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                ??碼云GVP開源項目 12k star Uniapp+ElementUI 功能強大 支持多語言、二開方便! 廣告
                ### 導航 - [索引](../genindex.xhtml "總目錄") - [模塊](../py-modindex.xhtml "Python 模塊索引") | - [下一頁](pydoc.xhtml "pydoc --- Documentation generator and online help system") | - [上一頁](development.xhtml "開發工具") | - ![](https://box.kancloud.cn/a721fc7ec672275e257bbbfde49a4d4e_16x16.png) - [Python](https://www.python.org/) ? - zh\_CN 3.7.3 [文檔](../index.xhtml) ? - [Python 標準庫](index.xhtml) ? - [開發工具](development.xhtml) ? - $('.inline-search').show(0); | # [`typing`](#module-typing "typing: Support for type hints (see PEP 484).") --- 類型標注支持 3\.5 新版功能. **源碼:** [Lib/typing.py](https://github.com/python/cpython/tree/3.7/Lib/typing.py) \[https://github.com/python/cpython/tree/3.7/Lib/typing.py\] 注解 typing 模塊以 [暫定狀態](../glossary.xhtml#term-provisional-api) 包含在標準庫中。如果核心開發人員認為有必要,可能會添加新功能,甚至可能會在次要版本之間改變 API。 - - - - - - 此模塊支持 [**PEP 484**](https://www.python.org/dev/peps/pep-0484) \[https://www.python.org/dev/peps/pep-0484\] 和 [**PEP 526**](https://www.python.org/dev/peps/pep-0526) \[https://www.python.org/dev/peps/pep-0526\] 指定的類型提示。最基本的支持由 [`Any`](#typing.Any "typing.Any"),[`Union`](#typing.Union "typing.Union"),[`Tuple`](#typing.Tuple "typing.Tuple"),[`Callable`](#typing.Callable "typing.Callable"),[`TypeVar`](#typing.TypeVar "typing.TypeVar") 和 [`Generic`](#typing.Generic "typing.Generic") 類型組成。有關完整的規范,請參閱 [**PEP 484**](https://www.python.org/dev/peps/pep-0484) \[https://www.python.org/dev/peps/pep-0484\]。有關類型提示的簡單介紹,請參閱 [**PEP 483**](https://www.python.org/dev/peps/pep-0483) \[https://www.python.org/dev/peps/pep-0483\]。 函數接受并返回一個字符串,注釋像下面這樣: ``` def greeting(name: str) -> str: return 'Hello ' + name ``` 在函數 `greeting` 中,參數 `name` 預期是 [`str`](stdtypes.xhtml#str "str") 類型,并且返回 [`str`](stdtypes.xhtml#str "str") 類型。子類型允許作為參數。 ## 類型別名 類型別名通過將類型分配給別名來定義。在這個例子中, `Vector` 和 `List[float]` 將被視為可互換的同義詞: ``` from typing import List Vector = List[float] def scale(scalar: float, vector: Vector) -> Vector: return [scalar * num for num in vector] # typechecks; a list of floats qualifies as a Vector. new_vector = scale(2.0, [1.0, -4.2, 5.4]) ``` 類型別名可用于簡化復雜類型簽名。例如: ``` from typing import Dict, Tuple, Sequence ConnectionOptions = Dict[str, str] Address = Tuple[str, int] Server = Tuple[Address, ConnectionOptions] def broadcast_message(message: str, servers: Sequence[Server]) -> None: ... # The static type checker will treat the previous type signature as # being exactly equivalent to this one. def broadcast_message( message: str, servers: Sequence[Tuple[Tuple[str, int], Dict[str, str]]]) -> None: ... ``` 請注意,`None` 作為類型提示是一種特殊情況,并且由 `type(None)` 取代。 ## NewType 使用 [`NewType()`](#typing.NewType "typing.NewType") 輔助函數創建不同的類型: ``` from typing import NewType UserId = NewType('UserId', int) some_id = UserId(524313) ``` 靜態類型檢查器會將新類型視為它是原始類型的子類。這對于幫助捕捉邏輯錯誤非常有用: ``` def get_user_name(user_id: UserId) -> str: ... # typechecks user_a = get_user_name(UserId(42351)) # does not typecheck; an int is not a UserId user_b = get_user_name(-1) ``` 您仍然可以對 `UserId` 類型的變量執行所有的 `int` 支持的操作,但結果將始終為 `int` 類型。這可以讓你在需要 `int` 的地方傳入 `UserId`,但會阻止你以無效的方式無意中創建 `UserId`: ``` # 'output' is of type 'int', not 'UserId' output = UserId(23413) + UserId(54341) ``` 請注意,這些檢查僅通過靜態類型檢查程序強制執行。在運行時,`Derived = NewType('Derived',Base)` 將 `Derived` 一個函數,該函數立即返回您傳遞它的任何參數。這意味著表達式 `Derived(some_value)` 不會創建一個新的類或引入任何超出常規函數調用的開銷。 更確切地說,表達式 `some_value is Derived(some_value)` 在運行時總是為真。 這也意味著無法創建 `Derived` 的子類型,因為它是運行時的標識函數,而不是實際的類型: ``` from typing import NewType UserId = NewType('UserId', int) # Fails at runtime and does not typecheck class AdminUserId(UserId): pass ``` 但是,可以基于'derived' `NewType` 創建 [`NewType()`](#typing.NewType "typing.NewType") ``` from typing import NewType UserId = NewType('UserId', int) ProUserId = NewType('ProUserId', UserId) ``` 并且 `ProUserId` 的類型檢查將按預期工作。 有關更多詳細信息,請參閱 [**PEP 484**](https://www.python.org/dev/peps/pep-0484) \[https://www.python.org/dev/peps/pep-0484\]。 注解 回想一下,使用類型別名聲明兩種類型彼此 *等效* 。`Alias = Original` 將使靜態類型檢查對待所有情況下 `Alias` *完全等同于*`Original`。當您想簡化復雜類型簽名時,這很有用。 相反,`NewType` 聲明一種類型是另一種類型的子類型。`Derived = NewType('Derived', Original)` 將使靜態類型檢查器將 `Derived` 當作 `Original` 的 *子類* ,這意味著 `Original` 類型的值不能用于 `Derived` 類型的值需要的地方。