AntiPython Colab Compiler,use Google Colab in your preferred language

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It's a source to source compiler for people interested in AI but don't want to touch Python. It's a work-in-progress(super-raw proof of concept). Frontend is a JavaScript Chrome extension and backend is a C transpiler. We use the Treesitter C lib to parse syntax trees and the Mongoose C lib to handle websockets. GitHub repo has a Java demo showing possible import syntax. Some keywords like 'from' and 'as' don't exist in Java. I found some workarounds. Please let me know what you think.

Visit product View on Hacker NewsJan 30, 2024

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

91%91% 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 · Missing: supports, reddit linkedin, podcasting

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

46%46% 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

28%28% 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

21%21% 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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