Sublime-Text Syntax Highlighting but for the command line

Hacker News

Hi HN, I'm new to the community, and after some lurking around from the shadows, I decided to debut with this project. It surely needs to be refined, but it is usable. Personally, I find it very useful and I always wanted to have something like this, but it would have been rather difficult and pointless IMO to create my own syntax highlighting and color scheme format, only to then be forced to also write many different syntaxes from scratch. So I thought, hey, Sublime Text is probably one of the most used text editors and already has many syntaxes and color-schemes already implemented, why reinvent the wheel! And so sublhighlight was born... Feedback is highly appreciated!

Visit product View on Hacker NewsOct 14, 2024

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Did not reach leaderboard

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

60%60% 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: new · Missing: mac, agents, macos

59%59% 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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% 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

20%20% 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.

Incorrect prediction on native model

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