            440.100-3
                 linux54-rt-nvidiabl              0.88-17              0.88-18
                    linux54-rt-r8168           8.048.03-4           8.048.03-5
                linux54-rt-rtl8723bu           20200405-6           20200405-7
                 linux54-rt-tp_smapi              0.43-17              0.43-18
              linux54-rt-vhba-module          20200106-14          20200106-15
 linux54-rt-virtualbox-guest-modules             6.1.10-3             6.1.12-1
  linux54-rt-virtualbox-host-modules             6.1.10-3             6.1.12-1
  linux56-rt-virtualbox-host-modules             6.1.10-2             6.1.12-1
                                 nim              1.2.4-0                    -
                           pacui-git      r1026.09cb8ec-1   1.14.r6.g846f892-1
                             polybar              3.4.3-1              3.4.3-3
                      qgnomeplatform   0.6.1+5+gc835c9e-1   0.6.1+7+g6886e33-1
                      ttf-font-icons                1.1-4                    -
                      ttf-font-logos               0.10-4                    -
                   ttf-icomoon-icons                1.0-1                    -
                  ttf-material-icons     r124.224895a86-1                    -
                   ttf-polybar-icons                1.0-1                    -
                                 yay             10.0.2-2             10.0.3-3


:: Different sync package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-17           2020-07-22
-------------------------------------------------------------------------------
                                 ack              3.3.1-2              3.4.0-1
                              acpica           20200528-1           20200717-1
                                 afl              2.57b-1              2.57b-2
                             ansible             2.9.10-1             2.9.11-1
                    arduino-avr-core              1.8.2-2              1.8.3-1
                               aubio              0.4.9-7              0.4.9-8
                             aws-cli            1.18.97-1           1.18.100-1
                             barrier              2.3.2-2              2.3.3-1
                    barrier-headless              2.3.2-2              2.3.3-1
                             bashtop             0.9.12-1             0.9.24-1
                               bazel              3.3.0-1              3.4.1-1
                           bettercap             2.27.1-2               2.28-1
                                cage 0.1.1.r40.gcc1f975-2            0.1.2.1-1
                             calibre             4.20.0-1             4.21.0-1
                      calibre-common             4.20.0-1             4.21.0-1
                     calibre-python3             4.20.0-1             4.21.0-1
                             cargo-c              0.6.8-1              0.6.9-1
                      cargo-outdated             0.9.10-1             0.9.11-1
                              catch2             2.12.2-1             2.13.0-1
                              ccache              3.7.9-1             3.7.10-1
                            checksec              2.2.2-1              2.2.3-1
                        cmake-fedora              2.9.3-1              2.9.3-2
                                code             1.47.1-1             1.47.2-2
                              conmon           1:2.0.18-2           1:2.0.19-1
                                croc             8.0.11-1             8.0.12-1
                   deepin-calculator             5.5.21-1             5.5.22-1
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                       python-joblib             0.14.1-1             0.16.0-1
                     python-m2crypto             0.35.2-3             0.36.0-1
                     python-markdown              3.1.1-4              3.2.2-1
                  python-marshmallow              3.7.0-1              3.7.1-1
                   python-matplotlib              3.2.2-1              3.3.0-1
                       python-minidb              2.0.3-1              2.0.4-1
                       python-nbxmpp             0.6.10-3              1.0.1-1
                python-nmigen-boards       r105.86ae791-1       r133.d9264bf-1
                      python-oslo-db              8.2.1-1              8.3.0-1
             python-ovirt-engine-sdk              4.3.0-3              4.4.4-1
            python-pandas-datareader              0.8.1-2              0.9.0-1
                       python-pg8000             1.16.0-1             1.16.1-1
                      python-pikepdf             1.17.1-1             1.17.2-1
                     python-pyfakefs              4.0.2-1              4.1.0-1
                      python-pymysql              0.9.3-3             0.10.0-1
               python-pytest-timeout              1.4.1-1              1.4.2-1
                        python-pyvcd              0.1.7-1              0.2.3-1
                        python-quart             0.12.0-1             0.13.0-1
                        python-regex           2020.6.8-1          2020.7.14-1
                    python-reportlab             3.5.42-2             3.5.44-1
                           python-rx              3.1.0-1              3.1.1-1
                   python-simplejson             3.17.0-1             3.17.2-1
                    python-stevedore              3.1.0-1              3.2.0-1
       python-tensorflow-serving-api              2.1.0-1              2.2.0-1
                    python-testinfra              5.2.1-1              5.2.2-1
                python-threadpoolctl              2.0.0-1              2.1.0-1
                          python-tox             3.17.0-1             3.17.1-1
                         python-tqdm             4.47.0-1             4.48.0-1
            python-typing_extensions            3.7.4.1-1            3.7.4.3-1
                       python-xcffib              0.9.0-2             0.10.0-1
                         python-yara              4.0.1-1              4.0.2-1
                       python-yaspin             0.17.0-1             0.18.0-1
              python-zope-exceptions                4.3-3                4.4-1
                        python2-caja             1.22.1-1                    -
                    python2-m2crypto             0.35.2-3             0.36.0-1
                    python2-markdown              3.1.1-4              3.1.1-5
              python2-pytest-timeout              1.4.1-1              1.4.2-1
                       python2-regex           2020.6.8-1          2020.7.14-1
                  python2-simplejson             3.17.0-1             3.17.2-1
                         python2-tox             3.17.0-1             3.17.1-1
                    python2-trollius                2.1-3          2.1.post2-1
                   python2-unittest2              1.1.0-5              1.1.0-6
                        python2-yara              4.0.1-1              4.0.2-1
             python2-zope-exceptions                4.3-3                4.4-1
                         qpid-proton             0.30.0-3             0.30.0-5
                               qt5ct                1.0-1                1.1-1
                         qutebrowser             1.13.0-2             1.13.1-1
                               redis              6.0.5-1              6.0.6-1
              retroarch-assets-ozone              1:323-1              1:325-1
                retroarch-assets-xmb              1:323-1              1:325-1
                      rime-cantonese     0.0.0.20200714-1     0.0.0.20200717-1
                                rink              0.4.5-1              0.5.0-1
                       roundcubemail              1.4.6-1              1.4.7-1
                       rust-analyzer           20200713-1           20200720-1
                        rust-bindgen             0.54.0-1             0.54.0-2
                          rust-racer             2.1.31-1             2.1.36-1
                               s-tui              1.0.1-1              1.0.2-1
                                 sbt           1:1.3.11-1           1:1.3.12-1
                              scrapy              2.2.0-1              2.2.1-1
                        sherlock.lv2             0.22.0-1             0.24.0-1
                            shotwell           2:0.30.8-2          2:0.30.10-1
                               siege              4.0.5-2              4.0.7-1
                      signal-desktop             1.34.3-2             1.34.4-1
                            sigutils              0.1.0-1              0.1.0-2
                            smplayer             20.4.2-1             20.6.0-1
                                sslh               1.20-2              1.21b-1
                               stack             2.3.1-62             2.3.1-64
                         stratis-cli              2.1.0-1              2.1.1-1
                              stylus             0.54.7-2             0.54.8-1
                              suscan              0.1.0-1              0.1.0-2
                             svt-vp9              0.2.0-1              0.2.1-1
                                sway              1:1.4-9              1:1.5-1
                          swi-prolog              8.2.0-1              8.2.1-1
                              sysdig             0.26.7-2             0.26.7-3
                        systemd-swap              4.3.0-1              4.3.2-1
                             taskell          1.9.2.0-128          1.9.2.0-129
                           tcpreplay              4.3.2-2              4.3.3-1
                               tiled              1.4.1-1              1.4.1-2
                    ttf-font-awesome             5.13.1-2             5.14.0-1
                          typescript              3.9.6-1              3.9.7-1
                        ukui-greeter              1.2.5-1              1.2.6-1
                          ukui-media              2.0.3-1              2.0.4-1
                ukui-session-manager              2.0.2-1              2.0.3-1
                         ukui-themes              1.3.0-1              1.4.0-1
                          unrealircd            5.0.5.1-1              5.0.6-1
                             uranium              4.5.0-1              4.5.0-2
                            urlwatch               2.18-4               2.19-1
                      usb_modeswitch              2.6.0-2              2.6.1-1
         v2ray-domain-list-community     20200715082334-1     20200721225648-1
                         v2ray-geoip       202007150004-1       202007220003-1
                                vico                1.2-1              1.2.1-1
                          virtualbox             6.1.10-1             6.1.12-2
                  virtualbox-ext-vnc             6.1.10-1             6.1.12-2
               virtualbox-guest-dkms             6.1.10-1             6.1.12-2
                virtualbox-guest-iso             6.1.10-1             6.1.12-1
              virtualbox-guest-utils             6.1.10-1             6.1.12-2
          virtualbox-guest-utils-nox             6.1.10-1             6.1.12-2
                virtualbox-host-dkms             6.1.10-1             6.1.12-2
                      virtualbox-sdk             6.1.10-1             6.1.12-2
                              vm.lv2              0.8.0-1             0.10.0-1
                                 vtk             8.2.0-13             8.2.0-14
                              waybar              0.9.2-2              0.9.2-3
                             weechat                2.8-3                2.9-1
                           widelands                 20-9                 21-1
                             wlroots             0.10.1-1             0.11.0-1
            xfce4-whiskermenu-plugin              2.4.4-1              2.4.5-1
                            yamllint             1.23.0-1             1.24.2-1
                                yara              4.0.1-1              4.0.2-1
                             you-get           0.4.1432-2           0.4.1456-1
                         zam-plugins               3.12-1               3.13-1
                             cpptoml                    -              0.1.1-2
                            easy-pdk                    -                1.3-1
                     element-desktop                    -              1.7.1-3
                         element-web                    -              1.7.1-3
               haskell-input-parsers                    -            0.1.0.1-1
                           marked0.8                    -              0.8.2-1
                                muse                    -              3.1.1-1
                         python-caja                    -             1.24.0-1
              python-hypothesis-auto                    -              1.1.4-1
                    python-miniupnpc                    -       2.1.20191224-1
                                qtqr                    -                2.0-2
                         wireplumber                    -              0.3.0-1


:: Different overlay package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-17           2020-07-22
-------------------------------------------------------------------------------
                           amd-ucode20200716.r1675.1d1c80b-120200721.r1678.2b823fc-1
                      linux-firmware20200716.r1675.1d1c80b-120200721.r1678.2b823fc-1
                            linux419           4.19.133-1           4.19.133-2
                    linux419-headers           4.19.133-1           4.19.133-2
                             linux54             5.4.52-1             5.4.52-2
                     linux54-headers             5.4.52-1             5.4.52-2
                             linux585.8rc5.d0712.g11ba468-15.8rc6.d0719.gba47d84-1
                     linux58-headers5.8rc5.d0712.g11ba468-15.8rc6.d0719.gba47d84-1


:: Different sync package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-17           2020-07-22
-------------------------------------------------------------------------------
                               gpgme             1.13.1-7             1.14.0-1
                            iana-etc           20200707-1           20200720-1
                            libevent             2.1.11-5             2.1.12-1
                          mkinitcpio                 27-3                 28-1
                             openssh              8.3p1-1              8.3p1-3
                        python-gpgme             1.13.1-7             1.14.0-1
                              qgpgme             1.13.1-7             1.14.0-1
                              shadow              4.8.1-2              4.8.1-3


:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-17           2020-07-22
-------------------------------------------------------------------------------
                                gvim           8.2.1185-0           8.2.1260-0
    linux414-virtualbox-host-modules             6.1.10-6             6.1.12-1
                  linux419-acpi_call            1.1.0-123            1.1.0-124
                   linux419-bbswitch              0.8-123              0.8-124
                linux419-broadcom-wl     6.30.223.271-122     6.30.223.271-123
                linux419-ndiswrapper              1.63-13              1.63-14
               linux419-nvidia-340xx           340.108-43           340.108-44
               linux419-nvidia-390xx           390.132-52           390.132-53
               linux419-nvidia-418xx           418.113-51           418.113-52
               linux419-nvidia-430xx            430.64-51            430.64-52
               linux419-nvidia-435xx            435.21-62            435.21-63
               linux419-nvidia-440xx            440.100-4            440.100-5
                   linux419-nvidiabl             0.88-122             0.88-123
                      linux419-r8168           8.048.03-9          8.048.03-10
                  linux419-rtl8723bu          20200405-19          20200405-20
                   linux419-tp_smapi              0.43-72              0.43-73
                linux419-vhba-module          20200106-37          20200106-38
   linux419-virtualbox-guest-modules             6.1.10-7             6.1.12-1
    linux419-virtualbox-host-modules             6.1.10-7             6.1.12-1
                        linux419-zfs             0.8.4-12             0.8.4-13
     linux44-virtualbox-host-modules             6.1.10-5             6.1.12-1
     linux49-virtualbox-host-modules             6.1.10-5             6.1.12-1
                   linux54-acpi_call             1.1.0-58             1.1.0-59
                    linux54-bbswitch               0.8-58               0.8-59
                 linux54-broadcom-wl      6.30.223.271-58      6.30.223.271-59
                 linux54-ndiswrapper              1.63-14              1.63-15
                linux54-nvidia-340xx           340.108-50           340.108-51
                linux54-nvidia-390xx           390.132-58           390.132-59
                linux54-nvidia-418xx           418.113-58           418.113-59
                linux54-nvidia-430xx            430.64-58            430.64-59
                linux54-nvidia-435xx            435.21-58            435.21-59
                linux54-nvidia-440xx            440.100-4            440.100-5
                    linux54-nvidiabl              0.88-58              0.88-59
                       linux54-r8168          8.048.03-10          8.048.03-11
                   linux54-rtl8723bu          20200405-22          20200405-23
                    linux54-tp_smapi              0.43-58              0.43-59
                 linux54-vhba-module          20200106-43          20200106-44
    linux54-virtualbox-guest-modules             6.1.10-8             6.1.12-1
     linux54-virtualbox-host-modules             6.1.10-8             6.1.12-1
                         linux54-zfs             0.8.4-13             0.8.4-14
    linux56-virtualbox-guest-modules             6.1.10-3             6.1.12-1
     linux56-virtualbox-host-modules             6.1.10-3             6.1.12-1
     linux57-virtualbox-host-modules            6.1.10-11             6.1.12-1
                   linux58-acpi_call            1.1.0-0.5            1.1.0-0.6
                    linux58-bbswitch              0.8-0.5              0.8-0.6
                 linux58-broadcom-wl     6.30.223.271-0.5     6.30.223.271-0.6
                linux58-nvidia-390xx          390.132-0.5          390.132-0.6
                linux58-nvidia-418xx          418.113-0.5          418.113-0.6
                linux58-nvidia-430xx           430.64-0.5           430.64-0.6
                linux58-nvidia-435xx           435.21-0.5           435.21-0.6
                linux58-nvidia-440xx          440.100-0.5          440.100-0.6
                       linux58-r8168         8.048.03-0.5         8.048.03-0.6
                    linux58-tp_smapi             0.43-0.5             0.43-0.6
                 linux58-vhba-module         20200106-0.5         20200106-0.6
               manjaro-arm-tools-git  2.8.6.r3.ga4db587-1  2.8.6.r4.g3f2e271-1
                                 vim           8.2.1185-0           8.2.1260-0
                         vim-runtime           8.2.1185-0           8.2.1260-0
                           zfs-utils              0.8.4-1              0.8.4-2
                                dkms                    -            2.8.3-1.1
                         linux58-zfs                    -            0.8.4-0.6


