Pyscn - Free AI code quality analysis tool open-sourced specifically for Python developers

What is Pyscn

Pyscn is an intelligent code quality analysis tool designed for Python developers to detect potential problems in code to improve maintainability. It analyzes dead code through control flow diagrams, identifies duplicate code using APTED+LSH algorithm, and calculates metrics such as module coupling and circle complexity. Tools using Go and Tree-sitter development , analysis speed up to 100,000 lines of code per second , support for generating reports in HTML or JSON format . Open source and free, available through GitHub, especially suitable for checking the quality of AI-generated code, such as redundant code or excessive dependencies between modules.

Features of Pyscn

• Efficient Code Analysis: Can quickly analyze large amounts of code at speeds of up to 100,000+ lines/second for large-scale projects.
• Multi-dimensional quality testingIt provides a variety of functions such as dead code detection, code clone detection, coupling metrics and circle complexity analysis to comprehensively assess code quality.
• Flexible configuration options: Supports customization of analysis rules via configuration files to meet the specific needs of different projects and individuals.
• Multiple report formats: Support for generating analysis reports in HTML and JSON formats for developers to view and integrate into other tools.
• Easy to integrate: Seamless integration with CI/CD tools such as GitHub Actions, pre-commit, etc. for easy use in continuous integration environments.
• Quick Installation and Use: Supports pipx, uv, and many other installation methods, so you can start using it quickly without complex configuration.
• Open Source and Community Support: Under MIT license, open source code, with active community support, easy for developers to participate in contributing and get help.

Pyscn's core strengths

• High Performance Analysis: Extremely high analytical speed and the ability to process large amounts of code quickly, making it suitable for large-scale projects and rapid iterative development.
• AI-driven: Utilizes AI technology for code structure analysis to accurately identify potential problems and provide smarter code quality inspection.
• Multi-dimensional detection: Covering a wide range of functions such as dead code detection, code clone detection, coupling metrics and circle complexity analysis, it provides comprehensive coverage of code quality issues.
• Flexible Configuration: Supports customization of analysis rules via configuration files to meet the specific needs of different projects and individuals.
• Multiple report formatsThe report is available in HTML and JSON formats for developers to view and integrate into other tools.
• Easy to integrate: Seamless integration with CI/CD tools such as GitHub Actions, pre-commit, etc. for easy use in continuous integration environments.

What is the official website of Pyscn

• Github repository:: https://github.com/ludo-technologies/pyscn

People for Pyscn

• Python Developer: Python programmers who need to improve code quality and optimize code structure.
• development team: Multi-person collaborative development teams need to standardize code quality standards and ensure code maintainability.
• Technology managers: People responsible for project quality control and technical team management need tools to monitor and improve code quality.
• Continuous Integration Engineer: Engineers responsible for building and maintaining CI/CD processes need to integrate code quality analysis tools into automated processes.
• New Developers: Beginners who wish to learn and improve their awareness of code quality can learn how to write better code with Pyscn's analysis reports.
• educator: Teachers who need instructional tools to help their students understand code quality issues and improve their code writing skills.