Languages Interoperability Tool

Hacker News

Hey all! I'm sure you all know that combining programming languages is super hard. Just imagine a project with Python frontend and C# backend or PInvoke Calling C++ code in C# I created a tool that makes language interoperability easy with lightning execution speed. Additionally, languages can be combined in full programs by just simple drag and dropping We are using this tool internally at my company Zenodys. I open sourced it https://github.com/tvinko/AlgoniaEngine And you can see it in action here https://dev.to/tvinko/languages-interoperability-406f There is huge lack of documentation at the moment but it's coming soon

Visit product View on Hacker NewsJul 8, 2021

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

66%66% 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: using, code, open · Missing: mac, agents, macos

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

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, io · Missing: https docs, excited, just released

48%48% 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 · 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

12%12% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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