jackfrued/Python-100-Days

Python - 100天从新手到大师

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jackfrued/Python-100-Days has 187k+ stars and 55k+ forks on GitHub, is written in Jupyter Notebook, and was last pushed on Jul 29, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 1 hour ago
Type:Template / ExampleCategory(s):Programming Courses & BooksLearning & Resources
Added to GitGenius on August 30th, 2026
Created on March 1st, 2018
Open Issues & Pull Requests: 718 (+0)
GitHub issues: Enabled
Number of forks: 55,759
Total Stargazers: 187,279 (+0)
Total Subscribers: 6,036 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 83.3 days
Mean response time: 245.9 days
90th percentile: 510.1 days
Tracked items: 100

How this project is maintained

Roughly one issue in two opened in the past year never receives a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 37% of issues opened in the past year have been closed. Three people close 86% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 37
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 362 days
Stale 30+ days: 35
Stale 90+ days: 22

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

Python - 100 Days from Beginner to Master is a learning curriculum delivered as Jupyter Notebooks that teaches Python programming from foundational concepts through practical application.

The project addresses the challenge of learning Python systematically by structuring knowledge across a hundred-day progression. It covers Python's core characteristics as an elegant, readable, and accessible language, then maps those capabilities onto real-world application domains including backend development, DevOps, data collection, quantitative trading, data science, machine learning, and automated testing. The curriculum connects language fundamentals to career pathways, helping learners understand which specializations align with their interests.

Prospective learners should know this material targets beginners with no prior programming experience, though it progresses to professional-level applications. The project suits anyone seeking a structured, comprehensive introduction to Python who prefers a curriculum-based approach over fragmented tutorials. It explicitly positions itself as an alternative to scattered online resources by offering a cohesive progression. The README emphasizes that data science represents a particularly active career direction within Python development, reflecting current market demand.

The project maintains active engagement through multiple channels beyond the repository itself, including supplementary content on alternative platforms and ongoing creation of specialized learning materials in related areas. The author provides direct community support through paid learning groups and consultation, indicating sustained involvement with learner outcomes. Documentation includes practical career guidance alongside technical instruction, suggesting the project evolves based on real employment trends rather than static curriculum design.