Python map() built-in function

From the Python 3 documentation

Return an iterator that applies function to every item of iterable, yielding the results. If additional iterable arguments are passed, function must take that many arguments and is applied to the items from all iterables in parallel. With multiple iterables, the iterator stops when the shortest iterable is exhausted. For cases where the function inputs are already arranged into argument tuples.


The map function, map(function, iterable) takes in one or more iterables, a ‘callback function’ (often a lambda), and returns a “Map Object”. The map object contains the result of the map function applying the callback to each element in the iterable arguments. Map iterates over the provided iterable objects simultaneously. As in, at every step, “i” in the map function, the element at index “i” of each iterable will be available to the map function at that time. You will often want to cast the resultant map object to a list, tuple, or another form of object that is more convenient to work with once you are finished mapping.

***An important note: As of the release of Python 3, if the iterables supplied to map are of different lengths, The map will stop and return when it has hit the number of steps corresponding to the length of the shortest iterable.

Input Parameters:

Function: takes the item (or items) at the index corresponding to the current step of the Map and gives the return result as an item to store in the Map Object. The type of element stored to the map object will be identical to the type returned from the function.

Iterable(s): tuple, list, range, dictionary, set, string.

A very simple example:

def double_map(func, iter):
  my_map = map(func, iter)
  return list(my_map)

def double(element):
  return element*2

nums = [1,2,3,4]

print(double_map(double, nums))

Will output the following: [2,4,6,8]

A less simple example:

This example employs callback function written as a lambda, as well as

def multi_map(func, *iters):
  my_map = map(func, *iters)
  return list(my_map)

list1 = [1,2,3]
list2 = [4,5,6]

print(multi_map((lambda item1, item2: item1*item2), list1, list2))

Will output the following: [4,10,18]

An example demonstrating map’s handling of different iterable lengths:

def max(a,b):
  if a > b: return a
  else: return b

list1= [1,1,1]

list2= [0,0,0,1,1,1,1,1,1,1]

result = list(map(max,list1,list2))


Will output the following: [1,1,1]

Notice how the length of the resultant list is equal to list1’s length?

Subscribe to

A weekly and bullshit free publication, full of interesting, relevant links.