當您想以最小的運行時間成本防止邏輯錯誤時,這非常有用。 3\.5.2 新版功能. ## Callable 期望特定簽名的回調函數的框架可以將類型標注為 `Callable[[Arg1Type, Arg2Type], ReturnType]`。 例如: ``` from typing import Callable def feeder(get_next_item: Callable[[], str]) -> None: # Body def async_query(on_success: Callable[[int], None], on_error: Callable[[int, Exception], None]) -> None: # Body ``` 通過用文字省略號替換類型提示中的參數列表: `Callable[...,ReturnType]`,可以聲明可調用的返回類型,而無需指定調用簽名。 ## 泛型(Generic) 由于無法以通用方式靜態推斷有關保存在容器中的對象的類型信息,因此抽象基類已擴展為支持訂閱以表示容器元素的預期類型。 ``` from typing import Mapping, Sequence def notify_by_email(employees: Sequence[Employee], overrides: Mapping[str, str]) -> None: ... ``` 泛型可以通過使用typing模塊中名為 [`TypeVar`](#typing.TypeVar "typing.TypeVar") 的新工廠進行參數化。 ``` from typing import Sequence, TypeVar T = TypeVar('T') # Declare type variable def first(l: Sequence[T]) -> T: # Generic function return l[0] ``` ## 用戶定義的泛型類型 用戶定義的類可以定義為泛型類。 ``` from typing import TypeVar, Generic from logging import Logger T = TypeVar('T') class LoggedVar(Generic[T]): def __init__(self, value: T, name: str, logger: Logger) -> None: self.name = name self.logger = logger self.value = value def set(self, new: T) -> None: self.log('Set ' + repr(self.value)) self.value = new def get(self) -> T: self.log('Get ' + repr(self.value)) return self.value def log(self, message: str) -> None: self.logger.info('%s: %s', self.name, message) ``` `Generic[T]` 作為基類定義了類 `LoggedVar` 采用單個類型參數 `T`。這也使得 `T` 作為類體內的一個類型有效。 [`Generic`](#typing.Generic "typing.Generic") 基類使用定義了 [`__getitem__()`](../reference/datamodel.xhtml#object.__getitem__ "object.__getitem__") 的元類,以便 `LoggedVar[t]` 作為類型有效: ``` from typing import Iterable def zero_all_vars(vars: Iterable[LoggedVar[int]]) -> None: for var in vars: var.set(0) ``` 泛型類型可以有任意數量的類型變量,并且類型變量可能會受到限制: ``` from typing import TypeVar, Generic ... T = TypeVar('T') S = TypeVar('S', int, str) class StrangePair(Generic[T, S]): ... ``` [`Generic`](#typing.Generic "typing.Generic") 每個參數的類型變量必須是不同的。這是無效的: ``` from typing import TypeVar, Generic ... T = TypeVar('T') class Pair(Generic[T, T]): # INVALID ... ``` 您可以對 [`Generic`](#typing.Generic "typing.Generic") 使用多重繼承: ``` from typing import TypeVar, Generic, Sized T = TypeVar('T') class LinkedList(Sized, Generic[T]): ... ``` 從泛型類繼承時,某些類型變量可能是固定的: ``` from typing import TypeVar, Mapping T = TypeVar('T') class MyDict(Mapping[str, T]): ... ``` 在這種情況下,`MyDict` 只有一個參數,`T`。 在不指定類型參數的情況下使用泛型類別會為每個位置假設 [`Any`](#typing.Any "typing.Any")。在下面的例子中,`MyIterable` 不是泛型,但是隱式繼承自 `Iterable[Any]`: ``` from typing import Iterable class MyIterable(Iterable): # Same as Iterable[Any] ``` 用戶定義的通用類型別名也受支持。例子: ``` from typing import TypeVar, Iterable, Tuple, Union S = TypeVar('S') Response = Union[Iterable[S], int] # Return type here is same as Union[Iterable[str], int] def response(query: str) -> Response[str]: ... T = TypeVar('T', int, float, complex) Vec = Iterable[Tuple[T, T]] def inproduct(v: Vec[T]) -> T: # Same as Iterable[Tuple[T, T]] return sum(x*y for x, y in v) ``` [`Generic`](#typing.Generic "typing.Generic") 使用的元類是 [`abc.ABCMeta`](abc.xhtml#abc.ABCMeta "abc.ABCMeta") 的子類。泛型類可以通過包含抽象方法或屬性成為ABC,并且泛型類也可以使用ABCs作為基類而不存在元類沖突。不支持泛型元類。參數化泛型的結果被緩存,并且typing模塊中的大部分類型都是可散列的,并且可以比較是否相等。 ## [`Any`](#typing.Any "typing.Any") 類型 [`Any`](#typing.Any "typing.Any") 是一種特殊的類型。靜態類型檢查器將所有類型視為與 [`Any`](#typing.Any "typing.Any") 兼容,反之亦然, [`Any`](#typing.Any "typing.Any") 也與所有類型相兼容。 這意味著可對類型為 [`Any`](#typing.Any "typing.Any") 的值執行任何操作或方法調用,并將其賦值給任何變量: ``` from typing import Any a = None # type: Any a = [] # OK a = 2 # OK s = '' # type: str s = a # OK def foo(item: Any) -> int: # Typechecks; 'item' could be any type, # and that type might have a 'bar' method item.bar() ... ``` 需要注意的是,將 [`Any`](#typing.Any "typing.Any") 類型的值賦值給另一個更具體的類型時,Python不會執行類型檢查。例如,當把 `a` 賦值給 `s` 時,即使 `s` 被聲明為 [`str`](stdtypes.xhtml#str "str") 類型,在運行時接收到的是 [`int`](functions.xhtml#int "int") 值,靜態類型檢查器也不會報錯。 此外,所有返回值無類型或形參無類型的函數將隱式地默認使用 [`Any`](#typing.Any "typing.Any") 類型: ``` def legacy_parser(text): ... return data # A static type checker will treat the above # as having the same signature as: def legacy_parser(text: Any) -> Any: ... return data ``` 當需要混用動態類型和靜態類型的代碼時,上述行為可以讓 [`Any`](#typing.Any "typing.Any") 被用作 *應急出口* 。 [`Any`](#typing.Any "typing.Any") 和 [`object`](functions.xhtml#object "object") 的行為對比。與 [`Any`](#typing.Any "typing.Any") 相似,所有的類型都是 [`object`](functions.xhtml#object "object") 的子類型。然而不同于 [`Any`](#typing.Any "typing.Any"),反之并不成立: [`object`](functions.xhtml#object "object") *不是* 其他所有類型的子類型。 這意味著當一個值的類型是 [`object`](functions.xhtml#object "object") 的時候,類型檢查器會拒絕對它的幾乎所有的操作。把它賦值給一個指定了類型的變量(或者當作返回值)是一個類型錯誤。比如說: ``` def hash_a(item: object) -> int: # Fails; an object does not have a 'magic' method. item.magic() ... def hash_b(item: Any) -> int: # Typechecks item.magic() ... # Typechecks, since ints and strs are subclasses of object hash_a(42) hash_a("foo") # Typechecks, since Any is compatible with all types hash_b(42) hash_b("foo") ``` 使用 [`object`](functions.xhtml#object "object") 示意一個值可以類型安全地兼容任何類型。使用 [`Any`](#typing.Any "typing.Any") 示意一個值地類型是動態定義的。 ## 類,函數和修飾器. 這個模塊定義了如下的類,模塊和修飾器. *class* `typing.``TypeVar`類型變量 用法: ``` T = TypeVar('T') # Can be anything A = TypeVar('A', str, bytes) # Must be str or bytes ``` Type variables exist primarily for the benefit of static type checkers. They serve as the parameters for generic types as well as for generic function definitions. See class Generic for more information on generic types. Generic functions work as follows: ``` def repeat(x: T, n: int) -> Sequence[T]: """Return a list containing n references to x.""" return [x]*n def longest(x: A, y: A) -> A: """Return the longest of two strings.""" return x if len(x) >= len(y) else y ``` The latter example's signature is essentially the overloading of `(str, str) -> str` and `(bytes, bytes) -> bytes`. Also note that if the arguments are instances of some subclass of [`str`](stdtypes.xhtml#str "str"), the return type is still plain [`str`](stdtypes.xhtml#str "str"). `isinstance(x, T)` 會在運行時拋出 [`TypeError`](exceptions.xhtml#TypeError "TypeError") 異常。一般地說, [`isinstance()`](functions.xhtml#isinstance "isinstance") 和 [`issubclass()`](functions.xhtml#issubclass "issubclass") 不應該和類型一起使用。 Type variables may be marked covariant or contravariant by passing `covariant=True` or `contravariant=True`. See [**PEP 484**](https://www.python.org/dev/peps/pep-0484) \[https://www.python.org/dev/peps/pep-0484\] for more details. By default type variables are invariant. Alternatively, a type variable may specify an upper bound using `bound=<type>`. This means that an actual type substituted (explicitly or implicitly) for the type variable must be a subclass of the boundary type, see [**PEP 484**](https://www.python.org/dev/peps/pep-0484) \[https://www.python.org/dev/peps/pep-0484\]. *class* `typing.``Generic`Abstract base class for generic types. A generic type is typically declared by inheriting from an instantiation of this class with one or more type variables. For example, a generic mapping type might be defined as: ``` class Mapping(Generic[KT, VT]): def __getitem__(self, key: KT) -> VT: ... # Etc. ``` 這個類之后可以被這樣用: ``` X = TypeVar('X') Y = TypeVar('Y') def lookup_name(mapping: Mapping[X, Y], key: X, default: Y) -> Y: try: return mapping[key] except KeyError: return default ``` *class* `typing.``Type`(*Generic\[CT\_co\]*)A variable annotated with `C` may accept a value of type `C`. In contrast, a variable annotated with `Type[C]` may accept values that are classes themselves -- specifically, it will accept the *class object* of `C`. For example: ``` a = 3 # Has type 'int' b = int # Has type 'Type[int]' c = type(a) # Also has type 'Type[int]' ``` Note that `Type[C]` is covariant: ``` class User: ... class BasicUser(User): ... class ProUser(User): ... class TeamUser(User): ... # Accepts User, BasicUser, ProUser, TeamUser, ... def make_new_user(user_class: Type[User]) -> User: # ... return user_class() ``` The fact that `Type[C]` is covariant implies that all subclasses of `C` should implement the same constructor signature and class method signatures as `C`. The type checker should flag violations of this, but should also allow constructor calls in subclasses that match the constructor calls in the indicated base class. How the type checker is required to handle this particular case may change in future revisions of [**PEP 484**](https://www.python.org/dev/peps/pep-0484) \[https://www.python.org/dev/peps/pep-0484\]. The only legal parameters for [`Type`](#typing.Type "typing.Type") are classes, [`Any`](#typing.Any "typing.Any"), [type variables](#generics), and unions of any of these types. For example: ``` def new_non_team_user(user_class: Type[Union[BaseUser, ProUser]]): ... ``` `Type[Any]` is equivalent to `Type` which in turn is equivalent to `type`, which is the root of Python's metaclass hierarchy. 