python-type-safetylisted
Install: claude install-skill Jartan-LLC/grimoire
# Python Type Safety
Leverage Python's type system to catch errors at static analysis time. Type annotations serve as enforced documentation that tooling validates automatically.
## Core Concepts
### 1. Type Annotations
Declare expected types for function parameters, return values, and variables.
### 2. Generics
Write reusable code that preserves type information across different types.
### 3. Protocols
Define structural interfaces without inheritance (duck typing with type safety).
### 4. Type Narrowing
Use guards and conditionals to narrow types within code blocks.
## Quick Start
```python
def get_user(user_id: str) -> User | None:
"""Return type makes 'might not exist' explicit."""
...
# Type checker enforces handling None case
user = get_user("123")
if user is None:
raise UserNotFoundError("123")
print(user.name) # Type checker knows user is User here
```
## Fundamental Patterns
### Pattern 1: Annotate All Public Signatures
Every public function, method, and class should have type annotations.
```python
def get_user(user_id: str) -> User:
"""Retrieve user by ID."""
...
def process_batch(
items: list[Item],
max_workers: int = 4,
) -> BatchResult[ProcessedItem]:
"""Process items concurrently."""
...
class UserRepository:
def __init__(self, db: Database) -> None:
self._db = db
async def find_by_id(self, user_id: str) -> User | None:
"""Return User if found, None otherwise."""
...
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