# Type narrowing

This section is dedicated to several type narrowing techniques which are supported by mypy.

Type narrowing is when you convince a type checker that a broader type is actually more specific, for instance, that an object of type `Shape` is actually of the narrower type `Square`.

## Type narrowing expressions

The simplest way to narrow a type is to use one of the supported expressions:

- `isinstance()` like in `isinstance(obj, float)` will narrow `obj` to have `float` type

- `issubclass()` like in `issubclass(cls, MyClass)` will narrow `cls` to be `Type[MyClass]`

- `type()` like in `type(obj) is int` will narrow `obj` to have `int` type

- `callable()` like in `callable(obj)` will narrow object to callable type

Type narrowing is contextual. For example, based on the condition, mypy will narrow an expression only within an `if` branch:

    def function(arg: object):
        if isinstance(arg, int):
            # Type is narrowed within the ``if`` branch only
            reveal_type(arg)  # Revealed type: "builtins.int"
        elif isinstance(arg, str) or isinstance(arg, bool):
            # Type is narrowed differently within this ``elif`` branch:
            reveal_type(arg)  # Revealed type: "builtins.str | builtins.bool"

            # Subsequent narrowing operations will narrow the type further
            if isinstance(arg, bool):
                reveal_type(arg)  # Revealed type: "builtins.bool"

        # Back outside of the ``if`` statement, the type isn't narrowed:
        reveal_type(arg)  # Revealed type: "builtins.object"

Mypy understands the implications `return` or exception raising can have for what type an object could be:

    def function(arg: int | str):
        if isinstance(arg, int):
            return

        # `arg` can't be `int` at this point:
        reveal_type(arg)  # Revealed type: "builtins.str"

We can also use `assert` to narrow types in the same context:

    def function(arg: Any):
        assert isinstance(arg, int)
        reveal_type(arg)  # Revealed type: "builtins.int"

Note

With `--warn-unreachable` narrowing types to some impossible state will be treated as an error.

    def function(arg: int):
        # error: Subclass of "int" and "str" cannot exist:
        # would have incompatible method signatures
        assert isinstance(arg, str)

        # error: Statement is unreachable
        print("so mypy concludes the assert will always trigger")

Without `--warn-unreachable` mypy will simply not check code it deems to be unreachable. See Unreachable code for more information.

    x: int = 1
    assert isinstance(x, str)
    reveal_type(x)  # Revealed type is "builtins.int"
    print(x + '!')  # Typechecks with `mypy`, but fails in runtime.

### issubclass

Mypy can also use `issubclass()` for better type inference when working with types and metaclasses:

    class MyCalcMeta(type):
        @classmethod
        def calc(cls) -> int:
            ...

    def f(o: object) -> None:
        t = type(o)  # We must use a variable here
        reveal_type(t)  # Revealed type is "builtins.type"

        if issubtype(t, MyCalcMeta):  # `issubtype(type(o), MyCalcMeta)` won't work
            reveal_type(t)  # Revealed type is "Type[MyCalcMeta]"
            t.calc()  # Okay

### callable

Mypy knows what types are callable and which ones are not during type checking. So, we know what `callable()` will return. For example:

    from typing import Callable

    x: Callable[[], int]

    if callable(x):
        reveal_type(x)  # N: Revealed type is "def () -> builtins.int"
    else:
        ...  # Will never be executed and will raise error with `--warn-unreachable`

`callable` function can even split `Union` type for callable and non-callable parts:

    from typing import Callable, Union

    x: Union[int, Callable[[], int]]

    if callable(x):
        reveal_type(x)  # N: Revealed type is "def () -> builtins.int"
    else:
        reveal_type(x)  # N: Revealed type is "builtins.int"

## Casts

Mypy supports type casts that are usually used to coerce a statically typed value to a subtype. Unlike languages such as Java or C#, however, mypy casts are only used as hints for the type checker, and they don’t perform a runtime type check. Use the function `cast()` to perform a cast:

    from typing import cast

    o: object = [1]
    x = cast(list[int], o)  # OK
    y = cast(list[str], o)  # OK (cast performs no actual runtime check)

To support runtime checking of casts such as the above, we’d have to check the types of all list items, which would be very inefficient for large lists. Casts are used to silence spurious type checker warnings and give the type checker a little help when it can’t quite understand what is going on.

Note

You can use an assertion if you want to perform an actual runtime check:

    def foo(o: object) -> None:
        print(o + 5)  # Error: can't add 'object' and 'int'
        assert isinstance(o, int)
        print(o + 5)  # OK: type of 'o' is 'int' here

You don’t need a cast for expressions with type `Any`, or when assigning to a variable with type `Any`, as was explained earlier. You can also use `Any` as the cast target type – this lets you perform any operations on the result. For example:

    from typing import cast, Any

    x = 1
    x.whatever()  # Type check error
    y = cast(Any, x)
    y.whatever()  # Type check OK (runtime error)

## User-Defined Type Guards

Mypy supports User-Defined Type Guards (PEP 647).

