python-patterns

Python Development Patterns

Idiomatic Python patterns and best practices for building robust, efficient, and maintainable applications.

Leading words

• Idiom — A Pythonic pattern that leverages the language's conventions for clarity and performance.
• Comprehension — List, dict, and set comprehensions with generator expressions for concise data transformation.
• EAFP — "Easier to Ask Forgiveness Than Permission" using try/except instead of look-before-you-leap.
• Context manager — with statement patterns for deterministic resource management.

When to Activate

• Writing new Python code
• Reviewing Python code
• Refactoring existing Python code
• Designing Python packages/modules

Core Principles

1. Readability Counts

Python prioritizes readability. Code should be obvious and easy to understand.

# Good: Clear and readable
def get_active_users(users: list[User]) -> list[User]:
    """Return only active users from the provided list."""
    return [user for user in users if user.is_active]


# Bad: Clever but confusing
def get_active_users(u):
    return [x for x in u if x.a]

2. Explicit is Better Than Implicit

Avoid magic; be clear about what your code does.

# Good: Explicit configuration
import logging

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)

# Bad: Hidden side effects
import some_module
some_module.setup()  # What does this do?

3. EAFP - Easier to Ask Forgiveness Than Permission

Python prefers exception handling over checking conditions.

# Good: EAFP style
def get_value(dictionary: dict, key: str, default_value: Any = None) -> Any:
    try:
        return dictionary[key]
    except KeyError:
        return default_value

# Bad: LBYL (Look Before You Leap) style
def get_value(dictionary: dict, key: str, default_value: Any = None) -> Any:
    if key in dictionary:
        return dictionary[key]
    else:
        return default_value