.. _`type-qualifiers`: Type qualifiers =============== This chapter describes the behavior of some :term:`type qualifiers `. Additional type qualifiers are covered in other chapters: * :ref:`ClassVar ` * :ref:`NotRequired ` * :ref:`ReadOnly ` * :ref:`Required ` .. _`at-final`: ``@final`` ---------- (Originally specified in :pep:`591`.) The ``typing.final`` decorator is used to restrict the use of inheritance and overriding. A type checker should prohibit any class decorated with ``@final`` from being subclassed and any method decorated with ``@final`` from being overridden in a subclass. The method decorator version may be used with all of instance methods, class methods, static methods, and properties. For example:: from typing import final @final class Base: ... class Derived(Base): # Error: Cannot inherit from final class "Base" ... and:: from typing import final class Base: @final def foo(self) -> None: ... class Derived(Base): def foo(self) -> None: # Error: Cannot override final attribute "foo" # (previously declared in base class "Base") ... For overloaded methods, ``@final`` should be placed on the implementation (or on the first overload, for stubs):: from typing import Any, overload class Base: @overload def method(self) -> None: ... @overload def method(self, arg: int) -> int: ... @final def method(self, x=None): ... It is an error to use ``@final`` on a non-method function. .. _`uppercase-final`: ``Final`` --------- (Originally specified in :pep:`591`.) The ``typing.Final`` :term:`type qualifier` is used to indicate that a variable or attribute should not be reassigned, redefined, or overridden. Syntax ^^^^^^ ``Final`` may be used in one of several forms: * With an explicit type, using the syntax ``Final[]``. Example:: ID: Final[float] = 1 * With no type annotation. Example:: ID: Final = 1 The typechecker should apply its usual type inference mechanisms to determine the type of ``ID`` (here, likely, ``int``). Note that unlike for generic classes this is *not* the same as ``Final[Any]``. * In class bodies and stub files you can omit the right hand side and just write ``ID: Final[float]``. If the right hand side is omitted, there must be an explicit type argument to ``Final``. * Finally, as ``self.id: Final = 1`` (also optionally with a type in square brackets). This is allowed *only* in ``__init__`` methods, so that the final instance attribute is assigned only once when an instance is created. Semantics and examples ^^^^^^^^^^^^^^^^^^^^^^ The two main rules for defining a final name are: * There can be *at most one* final declaration per module or class for a given attribute. There can't be separate class-level and instance-level constants with the same name. * There must be *exactly one* assignment to a final name. This means a type checker should prevent further assignments to final names in type-checked code:: from typing import Final RATE: Final = 3000 class Base: DEFAULT_ID: Final = 0 RATE = 300 # Error: can't assign to final attribute Base.DEFAULT_ID = 1 # Error: can't override a final attribute Note that a type checker need not allow ``Final`` declarations inside loops since the runtime will see multiple assignments to the same variable in subsequent iterations. Additionally, a type checker should prevent final attributes from being overridden in a subclass:: from typing import Final class Window: BORDER_WIDTH: Final = 2.5 ... class ListView(Window): BORDER_WIDTH = 3 # Error: can't override a final attribute A final attribute declared in a class body without an initializer must be initialized in the ``__init__`` method (except in stub files):: class ImmutablePoint: x: Final[int] y: Final[int] # Error: final attribute without an initializer def __init__(self) -> None: self.x = 1 # Good The generated ``__init__`` method of :doc:`dataclasses` qualifies for this requirement: a bare ``x: Final[int]`` is permitted in a dataclass body, because the generated ``__init__`` will initialize ``x``. Type checkers should infer a final attribute that is initialized in a class body as being a class variable, except in the case of :doc:`dataclasses`, where ``x: Final[int] = 3`` creates a dataclass field and instance-level final attribute ``x`` with default value ``3``; ``x: ClassVar[Final[int]] = 3`` is necessary to create a final class variable with value ``3``. In non-dataclasses, combining ``ClassVar`` and ``Final`` is redundant, and type checkers may choose to warn or error on the redundancy. ``Final`` may only be used in assignments or variable annotations. Using it in any other position is an error. In particular, ``Final`` can't be used in annotations for function arguments:: x: list[Final[int]] = [] # Error! def fun(x: Final[List[int]]) -> None: # Error! ... ``Final`` may be wrapped only by other type qualifiers (e.g. ``ClassVar`` or ``Annotated``). It cannot be used in a type parameter (e.g. ``list[Final[int]]`` is not permitted.) Note that declaring a name as final only guarantees that the name will not be re-bound to another value, but does not make the value immutable. Immutable ABCs and containers may be used in combination with ``Final`` to prevent mutating such values:: x: Final = ['a', 'b'] x.append('c') # OK y: Final[Sequence[str]] = ['a', 'b'] y.append('x') # Error: "Sequence[str]" has no attribute "append" z: Final = ('a', 'b') # Also works Type checkers should treat uses of a final name that was initialized with a literal as if it was replaced by the literal. For example, the following should be allowed:: from typing import NamedTuple, Final X: Final = "x" Y: Final = "y" N = NamedTuple("N", [(X, int), (Y, int)]) ``Final`` cannot be used as a qualifier for a :ref:`TypedDict ` item or a :ref:`NamedTuple ` field. Such