python-anti-patterns

# 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!

# 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}...")

# 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)

# 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

# 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
try:
    process()
except Exception:
    pass  # Silent failure - bugs hidden forever

# GOOD
try:
    process()
except ConnectionError as e:
    logger.warning("Connection failed, will retry", error=str(e))
    raise
except ValueError as e:
    logger.error("Invalid input", error=str(e))
    raise BadRequestError(str(e))

# BAD: Stops on first error
def process_batch(items):
    results = []
    for item in items:
        result = process(item)  # Raises on error - batch aborted
        results.append(result)
    return results

# GOOD
def process_batch(items) -> BatchResult:
    succeeded = {}
    failed = {}
    for idx, item in enumerate(items):
        try:
            succeeded[idx] = process(item)
        except Exception as e:
            failed[idx] = e
    return BatchResult(succeeded, failed)

# BAD: No validation
def create_user(data: dict):
    return User(**data)  # Crashes deep in code on bad input

# GOOD
def create_user(data: dict) -> User:
    validated = CreateUserInput.model_validate(data)
    return User.from_input(validated)

# BAD: File never closed
def read_file(path):
    f = open(path)
    return f.read()  # What if this raises?

# GOOD
def read_file(path):
    with open(path) as f:
        return f.read()

# BAD: Blocks the entire event loop
async def fetch_data():
    time.sleep(1)  # Blocks everything!
    response = requests.get(url)  # Also blocks!

# GOOD
async def fetch_data():
    await asyncio.sleep(1)
    async with httpx.AsyncClient() as client:
        response = await client.get(url)

# BAD: No types
def process(data):
    return data["value"] * 2

# GOOD
def process(data: dict[str, int]) -> int:
    return data["value"] * 2

# BAD: Generic list without type parameter
def get_users() -> list:
    ...

# GOOD
def get_users() -> list[User]:
    ...

# BAD: Only tests success case
def test_create_user():
    user = service.create_user(valid_data)
    assert user.id is not None

# GOOD
def test_create_user_success():
    user = service.create_user(valid_data)
    assert user.id is not None
 
def test_create_user_invalid_email():
    with pytest.raises(ValueError, match="Invalid email"):
        service.create_user(invalid_email_data)
 
def test_create_user_duplicate_email():
    service.create_user(valid_data)
    with pytest.raises(ConflictError):
        service.create_user(valid_data)

# BAD: Mocking everything
def test_user_service():
    mock_repo = Mock()
    mock_cache = Mock()
    mock_logger = Mock()
    mock_metrics = Mock()
    # Test doesn't verify real behavior