Griffe, load Python APIs, find breaking changes

Hacker News

Hey all, Griffe was already submitted two years ago on HN, but it nicely evolved since then so I figured I'd submit it again myself, especially since I just finished rewriting its documentation and reworking its API :) Griffe is a Python tool and library to load Python APIs as whole program signatures, kinda. With this data, static site generators can generate API docs. Griffe itself can use the data to compare two versions of your API and find breaking changes. No excuses for not bumping your major semver version now! Griffe is used by mkdocstrings (I'm the author too), and therefore indirectly used by FastAPI, Pydantic, and many other cool projects :) The docs provide a lot of hints, advice, recommendations for public APIs, deprecations, and Python code generally. They somewhat come from my own experience, and not everyone might share my opinions: happy to discuss about all this!

Visit product View on Hacker NewsJul 15, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: code, apis · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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