feat(python): prefer uv for Python dependency management; rename rule file; update tech stacks; restore globs (refs #144)

Author: whysage

rules/python-cursorrules-prompt-file-best-practices/README.md

@@ -3,7 +3,7 @@
 Author: Malcolm Jones (bossjones/Tony Dark)
 
 ## What you can build
-Python Project Scaffold Generator: A web-based tool that generates a Python project scaffold with directories for source code, tests, documentation, and configuration files. Users can specify project details and get a ready-to-use, structured project setup following best practices in modular design and documentation.Python Environment Manager: An application to automate the setup of virtual environments and manage dependencies using rye. Provides a user-friendly interface to add, remove, or update dependencies, while keeping track of versioning and compatibility.Error Handling and Logging Assistant: A service that integrates into Python projects to provide real-time suggestions on error handling and logging improvements. Uses AI to recommend best practices in context capture and logging enhancements, ensuring robust error management.CI/CD Configurator: A platform that helps developers create and manage CI/CD pipelines using GitHub Actions or GitLab CI. It tailors pipeline configurations specific to Python projects, focusing on testing, deployment, and style checks using Ruff.Python Code Quality Analyzer: An online tool that analyzes Python code for adherence to AI-friendly coding practices. It provides feedback on naming conventions, type hints, and comments, helping developers write maintainable and easily understandable code.Automated Test Generator for Python: A Python-based service that generates pytest test cases from existing codebases. It analyzes functions and modules to create comprehensive test suites, ensuring robust coverage and aiding in quality assurance.Python Documentation Enhancer: A browser extension or IDE plugin that automatically suggests improvements to docstrings and README files as you code. It utilizes AI to ensure that documentation is detailed and aligned with pep257 conventions.Config Management Dashboard: A tool to manage and visualize environment variables across different environments (development, testing, production). It offers a secure way to edit and deploy configuration settings without touching the code directly.Ruff Integration Plugin: An IDE plugin to enforce code style consistency using Ruff. It provides real-time feedback and correction suggestions to developers, ensuring code adheres to a consistent style guide for improved readability and maintenance.
+Python Project Scaffold Generator: A web-based tool that generates a Python project scaffold with directories for source code, tests, documentation, and configuration files. Users can specify project details and get a ready-to-use, structured project setup following best practices in modular design and documentation.Python Environment Manager: An application to automate the setup of virtual environments and manage dependencies using uv (preferred). Provides a user-friendly interface to add, remove, or update dependencies, while keeping track of versioning and compatibility.Error Handling and Logging Assistant: A service that integrates into Python projects to provide real-time suggestions on error handling and logging improvements. Uses AI to recommend best practices in context capture and logging enhancements, ensuring robust error management.CI/CD Configurator: A platform that helps developers create and manage CI/CD pipelines using GitHub Actions or GitLab CI. It tailors pipeline configurations specific to Python projects, focusing on testing, deployment, and style checks using Ruff.Python Code Quality Analyzer: An online tool that analyzes Python code for adherence to AI-friendly coding practices. It provides feedback on naming conventions, type hints, and comments, helping developers write maintainable and easily understandable code.Automated Test Generator for Python: A Python-based service that generates pytest test cases from existing codebases. It analyzes functions and modules to create comprehensive test suites, ensuring robust coverage and aiding in quality assurance.Python Documentation Enhancer: A browser extension or IDE plugin that automatically suggests improvements to docstrings and README files as you code. It utilizes AI to ensure that documentation is detailed and aligned with pep257 conventions.Config Management Dashboard: A tool to manage and visualize environment variables across different environments (development, testing, production). It offers a secure way to edit and deploy configuration settings without touching the code directly.Ruff Integration Plugin: An IDE plugin to enforce code style consistency using Ruff. It provides real-time feedback and correction suggestions to developers, ensuring code adheres to a consistent style guide for improved readability and maintenance.
 
 ## Benefits
 
@@ -12,5 +12,7 @@ Python Project Scaffold Generator: A web-based tool that generates a Python proj
 Developers building scalable, maintainable Python applications with CI/CD pipelines would benefit by adhering to best practices for structure, modularity, testing, and documentation.
 
