Pr

Practice Leetcode problems on your phone

Hacker News

Practice Leetcode problems on your phone

Hello everyone, I've been working on a project called CodenQuest, a coding practice app inspired by platforms like LeetCode, but with a major twist: it's heavily gamified, similar to Duolingo. The main goal is to make coding practice more engaging, especially on mobile. Key Features: - Diverse coding questions with integrated hints and timers. - Code editor with code completion and fill in the blanks questions - Performance statistics (runtime, memory, CPU usage, and more). - Gamified elements: leagues, ranking systems, daily challenges, friends, and streak mechanisms. - Available on iOS and the Web. I’ve put a lot of energy in this project and I am personally proud of the final look. I'd be grateful if you could take the time to check it out and give your valuable feedback. Thank you so much! iOS: https://apps.apple.com/us/app/codenquest/id1671648294 Web: https://codenquest.com/

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
92%92% 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: apple, apps, coding · Missing: mac, agents, macos
83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, video
60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, io · Missing: https docs, excited, just released
30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% 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.

Correct prediction on native model

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