Annotating Functions in Python

I just recently posted a blog about Annotating functions in Typescript. I just finished doing a bit of a study and understood more on how to annotate functions in Python and this blog is going to be all about annotating Python functions with similar examples to the last blog.

You can validate your type annotations in Visual Studio Code by setting python.analysis.typeCheckingMode to one of basic, standard, strict,. basic and standard options doesn't necessarily make sure you annotate your functions and variables but strict does.

Function Values

This might shock you but you can return functions and pass functions as values in Python. Callback functions are actually annotated using the Callable type which is written like this;

Callable[[argtype1, argtype2, argtype3], returnType]

For instance, a function length(text: str) -> int will be annotated as Callable[[str], int]

For example;

This function in JavaScript

function multiplier(factor){
    return value => factor * value
}

const n = multiplier(6)
n(8) // 48

can be written like this in Python

def multiplier(factor):
    def inner(value):
        return value * factor
    return inner     

n = multiplier(6)
n(8) #48

We can create a TypeAlias called number which is a Union (literally) of both an int and a float like;

from typing import TypeAlias, Union

number: TypeAlias = Union[int, float]

To approach the parameters as JavaScript numbers.

So therefore, to annotate this function, we have;

def multiplier(factor: number) -> Callable[[number], number]:
    def inner(value: number) -> inner:
        return value * factor
    return inner

a = multiplier(4.5)
a(3) #13.5

Generic functions

The classic generic function example is

def pick(array, index):
    return array[index]

pick([1,2,3], 2) #3

Using TypeVar we can now create generic verbose (more verbose than typescript).

from typing import TypeVar

T = TypeVar("T") # the argument and the name of the variable should be the same

so that we have

from typing import TypeVar, Sequence

def pick(array: Sequence[T], index: int) -> T:
    return array[index]

print(pick([1,2,3,4], 2))

So what about a custom myMap function that acts like map in JavaScript. such that we have;

Remember: map() in Python returns an Iterable type not a List type

def myMap(array, fn):
    return map(fn, array)

def twice(n): return n * 2
print(myMap([1,2,3], twice))

We can use a mixture of Callable and TypeVar types to annotate this function. Observe...

from typing import TypeVar, Iterable, Callable

Input = TypeVar("Input")  # Input and "Input" must be the same
Output = TypeVar("Output")

def myMap(array: Iterable[Input], fn: Callable[[Input], Output]) -> Iterable[Output]:
    return map(fn, array)

def twice(n: int) -> int: return n * 2
print(myMap([1,2,3], twice))

or we can alias the Callable function

from typing import TypeVar, Iterable, Callable

Input = TypeVar("Input")
Output = TypeVar("Output")

MappableFunction = Callable[[Input], Output]

def myMap(array: Iterable[Input], fn: MappableFunction[Input, Output]) -> Iterable[Output]:
    return map(fn, array)

Observe that MappableFunction takes those generic types Input and Output and applies them to the context of Callable[[Input], Output].

Take a minute to think of how the myFilter function will be annotated?

Well if you thought of this

from typing import Iterable, TypeVar, Callable

Input = TypeVar("Input")

def myFilter(array: Iterable[Input], fn: Callable[[Input], bool]) -> Iterable[Input]:
    return filter(fn, array)

You're right

Generic Classes

I know I'm not supposed to be talking about class annotation but give me some time to explain generic classes.

If you came from the Typescript-verse, this was how you would define them

class GenericStore<type>{
    stores: Array<type> = []

    constructor(){
        this.stores = []
    }

    add(item: Type){
        this.stores.push(item)
    }
}

const g1 = new GenericStore<string>(); //g1.stores: Array<string>
g1.add("Hello") //only string are allowed
</string></string></type></type>

But in Python they are rather different and awkward.

• First we import the Generic type, then we make them the child of the Generic class

So to recreate this GenericStore class in Python

Callable[[argtype1, argtype2, argtype3], returnType]

Why should I learn how to annotate functions in Python?

As I have said in the former blog, It helps in building a much smarter type system which in turn reduces your chances of bugs (especially when using static file checkers like mypy). Also when writing libraries (or SDKs) using a robust type system can improve the productivity of the developer using the library by a margin (mostly because of editor suggestions)

If you have any questions or there are mistakes in this writing, feel free to share them in the comments below ⭐

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