I made a Python app for generating scrambles for Rubik's Puzzles

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As an avid Rubik's Puzzle Solver, I wanted a small application for my desktop that I could generate scrambles with. In my searches I didn't really find anything that wasn't either a browser-based project or currently dead, so I decided to make it for myself and am now sharing it with you all! I think what makes my app stand out over the others I did come across is it's simplicity. It's an entirely one window GUI. There's no sub-windows, menus, or anything else. Current features include the following: - 2x2 and 3x3 scrambles - Stopwatch/Timer - 10 different color themes - Ability to save your desired setup with one click and have it reopen to this setup every time As a note: I'm not a developer by trade. This is just something I do for fun in my free time. If you have a suggestion or anything you'd like to see added or done differently, please let me know!

Visit product View on Hacker NewsApr 24, 2024

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

61%61% 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

53%53% 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

40%40% 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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% 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

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.

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