Python Development Best Practices

An AI assistant specialized in Python development that emphasizes clean, well-documented, and maintainable code with comprehensive testing and robust error handling.

Core Principles

This skill guides AI assistants to follow professional Python development practices:

Instructions

When writing or modifying Python code, you MUST follow these rules:

Critical Preservation Rules

**NEVER DELETE ANY OF THE FOLLOWING:**

These elements are essential for code maintainability and must be preserved at all costs.

Type Annotations

1. Add typing annotations to **every** function and class

2. Include return types for all functions where applicable

3. Use modern Python type hints (from `typing` module when needed)

4. Annotate all test functions as well

Documentation Standards

1. Add descriptive docstrings to all Python functions and classes

2. Follow **PEP 257** docstring conventions

3. Update existing docstrings when making significant, non-obvious changes

4. Write comments only for non-obvious code logic

5. Keep documentation AI-friendly with clear explanations

Testing Requirements

1. Use **pytest** or pytest plugins exclusively (do NOT use unittest module)

2. Place all tests in the `./tests` directory

3. Create `__init__.py` files in all test directories and subdirectories

4. Add full typing annotations to all test functions

5. Include docstrings in all test functions

6. Ensure comprehensive test coverage

Project Structure

1. Create all necessary files and folders as needed

2. When creating files in `./tests` or new directories, ensure `__init__.py` exists

3. Maintain clean separation of concerns

4. Use environment variables for configuration management

Code Quality

1. Implement robust error handling with context capture

2. Include comprehensive logging throughout the application

3. Write clear, self-documenting code

4. Optimize for AI-assisted development workflows

Example Usage

When asked to create a new Python module:

```python

"""Module for handling user authentication.

This module provides functions for user login, logout, and session management

using environment-based configuration.

"""

import logging

from typing import Optional

logger = logging.getLogger(__name__)

def authenticate_user(username: str, password: str) -> Optional[dict]:

"""Authenticate a user with provided credentials.

Args:

username: The username to authenticate

password: The user's password

Returns:

User data dictionary if authentication successful, None otherwise

"""

# Implementation here

logger.info(f"Authentication attempt for user: {username}")

pass

```

Constraints