python type annotations
#function expects a string and returns a string
def greeting(name: str) -> str:
return 'Hello ' + namepython type annotations
#function expects a string and returns a string
def greeting(name: str) -> str:
return 'Hello ' + namepython typing list of strings
from typing import List
def my_func(l: List[int]):
passpython type annotations
# Some basic type annotations
#
# Note that type annotations are not enforced by the interpreter.
# The code
# a: int = 5
# a = "hello"
# is valid Python.
# A built-in library with some extra types that can be used
# for annotations
from typing import Union, Optional, List, Tuple
a: int = 6 # A variable annotated as int
# This denotes a variable that will hold ints and floats over
# the course of its usage.
two_types: Union[int, float] = 5.6
# This variable could hold str or it could be None. This is
# effectively the same as typing opt as Union[str, None].
opt: Optional[str] = None
# This is a function with type annotations; it takes two
# int parameters and returns bool.
def annotated_func(x: int, y: int) -> bool:
return x > y
# You can also annotate a certain data structure and the type of
# data you intend it to contain.
l: List[int] = [1, 2, 3, 4]
t: Tuple[chr] = ('a', 'b', 'c', 'd')
# In Python 3.9+, list[<TYPE>] and tuple[<TYPE>] can be used
# instead. They're aliases for typing.List and typing.Tuple.typing generator python
# Iterator
def infinite_stream(start: int) -> Iterator[int]:
while True:
yield start
start += 1
# Generator
def infinite_stream(start: int) -> Generator[int, None, None]:
while True:
yield start
start += 1specify return type python function
def greeting(name: str) -> str:
return 'Hello, {}'.format(name)python type annotations
# This example illustrates both parameter and return type annotation
# Collection annotations are also supported
from typing import List
def greeting(names: List[str]) -> str:
return 'Hello, ' + names[0] ' and ' + names[1]Copyright © 2021 Codeinu
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