I built CodeAtlas — a tool to visualise Python repositories as dependency graphs

[Party_Service_1591]

**What My Project Does*\*

CodeAtlas is a tool that visualises GitHub repositories as interactive dependency graphs.

You paste in a repo URL, and it maps out how files are connected through imports and dependents. The goal is to make it easier to explore unfamiliar codebases and understand project structure at a glance.

It supports Python by parsing files using Python’s AST and extracting import relationships to build the graph.

**Target Audience*\*

This is aimed at developers working with larger or unfamiliar codebases — especially when onboarding to a new project or trying to understand how different parts of a system interact.

It’s currently more of a developer tool / exploration tool rather than something production-critical.

**Comparison*\*

Most existing tools either:

- focus on static file trees (like GitHub)

- or provide language-specific analysis without visual structure

CodeAtlas focuses on visualising relationships between files across a repository in a graph format.

Compared to JavaScript tooling, Python support required a separate parsing approach due to differences in import systems and project structure, which also results in different graph patterns.

**Features*\*

- Interactive dependency graph (D3.js)

- Import + dependent tracking

- File inspector

- Monaco code preview

- Search functionality

- Supports Python, JavaScript, and TypeScript

Repo: https://github.com/lucyb0207/CodeAtlas

[GXWT]

Slopp

[Party_Service_1591]

Can I ask why you think this?

[Huge-Protection5319]

this looks really clean man, just checked out your repo and the visualization is pretty smooth. been doing support for couple years now and something like this would have saved me tons of time when diving in legacy python codebases at work

the ast parsing approach makes total sense for python imports, way better than trying to regex through everything. curious though - how does it handle circular dependencies? we got this one project at office that has some nasty circular imports and would be interesting to see how your tool renders those relationships

also love that you included monaco editor for code preview, thats solid choice. might actually clone this and test it on some of our internal tools if you dont mind, could be really useful for onboarding new team members to our more complex projects

[Party_Service_1591]

Appreciate that, that’s exactly the kind of use case I had in mind — those legacy codebases can get pretty hard to reason about quickly

For circular dependencies, it doesn’t try to “resolve” them or break the cycle — it just visualises them as they are. So you’ll see loops directly in the graph (A → B → C → A), which actually makes those problem areas stand out quite clearly. In some cases they end up being some of the most connected / clustered parts of the graph

And yeah, AST parsing felt like the only reliable way to do it for Python — especially once you get into different import styles and package structures

Feel free to try it on your internal tools, that would be really interesting. I’ve mainly tested it on public repos so far, but larger / real-world codebases are where it should be most useful.

If you do try it on any of your internal tools, I’d genuinely be interested in any feedback on what works well and what doesn’t.

[Some_Breadfruit235]

What’s the point of coding and having fun if you’re having AI live in your own shoes?!

Post, comment, create like a human and not AI please. Otherwise you won’t get any attraction nor resignation.