Python's type annotations

Python's type annotations are a powerful tool for making code more readable and maintainable. By explicitly stating the types of variables, functions, and arguments, we can ensure that our code is being used correctly and make it easier for others to understand.

For example, consider the following function:

def add(a: int, b: int) -> int
    return a + b

result = add(2,3)
print(result) # prints 5:        

As you can see, add(a: int, b: int) -> int: specifies that the function add takes two integers as input and returns an integer. This makes it clear to anyone reading the code what type of data is expected and returned.

Type annotations can also be used with variables and class attributes. For example:

x: int = 
y: str = "hello"

print(x+y) # This will raise an error, as we are trying to add int and str        

In the above example, we have annotated variable x as int and variable y as str. This helps the developer to understand what type of data is being stored in those variables.

In addition to making code more readable, type annotations can also be used with tools such as mypy to catch type errors before the code is run. This can save a lot of time and effort in debugging.

def add(a: int, b: int) -> int
    return a + b

result = add("2","3")
print(result)        

By running the above code with mypy, it will raise an error indicating that a and b should be of int type, this helps the developer to catch the error in early stages.

Using type annotations in Python can greatly improve the readability and maintainability of your code.

Give it a try and see the difference it can make!