API for CRUD-ing JSON data

Hacker News

For purely selfish needs, I created a self-hosted API for CRUD-ing JSON data in GO. Optimized for simplicity and interoperability. Perfect for small personal projects. The API is based on your JSON structure. So the example below is for CRUD-ing [key1][key2] in file.json. The value (which can be anything) is then added to the body of the request. Moreover, there are helper functions for appending and incrementing values. DELETE/PUT/GET: /api/file/key1/key2/...

Visit product View on Hacker NewsSep 18, 2025

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

55%55% 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 HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

21%21% 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

16%16% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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