The Moment I Realized My Python Project Wasn't Really a Project
When I first started learning Python, my projects were about as simple as they could be.
project/
├── logic.py
└── main.py
If I wanted to run the program, I simply typed:
python main.py
If I needed another function, I created another file and imported it.
from logic import calculate
Everything worked.
At the time, I thought this was what "organizing a Python project" meant.
I was wrong.
A Collection of Scripts Is Not a Software Project
Over the past few months, I've been rebuilding Python's built-in functions from scratch as a way to understand how they actually work.
Instead of solving algorithm exercises, I implemented functions like:
map()filter()any()all()max()min()
One function became ten.
Ten became dozens.
Soon I wasn't just writing code anymore.
I started writing documentation for each implementation.
I added tests.
I kept notes about design decisions.
I experimented with different implementations.
Without realizing it, what began as a few learning scripts slowly evolved into a real project.
Unfortunately, my project structure never evolved with it.
Documentation Everywhere
At first, I stored documentation wherever it felt convenient.
Some notes were inside Markdown files.
Some were buried in my note-taking application.
Others existed only inside commit messages.
Every time I came back to the project, I had to spend several minutes remembering questions like:
- Where did I explain this implementation?
- Which version of this function is the latest?
- Why did I choose this approach?
- Where are the tests?
Nothing was technically broken.
But nothing felt organized either.
That was when I realized something interesting.
The biggest problem wasn't my code.
It was the environment surrounding my code.
"Maybe I Should Treat This Like a Real Project"
My first instinct was incredibly simple.
Create a folder.
pycore/
Then create a virtual environment.
python -m venv .venv
Problem solved.
Or so I thought.
The more I read the official Python Packaging documentation, the more I realized that a virtual environment is only one small piece of a much larger picture.
I had always thought "setting up a project" meant creating a folder and installing packages.
But a reusable software project needs much more than that.
Questions I had never asked before suddenly became important.
- Where should the source code live?
- How should dependencies be declared?
- Where do tests belong?
- How should documentation be organized?
- How do other people install this project?
- What exactly is
pyproject.toml?
These weren't Python syntax questions.
They were software engineering questions.
Learning Packaging Was Really Learning Software Design
At first, I assumed Python Packaging was simply about publishing libraries to PyPI.
I wasn't planning to publish anything.
I just wanted a clean project structure.
Ironically, that decision led me into an entirely different world.
I started reading Packaging User Guide documentation.
I discovered concepts like build systems, dependency management, editable installations, source layouts, and package metadata.
None of these topics had anything to do with writing better algorithms.
Instead, they answered a different question.
How should a software project be organized so that both humans and tools can understand it?
Looking back, that was the point where I stopped thinking like someone writing Python scripts and started thinking like someone building software.
What's Next
Before deciding where my code should live or what should go inside pyproject.toml, I first needed to understand something much more fundamental.
What actually makes up a Python project's environment?
At the time, I thought the answer was simply "a virtual environment."
It turns out that was only one piece of the puzzle.
In the next article, we'll build a mental model of a modern Python project by exploring the five concepts that completely changed how I think about Python Packaging.
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