Dak – a Lisp-like language that transpiles to JavaScript

Hacker News

Hi HN, author here. Happy to answer any questions. I had an itch to make a lisp like language that was a thin layer on top JavaScript. Something that could leverage the thriving ecosystem that exists around JavaScript. It's brittle, hot off the oven. Besides being a fan of parenthesis, I think macros fill in a gap that the JavaScript ecosystem today fills in with one-off compilers, bundler plugins and such. Macros can't do everything, but for example I think they have the potential to enable things like JSX, Solid and Svelte style libraries. Take the tour to get a feel for what it can do and play with the live code in your browser!

Visit product View on Hacker NewsFeb 27, 2023

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

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, ide, io · 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.

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.

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

50%50% 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

37%37% predicted probability of success on AppSumo, 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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