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Python – Itertools.accumulate()
  • Last Updated : 31 Mar, 2020

Python itertools module is a collection of tools for handling iterators.

According to the official documentation:

“Module [that] implements a number of iterator building blocks inspired by constructs from APL, Haskell, and SML… Together, they form an ‘iterator algebra’ making it possible to construct specialized tools succinctly and efficiently in pure Python.” this basically means that the functions in itertools “operate” on iterators to produce more complex iterators.

Simply put, iterators are data types that can be used in a for loop. The most common iterator in Python is the list.

Let’s create a list of strings and named it colors. We can use a for loop to iterate the list like:






colors = ['red', 'orange', 'yellow', 'green']
  
# Iterating List
for each in colors:
    print(each)


Output:

red
orange
yellow
green

There are many different kinds of iterables but for now, we will be using lists and sets.

Requirements to work with itertools

Must import the itertools module before using. We have to also import the operator module because we want to work with operators.

import itertools
import operator ## only needed if want to play with operators

Itertools module is a collection of functions. We are going to explore one of these accumulate() function.

Note: For more information, refer to Python Itertools

accumulate()

This iterator takes two arguments, iterable target and the function which would be followed at each iteration of value in target. If no function is passed, addition takes place by default. If the input iterable is empty, the output iterable will also be empty.

Syntax
itertools.accumulate(iterable[, func]) –> accumulate object



This function makes an iterator that returns the results of a function.

Parameters
iterable & function

Now its enough of the theory portion lets play with the code

Code: 1




# import the itertool module 
# to work with it
import itertools
  
# import operator to work 
# with operator
import operator
  
# creating a list GFG
GFG = [1, 2, 3, 4, 5]
  
# using the itertools.accumulate() 
result = itertools.accumulate(GFG, 
                              operator.mul)
  
# printing each item from list
for each in result:
    print(each)


Output:

1
2
6
24
120

Explanation :

The operator.mul takes two numbers and multiplies them.

operator.mul(1, 2)
2
operator.mul(2, 3)
6
operator.mul(6, 4)
24
operator.mul(24, 5)
120

Now in the next example, we will use the max function as it takes a function as a parameter also.

Code 2:




# import the itertool module 
# to work with it
import itertools
  
# import operator to work with
# operator
import operator
  
# creating a list GFG
GFG = [5, 3, 6, 2, 1, 9, 1]
  
# using the itertools.accumulate()
  
# Now here no need to import operator
# as we are not using any operator
# Try after removing it gives same result
result = itertools.accumulate(GFG, max)
  
# printing each item from list
for each in result:
    print(each)


Output:

5
5
6
6
6
9
9

Explanation:

5
max(5, 3)
5
max(5, 6)
6
max(6, 2)
6
max(6, 1)
6
max(6, 9)
9
max(9, 1)
9

Note: The passing function is optional as if you will not pass any function items will be summed i.e. added by default.

itertools.accumulate(set.difference)
This return accumulate of items of difference between sets.

Code to explain




# import the itertool module to
# work with it
import itertools
  
  
# creating a set GFG1 and GFG2
GFG1 = { 5, 3, 6, 2, 1, 9 }
GFG2 ={ 4, 2, 6, 0, 7 }
  
# using the itertools.accumulate()
  
# Now this will first give difference 
# and the give result by adding all 
# the element in result as by default
# if no function  passed it will add always
result = itertools.accumulate(GFG2.difference(GFG1))
  
# printing each item from list
for each in result:
    print(each)


Output:

0
4
11

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