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-17           2020-07-22
-------------------------------------------------------------------------------
                              amdvlk          2020.Q3.1-1          2020.Q3.1-2
            archlinux-appstream-data           20200612-1           20200720-1
                        avidemux-cli              2.7.4-5              2.7.6-1
                         avidemux-qt              2.7.4-5              2.7.6-1
                                bind             9.16.4-1             9.16.5-2
                          bind-tools             9.16.4-1                    -
                               check             0.15.0-1             0.15.0-2
                          check-docs             0.15.0-1             0.15.0-2
                               cmake             3.17.3-1             3.18.0-2
                            composer             1.10.8-1             1.10.9-1
                                cups              2.3.3-1              2.3.3-2
                      deluge 2.0.4.dev38+g23a48dd01-1 2.0.4.dev38+g23a48dd01-2
                  deluge-gtk 2.0.4.dev38+g23a48dd01-1 2.0.4.dev38+g23a48dd01-2
                             digikam             6.4.0-10              7.0.0-1
                                dkms              2.8.1-4              2.8.3-1
                             dnsmasq               2.81-4               2.82-1
                  gnome-disk-utility             3.36.1-2             3.36.3-1
                             gnuplot              5.2.8-2              5.4.0-1
                            harfbuzz              2.6.8-2              2.6.8-3
                        harfbuzz-icu              2.6.8-2              2.6.8-3
                             hddtemp      0.3.beta15.53-2      0.3.beta15.53-3
                            help2man            1.47.15-1            1.47.16-1
                         imagemagick          7.0.10.23-1          7.0.10.24-1
                     imagemagick-doc          7.0.10.23-1          7.0.10.24-1
                         jdk-openjdk          14.0.1.u7-1         14.0.2.u12-1
                       jdk11-openjdk         11.0.7.u10-1         11.0.8.u10-1
                        jdk8-openjdk             8.u252-1             8.u262-1
                         jre-openjdk          14.0.1.u7-1         14.0.2.u12-1
                jre-openjdk-headless          14.0.1.u7-1         14.0.2.u12-1
                       jre11-openjdk         11.0.7.u10-1         11.0.8.u10-1
              jre11-openjdk-headless         11.0.7.u10-1         11.0.8.u10-1
                        jre8-openjdk             8.u252-1             8.u262-1
               jre8-openjdk-headless             8.u252-1             8.u262-1
                             jsoncpp              1.9.2-1              1.9.3-1
                         jsoncpp-doc              1.9.2-1              1.9.3-1
                     lib32-rust-libs           1:1.44.1-1           1:1.45.0-2
                              libbpf              0.0.8-1              0.0.9-1
                             libcups              2.3.3-1              2.3.3-2
                            libevdev              1.9.0-1              1.9.1-1
                               libnm             1.24.2-1             1.26.0-1
                                 mlt             6.20.0-3             6.20.0-4
                                mono          6.8.0.123-1         6.10.0.104-1
                                nasm            2.14.02-2            2.15.02-1
                      networkmanager             1.24.2-1             1.26.0-1
                      nm-cloud-setup             1.24.2-1             1.26.0-1
                    noto-fonts-emoji           20191016-6           20200720-1
                         openjdk-doc          14.0.1.u7-1         14.0.2.u12-1
                         openjdk-src          14.0.1.u7-1         14.0.2.u12-1
                       openjdk11-doc         11.0.7.u10-1         11.0.8.u10-1
                       openjdk11-src         11.0.7.u10-1         11.0.8.u10-1
                        openjdk8-doc             8.u252-1             8.u262-1
                        openjdk8-src             8.u252-1             8.u262-1
                   perl-log-log4perl               1.49-7               1.50-1
             perl-lwp-protocol-https               6.07-5               6.09-1
              plasma-wayland-session             5.19.3-1             5.19.3-2
                    plasma-workspace             5.19.3-1             5.19.3-2
                        python-numpy             1.19.0-1             1.19.1-1
                 python-patiencediff              0.1.0-1              0.2.0-1
                 python2-ordered-set              3.1.1-2              3.1.1-3
                            rinutils              0.4.0-1              0.4.1-1
                                rust           1:1.44.1-1           1:1.45.0-2
                           rust-docs           1:1.44.1-1           1:1.45.0-2
                        sane-airscan             0.99.9-2            0.99.10-1
                           syslog-ng             3.27.1-1             3.28.1-1
                             tomcat7            7.0.104-1            7.0.105-1
                             tomcat8             8.5.56-1             8.5.57-1
                             tomcat9             9.0.35-1             9.0.37-1
                            wxmaxima            20.06.6-1            20.07.0-1
                            xorg-xev              1.2.3-2              1.2.4-1
                        zabbix-agent              5.0.1-1              5.0.2-1
                       zabbix-agent2              5.0.1-1              5.0.2-1
                 zabbix-frontend-php              5.0.1-1              5.0.2-1
                        zabbix-proxy              5.0.1-1              5.0.2-1
                       zabbix-server              5.0.1-1              5.0.2-1
                          kio-gdrive                    -              1.3.0-2


:: Different sync package(s) in repository multilib x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-07-17           2020-07-22
-------------------------------------------------------------------------------
                        lib32-amdvlk          2020.Q3.1-1          2020.Q3.1-2
                      lib32-harfbuzz              2.6.8-2              2.6.8-3
                  lib32-harfbuzz-icu              2.6.8-2              2.6.8-3
                     lib32-primus_vk                1.4-1                1.5-1
                        lib32-wxgtk2              3.0.4-2            3.0.5.1-1
                                wine               5.12-1               5.13-1
                        wine-staging             5.12.1-1               5.13-1

No issue, everything went smoothly
Yes there was an issue. I was able to resolve it myself.(Please post your solution)
Yes i am currently experiencing an issue due to the update. (Please post about it)

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Developer Snapshots: Programmierer-News in ein, zwei Sätzen

Fri, 05 Jun 2020 19:02:25 +0200

Unsere Übersicht der kleinen, aber interessanten Meldungen enthält diese Woche unter anderem PyCharm, Rust, Julia, MicroK8s und Eclipse Drigible.

Big Data Tools: JetBrains gibt Plug-in für IntelliJ, PyCharm und DataGrip frei

Tue, 02 Jun 2020 13:47:21 +0200

Nutzer der IDEs erhalten über das Plug-in direkten Zugriff auf Zeppelin Notebooks, Spark-Anwendungen sowie Dateien auf S3-Speicherinstanzen

[Stable Update] 2020-05-11 - Kernels, Systemd 245.5, Browsers, Thunderbird, Pamac, Deepin 20, Pamac 9.5

Mon, 11 May 2020 11:33:33 +0200

Hello community,

Another stable branch update with some interesting updates for you!

Get Gnome 20.0.1 and have fun! #stayhome, #staysave, #stayhealthy

Most of our Kernels got updated
Systemd is now at 245.5
KDE-git packages got updated
Thunderbird is at 68.8.0
Pamac 9.5 got its released. Find out more
Deepin got updated to v20 series
Some of our browsers got updated: Firefox 76.0.1, Firefox-Dev 77.0b3, Palemoon 28.9.3
The usual upstream updates

If you like following latest Plasma development you may also like to check out our current version of manjaro-kde-dev, which we build on a regular basis against kde-git master packages. Also check out stable release of Manjaro Lysia 20.0.1! XFCE, KDE and Gnome

Upstream notice

sudo pacman -Syy
sudo pacman -S pacman-static
sudo pacman-static -Syyu

Our current supported kernels

linux316 3.16.83
linux44 4.4.222
linux49 4.9.222
linux414 4.14.179
linux419 4.19.121
linux54 5.4.39
linux55 5.5.19 EOL
linux56 5.6.11
linux57 5.7-rc4
linux54-rt 5.4.28_rt19
linux56-rt 5.6.10_rt5

Package Changes (Sun May 10 10:41:45 CEST 2020)

stable community x86_64: 572 new and 573 removed package(s)
stable core x86_64: 34 new and 35 removed package(s)
stable extra x86_64: 476 new and 475 removed package(s)
stable multilib x86_64: 14 new and 15 removed package(s)



:: Different overlay package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-08           2020-05-11
-------------------------------------------------------------------------------
                          breeze-git5.18.80.r1984.g1a9dc381-15.18.80.r1989.g34862b27-1
                    breeze-icons-git5.70.0.r1554.g3e961ab3-15.70.0.r1555.gb94a7284-1
                               cpu-x3.2.4.r248.g10766c6-13.2.4.r256.g33c0406-1
      deepin-desktop-schemas-manjaro             3.13.9-1         5.4.0099.0-1
        deepin-file-manager-nomodule              5.0.0-5           5.1.1.25-1
                   deepin-wallpapers            2:1.7.5-2            2:1.7.7-1
                           downgrade              6.3.0-1              7.0.0-1
             extra-cmake-modules-git5.70.0.r3151.g8d18163-15.70.0.r3153.gbac7608-1
                             gtkhash                1.2-3                1.2-4
                        gtkhash-caja                1.2-3                1.2-4
                    gtkhash-nautilus                1.2-3                1.2-4
                        gtkhash-nemo                1.2-3                1.2-4
                      gtkhash-thunar                1.2-3                1.2-4
                                 jwm              2.3.7-1                    -
               kactivitymanagerd-git5.15.80.r1273.g50bde7c-15.15.80.r1274.g3bc86ea-1
                      kbookmarks-git5.70.0.r331.g8a28231-15.70.0.r333.g1d8d223-1
                     kcompletion-git5.70.0.r358.g9d05a00-15.70.0.r359.g5b08593-1
                         kconfig-git5.70.0.r688.g311e308-15.70.0.r689.g8e0f840-1
                     kcoreaddons-git5.70.0.r974.g7804a0c-15.70.0.r975.g0824e28-1
                    kdeclarative-git5.70.0.r771.g66c82cd-15.70.0.r772.g9725a21-1
                kdeplasma-addons-git5.18.80.r8335.g786062f1d-15.18.80.r8336.g1d64bd119-1
                             kio-git5.70.0.r3930.g692d9bc8-15.70.0.r3937.g81a7b118-1
                      kitemviews-git5.70.0.r267.g5ccc82f-15.70.0.r268.gdf9e5d3-1
                      knetattach-git5.18.80.r7592.g1d557e8a7-15.18.80.r7597.geeab79954-1
                  knotifications-git5.70.0.r528.g2012f67-15.70.0.r532.ga39883c-1
                     ksshaskpass-git5.18.80.r158.g54d2fa6-15.18.80.r159.g64d6c18-1
                       ksysguard-git5.18.80.r3242.g8e2603a6-15.18.80.r3244.gdbb0b515-1
                  kwidgetsaddons-git5.70.0.r663.g5a2ea81-15.70.0.r668.g5904c47-1
                            libcpuid 0.4.1.r35.g9d22c61-1 0.4.1.r50.g21e4b1f-1
                    libksysguard-git5.18.80.r1786.gd8e4677-15.18.80.r1789.gb1e9126-1
              linux56-rt-ndiswrapper               1.62-3               1.63-1
                        palemoon-bin             28.9.2-1             28.9.3-1
                    palemoon-i18n-ar             28.9.2-1             28.9.3-1
                    palemoon-i18n-bg             28.9.2-1             28.9.3-1
                    palemoon-i18n-cs             28.9.2-1             28.9.3-1
                    palemoon-i18n-da             28.9.2-1             28.9.3-1
                    palemoon-i18n-de             28.9.2-1             28.9.3-1
                    palemoon-i18n-el             28.9.2-1             28.9.3-1
                 palemoon-i18n-en-gb             28.9.2-1             28.9.3-1
                 palemoon-i18n-es-ar             28.9.2-1             28.9.3-1
                 palemoon-i18n-es-es             28.9.2-1             28.9.3-1
                 palemoon-i18n-es-mx             28.9.2-1             28.9.3-1
                    palemoon-i18n-fi             28.9.2-1             28.9.3-1
                    palemoon-i18n-fr             28.9.2-1             28.9.3-1
                    palemoon-i18n-gl             28.9.2-1             28.9.3-1
                    palemoon-i18n-hr             28.9.2-1             28.9.3-1
                    palemoon-i18n-hu             28.9.2-1             28.9.3-1
                    palemoon-i18n-id             28.9.2-1             28.9.3-1
                    palemoon-i18n-is             28.9.2-1             28.9.3-1
                    palemoon-i18n-it             28.9.2-1             28.9.3-1
                    palemoon-i18n-ja             28.9.2-1             28.9.3-1
                    palemoon-i18n-kn             28.9.2-1             28.9.3-1
                    palemoon-i18n-ko             28.9.2-1             28.9.3-1
                    palemoon-i18n-nl             28.9.2-1             28.9.3-1
                    palemoon-i18n-pl             28.9.2-1             28.9.3-1
                 palemoon-i18n-pt-br             28.9.2-1             28.9.3-1
                 palemoon-i18n-pt-pt             28.9.2-1             28.9.3-1
                    palemoon-i18n-ro             28.9.2-1             28.9.3-1
                    palemoon-i18n-ru             28.9.2-1             28.9.3-1
                    palemoon-i18n-sk             28.9.2-1             28.9.3-1
                    palemoon-i18n-sl             28.9.2-1             28.9.3-1
                    palemoon-i18n-sr             28.9.2-1             28.9.3-1
                 palemoon-i18n-sv-se             28.9.2-1             28.9.3-1
                    palemoon-i18n-tl             28.9.2-1             28.9.3-1
                    palemoon-i18n-tr             28.9.2-1             28.9.3-1
                    palemoon-i18n-uk             28.9.2-1             28.9.3-1
                    palemoon-i18n-vi             28.9.2-1             28.9.3-1
                 palemoon-i18n-zh-cn             28.9.2-1             28.9.3-1
                 palemoon-i18n-zh-tw             28.9.2-1             28.9.3-1
      plasma-browser-integration-git5.18.80.r1086.g64a63f2b-15.18.80.r1087.g811ae0dd-1
                  plasma-desktop-git5.18.80.r7592.g1d557e8a7-15.18.80.r7597.geeab79954-1
                plasma-framework-git5.70.0.r15423.g68d5995c6-15.70.0.r15425.g1bc004e5c-1
                       plasma-nm-git5.18.80.r2861.gbe3eaeef-15.18.80.r2863.g7c915638-1
                      plasma-sdk-git5.18.80.r2169.g2b7106b-15.18.80.r2170.g9010d95-1
     plasma-workspace-wallpapers-git5.18.80.r194.gcfd156e-15.18.80.r199.gf9d6a73-1
                      powerdevil-git5.18.80.r2271.g45dd7bbf-15.18.80.r2272.gaa60c4f6-1
                         purpose-git5.70.0.r754.g095ed6b-15.70.0.r756.g8cd6cca-1
                 deepin-desktop-base                    -       3:2019.07.10-1
              linux54-rt-ndiswrapper                    -               1.63-1
                      qgnomeplatform                    -   0.6.0+8+gd4277c9-1


