Hi Dev !
I'm Alex, a tech enthusiast. I'm excited to show you , my take on multi-format streaming serialization. Given its readability, the Paradict text format appears de facto as an interesting data format for config files. But using Paradict to manage config files would end up cluttering its programming interface and making it confusing for users who still have choices of alternative libraries (TOML, INI File, etc.) dedicated to config files. So I used Paradict as a dependency for ". , seemed like the right giant to stand on for my new project.
Jinbase started small as a (UID) is supposed to be automatically generated for each new record, saving the user the burden of providing an identifier that could accidentally be subject to a collision and thus overwrite an existing record. After that, I implemented a search capability that accepts UID ranges for the depot store, timespans (records are automatically timestamped) for both the depot and key-value stores and and de facto. For convenience, all tables related to Jinbase internals are prefixed with jinbase_, making Jinbase a useful tool for opening legacy SQLite files to add new data models that will safely coexist with the ad hoc relational model.
All four main data models (key-value, depot, queue, stack) support Paradict-compatible data types, such as dictionaries, strings, binary data, integers, booleans, datetimes, etc. Under the hood, when the user initiates a write operation, Jinbase serializes (except for binary data), chunks, and stores the data iteratively. A record can be accessed not only in bulk, but also with two levels of partial access granularity: the byte-level and the field-level.
While SQLite's incremental I/O for BLOBs is designed to target an individual BLOB column in a row, Jinbase extends this so that for each record, incremental reads cover all chunks as if they were a single unified BLOB. For dictionary records only, Jinbase automatically creates and maintains a lightweight
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