functools Library

The functools library provides higher-order functions that act on or return other functions, compatible with Python’s functools module.

Import

    
import functools

Available Functions

Function	Description
`reduce(function, iterable[, initializer])`	Reduce iterable to single value

Functions

reduce(function, iterable[, initializer])

Apply a function of two arguments cumulatively to the items of an iterable, from left to right, to reduce the iterable to a single value.

Parameters:

function - A function taking two arguments (accumulator, current_item)
iterable - A list of items to process
initializer - Optional. Starting value for the accumulator

Returns: The final accumulated value

Examples:

    
import functools

# Sum a list
def add(x, y):
    return x + y

result = functools.reduce(add, [1, 2, 3, 4, 5])  # Returns 15

    
# With initial value
result = functools.reduce(add, [1, 2, 3], 10)  # Returns 16

    
# Product of a list
def multiply(x, y):
    return x * y

result = functools.reduce(multiply, [1, 2, 3, 4])  # Returns 24

    
    
  
# Find maximum
def max_val(a, b):
    if a > b:
        return a
    return b

result = functools.reduce(max_val, [3, 1, 4, 1, 5, 9])  # Returns 9

    
# Concatenate strings
def concat(a, b):
    return a + b

result = functools.reduce(concat, ["a", "b", "c"])  # Returns "abc"

How reduce() Works

reduce() applies a function cumulatively:

reduce(add, [1, 2, 3, 4, 5])

Is equivalent to:

add(add(add(add(1, 2), 3), 4), 5)
= add(add(add(3, 3), 4), 5)
= add(add(6, 4), 5)
= add(10, 5)
= 15

With an initializer:

reduce(add, [1, 2, 3], 10)

Is equivalent to:

add(add(add(10, 1), 2), 3)
= add(add(11, 2), 3)
= add(13, 3)
= 16

Use Cases

Summing Values

    
import functools

def add(x, y):
    return x + y

total = functools.reduce(add, [100, 200, 300])  # 600

Building Data Structures

    
import functools

def merge_dicts(acc, item):
    acc[item[0]] = item[1]
    return acc

pairs = [["a", 1], ["b", 2], ["c", 3]]
result = functools.reduce(merge_dicts, pairs, {})
# {"a": 1, "b": 2, "c": 3}

Processing Pipelines

    
import functools

def apply_fn(value, fn):
    return fn(value)

def double(x):
    return x * 2

def add_one(x):
    return x + 1

functions = [double, add_one, double]
result = functools.reduce(apply_fn, functions, 5)
# double(5) = 10, add_one(10) = 11, double(11) = 22

Notes

If the iterable is empty and no initializer is provided, an error is raised
If the iterable has one item and no initializer, that item is returned
The function must take exactly 2 arguments

Python Compatibility

This library implements a subset of Python’s functools module:

Function	Supported
reduce	✅
partial	❌
partialmethod	❌
lru_cache	❌
cache	❌
cached_property	❌
wraps	❌
total_ordering	❌
cmp_to_key	❌

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