:: Different sync package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-08           2020-05-11
-------------------------------------------------------------------------------
               aarch64-linux-gnu-gcc              9.3.0-1             10.1.0-1
                             acme.sh              2.8.5-1              2.8.6-1
                               acorn            1:7.1.1-1            1:7.2.0-1
                                acpi                1.7-2                1.7-3
                          aliyun-cli             3.0.37-2             3.0.42-1
                             amsynth              1.9.0-1             1.10.0-1
                                anki             2.1.23-1             2.1.26-1
                        ansible-lint              4.2.0-1              4.2.0-3
                                 apm              2.4.5-2              2.5.0-1
                          arch-audit             0.1.15-1             0.1.15-2
                     archlinux-repro           20200502-1           20200507-1
                               aria2             1.35.0-1             1.35.0-2
                               ascii               3.18-1               3.18-2
                                atom             1.45.0-1             1.46.0-1
                          autocutsel             0.10.0-2             0.10.0-3
                         baidupcs-go              3.6.2-1              3.6.2-2
                bash-language-server             1.13.1-2             1.14.0-1
                                 bat             0.13.0-1             0.15.0-1
                              batctl             2020.0-1             2020.1-1
                              bemenu              0.3.0-3              0.4.0-1
                             benzene           20130630-1           20130630-2
                            binaryen               1:91-1               1:93-1
                            bonnie++             1.97.3-1             1.97.3-2
                          bsequencer              1.2.0-2              1.4.0-1
                               buddy                2.4-3                2.4-4
                               c-xsc              2.5.4-1              2.5.4-2
                             calibre             4.14.0-2             4.15.0-2
                      calibre-common             4.14.0-2             4.15.0-2
                     calibre-python3             4.14.0-2             4.15.0-2
                            capstone              4.0.1-3              4.0.2-1
                             certbot              1.3.0-1              1.4.0-1
                      certbot-apache              1.3.0-1              1.4.0-1
              certbot-dns-cloudflare              1.3.0-1              1.4.0-1
                certbot-dns-cloudxns              1.3.0-1              1.4.0-1
            certbot-dns-digitalocean              1.3.0-1              1.4.0-1
                certbot-dns-dnsimple              1.3.0-1              1.4.0-1
             certbot-dns-dnsmadeeasy              1.3.0-1              1.4.0-1
                  certbot-dns-gehirn              1.3.0-1              1.4.0-1
                  certbot-dns-google              1.3.0-1              1.4.0-1
                  certbot-dns-linode              1.3.0-1              1.4.0-1
                  certbot-dns-luadns              1.3.0-1              1.4.0-1
                   certbot-dns-nsone              1.3.0-1              1.4.0-1
                     certbot-dns-ovh              1.3.0-1              1.4.0-1
                 certbot-dns-rfc2136              1.3.0-1              1.4.0-1
                 certbot-dns-route53              1.3.0-1              1.4.0-1
             certbot-dns-sakuracloud              1.3.0-1              1.4.0-1
                       certbot-nginx              1.3.0-1              1.4.0-1
                               cgrep            6.6.32-23            6.6.32-24
                             chezmoi              1.8.0-1              1.8.1-1
                              chrony                3.5-2                3.5-3
                               chuck            1.4.0.0-3            1.4.0.1-1
                            conflict           20150705-3           20150705-4
                              coturn            4.5.1.1-8            4.5.1.2-1
                             coxeter       git.20180226-2       git.20180226-3
                                croc              8.0.9-1             8.0.10-1
                             cryptol            2.8.0-106            2.8.0-108
                               darcs             2.14.3-1             2.14.4-1
                           darktable            2:3.0.2-1            2:3.0.2-2
                                dart              2.7.2-1              2.7.4-1
                             dbeaver              7.0.3-1              7.0.4-1
                          deepin-api              5.0.0-4           5.1.11.1-1
                   deepin-boot-maker              5.0.1-1              5.4.8-1
                   deepin-calculator              5.0.1-1              5.5.9-1
                     deepin-calendar              5.0.1-1              5.6.2-1
                        deepin-clone              5.0.1-1              5.0.3-1
               deepin-control-center              5.0.0-1            5.1.0.5-1
                       deepin-daemon              5.0.0-4            5.9.4.2-1
                 deepin-desktop-base       2:2019.07.10-1     2:2020.04.12.2-1
              deepin-desktop-schemas             3.13.9-1         5.4.0099.0-1
                         deepin-dock              5.0.0-6            5.1.0.8-1
                         deepin-draw              1.0.0-2           5.8.0.15-2
                       deepin-editor            1.2.6.4-1              5.6.7-2
                 deepin-file-manager            1:5.0.0-6         1:5.1.1.25-1
                   deepin-icon-theme           15.12.71-1         2020.05.09-1
                 deepin-image-viewer              5.0.0-1            5.6.3.2-1
                         deepin-kwin              0.1.0-8           5.0.14.1-1
                     deepin-launcher              5.0.0-1         5.1.0099.0-1
                         deepin-menu              3.4.8-1              5.0.1-1
                        deepin-movie            1:5.0.0-2         1:5.7.6.29-1
                        deepin-music              5.0.1-3            6.0.1.8-1
                deepin-network-utils              5.0.1-1            5.1.0.0-1
                       deepin-picker              5.0.1-1              5.0.6-1
                 deepin-polkit-agent              5.0.0-1              5.1.0-1
              deepin-qt-dbus-factory              5.0.1-6            5.1.0.0-1
               deepin-qt5dxcb-plugin              5.0.1-6             5.0.11-1
               deepin-qt5integration             5.0.0-10              5.1.0-1
              deepin-screen-recorder              5.0.0-2           5.8.0.11-1
                   deepin-screenshot              5.0.0-2                    -
                   deepin-session-ui              5.0.0-1         5.1.0099.4-1
              deepin-shortcut-viewer              5.0.0-1              5.0.2-1
                  deepin-sound-theme            15.10.3-1            15.10.4-1
               deepin-system-monitor              5.0.0-3              5.6.1-1
                     deepin-terminal              5.0.0-1            5.0.4.1-1
               deepin-voice-recorder              5.0.0-1                    -
            deepin-wallpapers-plasma             5.13.4-1             5.18.5-1
                                 dfc              3.1.1-1              3.1.1-2
                               dhall            1.31.1-19             1.32.0-1
                          dhall-bash            1.0.29-23             1.0.30-2
                          dhall-json             1.6.3-23              1.6.4-1
                          disomaster              5.0.0-1              5.0.1-1
                         dns-lexicon             3.3.20-1             3.3.22-2
                      dns-over-https              2.2.1-2              2.2.1-3
                              dsniff             2.4b1-27             2.4b1-28
                             dtkcore            1:2.1.1-2            1:5.2.0-2
                           dtkwidget              2.1.1-6              5.2.0-1
                               dtkwm             2.0.12-6             2.0.12-7
                                dune              2.3.1-1              2.5.1-1
                            electron              8.2.5-1              8.2.5-2
                           electron4             4.2.12-5             4.2.12-6
                           electron5             5.0.13-4             5.0.13-5
                           electron6              6.1.9-4              6.1.9-5
                           electron7             7.1.14-4             7.1.14-5
                              emovix              0.9.0-7              0.9.0-8
                              erlang             22.2.7-1               22.3-1
                         erlang-docs               22.2-1               22.3-1
                          erlang-nox             22.2.7-1               22.3-1
                     erlang-unixodbc             22.2.7-1               22.3-1
                              eslint              6.8.0-1              7.0.0-1
                             fastjet              3.3.3-1              3.3.4-1
                              faudio              20.04-1              20.05-1
                               faust             2.20.2-4             2.20.2-5
                               fbida               2.14-1               2.14-2
                              fcitx5     0.0.0.20200428-1     0.0.0.20200509-3
                        fcitx5-anthy     0.0.0.20200424-1     0.0.0.20200509-2
                      fcitx5-chewing     0.0.0.20200325-1     0.0.0.20200509-1
               fcitx5-chinese-addons     0.0.0.20200428-1     0.0.0.20200509-2
                          fcitx5-gtk     0.0.0.20200402-1     0.0.0.20200509-1
                       fcitx5-hangul     0.0.0.20200325-1     0.0.0.20200509-1
                           fcitx5-qt     0.0.0.20200428-1     0.0.0.20200509-1
                         fcitx5-rime     0.0.0.20200501-1     0.0.0.20200509-1
                       fcitx5-unikey     0.0.0.20200404-1     0.0.0.20200509-1
           firefox-developer-edition             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-ach             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-af             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-an             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ar             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-ast             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-az             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-be             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-bg             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-bn             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-br             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-bs             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ca             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-ca-valencia       76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-cak             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-cs             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-cy             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-da             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-de             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-dsb             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-el             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-en-ca             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-en-gb             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-en-us             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-eo             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-es-ar             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-es-cl             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-es-es             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-es-mx             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-et             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-eu             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-fa             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ff             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-fi             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-fr             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-fy-nl             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-ga-ie             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-gd             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-gl             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-gn             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-gu-in             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-he             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-hi-in             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-hr             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-hsb             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-hu             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-hy-am             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ia             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-id             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-is             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-it             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ja             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ka             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-kab             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-kk             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-km             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-kn             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ko             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-lij             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-lt             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-lv             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-mk             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-mr             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ms             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-my             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-nb-no             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-ne-np             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-nl             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-nn-no             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-oc             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-pa-in             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-pl             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-pt-br             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-pt-pt             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-rm             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ro             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ru             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-si             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-sk             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-sl             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-son             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-sq             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-sr             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-sv-se             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ta             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-te             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-th             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-tl             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-tr             76.0b8-1             77.0b3-1
  firefox-developer-edition-i18n-trs             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-uk             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-ur             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-uz             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-vi             76.0b8-1             77.0b3-1
   firefox-developer-edition-i18n-xh             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-zh-cn             76.0b8-1             77.0b3-1
firefox-developer-edition-i18n-zh-tw             76.0b8-1             77.0b3-1
              firefox-tree-style-tab              3.5.3-1              3.5.4-1
                                fish              3.1.1-1              3.1.2-1
                               flite                2.1-1                2.1-2
               freepats-general-midi           20200405-1           20200508-1
                             freerdp            2:2.0.0-3            2:2.1.0-1
                        freewheeling              0.6.6-1              0.6.6-2
                             gendesk              1.0.5-1              1.0.5-2
                                gfan              0.6.2-1              0.6.2-2
                           git-annex         8.20200501-2         8.20200501-3
                           git-crypt              0.6.0-3              0.6.0-4
                             git-lfs             2.10.0-2             2.11.0-1
                          git-repair        1.20200102-75         1.20200504-1
                              gitlab            12.10.2-1            12.10.2-2
                              glider              0.9.3-1             0.10.0-2
                              gnunet             0.12.2-1             0.12.2-2
                               gnurl             7.69.1-1             7.69.1-2
                          go-bindata              3.5.0-1              3.5.2-1
                           gocryptfs              1.7.1-2              1.8.0-1
                   golang-deepin-lib              5.0.0-1              5.4.5-1
golang-github-linuxdeepin-go-dbus-factory         0.9.0-3              1.6.4-1
golang-github-linuxdeepin-go-x11-client           0.4.1-1              0.6.0-1
                               gsoap            2.8.101-1            2.8.102-1
                            hashdeep                4.4-5                4.4-6
                  haskell-aeson-diff           1.1.0.8-95           1.1.0.8-97
                  haskell-aeson-yaml           1.0.6.0-24           1.0.6.0-25
                         haskell-bz2           1.0.0.2-21            1.0.0.3-1
           haskell-ghc-lib-parser-ex           8.10.0.3-1           8.10.0.4-1
                     haskell-githash           0.1.4.0-15           0.1.4.0-16
                      haskell-hakyll          4.13.3.0-14          4.13.3.0-16
                    haskell-hopenpgp             2.9.4-69             2.9.4-71
                       haskell-hpack           0.33.0-118           0.33.0-119
                       haskell-ipynb            0.1.0.1-1            0.1.0.1-3
                    haskell-mustache             2.3.1-89             2.3.1-90
                      haskell-nettle             0.3.0-70             0.3.0-71
             haskell-optparse-simple          0.1.1.2-182          0.1.1.2-183
                      haskell-pantry           0.4.0.1-38           0.4.0.1-39
                         haskell-sbv               8.6-65               8.6-67
                        haskell-yaml          0.11.3.0-18           0.11.4.0-1
                       haskell-yesod           1.6.0.1-90           1.6.0.1-91
                                helm              3.2.0-1              3.2.1-1
                               hivex             1.3.18-4             1.3.18-5
                         hledger-web            1.17.1-34            1.17.1-35
                               hlint            2.2.11-47            2.2.11-49
                      hopenpgp-tools            0.23.1-30            0.23.1-33
                                hugo             0.69.2-1             0.70.0-1
                              hwinfo              21.70-1              21.70-2
               intel-compute-runtime        20.17.16650-1        20.18.16699-1
             intel-graphics-compiler         1:1.0.3864-1         1:1.0.3899-1
     intellij-idea-community-edition           2:2020.1-1         2:2020.1.1-1
                          inter-font               3.12-1               3.13-1
                     java-commons-io                2.6-1                2.6-2
                             jenkins              2.233-1              2.235-1
                   jupyterlab_server              1.1.1-2              1.1.3-1
                                 jwm              2.3.7-1              2.3.7-2
                          kcm-fcitx5     0.0.0.20200428-1     0.0.0.20200509-1
                             keepass               2.44-1               2.45-1
                            keycloak              9.0.3-2             10.0.0-1
                                kim4              0.9.5-7                    -
                               kitty             0.17.3-1             0.17.4-1
                      kitty-terminfo             0.17.3-1             0.17.4-1
                              kotlin             1.3.70-1             1.3.72-1
                      libcurl-gnutls             7.70.0-1             7.70.0-2
                        libfilezilla             0.19.3-1             0.19.3-2
                            libhandy             0.0.13-1             0.0.13-2
                              libime     0.0.0.20200425-1     0.0.0.20200509-1
                            libmupdf             1.16.1-3             1.17.0-1
                              libolm              3.1.4-2              3.1.4-3
                          librdkafka              1.4.0-1              1.4.2-2
                            libressl              3.1.0-1              3.1.1-1
                             librime            1:1.5.3-6            1:1.5.3-7
                            librtmp0                2.4-4                2.4-5
                        libsidplayfp              2.0.1-1              2.0.2-1
                             libvips              8.9.0-3              8.9.2-1
                             liteide               36.3-2               37.1-1
                                llpp                 31-4    31.r41.g233b1a0-1
                             lockdev          1.0.3_1.6-5          1.0.3_1.6-6
                      lua-filesystem            1.7.0.2-1              1.8.0-1
                         lua51-bitop              1.0.2-8              1.0.2-9
                    lua51-filesystem            1.7.0.2-1              1.8.0-1
                         lua52-bitop              1.0.2-8              1.0.2-9
                    lua52-filesystem            1.7.0.2-1              1.8.0-1
                                 lxd              4.0.1-1                4.1-1
                             mailman             2.1.32-1             2.1.33-1
                     man-pages-zh_cn            1.6.3.3-1            1.6.3.4-1
                     man-pages-zh_tw            1.6.3.3-1            1.6.3.4-1
                   massif-visualizer              0.7.0-2              0.7.0-3
               matrix-appservice-irc             0.17.0-1             0.17.1-1
                      matrix-synapse             1.11.0-1             1.12.4-1
                                mcqd              1.0.0-1              1.0.0-2
                             memconf               3.14-1               3.15-1
                          metasploit             5.0.86-1             5.0.88-1
                             mimetic              0.9.8-1              0.9.8-2
                               minio         2020.03.06-1         2020.05.06-1
                        minio-client         2019.12.17-2         2020.05.06-1
                              minted                2.5-1                2.5-2
                            mldonkey              3.1.6-2              3.1.6-3
                             moosefs            3.0.111-1            3.0.112-1
                     multipath-tools              0.8.3-3              0.8.4-1
                               mupdf             1.16.1-3             1.17.0-1
                            mupdf-gl             1.16.1-3             1.17.0-1
                         mupdf-tools             1.16.1-3             1.17.0-1
               netfilter-fullconenat       r73.0cf3b48-15       r73.0cf3b48-16
             nextcloud-app-bookmarks            1:3.0.0-1            1:3.0.4-1
                  nextcloud-app-deck            1:0.8.2-1            1:1.0.0-1
                  nextcloud-app-mail              1.3.3-1              1.3.4-1
                  nextcloud-app-news             14.1.6-1             14.1.7-1
                 nextcloud-app-notes              3.2.0-1              3.3.0-1
                              nodejs             14.1.0-2             14.2.0-1
                                 npm             6.14.4-1             6.14.5-1
                   npm-check-updates              4.1.2-1              5.0.0-1
                           oniguruma              6.9.5-1         6.9.5_rev1-1
                                opam              2.0.6-2              2.0.7-1
                             opendht           1:1.10.1-5           1:1.10.1-6
                           pam_mount               2.16-4               2.16-5
                              pandoc           2.9.2.1-29           2.9.2.1-31
                     pandoc-citeproc              0.17-90              0.17-92
                     pandoc-crossref           0.3.6.2-85           0.3.6.2-87
                               pbpst              1.4.1-1              1.4.1-2
                                  pd             0.50.2-2             0.50.2-3
              perl-scalar-list-utils               1.54-1               1.55-1
                            pgadmin4               4.20-1               4.21-1
                              picard              2.3.1-1              2.3.2-1
                               picom                  8-1                  8-2
                                plib              1.8.5-8                    -
                                po4a               0.57-1               0.58-1
                              polipo              1.1.1-3              1.1.1-4
                            powertop               2.11-1               2.12-1
                 profile-sync-daemon               6.38-1               6.40-1
                            pstreams              1.0.1-1                    -
                          pulsemixer              1.5.0-2              1.5.1-1
           pycharm-community-edition           2019.2.3-1           2020.1.1-1
                         python-acme              1.3.0-1              1.4.0-1
                 python-aioitertools              0.6.1-1              0.7.0-1
                      python-awkward            0.12.20-1            0.12.21-1
           python-aws-sam-translator             1.22.0-1             1.23.0-1
                       python-bleach              3.1.3-1              3.1.5-1
                      python-blinker                1.4-6                1.4-7
                    python-braintree              4.0.0-1              4.1.0-1
                     python-capstone              4.0.1-3              4.0.2-1
                       python-daemon              2.2.4-3              2.2.4-4
                          python-ddt              1.3.1-1              1.4.0-1
                      python-dropbox             10.1.1-1             10.1.2-1
                python-elasticsearch              7.6.0-1              7.6.0-2
                       python-fields              5.0.0-6              5.0.0-7
                        python-flask              1.1.2-1              1.1.2-2
                   python-flask-mail              0.9.1-3              0.9.1-4
               python-flask-paranoid                0.2-3                0.2-4
              python-flask-principal              0.4.0-3              0.4.0-4
                 python-flask-script              2.0.6-4              2.0.6-5
                    python-fonttools              4.8.1-1              4.9.0-1
                   python-hypothesis             5.10.4-1             5.11.0-1
                    python-icalendar              4.0.5-1              4.0.6-1
                 python-itsdangerous              1.1.0-3              1.1.0-4
               python-logilab-common              1.6.0-1              1.6.1-1
                        python-mamba               0.10-4             0.11.0-1
                  python-marshmallow              3.5.2-1              3.6.0-1
                          python-olm              3.1.4-2              3.1.4-3
                 python-phonenumbers             8.12.2-1             8.12.3-1
                     python-pwntools              4.0.1-3              4.1.0-1
                   python-py-cpuinfo              5.0.0-4              5.0.0-5
                       python-pyface              6.1.2-3              7.0.0-1
                        python-pygal            1:2.4.0-4            1:2.4.0-5
                       python-pyglet              1.5.4-2              1.5.5-1
                       python-pytest              5.4.1-1              5.4.2-1
             python-pytest-benchmark              3.2.3-1              3.2.3-2
                python-pytest-pylint             0.15.1-1             0.16.0-1
                python-requests-mock              1.7.0-4              1.8.0-1
                      python-seaborn             0.10.0-1             0.10.1-1
                       python-semver              2.9.1-1             2.10.0-1
                   python-tensorflow           2.2.0rc3-2              2.2.0-1
              python-tensorflow-cuda           2.2.0rc3-2              2.2.0-1
               python-tensorflow-opt           2.2.0rc3-2              2.2.0-1
          python-tensorflow-opt-cuda           2.2.0rc3-2              2.2.0-1
                       python-traits              5.2.0-1              6.0.0-1
                     python-traitsui              6.1.3-3              7.0.0-1
               python-update-checker               0.16-3               0.17-1
                       python-uproot             3.11.4-1             3.11.5-1
                  python-uproot-docs             3.11.4-1             3.11.5-1
               python-uproot-methods              0.7.3-2              0.7.4-1
                     python-werkzeug              1.0.1-1              1.0.1-2
                       python-yaspin             0.16.0-1             0.17.0-1
                     python2-blinker                1.4-6                    -
                      python2-daemon              2.2.4-3                    -
               python2-elasticsearch              7.6.0-1                    -
                      python2-fields              5.0.0-6              5.0.0-7
                       python2-flask              1.1.2-1                    -
                python2-itsdangerous              1.1.0-3                    -
                  python2-py-cpuinfo              5.0.0-4                    -
                       python2-pygal            1:2.4.0-4                    -
            python2-pytest-benchmark              3.2.3-1                    -
                python2-subprocess32              3.5.3-1                    -
                    python2-werkzeug              1.0.1-1                    -
                                 qiv              2.3.2-1              2.3.2-2
                                qmmp              1.3.7-1              1.4.0-1
                            qrupdate              1.1.2-3              1.1.2-4
                                qtox             1.17.2-1             1.17.2-2
                            qtractor             0.9.13-1             0.9.14-1
                         qutebrowser             1.11.0-1             1.11.1-1
                               qvkbd        git20170102-1        git20170102-2
                        r2ghidra-dec       r167.d8a184c-1              4.4.0-1
                             radare2              4.3.1-2              4.4.0-1
                      radare2-cutter           1:1.10.2-3           1:1.10.3-1
                              radcli             1.2.11-2             1.2.11-3
              rapid-photo-downloader             0.9.23-1             0.9.24-1
                              rclone             1.51.0-3             1.51.0-4
                            rdesktop              1.9.0-1              1.9.0-2
               react-native-debugger             0.11.1-1             0.11.3-1
                      rime-cantonese     0.0.0.20200502-1     0.0.0.20200510-1
                        riot-desktop             1.5.15-1              1.6.0-2
                            riot-web             1.5.15-1              1.6.0-2
                             ripgrep             12.0.1-1             12.1.0-1
              sage-data-polytopes_db           20170220-1           20170220-2
                                 sbt            1:1.3.9-1           1:1.3.10-1
                                  sd              0.7.4-1              0.7.5-1
                  shadowsocks-deepin              1.2.2-1                    -
                          shellcheck              0.7.1-8             0.7.1-10
                               shfmt              3.1.0-1              3.1.1-1
                         simple-scan             3.36.2-1           3.36.2.1-1
                            singular              4.1.3-1           4.1.3.p1-1
                            skanlite            2.1.0.1-1            2.1.0.1-2
                           sleuthkit              4.8.0-1              4.9.0-1
                                smem                1.5-1                1.5-2
                               smlnj             110.95-1             110.96-1
                            solidity              0.6.6-1              0.6.7-1
                               squid               4.10-1               4.10-2
                              ssdeep             2.14.1-1             2.14.1-2
                               stack              2.3.1-1              2.3.1-2
                            startdde              5.0.1-3            5.3.0.1-2
                             sthttpd             2.27.1-1             2.27.1-2
                         sunxi-tools              1.4.2-2              1.4.2-3
                            supermin             5.1.20-4              5.2.0-2
                           syncthing              1.4.2-1              1.5.0-1
                  syncthing-relaysrv              1.4.2-1              1.5.0-1
                              sysdig             0.26.6-3             0.26.7-1
                    telegram-desktop              2.1.1-1              2.1.4-1
                             tellico              3.2.3-1                3.3-1
                          tensorflow           2.2.0rc3-2              2.2.0-1
                     tensorflow-cuda           2.2.0rc3-2              2.2.0-1
                      tensorflow-opt           2.2.0rc3-2              2.2.0-1
                 tensorflow-opt-cuda           2.2.0rc3-2              2.2.0-1
                          testssl.sh              3.0.1-1              3.0.2-1
                            tigervnc             1.10.1-1             1.10.1-2
                               tilda              1.5.0-1              1.5.2-1
                               tokei             11.1.0-1             11.1.1-1
                             toxcore           1:0.2.11-1           1:0.2.12-1
                               toxic              0.8.3-2              0.8.3-3
                  ttf-jetbrains-mono              1.0.5-1              1.0.6-1
                          ttf-roboto              2.138-1              2.138-2
                              tuntox              0.0.9-1              0.0.9-2
                           typespeed              0.6.5-7              0.6.5-8
                         udisks2-qt5              5.0.0-1              5.0.3-1
                  ukui-window-switch              2.0.2-1              2.0.3-1
                            urlwatch               2.18-2               2.18-3
                                utox             0.17.2-1             0.17.2-2
                               v2ray             4.23.1-1             4.23.1-2
         v2ray-domain-list-community       202005041039-1       202005092152-1
                         v2ray-geoip       202004290001-1       202005060001-1
                             vagrant              2.2.7-5              2.2.8-1
                              viking                1.8-2                1.8-3
                        vim-nerdtree              6.5.0-1              6.6.1-1
                        wire-desktop          3.16.2923-1          3.17.2924-1
                      wishbone-utils              0.6.9-1             0.6.17-1
                           wordpress                5.4-1              5.4.1-1
                          xcb-imdkit     0.0.0.20200419-1     0.0.0.20200509-1
                                 xdo              0.5.7-1              0.5.7-2
                              xrootd             4.11.3-1             4.12.0-1
                          youtube-dl         2020.05.03-1         2020.05.08-1
                               zcash              2.1.2-1            2.1.2_3-1
                                zile             2.4.14-1             2.4.14-2
                       acme-redirect                    -              0.2.0-1
                      bemenu-ncurses                    -              0.4.0-1
                      bemenu-wlroots                    -              0.4.0-1
                          bemenu-x11                    -              0.4.0-1
                         cargo-watch                    -              7.3.0-2
                             dbxtool                    -                  7-1
                        deepin-album                    -           5.6.9.13-1
                deepin-session-shell                    -         5.0.0098.0-2
                              dtkgui                    -              5.2.0-1
                              global                    -              6.6.4-1
                             oscpack                    -              1.1.0-1
                         staticcheck                    -           2020.1.3-1


