Jl

Jlq – A CLI to easily tail+query JSON log files using Rust+SQLite

Hacker News

Jlq – A CLI to easily tail+query JSON log files using Rust+SQLite

Hi all! It's been a while since I posted something. Wrote this back in November to scratch an itch regarding tailing logs locally for multiple services. I know we all love jq...but I'm quite comfortable with SQLite and SQL so just wanted to use that instead. Published my first Rust crate today! My first public Rust project so be gentle :) . Hope you enjoy it! https://crates.io/crates/jlq https://github.com/hamin/jlq

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
64%64% 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 · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos
36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
27%27% 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
12%12% 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.

Correct prediction on native model

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