 ## Overview of .cursorrules prompt
-The .cursorrules file specifies guidelines for developing Python projects with a focus on AI-assisted development. It emphasizes a well-structured project with separate directories for various components, modular design, and comprehensive configuration management using environment variables. The approach includes robust error handling, thorough testing with pytest, and detailed documentation practices. Dependency management is handled via rye and virtual environments, while code style consistency is achieved using Ruff. Continuous Integration and Deployment (CI/CD) can be implemented using GitHub Actions or GitLab CI. The file promotes AI-friendly coding practices such as descriptive naming, type hints, and insightful comments, and provides code snippets and explanations tailored to these principles. Additionally, it outlines the importance of adding typing annotations, descriptive docstrings, and adhering to testing conventions using pytest, ensuring clarity and effectiveness in Python development.
+The .cursorrules file specifies guidelines for developing Python projects with a focus on AI-assisted development. It emphasizes a well-structured project with separate directories for various components, modular design, and comprehensive configuration management using environment variables. The approach includes robust error handling, thorough testing with pytest, and detailed documentation practices. Dependency management is handled via uv (preferred) and virtual environments, while code style consistency is achieved using Ruff. Continuous Integration and Deployment (CI/CD) can be implemented using GitHub Actions or GitLab CI. The file promotes AI-friendly coding practices such as descriptive naming, type hints, and insightful comments, and provides code snippets and explanations tailored to these principles. Additionally, it outlines the importance of adding typing annotations, descriptive docstrings, and adhering to testing conventions using pytest, ensuring clarity and effectiveness in Python development.
+
+
 

rules/python-llm-ml-workflow-cursorrules-prompt-file/README.md

@@ -6,7 +6,7 @@ This prompt file is designed for senior Python AI/ML engineers specializing in L
 ## Tech Stack
 
 - Python 3.10+
-- Poetry / Rye
+- uv (preferred) / Poetry
 - Ruff
 - `typing` module
 - `pytest`

rules/python-llm-ml-workflow-cursorrules-prompt-file/poetry-rye-dependency-management.mdc

@@ -0,0 +1,5 @@
+---
+description: Specifies uv (preferred) or Poetry for dependency management in Python projects.
+globs: **/pyproject.toml
+---
+- **Dependency Management:** uv (preferred) / Poetry

rules/python-llm-ml-workflow-cursorrules-prompt-file/uv-dependency-management.mdc

@@ -3,7 +3,7 @@
 Author: bossjones
 
 ## What you can build
-AI-Powered Python Project Boilerplate Generator: A web-based tool that generates a complete Python project structure adhering to best practices. Users can specify project details, and the tool outputs a zip file with directories for source code, tests, docs, and config, with pre-generated boilerplate code including models, services, controllers, utilities, and configuration files.Python Code Quality Dashboard: An app that integrates Ruff for style checks, pytest for testing, and includes CI/CD visualization. It provides insights into the health of a Python project by analyzing code structure, style, and testing results through a user-friendly dashboard interface.Automatic Environment Configuration Manager: A service for managing and deploying environment variables for Python applications. Users can securely store, update, and access environment configurations, which are automatically integrated into their development and CI/CD workflows.AI-Assisted Documentation Generator: A tool that automatically generates detailed documentation from Python code. It uses docstrings and AI to create comprehensive README files and rich documentation with clear explanations and examples suitable for both developers and AI models.Python Error Handling and Logging Framework: A library that provides robust error handling utilities, capturing context and enabling detailed logging. It can be integrated into any project to enhance error management and debugging capabilities, making it easier to trace issues across modules.Virtual Environment Dependency Visualizer: A web app that visualizes dependency trees of Python projects managed with Rye and virtual environments. It allows developers to understand dependencies and potential conflicts visually, aiding in more effective dependency management.CI/CD Template Repository: A GitHub repository template that includes pre-configured YAML files for GitHub Actions or GitLab CI. This service helps in setting up continuous integration and deployment pipelines with best practices out of the box.AI-Powered Code Review Assistant: An integration tool for GitHub or GitLab that uses AI to provide feedback on code quality, adherence to style guides, type hints, and descriptive naming conventions. It assists teams in maintaining high code standards and reduces the manual effort in code review processes.Comprehensive Logging and Error Monitoring Tool: A service similar to Sentry or LogRocket, but focused on Python applications. It offers real-time error tracking, context capture, and detailed insights into exceptions, with recommendations on how to resolve them.Python Modular Design Template Library: A collection of ready-made templates for common modular design patterns in Python, including MVC architecture, utilities organization, and more. It serves as a quick-start library for developers looking to implement robust project structures.
+AI-Powered Python Project Boilerplate Generator: A web-based tool that generates a complete Python project structure adhering to best practices. Users can specify project details, and the tool outputs a zip file with directories for source code, tests, docs, and config, with pre-generated boilerplate code including models, services, controllers, utilities, and configuration files.Python Code Quality Dashboard: An app that integrates Ruff for style checks, pytest for testing, and includes CI/CD visualization. It provides insights into the health of a Python project by analyzing code structure, style, and testing results through a user-friendly dashboard interface.Automatic Environment Configuration Manager: A service for managing and deploying environment variables for Python applications. Users can securely store, update, and access environment configurations, which are automatically integrated into their development and CI/CD workflows.AI-Assisted Documentation Generator: A tool that automatically generates detailed documentation from Python code. It uses docstrings and AI to create comprehensive README files and rich documentation with clear explanations and examples suitable for both developers and AI models.Python Error Handling and Logging Framework: A library that provides robust error handling utilities, capturing context and enabling detailed logging. It can be integrated into any project to enhance error management and debugging capabilities, making it easier to trace issues across modules.Virtual Environment Dependency Visualizer: A web app that visualizes dependency trees of Python projects managed with uv and virtual environments. It allows developers to understand dependencies and potential conflicts visually, aiding in more effective dependency management.CI/CD Template Repository: A GitHub repository template that includes pre-configured YAML files for GitHub Actions or GitLab CI. This service helps in setting up continuous integration and deployment pipelines with best practices out of the box.AI-Powered Code Review Assistant: An integration tool for GitHub or GitLab that uses AI to provide feedback on code quality, adherence to style guides, type hints, and descriptive naming conventions. It assists teams in maintaining high code standards and reduces the manual effort in code review processes.Comprehensive Logging and Error Monitoring Tool: A service similar to Sentry or LogRocket, but focused on Python applications. It offers real-time error tracking, context capture, and detailed insights into exceptions, with recommendations on how to resolve them.Python Modular Design Template Library: A collection of ready-made templates for common modular design patterns in Python, including MVC architecture, utilities organization, and more. It serves as a quick-start library for developers looking to implement robust project structures.
 
