YeetCode
Make LeetCode competitive and fun
What it does
Built by students at Stony Brook, YeetCode turns coding interview prep into a competitive, social experience. Instead of grinding LeetCode alone, you can duel friends in real-time, join groups, and climb leaderboards to stay consistent. What’s new: real-time head-to-head duels + social accountability layer on top of traditional practice. We built this because solo prep gets boring — this makes you actually come back and practice.
Does a similar job
all alternatives →- IMI made a spaced repetition tool to master coding problems2024 · lanki.xyz · ▲206
As you solve LeetCode questions, you can mark them as hard, medium, or easy. The tool will then recommend questions you should review based on (1) how hard the question was for you and (2) how much time has passed since you last reviewed it. I'd recommend normally attempting LeetCode problems and just marking them as hard, medium, or easy for you at first so the tool knows which problems to recommend you review! Here's the theory behind spaced repetition and learning if interested: https://www.codecademy.com/article/spaced-repetition
- CACodeRev.app – Code Review as Interview2024 · coderev.app · ▲150
I've long had a dislike for leetcode interviews on both sides of the coin. Project-based interviews can also be challenging because it can end up filtering out folks who don't want to spend several hours building something in their free time. I met up with a friend last year -- a very senior dev -- who had taken some time off to study leetcode exercises while preparing for FAANG interviews. It struck me that one of the key measures of whether a candidate is a fit for a team is rather synthetic. CodeRev.app is a simple, lightweight tool that helps teams evaluate candidates using code reviews.…
- LLLearn LLMs LeetCode Style2025 · github.com · ▲181
Openleetcode – Local LeetCode runner where tests live in the repo19d ago · github.com · ▲73You write a standard solution, just like on LeetCode, and run it through the CLI. It identifies the problem by ID or title, executes your code against local test cases, and shows the result. It currently supports around 1.4k problems and multiple languages, including Python, C++, Rust, Java, Go, TypeScript, Swift, and others. The project is still an MVP. System design, SQL, and concurrency problems are not supported yet, but support for more problem types is planned. Made in Haskell!
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