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Type Annotations

When writing Python code, there are often cases where variable types need to be specified. Type annotations were introduced in Python 3.5 and have been enhanced and improved in subsequent versions. Type annotations do not affect runtime results and are very similar to TypeScript.

Using Type Annotations

Type annotations are not required in Python. They are a way to specify variable types in Python, which can improve code readability and maintainability.


age: int = 25
name: str = "John"

Function Parameters and Return Values

def add(x: int, y: int) -> int:
return x + y

Optional Parameters and Default Values

from typing import Union
def greet(name: str, age: Union[int, None] = None) -> str:
if age is None:
return f"Hello, {name}!"
return f"Hello, {name}! You are {age} years old."


class Person:
def __init__(self, name: str, age: int): = name
self.age = age

def greet(self) -> str:
return f"Hello, my name is {} and I am {self.age} years old."

Type Aliases

from typing import List, Tuple

Coordinates = Tuple[float, float]
PointList = List[Coordinates]

def get_distance(point1: Coordinates, point2: Coordinates) -> float:
x1, y1 = point1
x2, y2 = point2
return ((x2 - x1) ** 2 + (y2 - y1) ** 2) ** 0.5

def process_points(points: PointList) -> List[float]:
distances = []
for i in range(len(points) - 1):
distance = get_distance(points[i], points[i+1])
return distances

Compile-Time Type Checking

In Python, mypy is a command-line tool similar to TypeScript's tsc that can be used to check the types of code.

pip install mypy