Python Code Patterns

Python Code Patterns

Exception: Tests Directory

All these rules can be relaxed in the tests/ directory. Go wild there - write whatever helps you test effectively.

Type Hints

Use modern Python type hints (PEP 585):

DO:

def process(items: list[str]) -> dict[str, int]:
    ...

data: list[dict[str, Any]] = []
```text

**DON'T:**

```python
from typing import List, Union, Optional

def process(items: List[str]) -> Dict[str, int]:
    ...

data: List[Dict[str, Any]] = []

Use lowercase built-in types: list, dict, tuple, set, frozenset, type, bytes

Import Organization

DO:

from typing import Any

def my_function(data: Any) -> None:
    ...
```text

**DON'T:**

```python
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from typing import Any

def my_function(data: Any) -> None:
    ...

• Never use TYPE_CHECKING guards
• Never use imports not at the top level (inside functions, classes, etc.)
• If you have circular imports, your code structure needs refactoring
• TYPE_CHECKING guards and late imports are code smells indicating poor architecture

Type Checking

Avoid # type: ignore as much as possible:

• Only use as a last resort when there's a genuine limitation in type checking
• If you find yourself needing # type: ignore frequently, reconsider your type annotations
• Comment why it's needed when you must use it:

result: int = some_complex_function()  # type: ignore  # external library has incorrect type stub
```text

## Comments

Don't add obvious/redundant comments:

**DON'T:**

```python
id: str  # id
name: str  # the name
count: int  # number of items

# loop through items
for item in items:
    # process the item
    process(item)

Comments should explain why, not what.

Router-Service Separation

Keep routers free of business logic:

DO:

from fastapi import APIRouter

router = APIRouter()

@router.get("/items/{item_id}")
async def get_item(item_id: int):
    return await service.get_item(item_id)

DON'T:

from fastapi import APIRouter

router = APIRouter()

@router.get("/items/{item_id}")
async def get_item(item_id: int):
    if item_id <= 0:
        raise HTTPException(status_code=400, detail="Invalid item ID")
    
    item = db.query(Item).filter(Item.id == item_id).first()
    if not item:
        raise HTTPException(status_code=404, detail="Item not found")
    
    return item

• Routers should only call service functions and return results
• Validation, checks, business logic belong in the service layer
• Services raise HTTPExceptions directly - let them bubble up through routers
• Services contain domain logic and return domain objects or primitives

Service layer handles:

• Input validation and sanitization
• Business rules and constraints
• Database operations and queries
• Error conditions and exceptions raising

Router layer handles:

• HTTP method routing
• Delegating to service functions
• Returning service results directly
• No business logic or validation

Docstrings

Keep docstrings concise and focused:

DON'T:

def process_data(data: list[str]) -> dict[str, int]:
    """
    Process data.
    
    Args:
        data: The data to process
        
    Returns:
        dict[str, int]: The processed data
    """
    ...
```text

**DO:**

```python
def process_data(data: list[str]) -> dict[str, int]:
    """
    Converts string data to word frequency counts, ignoring case and punctuation.
    """
    ...

• Type information already in signature - don't repeat it
• Only include non-obvious information
• Explain edge cases, constraints, algorithm choices, or complex behavior

When to Apply

Apply these patterns whenever:

• Writing new Python code (outside tests/)
• Reviewing or refactoring existing Python code (outside tests/)
• Updating type annotations (outside tests/)
• Adding or modifying imports (outside tests/)
• Implementing API routers or service layer functions