Implements Python type safety with annotations, generics, protocols, narrowing, and mypy/pyright configuration to catch errors statically.
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Leverage Python's type system to catch errors at static analysis time. Type annotations serve as enforced documentation that tooling validates automatically.
Declare expected types for function parameters, return values, and variables.
Write reusable code that preserves type information across different types.
Define structural interfaces without inheritance (duck typing with type safety).
Use guards and conditionals to narrow types within code blocks.
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
Every public function, method, and class should have type annotations.
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."""
...
async def find_by_email(self, email: str) -> User | None:
...
async def save(self, user: User) -> User:
"""Save and return user with generated ID."""
...
Use mypy --strict or pyright in CI to catch type errors early. For existing projects, enable strict mode incrementally using per-module overrides.
Python 3.10+ provides cleaner union syntax.
# Preferred (3.10+)
def find_user(user_id: str) -> User | None:
...
def parse_value(v: str) -> int | float | str:
...
# Older style (still valid, needed for 3.9)
from typing import Optional, Union
def find_user(user_id: str) -> Optional[User]:
...
Use conditionals to narrow types for the type checker.
def process_user(user_id: str) -> UserData:
user = find_user(user_id)
if user is None:
raise UserNotFoundError(f"User {user_id} not found")
# Type checker knows user is User here, not User | None
return UserData(
name=user.name,
email=user.email,
)
def process_items(items: list[Item | None]) -> list[ProcessedItem]:
# Filter and narrow types
valid_items = [item for item in items if item is not None]
# valid_items is now list[Item]
return [process(item) for item in valid_items]
Create type-safe reusable containers.
from typing import TypeVar, Generic
T = TypeVar("T")
E = TypeVar("E", bound=Exception)
class Result(Generic[T, E]):
"""Represents either a success value or an error."""
def __init__(
self,
value: T | None = None,
error: E | None = None,
) -> None:
if (value is None) == (error is None):
raise ValueError("Exactly one of value or error must be set")
self._value = value
self._error = error
@property
def is_success(self) -> bool:
return self._error is None
@property
def is_failure(self) -> bool:
return self._error is not None
def unwrap(self) -> T:
"""Get value or raise the error."""
if self._error is not None:
raise self._error
return self._value # type: ignore[return-value]
def unwrap_or(self, default: T) -> T:
"""Get value or return default."""
if self._error is not None:
return default
return self._value # type: ignore[return-value]
# Usage preserves types
def parse_config(path: str) -> Result[Config, ConfigError]:
try:
return Result(value=Config.from_file(path))
except ConfigError as e:
return Result(error=e)
result = parse_config("config.yaml")
if result.is_success:
config = result.unwrap() # Type: Config
Create type-safe data access patterns.
from typing import TypeVar, Generic
from abc import ABC, abstractmethod
T = TypeVar("T")
ID = TypeVar("ID")
class Repository(ABC, Generic[T, ID]):
"""Generic repository interface."""
@abstractmethod
async def get(self, id: ID) -> T | None:
"""Get entity by ID."""
...
@abstractmethod
async def save(self, entity: T) -> T:
"""Save and return entity."""
...
@abstractmethod
async def delete(self, id: ID) -> bool:
"""Delete entity, return True if existed."""
...
class UserRepository(Repository[User, str]):
"""Concrete repository for Users with string IDs."""
async def get(self, id: str) -> User | None:
row = await self._db.fetchrow(
"SELECT * FROM users WHERE id = $1", id
)
return User(**row) if row else None
async def save(self, entity: User) -> User:
...
async def delete(self, id: str) -> bool:
...
Restrict generic parameters to specific types.
from typing import TypeVar
from pydantic import BaseModel
ModelT = TypeVar("ModelT", bound=BaseModel)
def validate_and_create(model_cls: type[ModelT], data: dict) -> ModelT:
"""Create a validated Pydantic model from dict."""
return model_cls.model_validate(data)
# Works with any BaseModel subclass
class User(BaseModel):
name: str
email: str
user = validate_and_create(User, {"name": "Alice", "email": "a@b.com"})
# user is typed as User
# Type error: str is not a BaseModel subclass
result = validate_and_create(str, {"name": "Alice"}) # Error!
Define interfaces without requiring inheritance.
from typing import Protocol, runtime_checkable
@runtime_checkable
class Serializable(Protocol):
"""Any class that can be serialized to/from dict."""
def to_dict(self) -> dict:
...
@classmethod
def from_dict(cls, data: dict) -> "Serializable":
...
# User satisfies Serializable without inheriting from it
class User:
def __init__(self, id: str, name: str) -> None:
self.id = id
self.name = name
def to_dict(self) -> dict:
return {"id": self.id, "name": self.name}
@classmethod
def from_dict(cls, data: dict) -> "User":
return cls(id=data["id"], name=data["name"])
def serialize(obj: Serializable) -> str:
"""Works with any Serializable object."""
return json.dumps(obj.to_dict())
# Works - User matches the protocol
serialize(User("1", "Alice"))
# Runtime checking with @runtime_checkable
isinstance(User("1", "Alice"), Serializable) # True
Define reusable structural interfaces.
from typing import Protocol
class Closeable(Protocol):
"""Resource that can be closed."""
def close(self) -> None: ...
class AsyncCloseable(Protocol):
"""Async resource that can be closed."""
async def close(self) -> None: ...
class Readable(Protocol):
"""Object that can be read from."""
def read(self, n: int = -1) -> bytes: ...
class HasId(Protocol):
"""Object with an ID property."""
@property
def id(self) -> str: ...
class Comparable(Protocol):
"""Object that supports comparison."""
def __lt__(self, other: "Comparable") -> bool: ...
def __le__(self, other: "Comparable") -> bool: ...
Create meaningful type names.
Note: The type statement was introduced in Python 3.10 for simple aliases. Generic type statements require Python 3.12+.
# Python 3.10+ type statement for simple aliases
type UserId = str
type UserDict = dict[str, Any]
# Python 3.12+ type statement with generics
type Handler[T] = Callable[[Request], T]
type AsyncHandler[T] = Callable[[Request], Awaitable[T]]
# Python 3.9-3.11 style (needed for broader compatibility)
from typing import TypeAlias
from collections.abc import Callable, Awaitable
UserId: TypeAlias = str
Handler: TypeAlias = Callable[[Request], Response]
# Usage
def register_handler(path: str, handler: Handler[Response]) -> None:
...
Type function parameters and callbacks.
from collections.abc import Callable, Awaitable
# Sync callback
ProgressCallback = Callable[[int, int], None] # (current, total)
# Async callback
AsyncHandler = Callable[[Request], Awaitable[Response]]
# With named parameters (using Protocol)
class OnProgress(Protocol):
def __call__(
self,
current: int,
total: int,
*,
message: str = "",
) -> None: ...
def process_items(
items: list[Item],
on_progress: ProgressCallback | None = None,
) -> list[Result]:
for i, item in enumerate(items):
if on_progress:
on_progress(i, len(items))
...
For mypy --strict compliance:
# pyproject.toml
[tool.mypy]
python_version = "3.12"
strict = true
warn_return_any = true
warn_unused_ignores = true
disallow_untyped_defs = true
disallow_incomplete_defs = true
no_implicit_optional = true
Incremental adoption goals:
Any usage (acceptable for truly dynamic data)list[str] not list)For existing codebases, enable strict mode per-module using # mypy: strict or configure per-module overrides in pyproject.toml.
T | None - Modern union syntax over Optional[T]mypy --strict in CIAny - Use specific types or generics. Any is acceptable for truly dynamic data or when interfacing with untyped third-party code