Pixpy – "Oldschool" Python graphics library

Hacker News

Pixpy is a graphics library for python that makes it really easy to create small graphical applications or games. Some highlights: - A "Console" for both text input/output and tile graphics - Composable, lightweight image handling using only GL textures - Float2/Int2 types for 2D math Its inspired by projects like AMOS/STOS and other 2D/Game oriented Basic programming environments of old and runs on Windows, Mac & Linux. It is hopefully a good environment to learn programming. I have a lot of examples at https://github.com/sasq64/pixpy-examples and I made a short video at https://youtu.be/MKxGrsfhYsQ

Visit product View on Hacker NewsApr 16, 2024

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

73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, using · Missing: agents, macos, agent

32%32% predicted probability of success on Product Hunt, 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

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

Incorrect prediction on native model

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