JS

JSON-up – Like database migrations, but for JSON

Hacker News

JSON-up – Like database migrations, but for JSON

When you store JSON locally - app data, config files, browser storage - the schema inevitably changes between versions. New fields get added, old ones get renamed, formats evolve. Without a migration system, you end up with brittle ad-hoc upgrade code or broken user data. I built json-up, a small TypeScript library that lets you define a chain of versioned migrations that transform JSON data step by step. It's type-safe, so the compiler catches mismatches between versions. Originally, I needed this for upgrading local app data between mobile app releases for Whisper, but it works for anything where JSON schemas drift over time. Happy to hear what you think. --- json-up: https://github.com/Nano-Collective/json-up Whisper: https://usewhisper.org

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, code · Missing: mac, agents, macos
64%64% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
33%33% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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