usage also generates an error at runtime. Importing ``Final`` Variables ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ If a module declares a ``Final`` variable and another module imports that variable in an import statement by name or wildcard, the imported symbol inherits the ``Final`` type qualifier. Any attempt to assign a different value to this symbol should be flagged as an error by a type checker:: # lib/submodule.py from typing import Final PI: Final = 3.14 # lib/__init__.py from .submodule import PI # PI is Final # test1.py from lib import PI PI = 0 # Error: Can't assign to Final value from lib import PI as PI2 PI2 = 0 # Error: Can't assign to Final value # test2.py from lib import * PI = 0 # Error: Can't assign to Final value .. _`annotated`: ``Annotated`` ------------- (Originally specified by :pep:`593`.) Syntax ^^^^^^ ``Annotated`` is parameterized with a *base expression* and at least one Python value representing associated *metadata*:: from typing import Annotated Annotated[BaseExpr, Metadata1, Metadata2, ...] Here are the specific details of the syntax: * The base expression (the first argument to ``Annotated``) must be valid in the context where it is being used: * If ``Annotated`` is used in a place where arbitrary :term:`annotation expressions ` are allowed, the base expression may be an annotation expression. * Otherwise, the base expression must be a valid :term:`type expression`. * Multiple metadata elements are supported (``Annotated`` supports variadic arguments):: Annotated[int, ValueRange(3, 10), ctype("char")] * There must be at least one metadata element (``Annotated[int]`` is not valid) * The order of the metadata is preserved and matters for equality checks:: Annotated[int, ValueRange(3, 10), ctype("char")] != Annotated[ int, ctype("char"), ValueRange(3, 10) ] * Nested ``Annotated`` types are flattened, with metadata ordered starting with the innermost ``Annotated`` expression:: Annotated[Annotated[int, ValueRange(3, 10)], ctype("char")] == Annotated[ int, ValueRange(3, 10), ctype("char") ] * Duplicated metadata elements are not removed:: Annotated[int, ValueRange(3, 10)] != Annotated[ int, ValueRange(3, 10), ValueRange(3, 10) ] * ``Annotated`` can be used in definition of nested and generic aliases, but only if it wraps a :term:`type expression`:: T = TypeVar("T") Vec = Annotated[list[tuple[T, T]], MaxLen(10)] V = Vec[int] V == Annotated[list[tuple[int, int]], MaxLen(10)] * As with most :term:`special forms `, ``Annotated`` is not assignable to ``type`` or ``type[T]``:: v1: type[int] = Annotated[int, ""] # Type error SmallInt: TypeAlias = Annotated[int, ValueRange(0, 100)] v2: type[Any] = SmallInt # Type error * An attempt to call ``Annotated`` (whether parameterized or not) should be treated as a type error by type checkers:: Annotated() # Type error Annotated[int, ""](0) # Type error SmallInt = Annotated[int, ValueRange(0, 100)] SmallInt(1) # Type error :pep:`593` and an earlier version of this specification used the term "annotations" instead of "metadata" for the extra arguments to ``Annotated``. The term "annotations" is deprecated to avoid confusion with the parameter, return, and variable annotations that are part of the Python syntax. Meaning ^^^^^^^ The metadata provided by ``Annotated`` can be used for either static or runtime analysis. If a library (or tool) encounters an instance of ``Annotated[T, x]`` and has no special logic for metadata element ``x``, it should ignore it and treat the expression as equivalent to ``T``. Thus, in general, any :term:`type expression` or :term:`annotation expression` may be wrapped in ``Annotated`` without changing the meaning of the wrapped expression. However, type checkers may additionally choose to recognize particular metadata elements and use them to implement extensions to the standard type system. ``Annotated`` metadata may apply either to the base expression or to the symbol being annotated, or even to some other aspect of the program. Consuming metadata ^^^^^^^^^^^^^^^^^^ Ultimately, deciding how to interpret the metadata (if at all) is the responsibility of the tool or library encountering the ``Annotated`` type. A tool or library encountering an ``Annotated`` type can scan through the metadata to determine if they are of interest (e.g., using ``isinstance()``). **Unknown metadata:** When a tool or a library does not support metadata or encounters an unknown metadata element, it should ignore it and treat the annotation as the base expression. **Namespacing metadata:** Namespaces are not needed for metadata since the class of the metadata object acts as a namespace. **Multiple metadata elements:** It's up to the tool consuming the metadata to decide whether the client is allowed to have several metadata elements on one annotation and how to merge those elements. Since the ``Annotated`` type allows you to put several metadata elements of the same (or different) type(s) on any annotation, the tools or libraries consuming the metadata are in charge of dealing with potential duplicates. For example, if you are doing value range analysis you might allow this:: T1 = Annotated[int, ValueRange(-10, 5)] T2 = Annotated[T1, ValueRange(-20, 3)] Flattening nested annotations, this translates to:: T2 = Annotated[int, ValueRange(-10, 5), ValueRange(-20, 3)] Aliases & Concerns over verbosity ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Writing ``typing.Annotated`` everywhere can be quite verbose; fortunately, the ability to alias types means that in practice we don't expect clients to have to write lots of boilerplate code:: type Const[T] = Annotated[T, my_annotations.CONST] class C: def const_method(self, x: Const[list[int]]) -> int: ...