Tuc – When cut doesn’t cut it

Hacker News

Announcing `tuc`, a utility similar to coreutils `cut`, but more powerful. It allows to split text or bytes into parts and reassemble them in any order. I always found `cut` very practical for some tasks where `sed` or `awk` were overkill or awkward to use, but I also felt the need for more features. Some key differences from `cut`: - parts can be referenced by negative indexes - delimiters can be any number of characters long, or match a regex - can split text into lines, and reassemble them

Visit product View on Hacker NewsJun 13, 2022

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

62%62% 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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

15%15% 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

11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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