Esolang Park, a 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). Some features like non-debugging execution mode (0ms interval) are missing too. Currently the entire source code[0] (core + language providers) is written in TypeScript and React. Esolang code execution happens in a web worker. I'm planning to add support for WASM-based language providers for better performance, particularly for non-debugging execution. There's also a wiki[1] containing a description of the core design and a guide for implementing and contributing new language providers. Looking to hear some feedback on the idea and current implementation - bug reports are welcome too! [0] https://github.com/nilaymaj/esolang-park [1] https://github.com/nilaymaj/esolang-park/wiki

Visit product View on Hacker NewsFeb 26, 2022

Share card

Actual performance

53points

6comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

46%46% 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

36%36% 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

15%15% 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

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

Correct prediction on native model

Similar products

Esolang Park, an online visual debugger for esolangs70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Esolang Park, an online visual debugger for esolangs

Hacker News2

Park Turtle19%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Boat Park Tracking for Sailing Clubs

Indie Hackers

Luna Park45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Visual scripting platform for webdev.

Indie Hackers1productivity

ThrillEats65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Park Dining Made Easy

Indie Hackers1food-drinks

Park.IO adds .me backorders60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Park.IO adds .me backorders

Hacker News5

DiscoverNP32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Collect National Park stamps

Indie Hackers1travel

South Park in CSS66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

South Park in CSS

Hacker News6

Starter Park to EDA28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Starter Park to EDA

Hacker News2

Awesom-O from South Park built with GPT-252%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Awesom-O from South Park built with GPT-2

Hacker News4

Build your own theme park51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Build your own theme park

Hacker News58

Browse all products Analyze your launch