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An Online Playground for ArkScript

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An Online Playground for ArkScript

For context: ArkScript is a small scripting language in C++, made to be easy to embed in apps, quite minimalistic When I started working on a website for ArkScript, I drew inspiration from other proglang websites to see what I could show, what appeared to work or not work to grab people attention. What I got out of this was a good documentation going straight to the point (I think I'm on a good track, though this can always be improved) and a playground so visitors can try the language without installing/compiling anything. Here we are now, with a very minimalistic playground, that was forked from another project with way more functionalities ( https://github.com/ryusatgat/ryugod ), tailored for ArkScript and the needs I have (using it as a playground/small online IDE on the go and to embed it in the project documentation so that you can try code as you read). I'm not an expert in webdev nor in VueJS so the code isn't pretty and could be enhanced, but it works and I've done all I can on the security side (hardened docker image ; execution timeout ; limits on CPU, RAM and PID usage ; removed access to shell through `sys:exec` from the language (the functionality isn't even compiled) ; filtering user input to remove "dangerous" characters before sending them to the tty (so that you can't send ^C and get a shell)). The playground code: https://github.com/ArkScript-lang/playground The language code: https://github.com/ArkScript-lang/Ark

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, dock · Missing: mac, agents, macos
79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
78%78% predicted probability of success on Indie Hackers, 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
58%58% 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 · Missing: plus, platform, intuitive
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: apps, way · Missing: mobile apps, ios, personal
46%46% 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
14%14% 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.

Incorrect prediction on native model

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