:: Different overlay package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-08           2020-05-11
-------------------------------------------------------------------------------
                              json-c             0.14-2.1                    -
                            linux414           4.14.178-1           4.14.179-1
                    linux414-headers           4.14.178-1           4.14.179-1
                            linux419           4.19.120-1           4.19.121-1
                    linux419-headers           4.19.120-1           4.19.121-1
                             linux44            4.4.221-1            4.4.222-1
                     linux44-headers            4.4.221-1            4.4.222-1
                             linux49            4.9.221-1            4.9.222-1
                     linux49-headers            4.9.221-1            4.9.222-1
                             linux54             5.4.38-1             5.4.39-1
                     linux54-headers             5.4.38-1             5.4.39-1
                             linux56             5.6.10-3             5.6.11-1
                     linux56-headers             5.6.10-3             5.6.11-1
                     manjaro-release               20.0-1             20.0.1-1
                             systemd              244.4-1              245.5-2
                        systemd-libs              244.4-1              245.5-2
                  systemd-resolvconf              244.4-1              245.5-2
                  systemd-sysvcompat              244.4-1              245.5-2


:: Different sync package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-08           2020-05-11
-------------------------------------------------------------------------------
                                 acl             2.2.53-2             2.2.53-3
                              argon2           20190702-2           20190702-3
                                attr             2.4.48-2             2.4.48-3
                          cryptsetup              2.3.2-1              2.3.2-2
                       device-mapper           2.02.187-1           2.02.187-2
                           e2fsprogs             1.45.6-1             1.45.6-2
                              gnutls             3.6.13-1             3.6.13-2
                               gpgme             1.13.1-3             1.13.1-5
                              json-c               0.14-2               0.14-4
                            keyutils              1.6.1-3              1.6.1-4
                              libidn               1.35-2                    -
                       libmicrohttpd             0.9.70-2             0.9.70-3
                          libp11-kit            0.23.20-4            0.23.20-5
                                lvm2           2.02.187-1           2.02.187-2
                              nettle              3.5.1-2                3.6-1
                             p11-kit            0.23.20-4            0.23.20-5
                        python-gpgme             1.13.1-3             1.13.1-5
                              qgpgme             1.13.1-3             1.13.1-5


:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-08           2020-05-11
-------------------------------------------------------------------------------
                           calamares           3.2.23.2-3           3.2.23.2-1
               calamares-git 3.2.24.r7826.fb8e69ca6-3 3.2.24.r7826.fb8e69ca6-1
                linux316-ndiswrapper              1.62-17               1.63-1
                  linux414-acpi_call            1.1.0-150            1.1.0-151
                   linux414-bbswitch              0.8-150              0.8-151
                linux414-broadcom-wl     6.30.223.271-150     6.30.223.271-151
                linux414-ndiswrapper              1.62-45               1.63-1
               linux414-nvidia-340xx           340.108-19           340.108-20
               linux414-nvidia-390xx           390.132-27           390.132-28
               linux414-nvidia-418xx           418.113-24           418.113-25
               linux414-nvidia-430xx            430.64-25            430.64-26
               linux414-nvidia-435xx            435.21-35            435.21-36
               linux414-nvidia-440xx             440.82-4             440.82-5
                   linux414-nvidiabl             0.88-150             0.88-151
                      linux414-r8168           8.048.02-2           8.048.02-3
                  linux414-rt3562sta       2.4.1.1_r4-150       2.4.1.1_r4-151
                   linux414-tp_smapi              0.43-42              0.43-43
                linux414-vhba-module          20200106-13          20200106-14
    linux414-virtualbox-host-modules              6.1.6-3              6.1.6-4
                        linux414-zfs             0.8.3-12             0.8.3-13
                  linux419-acpi_call            1.1.0-110            1.1.0-111
                   linux419-bbswitch              0.8-110              0.8-111
                linux419-broadcom-wl     6.30.223.271-109     6.30.223.271-110
                linux419-ndiswrapper              1.62-59               1.63-1
               linux419-nvidia-340xx           340.108-30           340.108-31
               linux419-nvidia-390xx           390.132-39           390.132-40
               linux419-nvidia-418xx           418.113-38           418.113-39
               linux419-nvidia-430xx            430.64-38            430.64-39
               linux419-nvidia-435xx            435.21-49            435.21-50
               linux419-nvidia-440xx             440.82-7             440.82-8
                   linux419-nvidiabl             0.88-109             0.88-110
                      linux419-r8168           8.048.02-3           8.048.02-4
                  linux419-rtl8723bu           20200405-6           20200405-7
                   linux419-tp_smapi              0.43-59              0.43-60
                linux419-vhba-module          20200106-24          20200106-25
   linux419-virtualbox-guest-modules              6.1.6-6              6.1.6-7
    linux419-virtualbox-host-modules              6.1.6-6              6.1.6-7
                        linux419-zfs             0.8.3-23             0.8.3-24
                   linux44-acpi_call            1.1.0-152            1.1.0-153
                    linux44-bbswitch              0.8-152              0.8-153
                 linux44-broadcom-wl     6.30.223.271-122     6.30.223.271-123
                 linux44-ndiswrapper              1.62-34               1.63-1
                linux44-nvidia-340xx           340.108-16           340.108-17
                linux44-nvidia-390xx           390.132-22           390.132-23
                linux44-nvidia-418xx           418.113-21           418.113-22
                linux44-nvidia-430xx            430.64-20            430.64-21
                linux44-nvidia-435xx            435.21-22            435.21-23
                linux44-nvidia-440xx             440.82-4             440.82-5
                    linux44-nvidiabl             0.88-152             0.88-153
                       linux44-r8168           8.048.02-2           8.048.02-3
                   linux44-rt3562sta       2.4.1.1_r4-109       2.4.1.1_r4-110
                    linux44-tp_smapi              0.43-31              0.43-32
                 linux44-vhba-module          20200106-13          20200106-14
     linux44-virtualbox-host-modules              6.1.6-3              6.1.6-4
                         linux44-zfs             0.8.3-12             0.8.3-13
                   linux49-acpi_call            1.1.0-166            1.1.0-167
                    linux49-bbswitch              0.8-166              0.8-167
                 linux49-broadcom-wl     6.30.223.271-166     6.30.223.271-167
                 linux49-ndiswrapper              1.62-36               1.63-1
                linux49-nvidia-340xx           340.108-16           340.108-17
                linux49-nvidia-390xx           390.132-23           390.132-24
                linux49-nvidia-418xx           418.113-22           418.113-23
                linux49-nvidia-430xx            430.64-21            430.64-22
                linux49-nvidia-435xx            435.21-28            435.21-29
                linux49-nvidia-440xx             440.82-4             440.82-5
                    linux49-nvidiabl             0.88-166             0.88-167
                       linux49-r8168           8.048.02-2           8.048.02-3
                   linux49-rt3562sta       2.4.1.1_r4-150       2.4.1.1_r4-151
                    linux49-tp_smapi              0.43-34              0.43-35
                 linux49-vhba-module          20200106-13          20200106-14
     linux49-virtualbox-host-modules              6.1.6-3              6.1.6-4
                         linux49-zfs             0.8.3-12             0.8.3-13
                   linux54-acpi_call             1.1.0-44             1.1.0-45
                    linux54-bbswitch               0.8-44               0.8-45
                 linux54-broadcom-wl      6.30.223.271-44      6.30.223.271-45
                 linux54-ndiswrapper              1.62-44               1.63-1
                linux54-nvidia-340xx           340.108-36           340.108-37
                linux54-nvidia-390xx           390.132-44           390.132-45
                linux54-nvidia-418xx           418.113-44           418.113-45
                linux54-nvidia-430xx            430.64-44            430.64-45
                linux54-nvidia-435xx            435.21-44            435.21-45
                linux54-nvidia-440xx            440.82-11            440.82-12
                    linux54-nvidiabl              0.88-44              0.88-45
                       linux54-r8168           8.048.02-4           8.048.02-5
                   linux54-rtl8723bu           20200405-8           20200405-9
                    linux54-tp_smapi              0.43-44              0.43-45
                 linux54-vhba-module          20200106-29          20200106-30
    linux54-virtualbox-guest-modules              6.1.6-8              6.1.6-9
     linux54-virtualbox-host-modules              6.1.6-8              6.1.6-9
                         linux54-zfs             0.8.3-28             0.8.3-29
                 linux55-ndiswrapper              1.62-23               1.63-1
                   linux56-acpi_call             1.1.0-14             1.1.0-15
                    linux56-bbswitch               0.8-14               0.8-15
                 linux56-broadcom-wl      6.30.223.271-14      6.30.223.271-15
                 linux56-ndiswrapper              1.62-14               1.63-1
                linux56-nvidia-340xx           340.108-14           340.108-15
                linux56-nvidia-390xx           390.132-14           390.132-15
                linux56-nvidia-418xx           418.113-14           418.113-15
                linux56-nvidia-430xx            430.64-14            430.64-15
                linux56-nvidia-435xx            435.21-14            435.21-15
                linux56-nvidia-440xx            440.82-12            440.82-13
                       linux56-r8168           8.048.02-6           8.048.02-7
                   linux56-rtl8723bu          20200405-14          20200405-15
                    linux56-tp_smapi              0.43-14              0.43-15
                 linux56-vhba-module          20200106-14          20200106-15
    linux56-virtualbox-guest-modules             6.1.6-10             6.1.6-11
     linux56-virtualbox-host-modules             6.1.6-10             6.1.6-11
                         linux56-zfs             0.8.3-14             0.8.3-15
                 linux57-ndiswrapper             1.62-0.7             1.63-0.1
                   manjaro-architect             0.9.30-1             0.9.32-1
          manjaro-architect-launcher             0.9.30-1             0.9.32-1
                           pamac-cli              9.4.2-1              9.5.0-1
                       pamac-cli-dev            9.5.0rc-3              9.5.0-1
                        pamac-common              9.4.2-1              9.5.0-1
                    pamac-common-dev            9.5.0rc-3              9.5.0-1
                pamac-flatpak-plugin              9.4.2-1              9.5.0-1
            pamac-flatpak-plugin-dev            9.5.0rc-3              9.5.0-1
             pamac-gnome-integration              9.4.2-1              9.5.0-1
         pamac-gnome-integration-dev            9.5.0rc-3              9.5.0-1
                           pamac-gtk              9.4.2-1              9.5.0-1
                       pamac-gtk-dev            9.5.0rc-3              9.5.0-1
                   pamac-snap-plugin              9.4.2-1              9.5.0-1
               pamac-snap-plugin-dev            9.5.0rc-3              9.5.0-1
             pamac-tray-appindicator              9.4.2-1              9.5.0-1
         pamac-tray-appindicator-dev            9.5.0rc-3              9.5.0-1
                         xorg-server             1.20.8-1             1.20.8-2
                  xorg-server-common             1.20.8-1             1.20.8-2
                   xorg-server-devel             1.20.8-1             1.20.8-2
                  xorg-server-xephyr             1.20.8-1             1.20.8-2
                   xorg-server-xnest             1.20.8-1             1.20.8-2
                    xorg-server-xvfb             1.20.8-1             1.20.8-2
                xorg-server-xwayland             1.20.8-1             1.20.8-2
                            pamac-qt                    -              0.3.1-2


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-08           2



Massive Python Survey Reveals Popularity of Linux and PyCharm, Just 10% Still Using Python 2
Sun, 10 May 2020 13:46:18 +0200
The Python Software Foundation and JetBrains collected over 24,000 responses for the third annual Python Developer's Survey. Among its findings: 59% said they used Python for data analysis, "followed by web development at 51%, and machine learning at 40%," reports ZDNet:
Other major applications of Python include DevOps and system administration (39%), programming web tools like crawlers (37%), software testing (31%), education (26%), software prototyping (25%), network programming (21%), desktop development (18%), computer graphics (14%), embedded system development (8%), game development (7%) and mobile development (6%). 

However, at 28%, web development remains the top purpose when respondents were asked what they used Python for the most. It is followed by data analysis (18%), machine learning (13%), and DevOps, and system administration (9%). 

Good news given that the final version of Python 2 was just released, the survey found that 90% are using Python 3, up from 84% in 2018. Of those still on Python 2, 45% are using it for web development, and 41% are using it for DevOps and system administration. PSF speculates that web development's dominance in Python 2 is because of legacy code... 
Some 68% of Python developers are building on Linux, followed by Windows at 48%, while macOS has a 29% share... 
The PyCharm integrated development environment (IDE) from JetBrains is once again the top IDE with a 33% share, followed by Microsoft's open-source cross-platform editor VS Code with a 24% share. 

Python adoption is often attributed to its moderate learning curve. The survey found that 44% of users have just two years' experience and 30% had three to five years' experience.






Read more of this story at Slashdot.


[Testing Update] 2020-05-09 - Kernels, Deepin v20, Browsers, Pamac 9.5rc1, KDE-git
Sat, 09 May 2020 12:03:29 +0200
Hello community,
Another testing branch update with some interesting updates for you!

