A

A new kind of React store

Hacker News

A new kind of React store

Hey HN! I am a developer on a break from employment. I want to use this time to recharge and work on projects that I always wanted to do but lacked energy after regular job. One of the problems that we never solved properly is web application state management. What I want is a library that: - encourages separating application state and logic from React components - makes dealing async state dead simple (like react query) - makes creating derived (computed) state dead simple (like computed properties in vue) including deriving async state - allows to create reusable logic that can be imported as a library (like react hooks) - allows to easily compose a few simple pieces of application state into a bigger logical unit that can be developed, consumed and tested separately I've played with various ideas for the last few years, sometimes going crazy that I couldn't find, or create something meeting all these criteria. Finally, a few months ago something clicked and that's how active-store was born. I am terrible at writing documentation, but I am good at writing code. Take a look at the store for a simple HN client: https://codesandbox.io/p/sandbox/headless-resonance-dfzgzw . It's just ~100 lines of code with comments. The code handles the most important aspects of loading data from HN. I think this is a good example, because the HN API is quite difficult to work with. There's more documentation at https://github.com/ziolko/active-store and another project that I used as a playground at https://github.com/roombelt/timeline . Despite the terrible documentation I encourage you to give it a try. I will be happy to answer your comments here.

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Indie HackersFits the IH revenue-focused audience · Strong signals: para, including · Missing: supports, reddit linkedin, podcasting
80%80% 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: new, code · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
69%69% 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
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, way, para · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
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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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