That wants to use annotations for purposes outside Python’s static typing
#Definition of sequence synonym code
As such, Annotated can be useful for code No special logic for the metadata, it should ignore the metadata and simply If a library or tool encounters an annotation Annotated and has Metadata added using Annotated can be used by Special typing form to add context-specific metadata to an annotation.Īdd metadata x to a given type T by using the annotationĪnnotated. In this case, the ParamSpec indicates that the returnedĬallable’s parameter types are dependent on the parameter types of the Lock as the first argument, and returns a callable with a different type Used to indicate that with_lock expects a callable which takes in a Threading.Lock to the decorated function, Concatenate can be The last parameter to Concatenate must be a ParamSpec orįor example, to annotate a decorator with_lock which provides a Is currently only valid when used as the first argument to a Callable. ParamSpec to annotate a higher-order callable which adds, removes,Ĭoncatenate. Special form for annotating higher-order functions.Ĭoncatenate can be used in conjunction with Callable and What one would normally do in idiomatic dynamically typed Python code.Ĭhanged in version 3.10: Optional can now be written as X | None. To be explicitly marked to support them, which is unpythonic and unlike The problem with this approach is that a class had This requirement previously also applied to abstract base classes, such as This means that a class A is allowed whereĪ class B is expected if and only if A is a subclass of B. Initially PEP 484 defined the Python static type system as using Use Any to indicate that a value is dynamically typed. Use object to indicate that a value could be any type in a typesafe
# Passes type checking, since ints and strs are subclasses of object hash_a ( 42 ) hash_a ( "foo" ) # Passes type checking, since Any is compatible with all types hash_b ( 42 ) hash_b ( "foo" ) def hash_b ( item : Any ) -> int : # Passes type checking item. Take the form Callable andĬallable, ReturnType]ĭef hash_a ( item : object ) -> int : # Fails type checking an object does not have a 'magic' method. Parameter types are dependent on each other using ParamSpec.Īdditionally, if that callable adds or removes arguments from otherĬallables, the Concatenate operator may be used. batch_proc (, good_cb ) # OK batch_proc (, bad_cb ) # Error! Argument 2 has incompatible type because of # different name and kind in the callbackĬallables which take other callables as arguments may indicate that their def bad_cb ( * vals : bytes, maxitems : int | None ) -> list. def good_cb ( * vals : bytes, maxlen : int | None = None ) -> list. def batch_proc ( data : Iterable, cb_results : Combiner ) -> bytes : for item in data. Vector and list will be treated as interchangeable synonyms:įrom collections.abc import Iterable from typing import Protocol class Combiner ( Protocol ): def _call_ ( self, * vals : bytes, maxlen : int | None = None ) -> list. PEP 655: Marking individual TypedDict items as required or potentially missingĪ type alias is defined by assigning the type to the alias.PEP 612: Parameter Specification Variables.Introducing types.UnionType and the ability to use PEP 604: Allow writing union types as X | Y.PEP 593: Flexible function and variable annotations.PEP 591: Adding a final qualifier to typing.PEP 589: TypedDict: Type Hints for Dictionaries with a Fixed Set of Keys.Introducing types.GenericAlias and the ability to use standard PEP 585: Type Hinting Generics In Standard Collections.PEP 544: Protocols: Structural subtyping (static duck typing).
Introducing syntax for annotating variables outside of function PEP 526: Syntax for Variable Annotations.Number of PEPs have modified and enhanced Python’s framework for type Since the initial introduction of type hints in PEP 484 and PEP 483, a Type system features, useful typing related tools and typing best Type-checker-agnostic documentation written by the community detailing (Some parts may stillīe specific to mypy.) “Static Typing with Python” Should broadly apply to most Python type checkers. The Python typing system is standardised via PEPs, so this reference A quick overview of type hints (hosted at the mypy docs) “Type System Reference” section of the mypy docs
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