kamyu104/leetcode-solutions

🏋️ Python / Modern C++ Solutions of All 4046 LeetCode Problems (Weekly Update)

View on GitHub ↗Jump to charts ↓

Summary Information

Updated 30 minutes ago
Added to GitGenius on September 11th, 2026
Created on October 11th, 2018
Open Issues & Pull Requests: 45 (+0)
GitHub issues: Enabled
Number of forks: 1,798
Total Stargazers: 5,929 (+1)
Total Subscribers: 166 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 9.4 hours
Mean response time: 63.6 days
90th percentile: 379.5 days
Tracked items: 6

Most active contributors

Sign in to see contributor activity.

Related repositories by overlapping contributors

No overlapping-contributor repos identified yet.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 0
New in 7 days: 0
Closed in 7 days: 0
Avg open age: N/A days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

No label distribution available yet.

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

LeetCode Solutions is a comprehensive reference collection of algorithm solutions for coding interview preparation.

The repository addresses the need for accessible, well-implemented solutions to competitive programming problems. It provides implementations in both Python and Modern C++, allowing developers to study multiple approaches to the same algorithmic challenges. The solutions cover fundamental data structures and algorithms commonly tested in technical interviews, with each problem solved using idiomatic code in both languages.

This resource suits developers preparing for technical interviews who want to understand not just whether a solution works, but how to implement it cleanly in their language of choice. It works best as a study reference rather than a learning tool from scratch—someone should already understand the problem before consulting the solution. The dual-language approach means you can see how the same algorithmic idea translates between Python's expressiveness and C++'s performance characteristics, which is valuable for candidates who may interview in either language.

The project maintains comprehensive coverage across all available problems, with solutions organized into numbered ranges for easy navigation. Updates occur regularly to incorporate new problems as they are added to the platform. The repository includes solutions for premium-tier problems, marked clearly in the documentation. The codebase demonstrates consistent implementation patterns across problems, making it straightforward to locate and understand solutions for specific algorithmic categories.