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.
Variables
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}!"
else:
return f"Hello, {name}! You are {age} years old."
Classes
class Person:
def __init__(self, name: str, age: int):
self.name = name
self.age = age
def greet(self) -> str:
return f"Hello, my name is {self.name} 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])
distances.append(distance)
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
mypy my_script.py