asabeneh/30-days-of-python

The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than...

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Summary Information

Updated 59 minutes ago
Added to GitGenius on August 30th, 2026
Created on November 19th, 2019
Open Issues & Pull Requests: 202 (+0)
GitHub issues: Enabled
Number of forks: 13,277
Total Stargazers: 72,445 (+8)
Total Subscribers: 1,020 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 3.3 days
Mean response time: 115.3 days
90th percentile: 459.6 days
Tracked items: 65

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 38% of tracked open issues have had no activity in three months. Only 5% of issues opened in the past year have been closed.

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Issue Activity (beta)

Open issues: 66
New in 7 days: 5
Closed in 7 days: 2
Avg open age: 350 days
Stale 30+ days: 60
Stale 90+ days: 28

Recent activity

Opened in 7 days: 5
Closed in 7 days: 2
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

30 Days of Python is a structured learning curriculum that teaches Python programming fundamentals through a thirty-day challenge format.

The curriculum addresses the need for a comprehensive, self-paced introduction to Python by organizing core language concepts into sequential daily lessons. It progresses from foundational topics like variables and operators through data structures, control flow, and functions, then advances to practical applications including web scraping, data analysis with pandas, database integration with MongoDB, and API development. Each day focuses on a specific concept with explanatory material and exercises.

This resource suits beginners seeking a complete pathway from language basics to practical full-stack development skills. The curriculum spans both core Python language features and applied domains like data science, web development, and database work, making it appropriate for learners who want exposure to multiple specializations rather than depth in a single area. The progression from syntax fundamentals to web frameworks and data tools means someone following it will gain familiarity with the broader Python ecosystem.

The project maintains a stable, comprehensive curriculum structure with all thirty days documented and accessible. The material remains organized and complete, with translations available in multiple languages extending its reach beyond English-speaking learners.