New Typing Features in Python 3.13: ReadOnly, @warnings.deprecated, TypeIs, is_protocol, get_protocol_members, Default TypeVars, NoDefault, and Performance Improvements

Python 3.13 continues to push the limits of efficiency and elegance, adding seven new typing features that aim to improve code reliability and developer productivity.

1. ReadOnly type

The new ReadOnly type is a special construct for marking items in a TypedDict as read‑only.

<code>from typing import TypedDict, ReadOnly

class Leader(TypedDict):
    name: ReadOnly[str]
    age: int

author: Leader = {'name': 'Yang Zhou', 'age': 30}
author['age'] = 31  # no problem to change
author['name'] = 'Yang'  # Type check error: "name" is read‑only
</code>

When the name field is declared as ReadOnly[str] , static type checkers will flag any attempt to modify it.

Note: The ReadOnly type can only be used inside a TypedDict .

For a more concise definition you can also use ReadOnly directly in the TypedDict call:

<code>from typing import TypedDict, ReadOnly

Leader = TypedDict("Leader", {"name": ReadOnly[str], "age": int})

author: Leader = {'name': 'Yang Zhou', 'age': 30}
author['age'] = 31  # ok
author['name'] = 'Tim'  # Type check error
</code>

2. @warnings.deprecated

A new decorator @warnings.deprecated allows developers to mark functions or classes as deprecated, providing early warnings in IDEs while keeping the objects usable for a few more releases.

IDE integrations (e.g., PyCharm) will display a strike‑through on deprecated symbols.

3. TypeIs

The TypeIs concept enables type narrowing: a function declared as def foo(arg: TypeA) -> TypeIs[TypeB]: ... tells static checkers that a True return means arg is an instance of TypeB , and False means it is not.

4. is_protocol

The new is_protocol function provides a convenient way to test whether an object is a Protocol type.

<code>from typing import is_protocol, Protocol

class PersonProto(Protocol):
    name: str
    age: int

print(is_protocol(PersonProto))  # True
print(is_protocol(int))         # False
</code>

5. get_protocol_members

get_protocol_members() returns a frozenset containing all attribute names defined in a Protocol .

<code>from typing import Protocol, get_protocol_members

class PersonProto(Protocol):
    name: str
    age: int

print(get_protocol_members(PersonProto))  # frozenset({'age', 'name'})
</code>

6. Default types for TypeVar, ParamSpec, and TypeVarTuple

Python 3.13 allows specifying default types for type parameters. The has_default() method can check whether a TypeVar has a default.

<code>from typing import TypeVar
T = TypeVar("T", default=int)  # default is int
print(T.has_default())  # True
S = TypeVar("S")
print(S.has_default())  # False
</code>

7. NoDefault

The NoDefault sentinel indicates that a type variable has no default value.

<code>from typing import TypeVar, NoDefault
T = TypeVar("T")
print(T.__default__ is NoDefault)  # True
S = TypeVar("S", default=None)
print(S.__default__ is NoDefault)  # False
</code>

Performance improvements and API removals

Import time for the typing module is reduced by about one‑third thanks to the removal of dependencies on re and contextlib . Additionally, the deprecated namespaces typing.io and typing.re have been removed, and the keyword‑argument method for creating TypedDict types (deprecated since Python 3.11) is no longer available.

These changes streamline the typing ecosystem and encourage developers to import needed symbols directly from typing .