Doors – Server-Driven UI Framework for Go (SSR, State, Routing)

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It has reactive state, components, lifecycle control, SSR by default, and an HTTP API-free architecture. Highlights * Explicit and type-safe DOM manipulations * State is a communication primitive first, a render driver by choice * No coupling between state primitives, components, and dynamic containers — combine them into your own abstractions or use directly * URI decoded into a struct and exposed as a state primitive * Built on top of templ Core advantages over Phoenix LiveView * Non-blocking event handling and parallel rendering * Syncs via short-lived HTTP requests, taking full advantage of QUIC * Event hooks as separate HTTP requests, so forms are sent as native form-data It’s free for development and non-commercial production use. Licensed under BUSL-1.1 (each release goes open source after 4 years). Docs & tutorial: https://doors.dev Article series on dev.to: https://dev.to/derstruct/you-dont-need-npm-to-ship-fully-fea...

Visit product View on Hacker NewsSep 22, 2025

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Launch Intel predictions

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

80%80% 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: open source, io · Missing: https docs, excited, just released

60%60% 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: para · Missing: supports, reddit linkedin, podcasting

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

35%35% 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

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

14%14% 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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