---name: core-python-best-practices description: Essential guidelines for writing modern, type-safe, and idiomatic Python 3 code. license: MIT metadata: author: AI Group version: "1.0.0" category: Software_Engineering compatibility:

• system: Python 3.10+ allowed-tools:
• read_file
• replace
• write_file

keywords:

• core-python-best-practices
• automation
• biomedical measurable_outcome: execute task with >95% success rate. ---"

Core Python Best Practices

This skill defines the coding standards for Python development within the project. It emphasizes modern features, type safety, and readability.

When to Use This Skill

• New Scripts: Starting a new agent or tool.
• Refactoring: Modernizing legacy code.
• Library Design: Creating reusable modules.

Core Capabilities

1. Type Hinting: Mandatory use of typing module or native types (Python 3.9+).
2. Data Classes: Using @dataclass or Pydantic for data containers instead of raw dictionaries/tuples.
3. Modern Control Flow: Using match/case (Python 3.10) where appropriate.
4. Error Handling: Proper use of try/except chains and custom exceptions.

Workflow

1. Define Interface: Start with function signatures and type hints.
2. Select Structure: Choose between a simple function, a class, or a dataclass.
3. Implement: Write logic using list comprehensions and generators where possible.
4. Document: Add docstrings (Google or NumPy style).

Example Usage

User: "Write a function to process a list of users."

Agent Action:

1. Reads references/rules.md.
2. Generates:

   from dataclasses import dataclass
   
   @dataclass
   class User:
       id: int
       name: str
   
   def process_users(users: list[User]) -> None:
       """Processes a list of users."""
       for user in users:
           ...