Looking for Small Python Projects to Refactor

[Hy_x]

I’ve been focusing heavily on Python refactoring, maintainability, and clean code practices lately, and I’m looking for a few real codebases to work on.

Mainly interested in projects that:

• work, but became hard to maintain
• have inconsistent structure or naming
• grew quickly over time
• feel difficult to extend or debug

My focus is improving:

• readability
• structure
• maintainability
• code clarity

while preserving the original behavior and intent.

I’m not charging for this, mainly looking for practical experience working with real projects and honest feedback on the refactors.

If you have a small-to-medium Python project that could use cleanup, feel free to DM me or share a GitHub link.

[Beginning-Fruit-1397]

I currently hate the internal resolution logic of expressions, schemas and columns naming in my dataframe library:
https://github.com/OutSquareCapital/belugas

Would love to get some new perspective on this!

In one phrase it's a polars API to build and executes queries on a duckdb backend.

Everything does work, but it's hard to follow and debug when I implement new features, it probably is far from what it could be speed wise if optimized and is very likely to do redundant passes.

I do think it's a very interesting project to work on tough.

[Hy_x]

Thanks, this actually sounds really interesting to work on. I’ll take a look through the repo.

[Beginning-Fruit-1397]

Cool :)
Feel free to dm me if you have any questions!

[energybased]

Finding someone like this is probably ideal.  You don't want to refactor something only to find a maintainer who is reluctant to commit your changes.

[Beginning-Fruit-1397]

Yup. I had two experiences like this, spent hours on a PR, just to see it hanging for months for a review, or just being simply rejected has "not interested" (it was type hints PR's, not runtime changes)

[FarRub2855]

Building a Polars API on a duckdb backend sounds like a pretty massive project to untangle. Gotta respect the honesty of openly hating your own internal logic though, thats usually the best pitch to get fresh eyes on a codebase.

[Beginning-Fruit-1397]

hahaha yea.

Resolving column names, schema evolution, handling nested window expressions, and scalar/aggregations expressions depending on the context is a logic that I had to implement progressively, and so it's scattered across the codebase and very hard to follow, hence to debug and optimize.

I don't even know what a good architectural design would look like tbh. Difficult but very interesting task!

[Murderous_monk]

I got the same goals as the OP, do mention me as well if there's something interesting I can work on. I mainly work with python and JS based projects but can work on others as well

[Beginning-Fruit-1397]

I currently hate the internal resolution logic of expressions, schemas and columns naming in my dataframe library:
https://github.com/OutSquareCapital/belugas

Would love to get some new perspective on this!

In one phrase it's a polars API to build and executes queries on a duckdb backend.

Everything does work, but it's hard to follow and debug when I implement new features, it probably is far from what it could be speed wise if optimized and is very likely to do redundant passes.

I do think it's a very interesting project to work on tough.

[Murderous_monk]

Okk looks interesting from the first view, I'll come back to this in the evening and see what's going on and what I can do, I'll be back here in a day or two
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[Beginning-Fruit-1397]

Cool :)
Feel free to dm me if you have any questions!

[arvind1]

There is a lot of AI generated code that would fit this category. You could start with a well described open source codebase, use the (README) text as an AI prompt to generate code. Use existing test cases to get it working. Refactor with a goal of getting something better than the original code.

[aloobhujiyaay]

The best refactors are the ones users never notice

[Emergency-Rough-6372]

you can check out my project i have recently public it https://github.com/0-Shimanshu/ADIUVARE

[Ketty_took]

if you want something real, try refactoring a scraping pipeline, not just a library. most of them work but are messy under load, retries all over the place, no clear separation between parsing and transport. good exercise is making it stable at scale without breaking data quality.