norvig/pytudes

Python programs, usually short, of considerable difficulty, to perfect particular skills.

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Summary Information

Updated 8 minutes ago
Added to GitGenius on September 2nd, 2026
Created on March 1st, 2017
Open Issues & Pull Requests: 29 (+0)
GitHub issues: Enabled
Number of forks: 2,478
Total Stargazers: 24,409 (+0)
Total Subscribers: 778 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 5.5 days
Mean response time: 11.5 days
90th percentile: 29.1 days
Tracked items: 3

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Issue Activity (beta)

Open issues: 6
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 602 days
Stale 30+ days: 6
Stale 90+ days: 6

Recent activity

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

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Detailed Description

Pytudes is a collection of Python programming exercises designed to develop and demonstrate particular skills through challenging problems.

The project addresses the need for focused, high-quality practice material by offering short Python programs that combine conceptual difficulty with practical application. Each exercise targets specific skills and programming techniques, allowing developers to work through problems that require careful thought and solid understanding rather than rote implementation. The approach emphasizes learning through doing, with problems selected for their instructional value and their ability to reinforce core programming concepts.

Pytudes suits developers seeking deliberate practice in Python who want to move beyond trivial exercises toward problems with real intellectual substance. It works well for those preparing for technical interviews, strengthening algorithmic thinking, or simply deepening their Python proficiency. The collection is particularly valuable for self-directed learners who benefit from curated, difficulty-calibrated problems rather than randomly assembled coding challenges. Because the programs are usually short, they remain approachable while still demanding careful problem-solving.

The project shows consistent engagement with regular updates to its collection of exercises and refinements to existing material. Contributions arrive steadily, indicating ongoing community interest in expanding and improving the problem set. The codebase maintains active maintenance with responsive handling of issues and pull requests, suggesting the material remains current and relevant to practitioners.