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I wrote a Logo interpreter using JavaScript

Hacker News

I wrote a Logo interpreter using JavaScript

Hi everyone - I wrote a Logo interpreter in JavaScript, no regex, no external libraries. https://logo-lang.pages.dev I wanted to understand how interpreters work but I struggled with the regex that's used to implement parsers for most interpreters. Logo's syntax is simple and it allowed me to implement it without regex. There are no external libraries - SVG is used for drawings. I wrote a short book about the project: https://alabhya.gumroad.com/l/logo Source: https://github.com/alabhyajindal/logo

Visit productView on Hacker NewsMay 18, 2024
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Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
63%63% 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
58%58% 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
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos
41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
29%29% 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
18%18% 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
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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