Map Function All Versions

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Examples

• 19

  Basic use of map, itertools.imap and future_builtins.map

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  19

  The map function is the simplest one among Python built-ins used for functional programming. map() applies a specified function to each element in an iterable:

  names = ['Fred', 'Wilma', 'Barney']
  

  Python 3.x3.0

  map(len, names)  # map in python 3.x is a class; its instances are iterable
  # Out: <map object at 0x00000198B32E2CF8>
  

  Python 2.x2.6

  from future_builtins import map  # contains a python 3.x compatible map()
  map(len, names)                  # see below
  # Out: <itertools.imap instance at 0x3eb0a20>
  

  Python 2.x2.3

  map(len, names)   # map() returns a list
  # Out: [4, 5, 6]
  
  from itertools import imap
  imap(len, names)  # itertools.imap() returns a generator
  # Out: <itertools.imap at 0x405ea20>
  

  The result can be explicitly converted to a list to remove the differences:

  list(map(len, names))
  # Out: [4, 5, 6]
  

  map() can be replaced by an equivalent list comprehension or generator expression:

  [len(item) for item in names] # equivalent to python 2.x map()
  # Out: [4, 5, 6]
  
  (len(item) for item in names) # equivalent to python 3.x map()
  # Out: <generator object <genexpr> at 0x00000195888D5FC0>
  

  edited Nov 5 at 16:27

  

  

  

  

  

  +5
• 13

  Mapping each value in an iterable

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  13

  For example, you can take the absolute value of each element:

  list(map(abs, (1, -1, 2, -2, 3, -3))) # the call to `list` is unnecessary in 2.x
  # Out: [1, 1, 2, 2, 3, 3]
  

  Anonymous function also support for mapping a list:

  map(lambda x:x*2, [1, 2, 3, 4, 5])
  # Out: [2, 4, 6, 8, 10]
  

  or converting decimal values to percentages:

  def to_percent(num):
      return num * 100
  
  list(map(to_percent, [0.95, 0.75, 1.01, 0.1]))
  # Out: [95.0, 75.0, 101.0, 10.0]
  

  or converting dollars to euros (given an exchange rate):

  from functools import partial
  from operator import mul
  
  rate = 0.9  # fictitious exchange rate, 1 dollar = 0.9 euros
  dollars = {'under_my_bed': 1000,
             'jeans': 45,
             'bank': 5000}
  
  sum(map(partial(mul, rate), dollars.values()))
  # Out: 5440.5
  

  functools.partial is a convenient way to fix parameters of functions so that they can be used with map instead of using lambda or creating customized functions.

  edited Nov 5 at 16:27

  

  

  

  

  
• 5

  Mapping values of different iterables

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  5

  For example calculating the average of each i-th element of multiple iterables:

  def average(*args):
      return float(sum(args)) / len(args)  # cast to float - only mandatory for python 2.x
  
  measurement1 = [100, 111, 99, 97]
  measurement2 = [102, 117, 91, 102]
  measurement3 = [104, 102, 95, 101]
  
  list(map(average, measurement1, measurement2, measurement3))
  # Out: [102.0, 110.0, 95.0, 100.0]
  

  There are different requirements if more than one iterable is passed to map depending on the version of python:

  • The function must take as many parameters as there are iterables:

    def median_of_three(a, b, c):
        return sorted((a, b, c))[1]
    
    list(map(median_of_three, measurement1, measurement2))
    

    TypeError: median_of_three() missing 1 required positional argument: 'c'

    list(map(median_of_three, measurement1, measurement2, measurement3, measurement3))
    

    TypeError: median_of_three() takes 3 positional arguments but 4 were given

  Python 2.x2.0.1

  • map: The mapping iterates as long as one iterable is still not fully consumed but assumes None from the fully consumed iterables:

    import operator
    
    measurement1 = [100, 111, 99, 97]
    measurement2 = [102, 117]
    
    # Calculate difference between elements
    list(map(operator.sub, measurement1, measurement2))
    

    TypeError: unsupported operand type(s) for -: 'int' and 'NoneType'

  • itertools.imap and future_builtins.map: The mapping stops as soon as one iterable stops:

    import operator
    from itertools import imap
    
    measurement1 = [100, 111, 99, 97]
    measurement2 = [102, 117]
    
    # Calculate difference between elements
    list(imap(operator.sub, measurement1, measurement2))
    # Out: [-2, -6]
    list(imap(operator.sub, measurement2, measurement1))
    # Out: [2, 6]
    

  Python 3.x3.0.0

  • The mapping stops as soon as one iterable stops:

    import operator
    
    measurement1 = [100, 111, 99, 97]
    measurement2 = [102, 117]
    
    # Calculate difference between elements
    list(map(operator.sub, measurement1, measurement2))
    # Out: [-2, -6]
    list(map(operator.sub, measurement2, measurement1))
    # Out: [2, 6]
    

  edited Apr 2 at 16:22

  

  
• 1

  Transposing with Map: Using "None" as function argument (python 2.x only)

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  1

  from itertools import imap
  from future_builtins import map as fmap # Different name to highlight differences
  
  image = [[1, 2, 3],
           [4, 5, 6],
           [7, 8, 9]]
  
  list(map(None, *image))
  # Out: [(1, 4, 7), (2, 5, 8), (3, 6, 9)]
  list(fmap(None, *image))
  # Out: [(1, 4, 7), (2, 5, 8), (3, 6, 9)]
  list(imap(None, *image))
  # Out: [(1, 4, 7), (2, 5, 8), (3, 6, 9)]
  
  image2 = [[1, 2, 3],
            [4, 5],
            [7, 8, 9]]
  list(map(None, *image2))
  # Out: [(1, 4, 7), (2, 5, 8), (3, None, 9)]  # Fill missing values with None
  list(fmap(None, *image2))
  # Out: [(1, 4, 7), (2, 5, 8)]                # ignore columns with missing values
  list(imap(None, *image2))
  # Out: [(1, 4, 7), (2, 5, 8)]                # dito
  

  Python 3.x3.0.0

  list(map(None, *image))
  

  TypeError: 'NoneType' object is not callable

  But there is a workaround to have similar results:

  def conv_to_list(*args):
      return list(args)
  
  list(map(conv_to_list, *image))
  # Out: [[1, 4, 7], [2, 5, 8], [3, 6, 9]]
  

  created Apr 6 at 16:10