1912×967

Get Gnome 20.0.1rc1 and help us finding missed bugs #stayhome, #staysave, #stayhealthy
Most of our Kernels got updated

KDE-git packages got updated

Deepin got updated to v20 series
Some of our browsers got updated: Firefox 76.0.1, Firefox-Dev 77.0b3, Palemoon 28.9.3


Pamac 9.5 got its release candidate release.
The usual upstream updates
If you like following latest Plasma development you may also like to check out our current version of manjaro-kde-dev, which we build on a regular basis against kde-git master packages. Also check out stable release of Manjaro Lysia 20.0! XFCE, KDE and Gnome
Upstream notice
Arch updated their default compression to zstd. We adopted to the same standard. More and more packages will have the zst extension from now on. If you get for what ever reason an error with ZSTD not supported as archive format you can do this:
sudo pacman -Syy
sudo pacman -S pacman-static
sudo pacman-static -Syyu

Our current supported kernels
linux316 3.16.83
linux44 4.4.222
linux49 4.9.222
linux414 4.14.179
linux419 4.19.121
linux54 5.4.39
linux55 5.5.19 EOL
linux56 5.6.11
linux57 5.7-rc4
linux54-rt 5.4.28_rt19
linux56-rt 5.6.10_rt5
Package Changes (Sat May 9 10:55:34 CEST 2020)


:: Different overlay package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-06           2020-05-09
-------------------------------------------------------------------------------
                          breeze-git5.18.80.r1984.g1a9dc381-15.18.80.r1988.g6283b3e0-1
      deepin-desktop-schemas-manjaro             3.13.9-1         5.4.0099.0-1
        deepin-file-manager-nomodule              5.0.0-5           5.1.1.25-1
                   deepin-wallpapers            2:1.7.5-2            2:1.7.7-1
                           downgrade              6.3.0-1              7.0.0-1
                             gtkhash                1.2-3                1.2-4
                        gtkhash-caja                1.2-3                1.2-4
                    gtkhash-nautilus                1.2-3                1.2-4
                        gtkhash-nemo                1.2-3                1.2-4
                      gtkhash-thunar                1.2-3                1.2-4
                                 jwm              2.3.7-1                    -
               kactivitymanagerd-git5.15.80.r1273.g50bde7c-15.15.80.r1274.g3bc86ea-1
                    kdeclarative-git5.70.0.r771.g66c82cd-15.70.0.r772.g9725a21-1
                      knetattach-git5.18.80.r7592.g1d557e8a7-15.18.80.r7596.g82e7a6b68-1
                  knotifications-git5.70.0.r528.g2012f67-15.70.0.r529.g9a13dd2-1
                     ksshaskpass-git5.18.80.r158.g54d2fa6-15.18.80.r159.g64d6c18-1
                       ksysguard-git5.18.80.r3242.g8e2603a6-15.18.80.r3244.gdbb0b515-1
                    libksysguard-git5.18.80.r1786.gd8e4677-15.18.80.r1789.gb1e9126-1
                    matcha-gtk-theme           20200408-1           20200505-1
                        palemoon-bin             28.9.2-1             28.9.3-1
                    palemoon-i18n-ar             28.9.2-1             28.9.3-1
                    palemoon-i18n-bg             28.9.2-1             28.9.3-1
                    palemoon-i18n-cs             28.9.2-1             28.9.3-1
                    palemoon-i18n-da             28.9.2-1             28.9.3-1
                    palemoon-i18n-de             28.9.2-1             28.9.3-1
                    palemoon-i18n-el             28.9.2-1             28.9.3-1
                 palemoon-i18n-en-gb             28.9.2-1             28.9.3-1
                 palemoon-i18n-es-ar             28.9.2-1             28.9.3-1
                 palemoon-i18n-es-es             28.9.2-1             28.9.3-1
                 palemoon-i18n-es-mx             28.9.2-1             28.9.3-1
                    palemoon-i18n-fi             28.9.2-1             28.9.3-1
                    palemoon-i18n-fr             28.9.2-1             28.9.3-1
                    palemoon-i18n-gl             28.9.2-1             28.9.3-1
                    palemoon-i18n-hr             28.9.2-1             28.9.3-1
                    palemoon-i18n-hu             28.9.2-1             28.9.3-1
                    palemoon-i18n-id             28.9.2-1             28.9.3-1
                    palemoon-i18n-is             28.9.2-1             28.9.3-1
                    palemoon-i18n-it             28.9.2-1             28.9.3-1
                    palemoon-i18n-ja             28.9.2-1             28.9.3-1
                    palemoon-i18n-kn             28.9.2-1             28.9.3-1
                    palemoon-i18n-ko             28.9.2-1             28.9.3-1
                    palemoon-i18n-nl             28.9.2-1             28.9.3-1
                    palemoon-i18n-pl             28.9.2-1             28.9.3-1
                 palemoon-i18n-pt-br             28.9.2-1             28.9.3-1
                 palemoon-i18n-pt-pt             28.9.2-1             28.9.3-1
                    palemoon-i18n-ro             28.9.2-1             28.9.3-1
                    palemoon-i18n-ru             28.9.2-1             28.9.3-1
                    palemoon-i18n-sk             28.9.2-1             28.9.3-1
                    palemoon-i18n-sl             28.9.2-1             28.9.3-1
                    palemoon-i18n-sr             28.9.2-1             28.9.3-1
                 palemoon-i18n-sv-se             28.9.2-1             28.9.3-1
                    palemoon-i18n-tl             28.9.2-1             28.9.3-1
                    palemoon-i18n-tr             28.9.2-1             28.9.3-1
                    palemoon-i18n-uk             28.9.2-1             28.9.3-1
                    palemoon-i18n-vi             28.9.2-1             28.9.3-1
                 palemoon-i18n-zh-cn             28.9.2-1             28.9.3-1
                 palemoon-i18n-zh-tw             28.9.2-1             28.9.3-1
                  plasma-desktop-git5.18.80.r7592.g1d557e8a7-15.18.80.r7596.g82e7a6b68-1
                plasma-framework-git5.70.0.r15423.g68d5995c6-15.70.0.r15425.g1bc004e5c-1
                       plasma-nm-git5.18.80.r2861.gbe3eaeef-15.18.80.r2862.g040a5c8c-1
                      plasma-sdk-git5.18.80.r2169.g2b7106b-15.18.80.r2170.g9010d95-1
     plasma-workspace-wallpapers-git5.18.80.r194.gcfd156e-15.18.80.r198.gff9dda6-1
                 deepin-desktop-base                    -       3:2019.07.10-1


:: Different sync package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-06           2020-05-09
-------------------------------------------------------------------------------
                             acme.sh              2.8.5-1              2.8.6-1
                                acpi                1.7-2                1.7-3
                             amsynth              1.9.0-1             1.10.0-1
                                 apm              2.4.5-2              2.5.0-1
                          arch-audit             0.1.15-1             0.1.15-2
                     archlinux-repro           20200502-1           20200507-1
                               aria2             1.35.0-1             1.35.0-2
                               ascii               3.18-1               3.18-2
                                atom             1.45.0-1             1.46.0-1
                          autocutsel             0.10.0-2             0.10.0-3
                bash-language-server             1.13.1-2             1.14.0-1
                                 bat             0.13.0-1             0.15.0-1
                              batctl             2020.0-1             2020.1-1
                              bemenu              0.3.0-3              0.4.0-1
                             benzene           20130630-1           20130630-2
                            binaryen               1:91-1               1:93-1
                            bonnie++             1.97.3-1             1.97.3-2
                          bsequencer              1.2.0-2              1.4.0-1
                               buddy                2.4-3                2.4-4
                               c-xsc              2.5.4-1              2.5.4-2
                             calibre             4.14.0-2             4.15.0-2
                      calibre-common             4.14.0-2             4.15.0-2
                     calibre-python3             4.14.0-2             4.15.0-2
                            capstone              4.0.1-3              4.0.2-1
                             certbot              1.3.0-1              1.4.0-1
                      certbot-apache              1.3.0-1              1.4.0-1
              certbot-dns-cloudflare              1.3.0-1              1.4.0-1
                certbot-dns-cloudxns              1.3.0-1              1.4.0-1
            certbot-dns-digitalocean              1.3.0-1              1.4.0-1
                certbot-dns-dnsimple              1.3.0-1              1.4.0-1
             certbot-dns-dnsmadeeasy              1.3.0-1              1.4.0-1
                  certbot-dns-gehirn              1.3.0-1              1.4.0-1
                  certbot-dns-google              1.3.0-1              1.4.0-1
                  certbot-dns-linode              1.3.0-1              1.4.0-1
                  certbot-dns-luadns              1.3.0-1              1.4.0-1
                   certbot-dns-nsone              1.3.0-1              1.4.0-1
                     certbot-dns-ovh              1.3.0-1              1.4.0-1
                 certbot-dns-rfc2136              1.3.0-1              1.4.0-1
                 certbot-dns-route53              1.3.0-1              1.4.0-1
             certbot-dns-sakuracloud              1.3.0-1              1.4.0-1
                       certbot-nginx              1.3.0-1              1.4.0-1
                               cgrep            6.6.32-23            6.6.32-24
                             chezmoi              1.8.0-1              1.8.1-1
                              chrony                3.5-2                3.5-3
                               chuck            1.4.0.0-3            1.4.0.1-1
                            conflict           20150705-3           20150705-4
                             coxeter       git.20180226-2       git.20180226-3
                             cryptol            2.8.0-106            2.8.0-108
                               darcs             2.14.3-1             2.14.4-1
                           darktable            2:3.0.2-1            2:3.0.2-2
                                dart              2.7.2-1              2.7.4-1
                             dbeaver              7.0.3-1              7.0.4-1
                          deepin-api              5.0.0-4           5.1.11.1-1
                   deepin-boot-maker              5.0.1-1              5.4.8-1
                   deepin-calculator              5.0.1-1              5.5.9-1
                     deepin-calendar              5.0.1-1              5.6.2-1
                        deepin-clone              5.0.1-1              5.0.3-1
               deepin-control-center              5.0.0-1            5.1.0.5-1
                       deepin-daemon              5.0.0-4            5.9.4.2-1
                 deepin-desktop-base       2:2019.07.10-1     2:2020.04.12.2-1
              deepin-desktop-schemas             3.13.9-1         5.4.0099.0-1
                         deepin-dock              5.0.0-6            5.1.0.6-1
                         deepin-draw              1.0.0-2           5.8.0.15-2
                       deepin-editor            1.2.6.4-1              5.6.7-2
                 deepin-file-manager            1:5.0.0-6         1:5.1.1.25-1
                   deepin-icon-theme           15.12.71-1         2020.05.09-1
                 deepin-image-viewer              5.0.0-1            5.6.3.2-1
                         deepin-kwin              0.1.0-8           5.0.14.1-1
                     deepin-launcher              5.0.0-1         5.1.0099.0-1
                         deepin-menu              3.4.8-1              5.0.1-1
                        deepin-movie            1:5.0.0-2         1:5.7.6.29-1
                        deepin-music              5.0.1-3            6.0.1.8-1
                deepin-network-utils              5.0.1-1            5.1.0.0-1
                       deepin-picker              5.0.1-1              5.0.6-1
                 deepin-polkit-agent              5.0.0-1              5.1.0-1
              deepin-qt-dbus-factory              5.0.1-6            5.1.0.0-1
               deepin-qt5dxcb-plugin              5.0.1-6             5.0.11-1
               deepin-qt5integration             5.0.0-10              5.1.0-1
              deepin-screen-recorder              5.0.0-2           5.8.0.10-2
                   deepin-screenshot              5.0.0-2                    -
                   deepin-session-ui              5.0.0-1         5.1.0099.4-1
              deepin-shortcut-viewer              5.0.0-1              5.0.2-1
                  deepin-sound-theme            15.10.3-1            15.10.4-1
               deepin-system-monitor              5.0.0-3              5.6.1-1
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               react-native-debugger             0.11.1-1             0.11.3-1
                      rime-cantonese     0.0.0.20200502-1     0.0.0.20200509-2
                        riot-desktop             1.5.15-1              1.6.0-2
                            riot-web             1.5.15-1              1.6.0-2
                                 sbt            1:1.3.9-1           1:1.3.10-1
                  shadowsocks-deepin              1.2.2-1                    -
                          shellcheck              0.7.1-8             0.7.1-10
                               shfmt              3.1.0-1              3.1.1-1
                         simple-scan             3.36.2-1           3.36.2.1-1
                            singular              4.1.3-1           4.1.3.p1-1
                           sleuthkit              4.8.0-1              4.9.0-1
                                smem                1.5-1                1.5-2
                               smlnj             110.95-1             110.96-1
                            solidity              0.6.6-1              0.6.7-1
                               squid               4.10-1               4.10-2
                              ssdeep             2.14.1-1             2.14.1-2
                               stack              2.3.1-1              2.3.1-2
                            startdde              5.0.1-3            5.3.0.1-2
                             sthttpd             2.27.1-1             2.27.1-2
                         sunxi-tools              1.4.2-2              1.4.2-3
                            supermin             5.1.20-4              5.2.0-2
                              sysdig             0.26.6-3             0.26.7-1
                    telegram-desktop              2.1.1-1              2.1.3-1
                          tensorflow           2.2.0rc3-2              2.2.0-1
                     tensorflow-cuda           2.2.0rc3-2              2.2.0-1
                      tensorflow-opt           2.2.0rc3-2              2.2.0-1
                 tensorflow-opt-cuda           2.2.0rc3-2              2.2.0-1
                            tigervnc             1.10.1-1             1.10.1-2
                               tilda              1.5.0-1              1.5.1-1
                               tokei             11.1.0-1             11.1.1-1
                             toxcore           1:0.2.11-1           1:0.2.12-1
                               toxic              0.8.3-2              0.8.3-3
                  ttf-jetbrains-mono              1.0.5-1              1.0.6-1
                          ttf-roboto              2.138-1              2.138-2
                              tuntox              0.0.9-1              0.0.9-2
                           typespeed              0.6.5-7              0.6.5-8
                         udisks2-qt5              5.0.0-1              5.0.3-1
                  ukui-window-switch              2.0.2-1              2.0.3-1
                            urlwatch               2.18-2               2.18-3
                                utox             0.17.2-1             0.17.2-2
         v2ray-domain-list-community       202005041039-1       202005061230-1
                         v2ray-geoip       202004290001-1       202005060001-1
                             vagrant              2.2.7-5              2.2.8-1
                              viking                1.8-2                1.8-3
                        vim-nerdtree              6.5.0-1              6.6.0-1
                        wire-desktop          3.16.2923-1          3.17.2924-1
                      wishbone-utils              0.6.9-1             0.6.17-1
                           wordpress                5.4-1              5.4.1-1
                          xcb-imdkit     0.0.0.20200419-1     0.0.0.20200509-1
                                 xdo              0.5.7-1              0.5.7-2
                              xrootd             4.11.3-1             4.12.0-1
                          youtube-dl         2020.05.03-1         2020.05.08-1
                               zcash              2.1.2-1            2.1.2_3-1
                                zile             2.4.14-1             2.4.14-2
                       acme-redirect                    -              0.2.0-1
                      bemenu-ncurses                    -              0.4.0-1
                      bemenu-wlroots                    -              0.4.0-1
                          bemenu-x11                    -              0.4.0-1
                         cargo-watch                    -              7.3.0-2
                             dbxtool                    -                  7-1
                        deepin-album                    -           5.6.9.13-1
                deepin-session-shell                    -         5.0.0098.0-2
                              dtkgui                    -              5.2.0-1
                             oscpack                    -              1.1.0-1


:: Different overlay package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-06           2020-05-09
-------------------------------------------------------------------------------
                              json-c             0.14-2.1                    -
                            linux414           4.14.178-1           4.14.179-1
                    linux414-headers           4.14.178-1           4.14.179-1
                            linux419           4.19.120-1           4.19.121-1
                    linux419-headers           4.19.120-1           4.19.121-1
                             linux44            4.4.221-1            4.4.222-1
                     linux44-headers            4.4.221-1            4.4.222-1
                             linux49            4.9.221-1            4.9.222-1
                     linux49-headers            4.9.221-1            4.9.222-1
                             linux54             5.4.38-1             5.4.39-1
                     linux54-headers             5.4.38-1             5.4.39-1
                             linux56             5.6.10-3             5.6.11-1
                     linux56-headers             5.6.10-3             5.6.11-1


:: Different sync package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-06           2020-05-09
-------------------------------------------------------------------------------
                                 acl             2.2.53-2             2.2.53-3
                              argon2           20190702-2           20190702-3
                                attr             2.4.48-2             2.4.48-3
                          cryptsetup              2.3.2-1              2.3.2-2
                       device-mapper           2.02.187-1           2.02.187-2
                           e2fsprogs             1.45.6-1             1.45.6-2
                              gnutls             3.6.13-1             3.6.13-2
                               gpgme             1.13.1-3             1.13.1-5
                              json-c               0.14-2               0.14-4
                            keyutils              1.6.1-3              1.6.1-4
                              libidn               1.35-2                    -
                       libmicrohttpd             0.9.70-2             0.9.70-3
                          libp11-kit            0.23.20-4            0.23.20-5
                                lvm2           2.02.187-1           2.02.187-2
                              nettle              3.5.1-2                3.6-1
                             p11-kit            0.23.20-4            0.23.20-5
                        python-gpgme             1.13.1-3             1.13.1-5
                              qgpgme             1.13.1-3             1.13.1-5


:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-06           2020-05-09
-------------------------------------------------------------------------------
                           calamares           3.2.23.1-1           3.2.23.2-1
               calamares-git 3.2.24.r7775.d51bf842e-1 3.2.24.r7826.fb8e69ca6-1
                  linux414-acpi_call            1.1.0-150            1.1.0-151
                   linux414-bbswitch              0.8-150              0.8-151
                linux414-broadcom-wl     6.30.223.271-150     6.30.223.271-151
                linux414-ndiswrapper              1.62-45              1.62-46
               linux414-nvidia-340xx           340.108-19           340.108-20
               linux414-nvidia-390xx           390.132-27           390.132-28
               linux414-nvidia-418xx           418.113-24           418.113-25
               linux414-nvidia-430xx            430.64-25            430.64-26
               linux414-nvidia-435xx            435.21-35            435.21-36
               linux414-nvidia-440xx             440.82-4             440.82-5
                   linux414-nvidiabl             0.88-150             0.88-151
                      linux414-r8168           8.048.02-2           8.048.02-3
                  linux414-rt3562sta       2.4.1.1_r4-150       2.4.1.1_r4-151
                   linux414-tp_smapi              0.43-42              0.43-43
                linux414-vhba-module          20200106-13          20200106-14
    linux414-virtualbox-host-modules              6.1.6-3              6.1.6-4
                        linux414-zfs             0.8.3-12             0.8.3-13
                  linux419-acpi_call            1.1.0-110            1.1.0-111
                   linux419-bbswitch              0.8-110              0.8-111
                linux419-broadcom-wl     6.30.223.271-109     6.30.223.271-110
                linux419-ndiswrapper              1.62-59              1.62-60
               linux419-nvidia-340xx           340.108-30           340.108-31
               linux419-nvidia-390xx           390.132-39           390.132-40
               linux419-nvidia-418xx           418.113-38           418.113-39
               linux419-nvidia-430xx            430.64-38            430.64-39
               linux419-nvidia-435xx            435.21-49            435.21-50
               linux419-nvidia-440xx             440.82-7             440.82-8
                   linux419-nvidiabl             0.88-109             0.88-110
                      linux419-r8168           8.048.02-3           8.048.02-4
                  linux419-rtl8723bu           20200405-6           20200405-7
                   linux419-tp_smapi              0.43-59              0.43-60
                linux419-vhba-module          20200106-24          20200106-25
   linux419-virtualbox-guest-modules              6.1.6-6              6.1.6-7
    linux419-virtualbox-host-modules              6.1.6-6              6.1.6-7
                        linux419-zfs             0.8.3-23             0.8.3-24
                   linux44-acpi_call            1.1.0-152            1.1.0-153
                    linux44-bbswitch              0.8-152              0.8-153
                 linux44-broadcom-wl     6.30.223.271-122     6.30.223.271-123
                 linux44-ndiswrapper              1.62-34              1.62-35
                linux44-nvidia-340xx           340.108-16           340.108-17
                linux44-nvidia-390xx           390.132-22           390.132-23
                linux44-nvidia-418xx           418.113-21           418.113-22
                linux44-nvidia-430xx            430.64-20            430.64-21
                linux44-nvidia-435xx            435.21-22            435.21-23
                linux44-nvidia-440xx             440.82-4             440.82-5
                    linux44-nvidiabl             0.88-152             0.88-153
                       linux44-r8168           8.048.02-2           8.048.02-3
                   linux44-rt3562sta       2.4.1.1_r4-109       2.4.1.1_r4-110
                    linux44-tp_smapi              0.43-31              0.43-32
                 linux44-vhba-module          20200106-13          20200106-14
     linux44-virtualbox-host-modules              6.1.6-3              6.1.6-4
                         linux44-zfs             0.8.3-12             0.8.3-13
                   linux49-acpi_call            1.1.0-166            1.1.0-167
                    linux49-bbswitch              0.8-166              0.8-167
                 linux49-broadcom-wl     6.30.223.271-166     6.30.223.271-167
                 linux49-ndiswrapper              1.62-36              1.62-37
                linux49-nvidia-340xx           340.108-16           340.108-17
                linux49-nvidia-390xx           390.132-23           390.132-24
                linux49-nvidia-418xx           418.113-22           418.113-23
                linux49-nvidia-430xx            430.64-21            430.64-22
                linux49-nvidia-435xx            435.21-28            435.21-29
                linux49-nvidia-440xx             440.82-4             440.82-5
                    linux49-nvidiabl             0.88-166             0.88-167
                       linux49-r8168           8.048.02-2           8.048.02-3
                   linux49-rt3562sta       2.4.1.1_r4-150       2.4.1.1_r4-151
                    linux49-tp_smapi              0.43-34              0.43-35
                 linux49-vhba-module          20200106-13          20200106-14
     linux49-virtualbox-host-modules              6.1.6-3              6.1.6-4
                         linux49-zfs             0.8.3-12             0.8.3-13
                   linux54-acpi_call             1.1.0-44             1.1.0-45
                    linux54-bbswitch               0.8-44               0.8-45
                 linux54-broadcom-wl      6.30.223.271-44      6.30.223.271-45
                 linux54-ndiswrapper              1.62-44              1.62-45
                linux54-nvidia-340xx           340.108-36           340.108-37
                linux54-nvidia-390xx           390.132-44           390.132-45
                linux54-nvidia-418xx           418.113-44           418.113-45
                linux54-nvidia-430xx            430.64-44            430.64-45
                linux54-nvidia-435xx            435.21-44            435.21-45
                linux54-nvidia-440xx            440.82-11            440.82-12
                    linux54-nvidiabl              0.88-44              0.88-45
                       linux54-r8168           8.048.02-4           8.048.02-5
                   linux54-rtl8723bu           20200405-8           20200405-9
                    linux54-tp_smapi              0.43-44              0.43-45
                 linux54-vhba-module          20200106-29          20200106-30
    linux54-virtualbox-guest-modules              6.1.6-8              6.1.6-9
     linux54-virtualbox-host-modules              6.1.6-8              6.1.6-9
                         linux54-zfs             0.8.3-28             0.8.3-29
                   linux56-acpi_call             1.1.0-14             1.1.0-15
                    linux56-bbswitch               0.8-14               0.8-15
                 linux56-broadcom-wl      6.30.223.271-14      6.30.223.271-15
                 linux56-ndiswrapper              1.62-14              1.62-15
                linux56-nvidia-340xx           340.108-14           340.108-15
                linux56-nvidia-390xx           390.132-14           390.132-15
                linux56-nvidia-418xx           418.113-14           418.113-15
                linux56-nvidia-430xx            430.64-14            430.64-15
                linux56-nvidia-435xx            435.21-14            435.21-15
                linux56-nvidia-440xx            440.82-12            440.82-13
                       linux56-r8168           8.048.02-6           8.048.02-7
                   linux56-rtl8723bu          20200405-14          20200405-15
                    linux56-tp_smapi              0.43-14              0.43-15
                 linux56-vhba-module          20200106-14          20200106-15
    linux56-virtualbox-guest-modules             6.1.6-10             6.1.6-11
     linux56-virtualbox-host-modules             6.1.6-10             6.1.6-11
                         linux56-zfs             0.8.3-14             0.8.3-15
                   manjaro-architect             0.9.30-1             0.9.32-1
          manjaro-architect-launcher             0.9.30-1             0.9.32-1
                           pamac-cli              9.4.2-1            9.5.0rc-1
                        pamac-common              9.4.2-1            9.5.0rc-1
                pamac-flatpak-plugin              9.4.2-1            9.5.0rc-1
             pamac-gnome-integration              9.4.2-1            9.5.0rc-1
                           pamac-gtk              9.4.2-1            9.5.0rc-1
                   pamac-snap-plugin              9.4.2-1            9.5.0rc-1
               pamac-snap-plugin-dev          9.5.0beta-2            9.5.0rc-1
             pamac-tray-appindicator              9.4.2-1            9.5.0rc-1
         pamac-tray-appindicator-dev          9.5.0beta-2            9.5.0rc-1
                         xorg-server             1.20.8-1             1.20.8-2
                  xorg-server-common             1.20.8-1             1.20.8-2
                   xorg-server-devel             1.20.8-1             1.20.8-2
                  xorg-server-xephyr             1.20.8-1             1.20.8-2
                   xorg-server-xnest             1.20.8-1             1.20.8-2
                    xorg-server-xvfb             1.20.8-1             1.20.8-2
                xorg-server-xwayland             1.20.8-1             1.20.8-2
                            pamac-qt                    -              0.3.1-2
                         thunderbird                    -           68.8.0-0.1


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2020-05-06           2020-05-09
-------------------------------------------------------------------------------
                         389-ds-base            1.4.3.4-3            1.4.4.1-1
                                a2ps               4.14-8               4.14-9
                              anjuta             3.34.0-3             3.34.0-4
                                celt             0.11.3-3             0.11.3-4
                              chmlib               0.40-5               0.40-6
                            chromium      81.0.4044.129-2      81.0.4044.138-2
                          claws-mail             3.17.5-1             3.17.5-2
                               cmake             3.17.2-1             3.17.2-2
                            composer             1.10.5-1             1.10.6-1
                            cups-pdf              3.0.1-4              3.0.1-5
                     dleyna-renderer              0.6.0-3              0.6.0-4
                             dnsmasq               2.81-3               2.81-4
                             empathy 3.25.90+34+g78f4d4fda-3                 -
                            epiphany             3.36.1-1             3.36.1-2
                             firefox               76.0-2             76.0.1-1
                    firefox-i18n-ach               76.0-1             76.0.1-1
                     firefox-i18n-af               76.0-1             76.0.1-1
                     firefox-i18n-an               76.0-1             76.0.1-1
                     firefox-i18n-ar               76.0-1             76.0.1-1
                    firefox-i18n-ast               76.0-1             76.0.1-1
                     firefox-i18n-az               76.0-1             76.0.1-1
                     firefox-i18n-be               76.0-1             76.0.1-1
                     firefox-i18n-bg               76.0-1             76.0.1-1
                     firefox-i18n-bn               76.0-1             76.0.1-1
                     firefox-i18n-br               76.0-1             76.0.1-1
                     firefox-i18n-bs               76.0-1             76.0.1-1
                     firefox-i18n-ca               76.0-1             76.0.1-1
            firefox-i18n-ca-valencia               76.0-1             76.0.1-1
                    firefox-i18n-cak               76.0-1             76.0.1-1
                     firefox-i18n-cs               76.0-1             76.0.1-1
                     firefox-i18n-cy               76.0-1             76.0.1-1
                     firefox-i18n-da               76.0-1             76.0.1-1
                     firefox-i18n-de               76.0-1             76.0.1-1
                    firefox-i18n-dsb               76.0-1             76.0.1-1
                     firefox-i18n-el               76.0-1             76.0.1-1
                  firefox-i18n-en-ca               76.0-1             76.0.1-1
                  firefox-i18n-en-gb               76.0-1             76.0.1-1
                  firefox-i18n-en-us               76.0-1             76.0.1-1
                     firefox-i18n-eo               76.0-1             76.0.1-1
                  firefox-i18n-es-ar               76.0-1             76.0.1-1
                  firefox-i18n-es-cl               76.0-1             76.0.1-1
                  firefox-i18n-es-es               76.0-1             76.0.1-1
                  firefox-i18n-es-mx               76.0-1             76.0.1-1
                     firefox-i18n-et               76.0-1             76.0.1-1
                     firefox-i18n-eu               76.0-1             76.0.1-1
                     firefox-i18n-fa               76.0-1             76.0.1-1
                     firefox-i18n-ff               76.0-1             76.0.1-1
                     firefox-i18n-fi               76.0-1             76.0.1-1
                     firefox-i18n-fr               76.0-1             76.0.1-1
                  firefox-i18n-fy-nl               76.0-1             76.0.1-1
                  firefox-i18n-ga-ie               76.0-1             76.0.1-1
                     firefox-i18n-gd               76.0-1             76.0.1-1
                     firefox-i18n-gl               76.0-1             76.0.1-1
                     firefox-i18n-gn               76.0-1             76.0.1-1
                  firefox-i18n-gu-in               76.0-1             76.0.1-1
                     firefox-i18n-he               76.0-1             76.0.1-1
                  firefox-i18n-hi-in               76.0-1             76.0.1-1
                     firefox-i18n-hr               76.0-1             76.0.1-1
                    firefox-i18n-hsb               76.0-1             76.0.1-1
                     firefox-i18n-hu               76.0-1             76.0.1-1
                  firefox-i18n-hy-am               76.0-1             76.0.1-1
                     firefox-i18n-ia               76.0-1             76.0.1-1
                     firefox-i18n-id               76.0-1             76.0.1-1
                     firefox-i18n-is               76.0-1             76.0.1-1
                     firefox-i18n-it               76.0-1             76.0.1-1
                     firefox-i18n-ja               76.0-1             76.0.1-1
                     firefox-i18n-ka               76.0-1             76.0.1-1
                    firefox-i18n-kab               76.0-1             76.0.1-1
                     firefox-i18n-kk               76.0-1             76.0.1-1
                     firefox-i18n-km               76.0-1             76.0.1-1
                     firefox-i18n-kn               76.0-1             76.0.1-1
                     firefox-i18n-ko               76.0-1             76.0.1-1
                    firefox-i18n-lij               76.0-1             76.0.1-1
                     firefox-i18n-lt               76.0-1             76.0.1-1
                     firefox-i18n-lv               76.0-1             76.0.1-1
                     firefox-i18n-mk               76.0-1             76.0.1-1
                     firefox-i18n-mr               76.0-1             76.0.1-1
                     firefox-i18n-ms               76.0-1             76.0.1-1
                     firefox-i18n-my               76.0-1             76.0.1-1
                  firefox-i18n-nb-no               76.0-1             76.0.1-1
                  firefox-i18n-ne-np               76.0-1             76.0.1-1
                     firefox-i18n-nl               76.0-1             76.0.1-1
                  firefox-i18n-nn-no               76.0-1             76.0.1-1
                     firefox-i18n-oc               76.0-1             76.0.1-1
                  firefox-i18n-pa-in               76.0-1             76.0.1-1
                     firefox-i18n-pl               76.0-1             76.0.1-1
                  firefox-i18n-pt-br               76.0-1             76.0.1-1
                  firefox-i18n-pt-pt               76.0-1             76.0.1-1
                     firefox-i18n-rm               76.0-1             76.0.1-1
                     firefox-i18n-ro               76.0-1             76.0.1-1
                     firefox-i18n-ru               76.0-1             76.0.1-1
                     firefox-i18n-si               76.0-1             76.0.1-1
                     firefox-i18n-sk               76.0-1             76.0.1-1
                     firefox-i18n-sl               76.0-1             76.0.1-1
                    firefox-i18n-son               76.0-1             76.0.1-1
                     


CVE-2020-11694
Sat, 11 Apr 2020 00:48:09 +0200
In JetBrains PyCharm 2019.2.5 and 2019.3 on Windows, Apple Notarization Service credentials were included. This is fixed in 2019.2.6 and 2019.3.3.


can anyone tell , while I am using Pycharm why so many python process are running, like as pycharm itself takes approx 1.5 gb memory(as you can see by process named java) , but right now , due to multiple python process my memory usage is 7.3gb .
Sat, 29 Feb 2020 13:00:18 +0100
  submitted by    /u/snehil21  
[link]   [comments]


Chmod for Pycharm
Fri, 07 Feb 2020 20:30:17 +0100
So, I installed Pycharm IDE to write Python projects. However, I am unable to save or modify in any way, the contents of the /home/. I have tried using chmod u=rwx,g=rwx, o=rwx so that anything should be able to read, write or execute files within /home/* If it helps, I installed Pycharm from the software manager. Please, anyone help me as I need to boot from my old windows drive to write my python code and it's such a pain.
 Thanks in advance.
 
   submitted by    /u/xelab04  
[link]   [comments]


How to install the PyCharm IDE on Linux
Tue, 17 Dec 2019 20:00:09 +0100
PyCharm is an excellent IDE for Mac, Linux, and Windows. The app is specially designed for Python programming and development. In this guide, we’ll show you how to get the PyCharm IDE up and running in Linux. Note: This guide will focus on installing the “Community” edition of PyCharm as it is free of charge. […]
Read How to install the PyCharm IDE on Linux by Derrik Diener on AddictiveTips - Tech tips to make you smarter


How to install the PyCharm IDE on Linux
Tue, 17 Dec 2019 18:45:12 +0100
PyCharm is an excellent IDE for Mac, Linux, and Windows. The app is specially designed for Python programming and development. In this guide, we’ll show you how to get the PyCharm IDE up and running in Linux. Note: This guide will focus on installing the “Community” edition of PyCharm as it is free of charge. […]
Read How to install the PyCharm IDE on Linux by Derrik Diener on AddictiveTips - Tech tips to make you smarter


Step By Step Guide of Configuring Odoo 13 on Pycharm Ubuntu 18
Thu, 21 Nov 2019 10:45:10 +0100
Guide to configure Odoo 13 with Pycharm Ubuntu 18
 Watch Video: https://www.youtube.com/watch?v=nKguOFx0L08
 
   submitted by    /u/Johnkite7  
[link]   [comments]


Install Pycharm And Configure PostgreSQL On Ubuntu 18
Tue, 19 Nov 2019 13:00:17 +0100
Watch Video: https://www.youtube.com/watch?v=V8JxrYLX0VM
 
   submitted by    /u/Johnkite7  
[link]   [comments]


heise+ | Programmieren unter Googles Chrome OS mit Visual Studio Code, PyCharm und Co
Sat, 02 Nov 2019 07:04:55 +0100
Chrome OS taugt dank Linux-Apps prinzipiell zum Entwickeln. Wir zeigen, wie Sie Visual Studio Code, Android Studio und PyCharm unter Chrome OS installieren.


[Testing Update] 2019-09-27 - Pamac, Linux316, ZFS, Gnome 3.34, PHP
Fri, 25 Oct 2019 06:01:00 +0200
@philm wrote:
            
              Hello community,
I am happy to announce another Testing Update. Mostly we have Kernels, Gnome 3.34 and needed rebuilds with this one.

