Python Coding Guidelines
Python coding guidelines and best practices. Use when writing, reviewing, or refactoring Python code. Enforces PEP 8 style, syntax validation via py_compile, unit test execution, m…
Adarsh Divakaran
@adarshdigievo
What This Skill Does
Provides a comprehensive set of Python coding guidelines and best practices covering PEP 8 style, syntax validation, unit test execution, dependency management with uv, and idiomatic Python patterns. Includes a pre-commit checklist and anti-patterns to avoid.
Replaces ad-hoc code review checklists and scattered style guides by offering a single, actionable reference for writing, reviewing, and refactoring Python code.
When to Use It
- Review a pull request for Python code style and common anti-patterns
- Set up a new Python project with modern dependency management using uv
- Refactor legacy Python code to use idiomatic patterns like comprehensions and pathlib
- Write unit tests with pytest following naming conventions and best practices
- Format Python source files to comply with PEP 8 and Black defaults
- Add type hints and docstrings to public functions in an existing codebase
Install
$ openclaw skills install @adarshdigievo/pythonPython Coding Guidelines
Code Style (PEP 8)
- 4 spaces for indentation (never tabs)
- Max line length: 88 chars (Black default) or 79 (strict PEP 8)
- Two blank lines before top-level definitions, one within classes
- Imports: stdlib → third-party → local, alphabetized within groups
- Snake_case for functions/variables, PascalCase for classes, UPPER_CASE for constants
Before Committing
# Syntax check (always)
python -m py_compile *.py
# Run tests if present
python -m pytest tests/ -v 2>/dev/null || python -m unittest discover -v 2>/dev/null || echo "No tests found"
# Format check (if available)
ruff check . --fix 2>/dev/null || python -m black --check . 2>/dev/null
Python Version
- Minimum: Python 3.10+ (3.9 EOL Oct 2025)
- Target: Python 3.11-3.13 for new projects
- Never use Python 2 syntax or patterns
- Use modern features: match statements, walrus operator, type hints
Dependency Management
Check for uv first, fall back to pip:
# Prefer uv if available
if command -v uv &>/dev/null; then
uv pip install <package>
uv pip compile requirements.in -o requirements.txt
else
pip install <package>
fi
For new projects with uv: uv init or uv venv && source .venv/bin/activate
Pythonic Patterns
# ✅ List/dict comprehensions over loops
squares = [x**2 for x in range(10)]
lookup = {item.id: item for item in items}
# ✅ Context managers for resources
with open("file.txt") as f:
data = f.read()
# ✅ Unpacking
first, *rest = items
a, b = b, a # swap
# ✅ EAFP over LBYL
try:
value = d[key]
except KeyError:
value = default
# ✅ f-strings for formatting
msg = f"Hello {name}, you have {count} items"
# ✅ Type hints
def process(items: list[str]) -> dict[str, int]:
...
# ✅ dataclasses/attrs for data containers
from dataclasses import dataclass
@dataclass
class User:
name: str
email: str
active: bool = True
# ✅ pathlib over os.path
from pathlib import Path
config = Path.home() / ".config" / "app.json"
# ✅ enumerate, zip, itertools
for i, item in enumerate(items):
...
for a, b in zip(list1, list2, strict=True):
...
Anti-patterns to Avoid
# ❌ Mutable default arguments
def bad(items=[]): # Bug: shared across calls
...
def good(items=None):
items = items or []
# ❌ Bare except
try:
...
except: # Catches SystemExit, KeyboardInterrupt
...
except Exception: # Better
...
# ❌ Global state
# ❌ from module import *
# ❌ String concatenation in loops (use join)
# ❌ == None (use `is None`)
# ❌ len(x) == 0 (use `not x`)
Testing
- Use pytest (preferred) or unittest
- Name test files
test_*.py, test functionstest_* - Aim for focused unit tests, mock external dependencies
- Run before every commit:
python -m pytest -v
Docstrings
def fetch_user(user_id: int, include_deleted: bool = False) -> User | None:
"""Fetch a user by ID from the database.
Args:
user_id: The unique user identifier.
include_deleted: If True, include soft-deleted users.
Returns:
User object if found, None otherwise.
Raises:
DatabaseError: If connection fails.
"""
Quick Checklist
- Syntax valid (
py_compile) - Tests pass (
pytest) - Type hints on public functions
- No hardcoded secrets
- f-strings, not
.format()or% -
pathlibfor file paths - Context managers for I/O
- No mutable default args
Top skills in this category
Skill Vetter
@spclaudehomeSecurity-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.
Github
@steipeteInteract with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Humanizer
@biostartechnologyRemove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Free Ride - Unlimited free AI
@shaivpidadiManages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates opencla...
Elite Longterm Memory
@nextfrontierbuildsUltimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready.