Old Show HN post: https://news.ycombinator.com/item?id=46945343#46945443
But I have a dev branch where I am trying to get tree-sitter to work. As its ecosystem is an absolute beast when it comes to the amount of languages it supports this would definetly be my preferred method over doing all the languages manually.
The main challenge is normalizing the Trees and making sure all nodes are in a comparable state when we visualize them. (otherwise vsiualizing multilingual Codebases would be a real Pain)
Why AST? -> Simple regex or string parsing fails as soon as you hit complex decorators or nested classes. By using Python’s native AST module, we can get an objective map of the logic flow that doesn't care about formatting or comments.
The Visualization Challenge-> Rendering a dependency graph for a repo with hundreds of files can quickly turn into a laggy hairball. We spent a lot of time tweaking the D3.js force-directed graph parameters to ensure that nodes self-organize in a way that highlights clusters rather than just creating a mess.
Why Server-side? -> We chose server-side processing to handle larger repositories without crashing the user's browser (Numpy, FastAPI etc.), but we've architected it to be non permanent. The code lives in RAM just long enough to be parsed into a JSON structure for the frontend, then it's gone.
Next steps: -> I’m looking into adding Javascript, html and css support to make debugging the frontend much easier.
Hi HN,I built ast-visualizer.com because I wanted a way to visualize the architecture/structure of a Python repo before dived into the code.Most tools tell you what the code does; I wanted to see how it's built.The Problem: Onboarding onto a large codebase is a nightmare. LLMs help with single functions, but they struggle to show you the "God Objects," circular dependencies, or high-complexity...