EEblKiiW4AAtF53?format=jpg&name=large1220×882

Help us to debug pamac
Update news
This update holds the following changes:
Beginning with Pamac 9.0 series, we now support snaps via a plugin. We focused on fixing reported issues of this series.

ZFS got updated to 0.8.2

Some more Gnome 3.34 packages landed in our repos. We also added some of our tweaked versions.

php and regular python updates

Manjaro 18.1.0 got released today. Please test and give us feedback.
Latest efforts by KDE can be reviewed via our current KDE-Dev ISO or current KDE-Vanilla ISO

Give us the usual feedback and let us know what you think about this update.
Current supported Kernels
linux316 3.16.74
linux44 4.4.194 (no legacy nvidia-340 module!)
linux49 4.9.194
linux414 4.14.146
linux419 4.19.75
linux51 5.1.21 [EOL]
linux52 5.2.17 (no catalyst module!)
linux53 5.3.1 (no catalyst module!)
linux419-rt 4.19.72_rt25
linux52-rt 5.2.14_rt7
Package Updates (Fri Sep 27 19:51:30 CEST 2019)
testing community x86_64:  81 new and 78 removed package(s)
testing core x86_64:  4 new and 4 removed package(s)
testing extra x86_64:  76 new and 76 removed package(s)
testing multilib x86_64:  1 new and 1 removed package(s)
:: Different overlay package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2019-09-25           2019-09-27
-------------------------------------------------------------------------------
           bettercap-caplets v20190715.r327.5dbf77d-1 v20190925.r331.d1a936f-1
                            cinnamon              4.2.4-1              4.2.4-2
            firefox-gnome-theme-maia           20190923-2           20190925-1
                   manjaro-gdm-theme           20190921-1           20190926-1
                                 yad                3.0-1                    -
                           bettercap                    -               2.25-1
                 gnome-shell-manjaro               - 1:3.34.0+152+g0fdbde910-1
     libnautilus-extension-typeahead                    -             3.34.0-1
                  nautilus-typeahead                    -             3.34.0-1


:: Different sync package(s) in repository community x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2019-09-25           2019-09-27
-------------------------------------------------------------------------------
                               acorn            1:7.0.0-1            1:7.1.0-1
                               arcus              4.2.0-1              4.3.0-1
                            binaryen                 87-1                 89-1
                       brightnessctl                0.4-2                0.4-3
                browserpass-chromium              3.1.1-1              3.2.2-1
                 browserpass-firefox              3.1.1-1              3.2.2-1
                            cinnamon              4.2.4-1              4.2.4-2
                             cockpit              202.1-1                203-1
                   cockpit-dashboard              202.1-1                203-1
                         cockpit-pcp              202.1-1                203-1
                     consul-template             0.21.0-1             0.22.0-1
                             crystal             0.31.0-1             0.31.0-2
                                cura              4.2.1-1              4.3.0-1
                    cura-binary-data              4.2.0-1              4.3.0-1
            cura-resources-materials              4.2.0-1              4.3.0-1
                          curaengine              4.2.0-1              4.3.0-1
                            dos2unix              7.4.0-1              7.4.1-1
                          emscripten            1.38.43-1            1.38.46-1
                           filezilla             3.45.0-1             3.45.1-1
               firefox-ublock-origin             1.22.2-1             1.22.4-1
                             fractal              4.2.0-1              4.2.1-1
                               fwupd              1.3.1-3              1.3.2-1
                                grpc             1.23.0-1             1.24.0-1
                            grpc-cli             1.23.0-1             1.24.0-1
     intellij-idea-community-edition         2:2019.2.1-1         2:2019.2.3-1
                              kcptun           20190922-1           20190924-1
                          libchewing              0.5.1-2              0.5.1-3
                             libgiac           1.5.0.63-5           1.5.0.65-1
                          libsavitar              4.2.0-1              4.3.0-1
                        minio-client         2019.09.05-1         2019.09.24-1
                       mod_passenger              6.0.2-3              6.0.4-1
                           mosquitto              1.6.4-2              1.6.7-1
                 nginx-mod-passenger              6.0.2-3              6.0.4-1
                                nmon                16k-1                16m-1
                              nodejs            12.10.0-1            12.11.0-1
                                ogre             1.12.1-1             1.12.2-1
                           ogre-docs             1.12.1-1             1.12.2-1
                            openfire              4.4.1-1              4.4.2-1
                     parity-ethereum              2.5.8-1              2.5.9-1
                           passenger              6.0.2-3              6.0.4-1
                                  pd             0.50.0-1             0.50.1-1
                             pelican              4.1.1-1              4.1.2-1
                            php-grpc             1.23.0-1             1.24.0-1
                        postfixadmin              3.2.2-3              3.2.3-1
                              ppsspp              1.8.0-1              1.9.1-1
                     ppsspp-headless              1.8.0-1              1.9.1-1
                           ppsspp-qt              1.8.0-1              1.9.1-1
           pycharm-community-edition           2019.2.2-1           2019.2.3-1
                     python-cfn-lint             0.24.1-1             0.24.2-1
                         python-dkim              0.9.3-1              0.9.4-1
                        python-fido2              0.7.0-1              0.7.1-1
                       python-grpcio             1.23.0-1             1.24.0-1
                    python-mongomock             3.17.0-1             3.18.0-1
                        python-paste              3.2.0-1              3.2.1-1
                    python-soupsieve              1.9.3-1              1.9.4-1
                     python-tabulate              0.8.4-1              0.8.5-1
                   python2-mongomock             3.17.0-1             3.18.0-1
                       python2-paste              3.2.0-1              3.2.1-1
                   python2-soupsieve              1.9.3-1              1.9.4-1
                         qutebrowser              1.7.0-1              1.8.0-1
                         rawtherapee              1:5.6-1              1:5.7-1
                               redis              5.0.5-1              5.0.6-1
                             svt-av1              0.6.0-1              0.7.0-1
            switchboard-plug-display              2.1.8-1              2.1.9-1
                             sysstat             12.1.5-1             12.1.6-1
                               taskd              1.1.0-3              1.1.0-4
                       ttf-joypixels              5.0.2-2              5.0.3-1
                 ttf-tibetan-machine              1.901-9             1.901-10
                             unbound              1.9.3-3              1.9.3-4
                             uranium              4.2.0-1              4.3.0-1
                       vim-gitgutter        564.9147174-1        636.ba049e7-1
                                wabt             1.0.11-1             1.0.12-1
                                xcas           1.5.0.63-5           1.5.0.65-1
                             you-get           0.4.1347-1           0.4.1355-1


:: Different sync package(s) in repository core x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2019-09-25           2019-09-27
-------------------------------------------------------------------------------
                           e2fsprogs             1.45.3-1             1.45.4-1
                              hdparm               9.58-1               9.58-2
                            iproute2              5.2.0-1              5.3.0-1
                      wireless-regdb         2019.03.01-1         2019.06.03-1


:: Different overlay package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2019-09-25           2019-09-27
-------------------------------------------------------------------------------
               calamares-git 3.2.14.r6560.718f24b82-2 3.2.14.r6606.e1618f20a-1
                  linux316-acpi_call             1.1.0-53             1.1.0-54
                   linux316-bbswitch               0.8-52               0.8-53
                linux316-broadcom-wl      6.30.223.271-32      6.30.223.271-33
                   linux316-catalyst     1:15.201.1151-42     1:15.201.1151-43
                linux316-ndiswrapper               1.62-6               1.62-7
               linux316-nvidia-340xx           340.107-11           340.107-12
               linux316-nvidia-390xx            390.129-2            390.129-3
               linux316-nvidia-418xx             418.88-3             418.88-4
               linux316-nvidia-430xx             430.40-5             430.40-6
               linux316-nvidia-435xx             435.21-1             435.21-2
                   linux316-nvidiabl              0.88-42              0.88-43
                      linux316-r8168           8.047.02-2           8.047.02-3
                  linux316-rt3562sta        2.4.1.1_r4-32        2.4.1.1_r4-33
                   linux316-tp_smapi               0.43-2               0.43-3
   linux316-virtualbox-guest-modules             6.0.12-1             6.0.12-2
    linux316-virtualbox-host-modules             6.0.12-1             6.0.12-2
                        linux316-zfs              0.8.1-4              0.8.2-2
                        linux414-zfs             0.8.1-17              0.8.2-1
                        linux419-zfs             0.8.1-23              0.8.2-1
                         linux44-zfs              0.8.1-8              0.8.2-1
                         linux51-zfs             0.8.1-12              0.8.2-1
                         linux52-zfs             0.8.1-20              0.8.2-1
                         linux53-zfs              0.8.1-1              0.8.2-1
                           pamac-cli            9.0.0rc-4            9.0.0rc-5
                        pamac-common            9.0.0rc-4            9.0.0rc-5
                           pamac-gtk            9.0.0rc-4            9.0.0rc-5
                   pamac-snap-plugin            9.0.0rc-4            9.0.0rc-5
             pamac-tray-appindicator            9.0.0rc-4            9.0.0rc-5
                         xfce4-panel           4.14.0-2.1                    -
                         linux54-zfs                    -            0.8.2-0.1


:: Different sync package(s) in repository extra x86_64

-------------------------------------------------------------------------------
                             PACKAGE           2019-09-25           2019-09-27
-------------------------------------------------------------------------------
                         389-ds-base            1.4.1.6-7            1.4.2.2-1
                           appstream             0.12.9-1             0.12.9-2
                        appstream-qt             0.12.9-1             0.12.9-2
            archlinux-appstream-data           20190825-1           20190925-1
                                babl             0.1.66-1             0.1.72-1
                             enchant              2.2.6-1              2.2.7-1
                                  gc              7.6.8-1              8.0.4-2
                      gnome-mahjongg             3.32.0-1             3.34.0-1
                        gnome-tweaks3.33.90+27+ge26f21d-1             3.34.0-1
                             libical              3.0.5-1              3.0.6-1
                            liblouis             3.10.0-1             3.11.0-1
                        libpwquality              1.4.0-2              1.4.1-1
                            libunrar            1:5.8.1-1            1:5.8.2-1
                            libwacom                1.0-1                1.1-1
                             libxvmc             1.0.12-1             1.0.12-2
      mobile-broadband-provider-info           20190116-1           20190618-1
                                 mpd            0.21.14-1            0.21.15-1
                               pango           1:1.44.6-1         1:1.44.6+2-1
                    perl-alien-build               1.86-1               1.89-1
                          phonon-qt5             4.11.0-1             4.11.1-1
                      phonon-qt5-vlc             0.11.0-1             0.11.1-1
                                 php              7.3.9-1             7.3.10-1
                          php-apache              7.3.9-1             7.3.10-1
                             php-cgi              7.3.9-1             7.3.10-1
                           php-dblib              7.3.9-1             7.3.10-1
                           php-embed              7.3.9-1             7.3.10-1
                         php-enchant              7.3.9-1             7.3.10-1
                             php-fpm              7.3.9-1             7.3.10-1
                              php-gd              7.3.9-1             7.3.10-1
                            php-imap              7.3.9-1             7.3.10-1
                            php-intl              7.3.9-1             7.3.10-1
                            php-odbc              7.3.9-1             7.3.10-1
                           php-pgsql              7.3.9-1             7.3.10-1
                          php-phpdbg              7.3.9-1             7.3.10-1
                          php-pspell              7.3.9-1             7.3.10-1
                            php-snmp              7.3.9-1             7.3.10-1
                          php-sodium              7.3.9-1             7.3.10-1
                          php-sqlite              7.3.9-1             7.3.10-1
                            php-tidy              7.3.9-1             7.3.10-1
                             php-xsl              7.3.9-1             7.3.10-1
                        python-numpy             1.17.1-1             1.17.2-1
                       qt5-webengine             5.13.1-2             5.13.1-3
                              strace                5.2-1                5.3-1
                               unrar            1:5.8.1-1            1:5.8.2-1
                             varnish              6.2.1-1              6.3.0-1
                         xfce4-panel             4.14.0-2             4.14.1-1


:: Different sync package(s) in repository multilib x86_64

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                             PACKAGE           2019-09-25           2019-09-27
-------------------------------------------------------------------------------
                     lib32-e2fsprogs             1.45.3-1             1.45.4-1




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Fedora on Lenovo Thinkpad T450?
Thu, 29 Aug 2019 23:30:14 +0200


Hello!I have previously ran Linux Mint on an old notebook, but in January I got a Lenovo Thinkpad T450, and getting it ready for the coming school year (entering Grade 10!), I realized I was still running windows. I was looking into it -- And I remember not being too satisfied with Mint near the end of the notebooks life, it became incredibly slow and bogged down -- and it seems that Fedora is a solid build still, and is probably the best option currently on the market. I come from a Mac family, but have to use Windows for games & cannot get a mac book because it's too expensive to bring to school.
 Anyway, i just wanted thoughts on using Fedora on a thinkpad, and if it is a good distro to go with for schoolwork? Most everything I do is through LibreOffice & Dropbox. The only other programs I use on here are iTunes (Ecosia says I can just use virtualbox here), and a few steam games (mindustry, factorio, and Civ are the only things my laptop can run). But it is primarily a school computer & I remember liking linux objectively, even if mint left a bad taste in my mouth.
 ---
 EDIT: I do dabble in web development/general programming, for which I use the Jetbrains suite (WebStorm & Pycharm mostly), and I believe those are available on Linux as well.
 
 Edit: Y'all may hate me for this, but I do not want to use ubuntu. Something about it is off, I can't place it but I just don't really like it.
 
   submitted by    /u/AFrostNova  
[link]   [comments]



Building a Free Malware Lab
Wed, 28 Aug 2019 07:32:13 +0200
Welcome to rinse and REpeat analysis!  What better way to start a blog than to begin with recommendations for starting up an environment for Malware Analysis.

Here is a list of what tools I recommend downloading:

Virtualization software - VMware Workstation Player or VirtualBox

This will allow us to perform analysis in a safe/isolated environment
VMware is preferred but VirtualBox will also do the job! 

Windows 7 Image

Most malware is written for Windows and we must provide it with the right environment for it to run correctly

List of tools to download for this VM:

Exeinfo
PEID
PEView
PEStudio
Resource Hacker
HxD
Process Monitor
Process Hacker
Autoruns
RegShot
API Monitor
FakeNet
Apate DNS
WinPcap
Wireshark
IDAPro (idafree)
Ollydbg
x64Dbg
Python
PyCharm



REMnux

This is a free VM/fully loaded Linux-based toolkit with tons of amazing tools for analyzing malware
Primarily for static analysis
Tons of python scripts to run against malware
Especially awesome for deobfuscation, malicious PS/VB scripts, shellcode, etc... 

SIFT Workstation

This is a free VM/fully loaded Linux-based toolkit with tons of amazing tools for forensics
Can be used to analyze malware forensically
Identify artifacts that malware leaves on disk
Analyze evasive fileless malware that doesn't touch disk
Easily spot code injection, API hooks, and rootkits

Kali Linux

This is a free VM/fully loaded Linux-based toolkit with tons of amazing tools for penetration testing
Recreate compromises, create and deploy payloads
Think like the adversary


These tools will provide you with absolutely everything you need to begin analyzing malware!!



Linux and 4k monitors
Fri, 09 Aug 2019 14:30:38 +0200


What is the best desktop environment for running 4k monitors? Gnome, and Ubuntu 19.04 just don't handle it gracefully. I've followed guides to set 150% scaling but it doesn't come into effect. The default scale is far too small to read and 200% scaling is just way too big. 
 I've been a developer using a mac for some time so 4k has never been a problem. However, I've switched job and am a c# developer using Windows. I've been provided with a Windows laptop and I've returned my MacBook to my previous company. The problem I have is I just don't like using Windows, and prefer living in Linux space, so at home, any home projects I'm likely to do, will still be in Python/PHP/Javascript and maybe even DOTNET core. 
 
 Ideally, I'd like to get up and running with Ubuntu/Debian. I've used Manjaro/Arch/CentOS etc before but I want to spend a bit less time configuring my OS and actually using it.
 
 Tools and apps I use daily are:
 Docker
 PHPStorm / Rider / PyCharm / Webstorm / VSCode
 MySQL Workbench
 Spotify
 
 I prefer the command line to GUI's but happy to use either / both.
 
   submitted by    /u/mossiv  
[link]   [comments]



JetBrains holt zum Update-Rundumschlag aus mit IntelliJ IDEA, CLion und PyCharm
Thu, 25 Jul 2019 12:37:12 +0200
Neben JetBrains Flaggschiff-IDE für Java sind auch die Entwicklungsumgebungen für C/C++ und Python als 2019.2-Release erschienen.