3\.5.2 新版功能. *class* `typing.``Iterable`(*Generic\[T\_co\]*)[`collections.abc.Iterable`](collections.abc.xhtml#collections.abc.Iterable "collections.abc.Iterable") 的泛型版本。 *class* `typing.``Iterator`(*Iterable\[T\_co\]*)[`collections.abc.Iterator`](collections.abc.xhtml#collections.abc.Iterator "collections.abc.Iterator") 的泛型版本。 *class* `typing.``Reversible`(*Iterable\[T\_co\]*)[`collections.abc.Reversible`](collections.abc.xhtml#collections.abc.Reversible "collections.abc.Reversible") 的泛型版本。 *class* `typing.``SupportsInt`An ABC with one abstract method `__int__`. *class* `typing.``SupportsFloat`An ABC with one abstract method `__float__`. *class* `typing.``SupportsComplex`An ABC with one abstract method `__complex__`. *class* `typing.``SupportsBytes`An ABC with one abstract method `__bytes__`. *class* `typing.``SupportsAbs`An ABC with one abstract method `__abs__` that is covariant in its return type. *class* `typing.``SupportsRound`An ABC with one abstract method `__round__`that is covariant in its return type. *class* `typing.``Container`(*Generic\[T\_co\]*)[`collections.abc.Container`](collections.abc.xhtml#collections.abc.Container "collections.abc.Container") 的泛型版本。 *class* `typing.``Hashable`[`collections.abc.Hashable`](collections.abc.xhtml#collections.abc.Hashable "collections.abc.Hashable") 的別名。 *class* `typing.``Sized`[`collections.abc.Sized`](collections.abc.xhtml#collections.abc.Sized "collections.abc.Sized") 的別名。 *class* `typing.``Collection`(*Sized, Iterable\[T\_co\], Container\[T\_co\]*)[`collections.abc.Collection`](collections.abc.xhtml#collections.abc.Collection "collections.abc.Collection") 的泛型版本。 3\.6 新版功能. *class* `typing.``AbstractSet`(*Sized, Collection\[T\_co\]*)[`collections.abc.Set`](collections.abc.xhtml#collections.abc.Set "collections.abc.Set") 的泛型版本。 *class* `typing.``MutableSet`(*AbstractSet\[T\]*)[`collections.abc.MutableSet`](collections.abc.xhtml#collections.abc.MutableSet "collections.abc.MutableSet") 的泛型版本。 *class* `typing.``Mapping`(*Sized, Collection\[KT\], Generic\[VT\_co\]*)[`collections.abc.Mapping`](collections.abc.xhtml#collections.abc.Mapping "collections.abc.Mapping") 的泛型版本。這個類型可以如下使用: ``` def get_position_in_index(word_list: Mapping[str, int], word: str) -> int: return word_list[word] ``` *class* `typing.``MutableMapping`(*Mapping\[KT, VT\]*)[`collections.abc.MutableMapping`](collections.abc.xhtml#collections.abc.MutableMapping "collections.abc.MutableMapping") 的泛型版本。 *class* `typing.``Sequence`(*Reversible\[T\_co\], Collection\[T\_co\]*)[`collections.abc.Sequence`](collections.abc.xhtml#collections.abc.Sequence "collections.abc.Sequence") 的泛型版本。 *class* `typing.``MutableSequence`(*Sequence\[T\]*)[`collections.abc.MutableSequence`](collections.abc.xhtml#collections.abc.MutableSequence "collections.abc.MutableSequence") 的泛型版本。 *class* `typing.``ByteString`(*Sequence\[int\]*)[`collections.abc.ByteString`](collections.abc.xhtml#collections.abc.ByteString "collections.abc.ByteString") 的泛型版本。 This type represents the types [`bytes`](stdtypes.xhtml#bytes "bytes"), [`bytearray`](stdtypes.xhtml#bytearray "bytearray"), and [`memoryview`](stdtypes.xhtml#memoryview "memoryview"). As a shorthand for this type, [`bytes`](stdtypes.xhtml#bytes "bytes") can be used to annotate arguments of any of the types mentioned above. *class* `typing.``Deque`(*deque, MutableSequence\[T\]*)[`collections.deque`](collections.xhtml#collections.deque "collections.deque") 的泛型版本。 3\.6.1 新版功能. *class* `typing.``List`(*list, MutableSequence\[T\]*)Generic version of [`list`](stdtypes.xhtml#list "list"). Useful for annotating return types. To annotate arguments it is preferred to use an abstract collection type such as [`Sequence`](#typing.Sequence "typing.Sequence") or [`Iterable`](#typing.Iterable "typing.Iterable"). 