I

I generated API documentation for all Java packages

Hacker News

I generated API documentation for all Java packages

Hi HN! I'm excited to share a project I've been working on for the past year: Docland. It is an API documentation browser that generates documentation on demand (through compilation, not LLMs) for Java packages. Instead of relying on Javadoc, the built-in doc generator, I created the engine from scratch to give the documentations a modern look, build fast search indexes, and enable link resolution to other packages. I built Docland because I constantly found it frustrating to locate and view API definitions when programming. You'd have to Google the function/class name, skip all the SEO articles, find the page you want, yet the documentation might be poorly formatted or does not support searching. So I thought it would be really cool to create a documentation site dedicated for programming languages and libraries, so that you can find the docs all in one place with a uniform look. Docland currently only supports Java, but more programming languages can be supported thanks to its modular architecture. Please try it out and let me know what you think! Also, the process of building Docland was extremely fun and challenging. I'm happy to share about that too. Thank you! Martin

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, created · Missing: reddit linkedin, podcasting, latex
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: google · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist
67%67% 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
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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