 ## Benefits
 
@@ -12,5 +12,5 @@ AI-Powered Python Project Boilerplate Generator: A web-based tool that generates
 Developers can use this prompt to build well-structured, maintainable Python applications with robust CI/CD, testing, and AI-friendly coding practices.
 
 ## Overview of .cursorrules prompt
-The .cursorrules file defines the behavior of an AI assistant that specializes in Python development. It is designed to guide developers in organizing projects with a clear structure by using separate directories for source code, tests, documentation, and configurations. It promotes modular design through distinct files for various components like models and services, and emphasizes configuration management via environment variables. The assistant advocates for strong error handling, comprehensive testing with pytest, and thorough documentation. It encourages dependency management using rye and virtual environments, while ensuring code style consistency with Ruff. Additionally, it supports CI/CD implementation using GitHub Actions or GitLab CI. The assistant aims to provide AI-friendly coding practices with descriptive names, type hints, detailed comments, and rich error context. Code snippets and explanations are tailored to these principles, optimizing for clarity and leveraging AI for development tasks.
+The .cursorrules file defines the behavior of an AI assistant that specializes in Python development. It is designed to guide developers in organizing projects with a clear structure by using separate directories for source code, tests, documentation, and configurations. It promotes modular design through distinct files for various components like models and services, and emphasizes configuration management via environment variables. The assistant advocates for strong error handling, comprehensive testing with pytest, and thorough documentation. It encourages dependency management using uv (preferred) and virtual environments, while ensuring code style consistency with Ruff. Additionally, it supports CI/CD implementation using GitHub Actions or GitLab CI. The assistant aims to provide AI-friendly coding practices with descriptive names, type hints, detailed comments, and rich error context. Code snippets and explanations are tailored to these principles, optimizing for clarity and leveraging AI for development tasks.
 

rules/python-projects-guide-cursorrules-prompt-file/README.md

@@ -1,5 +1,5 @@
 ---
-description: Specifies dependency management using Rye and virtual environments for consistent and isolated project dependencies.
+description: Specifies uv (preferred) for dependency management and virtual environments for consistent and isolated project dependencies.
 globs: /**/pyproject.toml
 ---
-- Manage dependencies via https://github.com/astral-sh/rye and virtual environments.
+- Manage dependencies via https://github.com/astral-sh/uv and virtual environments.