FastFN – a polyglot file-based runtime for APIs and SPAs

Hacker News

Part of the idea comes from liking the simplicity of older CGI-style models: put code in a place, map it to a route, and keep the deployment model understandable. FastFN takes that in a more modern direction with multiple runtimes, local dev, OpenAPI, and a simpler path for mixed API + frontend projects. It supports Python, Node, PHP, Lua, Rust, and Go in one project. This started as a weekend project that got out of hand. I am thinking were to take it next now. Docs: https://fastfn.dev/ Repo: https://github.com/misaelzapata/fastfn

Visit product View on Hacker NewsMar 29, 2026

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

75%75% 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.

Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released

68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created

47%47% 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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

Incorrect prediction on native model

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