3.3. Functools

functools is a built-in Python library to work with functions efficiently. This section will show you some useful methods of functools.

3.3.1. functools.partial: Generate a New Function with Fewer Arguments

If you want to fix some arguments of a function and generate a new function with fewer arguments, use functools.partial.

In the code below, I use partial to create a new function with only x as the argument.

from functools import partial


def linear_func(x, a, b):
    return a * x + b


linear_func_partial = partial(linear_func, a=2, b=3)
print(linear_func_partial(2))
print(linear_func_partial(4))

7
11

3.3.2. functools.singledispatch: Call Another Function Based on the Type of the Current Function’s Argument

Normally, to call another function based on the type of the current function’s argument, we use an if-else statement:

data = {"a": [1, 2, 3], "b": [4, 5, 6]}
data2 = [{"a": [1, 2, 3]}, {"b": [4, 5, 6]}]

def process_data(data):
    if isinstance(data, dict):
        process_dict(data)

    else:
        process_list(data)


def process_dict(data: dict):
    print("Dict is processed")


def process_list(data: list):
    print("List is processed")

process_data(data)

Dict is processed

process_data(data2)

List is processed

With singledispatch, you don’t need to use an if-else statement to call an appropriate function. singledispatch will choose the right function based on the type of current function’s first argument.

from functools import singledispatch


@singledispatch
def process_data2(data):
    raise NotImplementedError("Please implement process_data2")


@process_data2.register
def process_dict2(data: dict):
    print("Dict is processed")


@process_data2.register
def process_list2(data: list):
    print("List is processed")

process_data2(data)

Dict is processed

process_data2(data2)

List is processed

3.3.3. functools.reduce: Apply Function Cumulatively to the Items of Iterable

If you want to apply a function of two arguments cumulatively to the items of iterable from left to right, use functools’s reduce. This method reduces the iterable to a single value.

In the code below, 3 is the result of the function add_nums(2, 1). 3 is then used as the first argument of the function add_nums(3, 2).

from functools import reduce


def add_nums(num1, num2):
    res = num1 + num2
    print(f"{num1} + {num2} = {res}")
    return res


print(reduce(add_nums, [1, 2, 3], 2))

2 + 1 = 3
3 + 2 = 5
5 + 3 = 8
8

3.3.4. Combine Reduce and Operator Methods

You can combine functools.reduce with a method from operator to achieve the similar functionality and make the code more readable.

import functools
import operator

# 2+1=3, 3+2=5, 5+3=8
functools.reduce(operator.add, [1, 2, 3], 2)

8