jsonpipe - stream JSON tweaks toolkit in GO

Hacker News

Hi, after I switched jobs I encountered a problem with "correcting" JSONs. The rules of changes were repetitive and boring... So I thought: what about a toolkit I can use like a "single command" to make my changes? JsonPipe is a streaming JSON transformer for when you want to tweak JSON without the ceremony of unmarshaling into structs and patching things up afterward. Just define rules like “drop this” or “rename that” and let it flow. It won’t outpace gjson/sjson — and it’s not trying to — but if you like the idea of modifying JSON mid-stream with minimal fuss, give it a shot. Or don’t. It won’t take it personally. I'm still developing and adding more and more features that I see feasible. Thanks, Peace!

Visit product View on Hacker NewsSep 30, 2025

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

61%61% 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 NewsMay not resonate with HN audience · Strong signals: ide, pipe · Missing: https docs, excited, just released

49%49% 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 · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

46%46% 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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

34%34% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

16%16% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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