Using map to sum the elements of list

Question

I was wondering if map can be used at all to sum the elements of a list.

assume a = [1, 2, 3, 4]

list(map(sum, a)) will give an error that int object is not iterable because list wants iterables.

map(sum, a) is a valid statement but given the object, I do not see an easy way to dereference it.

[map(sum, a)] will return an object inside the list

this answer states that it should be easy. What am I missing here?

Answer 1

map applies a function to every element in the list. Instead, you can use reduce:

a = [1, 2, 3, 4]
sum_a = reduce(lambda x, y:x+y, a)

In this case, purely sum can be used, however, to be more functional, reduce is a better option.

Or, in Python3:

from functools import reduce
a = [1, 2, 3, 4]
sum_a = reduce(lambda x, y:x+y, a)

Answer 2

Indirectly you can add all the elements of a list using a map function using a global variable like below:

# reading the file
with open('numbers.txt') as f:
    lines = [line.strip() for line in f]

numbers = [int(line) for line in lines]
all_sum = 0
def add(n):
    global all_sum
    all_sum += n
    return(all_sum)

result = map(add, numbers)
print(list(result)[-1])

There is only one number in one line in the text file.

Answer 3

reduce(lambda x,y:x+y, L) #summing all elements of a list L

Using map reduce and printing the elapsed time in seconds

import time
from six.moves import reduce
import numpy as np
start=time.time()
L = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
result = reduce(lambda x,y:x+y, L)
end=time.time()
print("sum of list L ", L, " is equal to", result)
print("elapsed time is ", end-start, ' seconds')

output:

sum of list L  [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]  is equal to 55
elapsed time is  0.00014519691467285156  seconds

using python's build-in sum function and elapsed time

start=time.time()
s = sum([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
end=time.time()
print("elapsed time is ", end-start, ' seconds')

output:

elapsed time is  9.226799011230469e-05  seconds

sum is a slightly faster method since 9e-05 is less than 1e-04

Answer 4

Here's one way to do it purely functionally.

from operator import add
from functools import reduce
result = reduce(add, a)

Answer 5

Of course if one just want to sum the elements of a list, he should simply call sum(list_).

Now, comming to your question: map, both the Python built-in and the pattern refer to applying a function to a data sequence, and yield another sequence, with a separate result for each element in the initial sequence.

sum does not do that - it yields a single result for the whole sequence. That pattern is called reduce, and so is the Python ex-built-in to do that. In Python 3, it was "demoted" to the functools module, as it is rarely used when compared to the map pattern.

The sum built-in itself employs the "reduce" pattern alone - but if you were to explicitly recreate sum using the reduce pattern it goes like:

from functools import reduce
a = [1, 2, 3, 4]
reduce(lambda result, value: result + value, a, 0)

The first parameter is a callable that takes the "accumulated result so far", the second value is the sequence of items you want to run reduce at, and the third parameter is the initial value to be passed as the accumulated result. (so,it starts at zero). For a multiplicatory, we could use:

reduce(lambda result, value: result * value, a, 1)

update: Python 3.8 implemented the "multiplicatory" in the standard library as math.prod.

Answer 6

x = list(map(sum,a)) 

Is equivalent to

x = []
for i in a:
    x.append(sum(i))

Sum needs a iterable to apply sum across. If you see the docs syntax goes this way sum(iterable[, start]). Since int is not an iterable you get that error.

Answer 7

The error int object is not iterable is not because list expects an iterable, but sum expected an iterable. The following code:

map(sum , [1,2,3,4])

Is somewhat equivalent to:

[sum(x) for x in [1,2,3,4]]

Executing the last expression yields the same error.