Understanding the map function

Question

map function  iterable         Apply function to every item of iterable and return a list of 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    If one iterable is shorter than another it is assumed to be extended with None items    If function is None  the identity function is assumed  if there are multiple arguments  map   returns a list consisting of tuples containing the corresponding items from all iterables  a kind of transpose operation     The iterable arguments may be a sequence or any iterable object  the result is always a list   What role does this play in making a Cartesian product   content   map tuple  array    What effect does putting a tuple anywhere in there have  I also noticed that without the map function the output is abc and with it  it s a  b  c   I want to fully understand this function  The reference definitions is also hard to understand  Too much fancy fluff

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Python3 - map func  iterable  One thing that wasn t mentioned completely  although  BlooB kinda mentioned it  is that map returns a map object NOT a list  This is a big difference when it comes to time performance on initialization and iteration  Consider these two tests  import time def test1 iterable       a   time clock       map str  iterable      a   time clock   - a      b   time clock         str x  for x in iterable       b   time clock   - b      print a b    def test2 iterable       a   time clock         x for x in map str  iterable       a   time clock   - a      b   time clock         str x  for x in iterable       b   time clock   - b      print a b    test1 range 2000000      Prints  1 7e-5s    8s test2 range 2000000      Prints  9s         8s  As you can see initializing the map function takes almost no time at all  However iterating through the map object takes longer than simply iterating through the iterable  This means that the function passed to map   is not applied to each element until the element is reached in the iteration  If you want a list use list comprehension  If you plan to iterate through in a for loop and will break at some point  then use map

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map isn t particularly pythonic  I would recommend using list comprehensions instead   map f  iterable    is basically equivalent to    f x  for x in iterable    map on its own can t do a Cartesian product  because the length of its output list is always the same as its input list  You can trivially do a Cartesian product with a list comprehension though     a  b  for a in iterable a for b in iterable b    The syntax is a little confusing -- that s basically equivalent to   result      for a in iterable a      for b in iterable b          result append  a  b

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map doesn t relate to a Cartesian product at all  although I imagine someone well versed in functional programming could come up with some impossible to understand way of generating a one using map    map in Python 3 is equivalent to this   def map func  iterable       for i in iterable          yield func i    and the only difference in Python 2 is that it will build up a full list of results to return all at once instead of yielding   Although Python convention usually prefers list comprehensions  or generator expressions  to achieve the same result as a call to map  particularly if you re using a lambda expression as the first argument    func i  for i in iterable    As an example of what you asked for in the comments on the question -  turn a string into an array   by  array  you probably want either a tuple or a list  both of them behave a little like arrays from other languages  -    gt  gt  gt  a    hello  world    gt  gt  gt  list a    h    e    l    l    o              w    o    r    l    d    gt  gt  gt  tuple a    h    e    l    l    o              w    o    r    l    d     A use of map here would be if you start with a list of strings instead of a single string - map can listify all of them individually    gt  gt  gt  a     foo    bar    baz    gt  gt  gt  list map list  a      f    o    o      b    a    r      b    a    z      Note that map list  a  is equivalent in Python 2  but in Python 3 you need the list call if you want to do anything other than feed it into a for loop  or a processing function such as sum that only needs an iterable  and not a sequence   But also note again that a list comprehension is usually preferred    gt  gt  gt   list b  for b in a     f    o    o      b    a    r      b    a    z

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Simplifying a bit  you can imagine map   doing something like this   def mymap func  lst       result          for e in lst          result append func e       return result   As you can see  it takes a function and a list  and returns a new list with the result of applying the function to each of the elements in the input list  I said  simplifying a bit  because in reality map   can process more than one iterable      If additional iterable arguments are passed  function must take that many arguments and is applied to the items from all iterables in parallel  If one iterable is shorter than another it is assumed to be extended with None items    For the second part in the question  What role does this play in making a Cartesian product  well  map   could be used for generating the cartesian product of a list like this   lst    1  2  3  4  5   from operator import add reduce add  map lambda i  map lambda j   i  j   lst   lst         But to tell the truth  using product   is a much simpler and natural way to solve the problem   from itertools import product list product lst  lst     Either way  the result is the cartesian product of lst as defined above     1  1    1  2    1  3    1  4    1  5     2  1    2  2    2  3    2  4    2  5     3  1    3  2    3  3    3  4    3  5     4  1    4  2    4  3    4  4    4  5     5  1    5  2    5  3    5  4    5  5

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The map   function is there to apply the same procedure to every item in an iterable data structure  like lists  generators  strings  and other stuff   Let s look at an example  map   can iterate over every item in a list and apply a function to each item  than it will return  give you back  the new list   Imagine you have a function that takes a number  adds 1 to that number and returns it   def add one num     new num   num   1   return new num   You also have a list of numbers   my list    1  3  6  7  8  10    if you want to increment every number in the list  you can do the following    gt  gt  gt  map add one  my list   2  4  7  8  9  11    Note  At minimum map   needs two arguments  First a function name and second something like a list   Let s see some other cool things map   can do  map   can take multiple iterables  lists  strings  etc   and pass an element from each iterable to a function as an argument   We have three lists   list one    1  2  3  4  5  list two    11  12  13  14  15  list three    21  22  23  24  25    map   can make you a new list that holds the addition of elements at a specific index   Now remember map    needs a function  This time we ll use the builtin sum   function  Running map   gives the following result    gt  gt  gt  map sum  list one  list two  list three   33  36  39  42  45    REMEMBER  In Python 2 map    will iterate  go through the elements of the lists  according to the longest list  and pass None to the function for the shorter lists  so your function should look for None and handle them  otherwise you will get errors  In Python 3 map   will stop after finishing with the shortest list  Also  in Python 3  map   returns an iterator  not a list

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map creates a new list by applying a function to every element of the source   xs    1  2  3     all of those are equivalent     the output is  2  4  6    1  map ys   map lambda x  x   2  xs    2  list comprehension ys    x   2 for x in xs    3  explicit loop ys      for x in xs      ys append x   2    n-ary map is equivalent to zipping input iterables together and then applying the transformation function on every element of that intermediate zipped list  It s not a Cartesian product   xs    1  2  3  ys    2  4  6   def f x  y       return  x   2  y    2     output    2  1    4  2    6  3     1  map zs   map f  xs  ys    2  list comp zs    f x  y  for x  y in zip xs  ys     3  explicit loop zs      for x  y in zip xs  ys       zs append f x  y     I ve used zip here  but map behaviour actually differs slightly when iterables aren t the same size     as noted in its documentation  it extends iterables to contain None

[python] Understanding the map function

Python3 - map(func, iterable)

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