My Rust-based Tetris game with advanced features

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Hey everyone, I wanted to share my latest project with you. I've created a Tetris game using Rust and the Cursive TUI library. It has all the basic features of Tetris, but I've also added some advanced features that reduce the number of keys you need to press. One of the most useful features is the leftmost and rightmost block movement. This means you can move a block all the way to the left or right of the screen with just one key press. I've also included a counter-clockwise rotation feature, which makes it easier to get your blocks into the right position. If you're interested in checking it out, you can find the source code on my GitHub repo. Thanks for taking the time to read this, and I hope you enjoy playing my Tetris game! https://github.com/genieCS/retris demo: https://youtu.be/S2iB4frfaLo

Visit product View on Hacker NewsJun 9, 2023

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

62%62% 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 · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

57%57% 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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% 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

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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