Visual Studio Code vs Jetbrains
Wed, 15 May 2019 06:00:13 +0200


I see a lot of folks are using VSC over other IDEs like Jetbrains, Eclipse, etc. I'm a python developer who switched to full Pycharm from VIM a couple years ago. I've tried VSC, but still can't get into it. For those who have worked with Pycharm, Jetbrains, etc, what made you choose one over the other?
 
   submitted by    /u/sternebrau  
[link]   [comments]



Made the full leap to Ubuntu Linux yesterday! A love letter of happiness.
Thu, 07 Feb 2019 17:45:50 +0100


I'm a Windows 10 power user. I run lean machines, and have always maintained them so.
 Yet Windows 10, over the past two years, has been gradually annoying me with its forced updates, and the forced telemetry/privacy/'diagnostics' with Cortana. What first irked me: my Windows was slowing down constantly, despite reformatting and/or refreshing, and I couldn't really keep my machine on for more than a few days running because of updates. What worried me: multiple Explorer processes kept running or resurrecting without my knowledge - despite the anti-malware and anti-virus and other stuff I'm running, and reformats every 2-3 months. Windows 10, despite my fairly-beast machine (i7-7700k 4.2Ghx x8, 32GB RAM, GTX 1080), felt slow and just sluggish.
 So I tried running Ubuntu first in a VM for about a week. Was hitting Stack Overflow and other places everyday to just learn about the basics of terminal syntax and the OS, and customizing the setup to ensure compatibility of frequently used office software (e.g. like SumatraPDF, custom-written scripts and others) -- and observed that they run equally well on Wine. Ubuntu on the VM also ran fast, even though using VM obviously had performance tradeoffs.
 I then decided to take the plunge, first with my old 2012 Dell XPS. I chose that because it had one issue that made me abandon it: the brightness settings, which couldn't be adjusted and stayed maxed out at 100% constantly (which I thought was a hardware issue). I had before this spent hours before trying to get that brightness thing fixed.
 ...Instead, and magically, Ubuntu did some sorcery to the brightness drivers: that machine's brightness worked again. It just did. A full cure. With zero config.
 I also noticed that despite the 4GB on that laptop, Ubuntu was running fast. Maybe not objectively 'fast', but it felt smooth - smoother than in Windows; I first noticed this with the scrolling in Chrome and in Sublime Text. That machine could now acceptably run Pycharm and Datagrip and heavy scripts too, which was surprising. That made me consider that Ubuntu would perform better on better specs.
 So I took the leap. I've another PC with the same specs as my beast machine (but without the GTX1080), and installed Ubuntu fully on it, cleaned out everything and put on LUKS for disk-encryption. I've just been warbling-garbling in happiness all day as a result. Because after customising it properly, this thing just screams. I'm not sure if it's just me, but:
 
Browser rendering is crazy fast -- tabs/windows close and open instantly (which was never and still not is my experience even with freshly formatted copies of Windows 10).
 LibreOffice opens instantaneously, compared to Microsoft Word.
 VMWare Pro runs my office copies of Windows 10 VM images at speeds indistinguishable from my current live Win 10 box too. (The office copy has special court-filing related Java software, which is why I install it in an image, rather than letting it pollute my main box.)
 Steam on Windows/for Linux runs the games I play perfectly.
 Japanese IME support is smooth and super fast.
 I'm really impressed with Linux's filesystem (the '/' nomenclature), which is well-designed and thought out, compared to the haphazard registry and Program Files/Local/Appdata placement of files in Windows.
 
I've a few niggling issues still -- e.g. there's some Japanese software I use, which has only Windows support - and while that software is functionally sound in Wine, the menu interface is... not pretty, even after installing Microsoft font support. Launchy, while available, doesn't work as well as in Windows, and has problems launching *.desktop files. The fantastic Everything search engine is missing, so I've had to use Fsearch, which doesn't have an extensive search setup. And Linux text expansion software is generally poor for choice -- I've had to employ Autokey + Python for a lot of things, whereas in Windows there's a lot of choices (like Breevy, PhraseExpander, etc). If it matters -- I'm a lawyer, so software like these are necessary, and not having them (or they're not being able for purchase) is disappointing. I also write a lot in Python in Windows, so there's some inconsistency/way of doing things with the Linux terminal which I've to relearn. 
 But otherwise, I'm really surprised, and extremely pleased, with the speed, performance, security and privacy and peace of mind I'm getting.
 To the guys at Ubuntu/Canonical, and to Linus T and friends: you guys are awesome. Thank you so much. I'm sticking around, and figuring out more of Ubuntu, and will do my part to contribute to the ecosystem in time. 
 
   submitted by    /u/annoir  
[link]   [comments]



AI-Driven Python Code-Completion Tool 'Kite' Attracts $17M In Investments
Sat, 02 Feb 2019 18:31:45 +0100
An AI-enhanced tool that suggests code snippets for Python developers in real time just raised $17 million in VC funding to expand its R&D team "with a focus on accelerating developer productivity."
 
 An anonymous reader quotes VentureBeat:

"Our mission is to bring the latest advancements in AI and machine learning (ML) to make writing code fluid, effortless, and more enjoyable," explained [founder Adam] Smith. "Developers using Kite can focus their productive energy toward solving the next big technical challenges, instead of searching the web for code examples illustrating mundane and frequently repeated code patterns...." 

Instead of relying on the cloud to run its AI engine, Kite now runs locally on a user's computer, letting developers use it offline and without having to upload any code. (Kite still trains its machine learning models with thousands of publicly available code sources from highly rated developers.) Furthermore, running locally allows Kite to fully operate with lower latencies... In addition to ditching the cloud, the new version of Kite brings a feature the team calls Line-of-Code Completions. Until now, Kite's machine learning models could only suggest the next "token" in a line of code. Line-of-Code Completions can complete entire function calls with a single keystroke... The team boasts that Kite is "the only developer product on the market to offer such advanced completions." 
"Today, Kite is used by more than 30,000 Python developers worldwide," reports VentureBeat, adding it locally-based ML plugin is available for top Python IDEs including Visual Studio Code, Atom, Sublime Text, PyCharm, IntelliJ, and Vim. 
Kite's investors include the CEO of GitHub, as well as the founders of Dropbox, Paypal, and Twitch.tv, and the company hopes to eventually support more languages, starting with either Java, JavaScript, or Go.









Read more of this story at Slashdot.



From Install to running python with PyCharm on Ubuntu 18
Tue, 29 Jan 2019 21:00:27 +0100
  submitted by    /u/gerryjenkinslb  
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Help with PyCharm and Shell scripting
Thu, 17 Jan 2019 23:00:14 +0100


Hi!, I'm new to the linux/python world, I've worked with other languages, but I'm having issues with Python and shell scripting on PyCharm, can anyone help me by explaining the repositories I need to import, or is there any tutorial that might help me with this? 
 
 any help is much appreciated! 
 Cheers!
 
 
   submitted by    /u/Flkmeyer  
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JetBrains: Die 2018.3-Updates für IntelliJ IDEA, PyCharm und GoLand
Thu, 22 Nov 2018 13:19:25 +0100
Planmäßig liefert der Tool-Hersteller JetBrains die neuen 2018.3-Versionen der Entwicklungsumgebungen IntelliJ IDEA, PyCharm und GoLand.


Let's see why Flatpak and sandboxing are awesome! (Also, a response to the recent Flatkill page)
Thu, 11 Oct 2018 03:15:14 +0200


Okay, so sometimes I see some misunderstandings about Flatpak going around, and this interesting page unfortunately has not done much to help. I figured I'd take a brief moment to try and give a bit of an explanation of how exactly it works and why it's even a thing.
 Portability
 I'm not going to bother with this too much, since I think everyone knows this is one of Flatpak's main points. However, I've seen some people say that distro packaging helps improve security because of the people reviewing everything first.
 Distro packaging can bring its own set of interesting problems, but this only works for packages they want to accept. Closed-source packages, where malicious software would realistically come from, are downloaded from the internet and never go through the actual distro screening. The only thing it really does is cause a higher barrier of entry for the average user trying to deploy their applications.
 Sandboxing
 This is the #1 question I see: why do we need sandboxing? It's easy to imagine when it comes to commercial applications, but it doesn't seem immediately obvious as to why you'd need it for an average application.
 However, sandboxing isn't just for malicious software. Remember: security vulnerabilities are a thing! Imagine your open-source messaging client got a security vulnerability. Now an attacker can send a malicious message, run arbitrary code, and be able to see...the application's other data. Yup: most applications that use GTK+ 3 or Qt 5 (more on this later) will usually have pretty thorough sandboxing. More portals are being created to cover more things (such as the infamous webcam), but even in its current state, if GNOME MPV were to come across an infected file, not much would really happen.
 Sandboxing (redux)
 Okay, now comes the main part of the Flatkill page:
  Almost all popular applications on flathub come with filesystem=host, filesystem=home or device=all permissions, that is, write permissions to the user home directory (and more), this effectively means that all it takes to "escape the sandbox" is echo download_and_execute_evil >> ~/.bashrc. That's it.
 This includes Gimp, VSCode, PyCharm, Octave, Inkscape, Steam, Audacity, VLC, ...
 
 First off, Flatpak has actually solved this problem. It has a concept called "portals", which let applications tap into the host for various reasons. The default filesystem portal will send a D-Bus message to your desktop environment, which will display an open or save dialog and then expose only the absolute minimum to the Flatpak'd app.
 If this is the case, then why do all these apps require filesystem permissions? Look a second. Is there anything they share in common?
 GTK+ 2!
 Filesystem portals are used by GTK+ 3 and Qt 5, but GTK+ 2 doesn't support them. This also impacts applications built with Electron 1, since it didn't switch to GTK+ 3 until Electron 2.
 Of course, this problem will gradually disappear over time. GIMP is moving GTK+ 3, Inkscape already has it working in the trunk, and Electron apps like Discord will gradually move over to Electron 2 (Zulip already has).
  To make matters worse, the users are misled to believe the apps run sandboxed. For all these apps flatpak shows a reassuring "sandbox" icon when installing the app (things do not get much better even when installing in the command line - you need to know flatpak internals to understand the warnings).
 
 This has nothing to do with Flatpak itself; if you install from the command-line, then you'll see all the permissions (this came out shortly before 1.0). This is an issue with GNOME Software. I'm not arguing it's not a problem, but it's hardly worth an entire section of this page.
 Runtime updating
  CVE-2018-11235 reported and fixed more than 4 months ago. Flatpak VSCode, Android Studio and Sublime Text still use unpatched git version 2.9.3.
 
 This was a pretty unfortunate issue; the way runtimes are built has entirely changed with org.freedesktop.Platform 18.08, and as a result it took a long time to get out, and not all applications have upgraded to it. Eventually everything will have moved over, at which point this will no longer be an issue.
 In addition, the new system makes it easier for runtimes to have LTS support for at least 2 years. That means major issues like this requiring migrations aren't really going to happen.
 Desktop integration
  Running KDE apps in fakepak? Forget about desktop integration (not even font size).
 
 Okay, I genuinely have no clue what exactly they're referring to here... KDE itself has embraced Flatpak has a method of application distribution, and it's Kube's primary method of distribution.
 Other security
  Up until 0.8.7 all it took to get root on the host was to install a flatpak package that contains a suid binary (flatpaks are installed to /var/lib/flatpak on your host system). Again, could this be any easier? A high severity CVE-2017-9780 (CVSS Score 7.2) has indeed been assigned to this vulnerability. Flatpak developers consider this a minor security issue.
 
 I'm honestly not sure how a security issue with Flatpak while it was still in beta and an out-of-context phrase from the changelog mean that it's terrible...
 Summary
 I'm personally all-aboard the Flatpak hype train! If you have any other doubts, please remember to take a look around instead of reading random stuff on the internet, because the internet has a tendency to...well, exaggerate stuff sometimes... ¯\_(ツ)_/¯
 Side note: I find it interesting that a page mentioning Flatpak and the "cornerstone of linux security" doesn't use HTTPS...
 
   submitted by    /u/kirbyfan64sos  
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Looking for buying suggestion
Wed, 26 Sep 2018 21:15:16 +0200


Hey there, I am using KUbuntu for last year or so. At the moment I am using it on a notebook with 2gb DDR3L Ram and a BayTrail M Quad Processor. I now am looking for a now laptop for around 300€-400€. Do you have any suggestions for a new one. I need about 8gb Ram for coding Python with PyCharm. I already own a SSD so there is no need for this.
 
   submitted by    /u/Edeiir  
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[Rant] Why is curl | bash still a thing with this abundance of package managing systems?!
Sun, 09 Sep 2018 20:15:26 +0200


I am an infrastructure guy, who takes an software development course to understand what developers are building nowadays, talk about microservices and stuff.
 And i currently prepare for that course, not easy, but okay. but what REALLY is getting to me is this attitude not to bring in the stuff of developers in maintained repositories. There are still too many kinda-install-via-curl-pipe-bash installation mechanism out there. And with the advent of devops it seems to get worse.
 We as a software community have following repository systems
 
deb/rpm (with tools like fpm and aptly not that hard to use)
 appimage
 flatpak
 snap
 linuxbrew
 guix/nix
 pkgsrc
 fuckin containersystems like lxc and docker with stuff like hub.docker.com
 
Applications like Idea or Pycharm be available via snap or flatpak, but that is shaky too, but WHY for the love of god do framework and library developers do not commit their stuff to repositories like the above? if you are lucky, you have something like pypi, but even that is not always available. and sometimes that even worsens the problems. Because you need to know just ANOTHER repository type and their quirks.
 For Users, the Dependency world may be nice. But for developers, integrators and admins it sure is like a dystopia. TLDR: Rant about curl | bash instead of nice repository installation mechanisms.. 
 
   submitted by    /u/linuxlover81  
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How do you all handle children with computing and access to linux?
Wed, 01 Aug 2018 16:45:18 +0200


Hey /r/linux!
 I have had my son, just shy of teen years, using ubuntu on a junky laptop for a while and things have been AOK. Linux itself is great for him, although he wants to be able play more games... don't we all?
 As with anything, too much access is bad. I see it in his phone usage, so we have had to take it away and are guarded on his access to any other devices. Main issues are access to youtube and other video sites - as great as stuff can be on there, there is easily as much or more bad stuff. Another thing is limiting the apps he can access on a schedule. 
 An example from 6:30pm to 8:30pm he could access YouTube through the browser - or a total of an hour or two a day that would tally it, but can always get on pycharm or scratch, maybe wikipedia or learning sites and they dont count against the tally. 
 For access, I would thinking I could use a cron job to swap out the hosts file with something blocking sites most of the time and swap in something more permissive for the whitelisted hours. 
 Does anyone employ anything similar, or have any suggestions on solutions that exist? How has your experience been? 
 Thanks!
 
   submitted by    /u/SmokingSignals  
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JetBrains: Die Updates für IntelliJ IDEA, PyCharm, CLion und GoLand
Thu, 26 Jul 2018 10:48:25 +0200
Alle Quartale wieder: Der Tool-Hersteller JetBrains hat die neuen Versionen der Entwicklungsumgebungen PyCharm, IntelliJ IDEA, CLion und GoLand veröffentlicht.


Ubuntu 18.04 WSL on Windows 10 -- Is it any good?
Sat, 19 May 2018 14:15:05 +0200


Hi all,
 Here is the brief TL;DR: 
 I have to switch to Windows 10 from Linux and I was wondering if anyone can recommend running Ubuntu as a WSL and if so, where / when do you find it useful?
 Here is the longer story:
 I just bought a new laptop that came pre-packaged with Windows 10, but I was going to install Linux Mint on it right after unpacking it. Unfortunately, that didn't work out due to this problem.
 So, unwillingly, I decided to give Windows a go.
 I can't say I like it, but I guess I'll have to make it work, as some of the workarounds (examples here and here and FYI, updating BIOS, disabling secure boot and changing SATA mode to AHCI did not resolve my kernel panic problem) to overcome this issue could potentially damage my expensive machine.
 Right after getting started with Windows 10, I noticed that you could install Ubuntu 18.04 as a "Linux Subsystem" (WSL) so I was wondering if it could somehow make my life easier. At this stage, I cannot imagine exactly how it works other than allowing you to use the bash to navigate your system. To get a sense for how the WSL could help, I had a brief look at how I might be able to connect an IDE to Python running on Linux and it doesn't look that straightforward.
 Does anyone have any experience with running a Linux subsystem on Windows? If so, what do you think of it? Is it actually useful?
 Thanks for reading!
 
   submitted by    /u/de1pher  
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Entwicklungsumgebung: JetBrains aktualisiert PhpStorm und PyCharm
Thu, 30 Nov 2017 09:18:53 +0100
Die Update-Welle der IDEs von JetBrains läuft. Python-Entwickler finden vor allem Performanceverbesserungen in PyCharm, und PhpStorm erscheint kurz vor dem geplanten Release von PHP 7.2, das es wohl noch nicht berücksichtigt.


Python For Ethical Hacking - #2 - Installing Pycharm & Creating Our First Script
Mon, 23 Oct 2017 19:49:19 +0200


				


PyCharm 2-0 / 2017 Buffer Overflow
Fri, 14 Jul 2017 07:19:32 +0200
PyCharm 2-0 / 2017 suffers from a command-line buffer overflow vulnerability.


Python-Lern-IDE PyCharm Edu 3 mit adaptivem Kurs und Debuggingoptionen
Sat, 13 Aug 2016 17:01:45 +0200
Mit der neuen Version der auf das Lernen von Python ausgelegten IDE soll vor allem das Erstellen von Kursen leichter fallen. Lernbegierige hingegen können nach dem Update eine individuellere Schulungsmaßnahme testen.


Python-Lern-IDE PyCharm Edu 3 mit adaptivem Kurs und Debuggingoptionen
Sat, 13 Aug 2016 17:01:45 +0200
Mit der neuen Version der auf das Lernen von Python ausgelegten IDE soll vor allem das Erstellen von Kursen leichter fallen. Lernbegierige hingegen können nach dem Update eine individuellere Schulungsmaßnahme testen.


JetBrains PyCharm Professional 2016.1.4 DLL Hijacking
Sat, 09 Jul 2016 05:38:40 +0200
JetBrains PyCharm Professional 2016.1.4 suffers from a dll hijacking vulnerability.


JetBrains PyCharm Professional 2016.1.4 DLL Hijacking
Sat, 09 Jul 2016 05:38:40 +0200
JetBrains PyCharm Professional 2016.1.4 suffers from a dll hijacking vulnerability.