A type guard is a way for programs to influence conditional type narrowing employed by a type checker based on runtime checks.

Basically, a `TypeGuard` is a “smart” alias for a `bool` type. Let’s have a look at the regular `bool` example:

    def is_str_list(val: list[object]) -> bool:
      """Determines whether all objects in the list are strings"""
      return all(isinstance(x, str) for x in val)

    def func1(val: list[object]) -> None:
        if is_str_list(val):
            reveal_type(val)  # Reveals list[object]
            print(" ".join(val)) # Error: incompatible type

The same example with `TypeGuard`:

    from typing import TypeGuard  # use `typing_extensions` for Python 3.9 and below

    def is_str_list(val: list[object]) -> TypeGuard[list[str]]:
        """Determines whether all objects in the list are strings"""
        return all(isinstance(x, str) for x in val)

    def func1(val: list[object]) -> None:
        if is_str_list(val):
            reveal_type(val)  # list[str]
            print(" ".join(val)) # ok

How does it work? `TypeGuard` narrows the first function argument (`val`) to the type specified as the first type parameter (`list[str]`).

Note

Narrowing is not strict. For example, you can narrow `str` to `int`:

    def f(value: str) -> TypeGuard[int]:
        return True

Note: since strict narrowing is not enforced, it’s easy to break type safety.

However, there are many ways a determined or uninformed developer can subvert type safety – most commonly by using cast or Any. If a Python developer takes the time to learn about and implement user-defined type guards within their code, it is safe to assume that they are interested in type safety and will not write their type guard functions in a way that will undermine type safety or produce nonsensical results.

### Generic TypeGuards

`TypeGuard` can also work with generic types:

    from typing import TypeVar
    from typing import TypeGuard  # use `typing_extensions` for `python<3.10`

    _T = TypeVar("_T")

    def is_two_element_tuple(val: tuple[_T, ...]) -> TypeGuard[tuple[_T, _T]]:
        return len(val) == 2

    def func(names: tuple[str, ...]):
        if is_two_element_tuple(names):
            reveal_type(names)  # tuple[str, str]
        else:
            reveal_type(names)  # tuple[str, ...]

### Typeguards with parameters

Type guard functions can accept extra arguments:

    from typing import Type, TypeVar
    from typing import TypeGuard  # use `typing_extensions` for `python<3.10`

    _T = TypeVar("_T")

    def is_set_of(val: set[Any], type: Type[_T]) -> TypeGuard[set[_T]]:
        return all(isinstance(x, type) for x in val)

    items: set[Any]
    if is_set_of(items, str):
        reveal_type(items)  # set[str]

### TypeGuards as methods

> A method can also serve as the `TypeGuard`:

    class StrValidator:
        def is_valid(self, instance: object) -> TypeGuard[str]:
            return isinstance(instance, str)

    def func(to_validate: object) -> None:
        if StrValidator().is_valid(to_validate):
            reveal_type(to_validate)  # Revealed type is "builtins.str"

Note

Note, that `TypeGuard` does not narrow types of `self` or `cls` implicit arguments.

If narrowing of `self` or `cls` is required, the value can be passed as an explicit argument to a type guard function:

    class Parent:
        def method(self) -> None:
            reveal_type(self)  # Revealed type is "Parent"
            if is_child(self):
                reveal_type(self)  # Revealed type is "Child"

    class Child(Parent):
        ...

    def is_child(instance: Parent) -> TypeGuard[Child]:
        return isinstance(instance, Child)

### Assignment expressions as TypeGuards

Sometimes you might need to create a new variable and narrow it to some specific type at the same time. This can be achieved by using `TypeGuard` together with := operator.

    from typing import TypeGuard  # use `typing_extensions` for `python<3.10`

    def is_float(a: object) -> TypeGuard[float]:
        return isinstance(a, float)

    def main(a: object) -> None:
        if is_float(x := a):
            reveal_type(x)  # N: Revealed type is 'builtins.float'
            reveal_type(a)  # N: Revealed type is 'builtins.object'
        reveal_type(x)  # N: Revealed type is 'builtins.object'
        reveal_type(a)  # N: Revealed type is 'builtins.object'

What happens here?

1. We create a new variable `x` and assign a value of `a` to it

2. We run `is_float()` type guard on `x`

3. It narrows `x` to be `float` in the `if` context and does not touch `a`

Note

The same will work with `isinstance(x := a, float)` as well.