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Any is a special type.

The static type checker treats all types as compatible with Any, and vice versa, and Any is also compatible with all types.

This means that you can perform any operation or method call on a value of type Any and assign it to any variable:

From typing import Anya = None # type: Anya = [] # OKa = 2 # OKs =''# type: strs = a # OKdef foo (item: Any)-> int: # Typechecks; 'item' could be any type, # and that type might have a' bar' method item.bar ().

It is important to note that Python does not perform type checking when assigning a value of type Any to a more specific type. For example, when assigning a to s, the static type checker does not report an error even if s is declared to be of type str and receives an int value at run time.

In addition, all functions that return untyped or parameter-untyped functions implicitly default to the Any type:

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

The above behavior allows Any to be used as an emergency exit when you need to mix dynamically and statically typed code.

The behavior comparison of Any and object.

Like Any, all types are subtypes of object. Unlike Any, however, the opposite is not true: object is not a subtype of all other types.

This means that when a value is of type object, the type checker rejects almost all operations on it. Assigning it to a variable of a specified type (or as a return value) is a type error.

For example:

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 objecthash_a (42) hash_a ("foo") # Typechecks, since Any is compatible with all typeshash_b (42) hash_b ("foo")

Use object to imply that a value can be type-safe compatible with any type. Use Any to indicate that the type of a value is dynamically defined.

Add: python3.5 typing-type annotation support

Function accepts and returns a string with comments like this:

Def greeting (name: str)-> str: return 'Hello' + name

In the function greeting, the parameter name is expected to be of type str and returns a type of str. Subtypes are allowed as parameters.

1.1. Type alias

A type name is defined by assigning a type to an alias. In this example, Vector and List [float] will be considered interchangeable synonyms:

From typing import ListVector = 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]) type aliases can be used to simplify complex type signatures.

For example:

From typing import Dict, Tuple, ListConnectionOptions = Dict [str, str] Address = Tuple [str, int] Server = Tuple [Address, ConnectionOptions] def broadcast_message (message: str, servers: List [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: List [Tuple [Tuple [str, int], Dict [str, str]])-> None:.

Note that None as a type hint is a special case and is replaced by type (None).

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