這個類型可以這樣用: ``` T = TypeVar('T', int, float) def vec2(x: T, y: T) -> List[T]: return [x, y] def keep_positives(vector: Sequence[T]) -> List[T]: return [item for item in vector if item > 0] ``` *class* `typing.``Set`(*set, MutableSet\[T\]*)A generic version of [`builtins.set`](stdtypes.xhtml#set "set"). Useful for annotating return types. To annotate arguments it is preferred to use an abstract collection type such as [`AbstractSet`](#typing.AbstractSet "typing.AbstractSet"). *class* `typing.``FrozenSet`(*frozenset, AbstractSet\[T\_co\]*)A generic version of [`builtins.frozenset`](stdtypes.xhtml#frozenset "frozenset"). *class* `typing.``MappingView`(*Sized, Iterable\[T\_co\]*)[`collections.abc.MappingView`](collections.abc.xhtml#collections.abc.MappingView "collections.abc.MappingView") 的泛型版本。 *class* `typing.``KeysView`(*MappingView\[KT\_co\], AbstractSet\[KT\_co\]*)[`collections.abc.KeysView`](collections.abc.xhtml#collections.abc.KeysView "collections.abc.KeysView") 的泛型版本。 *class* `typing.``ItemsView`(*MappingView, Generic\[KT\_co, VT\_co\]*)[`collections.abc.ItemsView`](collections.abc.xhtml#collections.abc.ItemsView "collections.abc.ItemsView") 的泛型版本。 *class* `typing.``ValuesView`(*MappingView\[VT\_co\]*)[`collections.abc.ValuesView`](collections.abc.xhtml#collections.abc.ValuesView "collections.abc.ValuesView") 的泛型版本。 *class* `typing.``Awaitable`(*Generic\[T\_co\]*)[`collections.abc.Awaitable`](collections.abc.xhtml#collections.abc.Awaitable "collections.abc.Awaitable") 的泛型版本。 *class* `typing.``Coroutine`(*Awaitable\[V\_co\], Generic\[T\_co T\_contra, V\_co\]*)A generic version of [`collections.abc.Coroutine`](collections.abc.xhtml#collections.abc.Coroutine "collections.abc.Coroutine"). The variance and order of type variables correspond to those of [`Generator`](#typing.Generator "typing.Generator"), for example: ``` from typing import List, Coroutine c = None # type: Coroutine[List[str], str, int] ... x = c.send('hi') # type: List[str] async def bar() -> None: x = await c # type: int ``` *class* `typing.``AsyncIterable`(*Generic\[T\_co\]*)[`collections.abc.AsyncIterable`](collections.abc.xhtml#collections.abc.AsyncIterable "collections.abc.AsyncIterable") 的泛型版本。 *class* `typing.``AsyncIterator`(*AsyncIterable\[T\_co\]*)[`collections.abc.AsyncIterator`](collections.abc.xhtml#collections.abc.AsyncIterator "collections.abc.AsyncIterator") 的泛型版本。 *class* `typing.``ContextManager`(*Generic\[T\_co\]*)[`contextlib.AbstractContextManager`](contextlib.xhtml#contextlib.AbstractContextManager "contextlib.AbstractContextManager") 的泛型版本。 3\.6 新版功能. *class* `typing.``AsyncContextManager`(*Generic\[T\_co\]*)[`contextlib.AbstractAsyncContextManager`](contextlib.xhtml#contextlib.AbstractAsyncContextManager "contextlib.AbstractAsyncContextManager") 的泛型版本。 3\.6 新版功能. *class* `typing.``Dict`(*dict, MutableMapping\[KT, VT\]*)[`dict`](stdtypes.xhtml#dict "dict") 的泛型版本。對標注返回類型比較有用。如果要標注參數的話,使用如 [`Mapping`](#typing.Mapping "typing.Mapping") 的抽象容器類型是更好的選擇。 這個類型可以這樣使用: ``` def count_words(text: str) -> Dict[str, int]: ... ``` *class* `typing.``DefaultDict`(*collections.defaultdict, MutableMapping\[KT, VT\]*)[`collections.defaultdict`](collections.xhtml#collections.defaultdict "collections.defaultdict") 的泛型版本。 3\.5.2 新版功能. *class* `typing.``OrderedDict`(*collections.OrderedDict, MutableMapping\[KT, VT\]*)[`collections.OrderedDict`](collections.xhtml#collections.OrderedDict "collections.OrderedDict") 的泛型版本。 3\.7.2 新版功能. *class* `typing.``Counter`(*collections.Counter, Dict\[T, int\]*)[`collections.Counter`](collections.xhtml#collections.Counter "collections.Counter") 的泛型版本。 3\.6.1 新版功能. *class* `typing.``ChainMap`(*collections.ChainMap, MutableMapping\[KT, VT\]*)[`collections.ChainMap`](collections.xhtml#collections.ChainMap "collections.ChainMap") 的泛型版本。 3\.6.1 新版功能. *class* `typing.