Use this skill when reviewing Python code for common anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.
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-design-patterns skill.
# 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.
# 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)
# 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.
# BAD: Secrets and config in code
DB_HOST = "prod-db.example.com"
API_KEY = "sk-12345"
def connect():
return psycopg.connect(f"host={DB_HOST}...")
Fix: Use environment variables with typed settings.
# GOOD
from pydantic_settings import BaseSettings
class Settings(BaseSettings):
db_host: str = Field(alias="DB_HOST")
api_key: str = Field(alias="API_KEY")
settings = Settings()
# BAD: Leaking ORM model to API
@app.get("/users/{id}")
def get_user(id: str) -> UserModel: # SQLAlchemy model
return db.query(UserModel).get(id)
Fix: Use DTOs/response models.
# GOOD
@app.get("/users/{id}")
def get_user(id: str) -> UserResponse:
user = db.query(UserModel).get(id)
return UserResponse.from_orm(user)
# BAD: SQL embedded in business logic
def calculate_discount(user_id: str) -> float:
user = db.query("SELECT * FROM users WHERE id = ?", user_id)
orders = db.query("SELECT * FROM orders WHERE user_id = ?", user_id)
# Business logic mixed with data access
if len(orders) > 10:
return 0.15
return 0.0
Fix: Repository pattern. Keep business logic pure.
# GOOD
def calculate_discount(user: User, orders: list[Order]) -> float:
# Pure business logic, easily testable
if len(orders) > 10:
return 0.15
return 0.0
# BAD: Swallowing all exceptions