Python Style Guide Compact

Python Style Essentials

Imports

# Standard library
import os
from pathlib import Path

# Third-party
import numpy as np

# Application
from myproject import utils

• Absolute imports only, alphabetized within groups
• Application imports: Prefer module imports (from myproj import utils) to avoid circular deps.
• Third-party/Std: Class imports ok (from pathlib import Path, from pydantic import BaseModel).

Type Annotations

def process(items: list[str], config: dict[str, Any] | None = None) -> int:
    """Process items with optional config."""
    if config is None:
        config = {}
    return len(items)

• Use built-in types: list, dict, set, tuple (not typing.List)
• Annotate all public functions
• Never use mutable defaults: = None then check inside

Naming

Docstrings (Google style)

def fetch_data(url: str, timeout: int = 30) -> dict[str, Any]:
    """Fetch data from URL.

    Args:
        url: The endpoint URL.
        timeout: Request timeout in seconds.

    Returns:
        Parsed JSON response as dict.

    Raises:
        ConnectionError: If request fails.
    """

Key Rules

• 88 char lines (Ruff/Black default), 4-space indent
• f-strings for string interpolation
• Logging: Use Loguru: logger.info("Item {}", item) (lazy {})
• File I/O: Prefer Path.read_text()/write_text() over open() for simple operations
• Implicit false: if not items: not if len(items) == 0:
• Comprehensions: keep simple, use loop if complex
• Exceptions: catch specific, never bare except:
• Empty __init__.py: no code in __init__.py files

Preferred Libraries

Common Patterns

# Property
@property
def area(self) -> float:
    return self._side ** 2

# Ternary
x = "yes" if condition else "no"

# Main guard
if __name__ == "__main__":
    main()