``Generator`(*Iterator\[T\_co\], Generic\[T\_co, T\_contra, V\_co\]*)A generator can be annotated by the generic type `Generator[YieldType, SendType, ReturnType]`. For example: ``` def echo_round() -> Generator[int, float, str]: sent = yield 0 while sent >= 0: sent = yield round(sent) return 'Done' ``` Note that unlike many other generics in the typing module, the `SendType`of [`Generator`](#typing.Generator "typing.Generator") behaves contravariantly, not covariantly or invariantly. If your generator will only yield values, set the `SendType` and `ReturnType` to `None`: ``` def infinite_stream(start: int) -> Generator[int, None, None]: while True: yield start start += 1 ``` Alternatively, annotate your generator as having a return type of either `Iterable[YieldType]` or `Iterator[YieldType]`: ``` def infinite_stream(start: int) -> Iterator[int]: while True: yield start start += 1 ``` *class* `typing.``AsyncGenerator`(*AsyncIterator\[T\_co\], Generic\[T\_co, T\_contra\]*)An async generator can be annotated by the generic type `AsyncGenerator[YieldType, SendType]`. For example: ``` async def echo_round() -> AsyncGenerator[int, float]: sent = yield 0 while sent >= 0.0: rounded = await round(sent) sent = yield rounded ``` Unlike normal generators, async generators cannot return a value, so there is no `ReturnType` type parameter. As with [`Generator`](#typing.Generator "typing.Generator"), the `SendType` behaves contravariantly. If your generator will only yield values, set the `SendType` to `None`: ``` async def infinite_stream(start: int) -> AsyncGenerator[int, None]: while True: yield start start = await increment(start) ``` Alternatively, annotate your generator as having a return type of either `AsyncIterable[YieldType]` or `AsyncIterator[YieldType]`: ``` async def infinite_stream(start: int) -> AsyncIterator[int]: while True: yield start start = await increment(start) ``` 3\.5.4 新版功能. *class* `typing.``Text``Text` is an alias for `str`. It is provided to supply a forward compatible path for Python 2 code: in Python 2, `Text` is an alias for `unicode`. Use `Text` to indicate that a value must contain a unicode string in a manner that is compatible with both Python 2 and Python 3: ``` def add_unicode_checkmark(text: Text) -> Text: return text + u' \u2713' ``` 3\.5.2 新版功能. *class* `typing.``IO`*class* `typing.``TextIO`*class* `typing.``BinaryIO`Generic type `IO[AnyStr]` and its subclasses `TextIO(IO[str])`and `BinaryIO(IO[bytes])`represent the types of I/O streams such as returned by [`open()`](functions.xhtml#open "open"). *class* `typing.``Pattern`*class* `typing.``Match`These type aliases correspond to the return types from [`re.compile()`](re.xhtml#re.compile "re.compile") and [`re.match()`](re.xhtml#re.match "re.match"). These types (and the corresponding functions) are generic in `AnyStr` and can be made specific by writing `Pattern[str]`, `Pattern[bytes]`, `Match[str]`, or `Match[bytes]`. *class* `typing.``NamedTuple`Typed version of [`collections.namedtuple()`](collections.xhtml#collections.namedtuple "collections.namedtuple"). 用法: ``` class Employee(NamedTuple): name: str id: int ``` This is equivalent to: ``` Employee = collections.namedtuple('Employee', ['name', 'id']) ``` To give a field a default value, you can assign to it in the class body: ``` class Employee(NamedTuple): name: str id: int = 3 employee = Employee('Guido') assert employee.id == 3 ``` Fields with a default value must come after any fields without a default. The resulting class has two extra attributes: `_field_types`, giving a dict mapping field names to types, and `_field_defaults`, a dict mapping field names to default values. (The field names are in the `_fields` attribute, which is part of the namedtuple API.) `NamedTuple` subclasses can also have docstrings and methods: ``` class Employee(NamedTuple): """Represents an employee.""" name: str id: int = 3 def __repr__(self) -> str: return f'<Employee {self.name}, id={self.id}>' ``` Backward-compatible usage: ``` Employee = NamedTuple('Employee', [('name', str), ('id', int)]) ``` 在 3.6 版更改: Added support for [**PEP 526**](https://www.python.org/dev/peps/pep-0526) \[https://www.python.org/dev/peps/pep-0526\] variable annotation syntax. 在 3.6.1 版更改: Added support for default values, methods, and docstrings. `typing.``NewType`(*typ*)A helper function to indicate a distinct types to a typechecker, see [NewType](#distinct). At runtime it returns a function that returns its argument. Usage: ``` UserId = NewType('UserId', int) first_user = UserId(1) ``` 3\.5.2 新版功能. `typing.