LineSelect, shell utility to interactively select lines in a pipeline

Hacker News

Allows you to "pause" a shell pipeline to interactively select a subset of lines to proceed with. I've always wanted a tool like this, as it effectively combines the best of shell pipes (easy to automate) and visual file managers (easy to make selections). Now that I have it I can't believe a tool like this is not already part of the standard set of shell utilities. There are so many situations where it is useful. Tested on Linux but should also work on MacOS. Also: please help me come up with a better name!

Visit product View on Hacker NewsJul 5, 2023

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

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

14%14% 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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