> I tried SQLite first, but its extension API is limited and write performance with custom storage was painfully slow
For many use cases, write performance does not matter much. Other than the initial import, in many cases we don't change text that fast. But the simpler logistics of having a sqlite database, with the dual (git+SQL) access to text is huge.
That said, for the specific use case I have in mind, postgres is perfectly fine
2) You can do more complex analyses faster and easier (you don't need to pipe the git outputs) since it's just SQL
but pgit is not meant to replace git.
- "Checking out" a specific branch (which can be reasonably slow)
- Query all files and folders in path `/src`
- Query all files and folders in path `/src/*` (and maybe with extra pattern matches)
- Be able to read contents of a file from a certain offset for a certain length
These are similar to file system queries to a working directory
Is there an example of the tool enabling LLM 'discovering' something non-deterministic and surprising?
Did you find you needed to give agents the schema produced by this or they just query it themselves from postgres?
even humans don’t do this unless there’s a crazy bug causing them to search around every possible angles.
that said, this sound like a great and fun project to work on.
1) commit messages often capture the "why" something changed - versus the code/tests which focus on the what/how for right now.
2) when you have a regression being able to see the code before it was introduced and the code which was changed at the same time is very helpful in understanding the developer's intent, blindspots in their approach, etc.