``cast`(*typ*, *val*)Cast a value to a type. This returns the value unchanged. To the type checker this signals that the return value has the designated type, but at runtime we intentionally don't check anything (we want this to be as fast as possible). `typing.``get_type_hints`(*obj*\[, *globals*\[, *locals*\]\])返回一個字典,字典內含有函數、方法、模塊或類對象的類型提示。 This is often the same as `obj.__annotations__`. In addition, forward references encoded as string literals are handled by evaluating them in `globals` and `locals` namespaces. If necessary, `Optional[t]` is added for function and method annotations if a default value equal to `None` is set. For a class `C`, return a dictionary constructed by merging all the `__annotations__` along `C.__mro__` in reverse order. `@``typing.``overload`The `@overload` decorator allows describing functions and methods that support multiple different combinations of argument types. A series of `@overload`-decorated definitions must be followed by exactly one non-`@overload`-decorated definition (for the same function/method). The `@overload`-decorated definitions are for the benefit of the type checker only, since they will be overwritten by the non-`@overload`-decorated definition, while the latter is used at runtime but should be ignored by a type checker. At runtime, calling a `@overload`-decorated function directly will raise [`NotImplementedError`](exceptions.xhtml#NotImplementedError "NotImplementedError"). An example of overload that gives a more precise type than can be expressed using a union or a type variable: ``` @overload def process(response: None) -> None: ... @overload def process(response: int) -> Tuple[int, str]: ... @overload def process(response: bytes) -> str: ... def process(response): <actual implementation> ``` See [**PEP 484**](https://www.python.org/dev/peps/pep-0484) \[https://www.python.org/dev/peps/pep-0484\] for details and comparison with other typing semantics. `@``typing.``no_type_check`用于指明標注不是類型提示的裝飾器。 此 [decorator](../glossary.xhtml#term-decorator) 裝飾器生效于類或函數上。如果作用于類上的話,它會遞歸地作用于這個類的所定義的所有方法上(但是對于超類或子類所定義的方法不會生效)。 此方法會就地地修改函數。 `@``typing.``no_type_check_decorator`使其它裝飾器起到 [`no_type_check()`](#typing.no_type_check "typing.no_type_check") 效果的裝飾器。 This wraps the decorator with something that wraps the decorated function in [`no_type_check()`](#typing.no_type_check "typing.no_type_check"). `@``typing.``type_check_only`標記一個類或函數在運行時內不可用的裝飾器。 This decorator is itself not available at runtime. It is mainly intended to mark classes that are defined in type stub files if an implementation returns an instance of a private class: ``` @type_check_only class Response: # private or not available at runtime code: int def get_header(self, name: str) -> str: ... def fetch_response() -> Response: ... ``` Note that returning instances of private classes is not recommended. It is usually preferable to make such classes public. `typing.``Any`特殊類型,表明類型沒有任何限制。 - 每一個類型都對 [`Any`](#typing.Any "typing.Any") 兼容。 - [`Any`](#typing.Any "typing.Any") 對每一個類型都兼容。 `typing.``NoReturn`標記一個函數沒有返回值的特殊類型。比如說: ``` from typing import NoReturn def stop() -> NoReturn: raise RuntimeError('no way') ``` 3\.5.4 新版功能. `typing.``Union`聯合類型; `Union[X, Y]` 意味著:要不是 X,要不是 Y。 使用形如 `Union[int, str]` 的形式來定義一個聯合類型。細節如下: - 參數必須是類型,而且必須至少有一個參數。 - 聯合類型的聯合類型會被展開打平,比如: ``` Union[Union[int, str], float] == Union[int, str, float] ``` - 僅有一個參數的聯合類型會坍縮成參數自身,比如: ``` Union[int] == int # The constructor actually returns int ``` - 多余的參數會被跳過,比如: ``` Union[int, str, int] == Union[int, str] ``` - 在比較聯合類型的時候,參數順序會被忽略,比如: ``` Union[int, str] == Union[str, int] ``` - 你不能繼承或者實例化一個聯合類型。 - 你不能寫成 `Union[X][Y]` 。 - 你可以使用 `Optional[X]` 作為 `Union[X, None]` 的縮寫。 在 3.7 版更改: 不要在運行時內從聯合類型中移除顯式說明的子類。 `typing.``Optional`Optional type. `Optional[X]` is equivalent to `Union[X, None]`. Note that this is not the same concept as an optional argument, which is one that has a default. An optional argument with a default does not require the `Optional` qualifier on its type annotation just because it is optional. For example: ``` def foo(arg: int = 0) -> None: ... ``` On the other hand, if an explicit value of `None` is allowed, the use of `Optional` is appropriate, whether the argument is optional or not. For example: ``` def foo(arg: Optional[int] = None) -> None: ... ``` `typing.