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Write Code to Solve Minigames

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Write Code to Solve Minigames

Hi HN! Codyssey is a small programming game where you write Python functions to solve minigames. Think pong, flappy bird - the functions serve as a control mechanism for the player. It evolved from an end-of-year activity I made for an introduction to programming class for 9th graders, difficulty has been adjusted obviously. I ran it as a workshop / competition at several conferences, now considering making it available as a small game. Some technical details: It runs python in the browser with Brython [0], I originally used Pyodide but it was too heavy for conference WiFis. Code editor is Ace [1]. I'd love to hear your feedback :) [0] https://brython.info/ [1] https://ace.c9.io/

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
77%77% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: activity, code · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, 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 · Missing: mobile apps, ios, personal
37%37% 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
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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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