Modern type hints for safe, documented Python code.
\n# Variables\nname: str = \"Alice\"\ncount: int = 42\nitems: list[str] = [\"a\", \"b\"]\nmapping: dict[str, int] = {\"key\": 1}\n\n# Function signatures\ndef greet(name: str, times: int = 1) -> str:\n return f\"Hello, {name}!\" * times\n\n# None handling\ndef find(id: int) -> str | None:\n return db.get(id) # May return None\nfrom collections.abc import Sequence, Mapping, Iterable\n\n# Use collection ABCs for flexibility\ndef process(items: Sequence[str]) -> list[str]:\n \"\"\"Accepts list, tuple, or any sequence.\"\"\"\n return [item.upper() for item in items]\n\ndef lookup(data: Mapping[str, int], key: str) -> int:\n \"\"\"Accepts dict or any mapping.\"\"\"\n return data.get(key, 0)\n\n# Nested types\nMatrix = list[list[float]]\nConfig = dict[str, str | int | bool]\n# Modern syntax (3.10+)\ndef find(id: int) -> User | None:\n pass\n\ndef parse(value: str | int | float) -> str:\n pass\n\n# With default None\ndef fetch(url: str, timeout: float | None = None) -> bytes:\n pass\nfrom typing import TypedDict, Required, NotRequired\n\nclass UserDict(TypedDict):\n id: int\n name: str\n email: str | None\n\nclass ConfigDict(TypedDict, total=False): # All optional\n debug: bool\n log_level: str\n\nclass APIResponse(TypedDict):\n data: Required[list[dict]]\n error: NotRequired[str]\n\ndef process_user(user: UserDict) -> str:\n return user[\"name\"] # Type-safe key access\nfrom collections.abc import Callable\n\n# Function type\nHandler = Callable[[str, int], bool]\n\ndef register(callback: Callable[[str], None]) -> None:\n pass\n\n# With keyword args (use Protocol instead)\nfrom typing import Protocol\n\nclass Processor(Protocol):\n def __call__(self, data: str, *, verbose: bool = False) -> int:\n ...\nfrom typing import TypeVar\n\nT = TypeVar(\"T\")\n\ndef first(items: list[T]) -> T | None:\n return items[0] if items else None\n\n# Bounded TypeVar\nfrom typing import SupportsFloat\n\nN = TypeVar(\"N\", bound=SupportsFloat)\n\ndef average(values: list[N]) -> float:\n return sum(float(v) for v in values) / len(values)\nfrom typing import Protocol\n\nclass Readable(Protocol):\n def read(self, n: int = -1) -> bytes:\n ...\n\ndef load(source: Readable) -> dict:\n \"\"\"Accepts any object with read() method.\"\"\"\n data = source.read()\n return json.loads(data)\n\n# Works with file, BytesIO, custom classes\nload(open(\"data.json\", \"rb\"))\nload(io.BytesIO(b\"{}\"))\nfrom typing import TypeGuard\n\ndef is_string_list(val: list[object]) -> TypeGuard[list[str]]:\n return all(isinstance(x, str) for x in val)\n\ndef process(items: list[object]) -> None:\n if is_string_list(items):\n # items is now list[str]\n print(\", \".join(items))\nfrom typing import Literal, Final\n\nMode = Literal[\"read\", \"write\", \"append\"]\n\ndef open_file(path: str, mode: Mode) -> None:\n pass\n\n# Constants\nMAX_SIZE: Final = 1024\nAPI_VERSION: Final[str] = \"v2\"\n| Type | \nUse Case | \n
|---|---|
X \\| None | \nOptional value | \n
list[T] | \nHomogeneous list | \n
dict[K, V] | \nDictionary | \n
Callable[[Args], Ret] | \nFunction type | \n
TypeVar(\"T\") | \nGeneric parameter | \n
Protocol | \nStructural typing | \n
TypedDict | \nDict with fixed keys | \n
Literal[\"a\", \"b\"] | \nSpecific values only | \n
Final | \nCannot be reassigned | \n
# mypy (run inside the project env)\nuv run mypy src/ --strict\n\n# pyright\nuv run pyright src/\n\n# In pyproject.toml\n[tool.mypy]\nstrict = true\npython_version = \"3.11\"\nEmerging: ty — Astral's Rust-based type checker (same toolchain as uv +\nruff), dramatically faster than mypy. Still in preview (pre-1.0), so mypy or\npyright remain the production default — but worth watching, and easy to try:\nuvx ty check. Adopt for new projects once it stabilizes.
./references/generics-advanced.md - TypeVar, ParamSpec, TypeVarTuple./references/protocols-patterns.md - Structural typing, runtime protocols./references/type-narrowing.md - Guards, isinstance, assert./references/mypy-config.md - mypy/pyright configuration./references/runtime-validation.md - Pydantic v2, typeguard, beartype./references/overloads.md - @overload decorator patterns./scripts/check-types.sh - Run type checkers with common options./assets/pyproject-typing.toml - Recommended mypy/pyright configThis is a foundation skill with no prerequisites.
\nRelated Skills:
\npython-pytest-ops - Type-safe fixtures and mockingBuild on this skill:
\npython-async-ops - Async type annotationspython-fastapi-ops - Pydantic models and validationpython-database-ops - SQLAlchemy type annotations