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10.7: Map, filter and reduce

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    To add up all the numbers in a list, you can use a loop like this:

    def add_all(t):
        total = 0
        for x in t:
            total += x
        return total

    total is initialized to 0. Each time through the loop, x gets one element from the list. The += operator provides a short way to update a variable. This augmented assignment statement,

        total += x

    is equivalent to

        total = total + x

    As the loop runs, total accumulates the sum of the elements; a variable used this way is sometimes called an accumulator.

    Adding up the elements of a list is such a common operation that Python provides it as a built-in function, sum:

    >>> t = [1, 2, 3]
    >>> sum(t)

    An operation like this that combines a sequence of elements into a single value is sometimes called reduce.

    Sometimes you want to traverse one list while building another. For example, the following function takes a list of strings and returns a new list that contains capitalized strings:

    def capitalize_all(t):
        res = []
        for s in t:
        return res

    res is initialized with an empty list; each time through the loop, we append the next element. So res is another kind of accumulator.

    An operation like capitalize_all is sometimes called a map because it “maps” a function (in this case the method capitalize) onto each of the elements in a sequence.

    Another common operation is to select some of the elements from a list and return a sublist. For example, the following function takes a list of strings and returns a list that contains only the uppercase strings:

    def only_upper(t):
        res = []
        for s in t:
            if s.isupper():
        return res

    isupper is a string method that returns True if the string contains only upper case letters.

    An operation like only_upper is called a filter because it selects some of the elements and filters out the others.

    Most common list operations can be expressed as a combination of map, filter and reduce.

    This page titled 10.7: Map, filter and reduce is shared under a CC BY-NC 3.0 license and was authored, remixed, and/or curated by Allen B. Downey (Green Tea Press) .

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