python-anti-patternslisted

# 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. **Note:** This skill focuses on what to avoid. For guidance on positive patterns and architecture, see the `python-patterns` skill. ## Core Concepts ### 1. Centralize Cross-Cutting Concerns Timeouts, retries, and configuration should live in one place, not scattered across every call site. ### 2. Separate Layers Keep I/O, business logic, and API concerns in distinct layers. Don't mix SQL into business functions or leak ORM models to API consumers. ### 3. Handle Failures Explicitly Catch specific exceptions, preserve partial results in batch operations, and validate inputs at boundaries. ### 4. Use the Type System Annotate all public functions, use typed collections, and let static analysis catch bugs before runtime. ## 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_