Python Function Annotations: Add Meaning to Function Parameters and Return Types

Python’s function annotations provide a way to add additional metadata to function arguments and return types. These annotations serve as an informative tool for developers and IDEs but are ignored at runtime by the Python interpreter.

Why Use Function Annotations?

Function annotations are mainly used to provide descriptive metadata for arguments and return types, making your code more readable and maintainable. They are especially useful in large codebases, helping IDEs and static type checkers (like mypy) provide additional insights and error detection.

Basic Example of Function Annotations

Here’s a simple example where we annotate the arguments with data types:

def myfunction(a: int, b: int):
   c = a + b
   return c
   
print(myfunction(10, 20))
print(myfunction("Hello ", "Python"))

Output:

30
Hello Python

Annotations with Return Type

You can also annotate the return type of a function using the arrow (->) syntax:

def myfunction(a: int, b: int) -> int:
   c = a + b
   return c
   
print(myfunction(56, 88))

Output:

144

Annotations with Arbitrary Expressions

Function annotations can also be arbitrary expressions, not just data types. This allows flexibility and customization, such as describing the purpose of arguments:

def total(x : 'marks in Physics', y: 'marks in Chemistry'):
   return x + y
   
print(total(86, 88))

Output:

174

Default Arguments with Annotations

You can specify default arguments along with annotations. Default arguments should come after the required ones:

def myfunction(a: "physics", b: "Maths" = 20) -> int:
   c = a + b
   return c
   
print(myfunction(10))

Output:

30

Advanced Example: Annotations with Arbitrary Arguments

You can annotate arbitrary positional (*args) and keyword (**kwargs) arguments as well:

def myfunction(*args: "arbitrary args", **kwargs: "arbitrary keyword args") -> int:
   pass
   
print(myfunction.__annotations__) 

Output:

{'args': 'arbitrary args', 'kwargs': 'arbitrary keyword args', 'return': }

Key Takeaways

• Annotations are for documentation: They are ignored at runtime but can be used for providing helpful metadata.
• Flexibility: You can annotate with data types, arbitrary expressions, and default arguments.
• Increased Readability: Annotations help IDEs and static type checkers like mypy improve code quality.

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