--> --- name: 'core-python-best-practices' description: 'Essential guidelines for writing modern, type-safe, and idiomatic Python 3 code.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command - write_file --- This skill defines the coding standards for Python development within the project. It emphasizes modern features, type safety, and readability.
Installs into .claude/skills of the current project.
Are you the author of Core Python Best Practices?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/mdbabumiamssm-core-python-best-practices-ai-agentic-skills-by-dr-mia)
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal AI Agentic Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
-->
---
name: 'core-python-best-practices'
description: 'Essential guidelines for writing modern, type-safe, and idiomatic Python 3 code.'
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
- read_file
- run_shell_command
- write_file
---
# 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:
```python
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:
...
```
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->