Python Coding Standards
Manage and enforce Python coding standards across your team with CodeContext. Ensure AI assistants follow your Python conventions through MCP integration.
Standard Categories
Naming Conventions
Error Handling
Type Hints
Module Structure
Class Design
Testing Patterns
Docstring Format
Import Organization
Example Standard
Python
# Standard: Use structured error handling with custom exceptions
# Category: Error Handling
# Avoid
def get_user(user_id):
try:
user = db.query(user_id)
return user
except Exception:
return None
# Prefer
class UserNotFoundError(Exception):
def __init__(self, user_id):
self.user_id = user_id
super().__init__(f"User {user_id} not found")
def get_user(user_id: int) -> User:
user = db.query(user_id)
if user is None:
raise UserNotFoundError(user_id)
return userFrequently Asked Questions
Does CodeContext work with Python linters like Ruff or Flake8?
CodeContext complements linters. While Ruff and Flake8 enforce syntax rules, CodeContext manages higher-level standards like architecture patterns, error handling strategies, and design decisions.
Can I include PEP standards in CodeContext?
Yes. You can document which PEPs your team follows and any team-specific interpretations or extensions of those standards.
Does this work with Django and Flask projects?
Absolutely. You can create framework-specific categories for Django or Flask conventions alongside your general Python standards.
Manage Python Standards with CodeContext
Define your Python conventions and deliver them to AI assistants automatically.