``Tuple`Tuple type; `Tuple[X, Y]` is the type of a tuple of two items with the first item of type X and the second of type Y. Example: `Tuple[T1, T2]` is a tuple of two elements corresponding to type variables T1 and T2. `Tuple[int, float, str]` is a tuple of an int, a float and a string. To specify a variable-length tuple of homogeneous type, use literal ellipsis, e.g. `Tuple[int, ...]`. A plain [`Tuple`](#typing.Tuple "typing.Tuple")is equivalent to `Tuple[Any, ...]`, and in turn to [`tuple`](stdtypes.xhtml#tuple "tuple"). `typing.``Callable`Callable type; `Callable[[int], str]` is a function of (int) -> str. The subscription syntax must always be used with exactly two values: the argument list and the return type. The argument list must be a list of types or an ellipsis; the return type must be a single type. There is no syntax to indicate optional or keyword arguments; such function types are rarely used as callback types. `Callable[..., ReturnType]` (literal ellipsis) can be used to type hint a callable taking any number of arguments and returning `ReturnType`. A plain [`Callable`](#typing.Callable "typing.Callable") is equivalent to `Callable[..., Any]`, and in turn to [`collections.abc.Callable`](collections.abc.xhtml#collections.abc.Callable "collections.abc.Callable"). `typing.``ClassVar`Special type construct to mark class variables. As introduced in [**PEP 526**](https://www.python.org/dev/peps/pep-0526) \[https://www.python.org/dev/peps/pep-0526\], a variable annotation wrapped in ClassVar indicates that a given attribute is intended to be used as a class variable and should not be set on instances of that class. Usage: ``` class Starship: stats: ClassVar[Dict[str, int]] = {} # class variable damage: int = 10 # instance variable ``` [`ClassVar`](#typing.ClassVar "typing.ClassVar") accepts only types and cannot be further subscribed. [`ClassVar`](#typing.ClassVar "typing.ClassVar") is not a class itself, and should not be used with [`isinstance()`](functions.xhtml#isinstance "isinstance") or [`issubclass()`](functions.xhtml#issubclass "issubclass"). [`ClassVar`](#typing.ClassVar "typing.ClassVar") does not change Python runtime behavior, but it can be used by third-party type checkers. For example, a type checker might flag the following code as an error: ``` enterprise_d = Starship(3000) enterprise_d.stats = {} # Error, setting class variable on instance Starship.stats = {} # This is OK ``` 3\.5.3 新版功能. `typing.``AnyStr``AnyStr` is a type variable defined as `AnyStr = TypeVar('AnyStr', str, bytes)`. It is meant to be used for functions that may accept any kind of string without allowing different kinds of strings to mix. For example: ``` def concat(a: AnyStr, b: AnyStr) -> AnyStr: return a + b concat(u"foo", u"bar") # Ok, output has type 'unicode' concat(b"foo", b"bar") # Ok, output has type 'bytes' concat(u"foo", b"bar") # Error, cannot mix unicode and bytes ``` `typing.``TYPE_CHECKING`A special constant that is assumed to be `True` by 3rd party static type checkers. It is `False` at runtime. Usage: ``` if TYPE_CHECKING: import expensive_mod def fun(arg: 'expensive_mod.SomeType') -> None: local_var: expensive_mod.AnotherType = other_fun() ``` Note that the first type annotation must be enclosed in quotes, making it a "forward reference", to hide the `expensive_mod` reference from the interpreter runtime. Type annotations for local variables are not evaluated, so the second annotation does not need to be enclosed in quotes. 3\.5.2 新版功能. ### 導航 - [索引](../genindex.xhtml "總目錄") - [模塊](../py-modindex.xhtml "Python 模塊索引") | - [下一頁](pydoc.xhtml "pydoc --- Documentation generator and online help system") | - [上一頁](development.xhtml "開發工具") | - ![](https://box.kancloud.cn/a721fc7ec672275e257bbbfde49a4d4e_16x16.png) - [Python](https://www.python.org/) ? - zh\_CN 3.7.3 [文檔](../index.xhtml) ? - [Python 標準庫](index.xhtml) ? - [開發工具](development.xhtml) ? - $('.inline-search').show(0); | ? [版權所有](../copyright.xhtml) 2001-2019, Python Software Foundation. Python 軟件基金會是一個非盈利組織。 [請捐助。](https://www.python.org/psf/donations/) 最后更新于 5月 21, 2019. [發現了問題](../bugs.xhtml)? 使用[Sphinx](http://sphinx.pocoo.org/)1.8.4 創建。
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