Esolang Park, an online visual debugger for esolangs

Hacker News

Hey HN! Esolang Park is an online visual debugger interface for esoteric programming languages, that I've been working on for the past few months. For every supported language, Esolang Park provides the powerful Monaco code editor, syntax checking, debugging functionality and a visualisation of the runtime state. The core is language-agnostic - a "language provider" only needs to implement the esolang's parser, interpreter and visualisation UI (and some other little stuff). Apart from trying to boost DX for esolangs, the idea is for this to grow into a platform where people can discover and play around with a variety of esolangs without leaving the browser. That's quite far away though - the project is quite early in development and currently only has 5 languages (Befunge-93, Brainf*ck, Chef, Deadfish and Shakespeare). Happy to hear any feedback (and bug reports too)!

Visit product View on Hacker NewsFeb 22, 2022

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

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

70%70% 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: visual, code · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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