python-anti-patterns

# Python Anti-Patterns Checklist A reference checklist of common mistakes and anti-patterns in Python code. Review this before finalizing implementations to catch issues early. ## When to Use This Skill - Reviewing code before merge - Debugging mysterious issues - Teaching or learning Python best practices - Establishing team coding standards - Refactoring legacy code **Note:** This skill focuses on what to avoid. For guidance on positive patterns and architecture, see the `python-design-patterns` skill. ## Infrastructure Anti-Patterns ### Scattered Timeout/Retry Logic ```python # BAD: Timeout logic duplicated everywhere def fetch_user(user_id): try: return requests.get(url, timeout=30) except Timeout: logger.warning("Timeout fetching user") return None def fetch_orders(user_id): try: return requests.get(url, timeout=30) except Timeout: logger.warning("Timeout fetching orders") return None ``` **Fix:** Centralize in decorators or client wrappers. ```python # GOOD: Centralized retry logic @retry(stop=stop_after_attempt(3), wait=wait_exponential()) def http_get(url: str) -> Response: return requests.get(url, timeout=30) ``` ### Double Retry ```python # BAD: Retrying at multiple layers @retry(max_attempts=3) # Application retry def call_service(): return client.request() # Client also has retry configured! ``` **Fix:** Retry at one layer only. Know your infrastructure's retry behavior. ### Ha...