samueli924/chaoxing

超星学习通/超星尔雅/泛雅超星全自动无人值守完成任务点

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Summary Information

Updated 44 minutes ago
Added to GitGenius on September 20th, 2026
Created on November 20th, 2020
Open Issues & Pull Requests: 22 (+0)
GitHub issues: Enabled
Number of forks: 441
Total Stargazers: 3,421 (+0)
Total Subscribers: 8 (+0)

Charts & Analytics

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Issue Activity (beta)

Open issues: 20
New in 7 days: 2
Closed in 7 days: 0
Avg open age: 166 days
Stale 30+ days: 9
Stale 90+ days: 8

Recent activity

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

Top labels

  • bug (104)
  • Support (3)

Detailed Description

Chaoxing is a command-line automation tool that completes learning tasks in the Chaoxing learning platform used by Chinese educational institutions.

The tool addresses the problem of manually completing course tasks in Chaoxing's learning management system by automating the process end-to-end. It works by accepting user credentials and course identifiers, then automatically progressing through assigned learning activities without requiring manual intervention. The tool supports multiple deployment methods including direct Python execution, packaged executables, and Docker containers, making it accessible to users with different technical backgrounds.

The tool suits students or administrators managing multiple courses who want to automate routine task completion. It works with Chaoxing's main platforms including the learning portal and Erya courses. A notable capability is support for question bank integration, allowing the tool to automatically answer quiz questions when configured with appropriate question bank providers. Users can run the tool through configuration files, command-line arguments, or Docker, depending on their environment and preference.

Development activity shows consistent maintenance with code contributions addressing specific feature gaps. The project accepts pull requests that expand functionality, such as recent additions for question bank answer support. The tool requires Python 3.13 or later for source-based execution, and the project provides multiple distribution channels including pre-built executables and Docker images to reduce setup friction for non-technical users.