python map, reduce,filter 使用

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mob604756e605af 2013-10-22 15:23:00

文章标签 字符串 python ide lambda表达式 c语言 文章分类 Python 后端开发

python built-on function:

http://docs.python.org/2.7/library/functions.html?highlight=map%20reduce

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.

>>> def cube(x): return x*x*x

>>> map(cube, range(1, 11))

[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]

另外map也支持多个sequence，这就要求function也支持相应数量的参数输入：

>>> def add(x, y): return x+y

>>> map(add, range(8), range(8))

[0, 2, 4, 6, 8, 10, 12, 14]

reduce(function, iterable[, initializer])

Apply function of two arguments cumulatively to the items of iterable, from left to right, so as to reduce the iterable to a single value. For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates ((((1+2)+3)+4)+5). The left argument, x, is the accumulated value and the right argument, y, is the update value from the iterable. If the optional initializer is present, it is placed before the items of the iterable in the calculation, and serves as a default when the iterable is empty. If initializer is not given and iterablecontains only one item, the first item is returned. Roughly equivalent to:

def reduce(function, iterable, initializer=None):
    it = iter(iterable)
    if initializer is None:
        try:
            initializer = next(it)
        except StopIteration:
            raise TypeError('reduce() of empty sequence with no initial value')
    accum_value = initializer
    for x in it:
        accum_value = function(accum_value, x)
    return accum_value

reduce(function, sequence, starting_value)：对sequence中的item顺序迭代调用function，如果有starting_value，还可以作为初始值调用，例如可以用来对List求和：

>>> def add(x,y): return x + y

>>> reduce(add, range(1, 11))

55 （注：1+2+3+4+5+6+7+8+9+10）

>>> reduce(add, range(1, 11), 20)

75 （注：1+2+3+4+5+6+7+8+9+10+20）

又例如：

a = [1,2,3,4,5]

reduce(lambda x, y : x +y, a)

则返回值为：15

加入我们设定init的值，即：

a = [1,2,3,4,5]

reduce(lambda x, y : x +y, a， 3)

则返回值为：18

注意：传递给reduce的func,必须要能接受两个参数。并返回一个结果。这个结果将会是传递给func进行下次一调用；上面的例子，调用过程是：

1,func(1, 2) 返回 x1

2,func(x1, 3) 返回 x2

3,func(x2, 4) 返回 x3

…...

其实，通过，reduce中func的设计，reduce可以完成map和filter的功能。

lambda：这是Python支持一种有趣的语法，它允许你快速定义单行的最小函数，类似与C语言中的宏，这些叫做lambda的函数，是从LISP借用来的，可以用在任何需要函数的地方：

>>> g = lambda x: x * 2

>>> g(3)

>>> (lambda x: x * 2)(3)

filter(function, iterable)

Construct a list from those elements of iterable for which function returns true. iterable may be either a sequence, a container which supports iteration, or an iterator. If iterable is a string or a tuple, the result also has that type; otherwise it is always a list. If function is None, the identity function is assumed, that is, all elements of iterable that are false are removed.

Note that filter(function, iterable) is equivalent to [item for item in iterable if function(item)] if function is not None and [item for item in iterableif item] if function is None.

See itertools.ifilter() and itertools.ifilterfalse() for iterator versions of this function, including a variation that filters for elements where the function returns false.

filter(function, sequence)：对sequence中的item依次执行function(item)，将执行结果为True的item组成一个List/String/Tuple（取决于sequence的类型）返回：

>>> def f(x): return x % 2 != 0 and x % 3 != 0

>>> filter(f, range(2, 25))

[5, 7, 11, 13, 17, 19, 23]

>>> [i for i in range(2,25) if f(i)] 也输出:

[5, 7, 11, 13, 17, 19, 23]

>>> def f(x): return x != 'a'

>>> filter(f, "abcdef")

'bcdef'

我们也可以把filter map reduce 和lambda结合起来用，函数就可以简单的写成一行。

例如

kmpathes = filter(lambda kmpath: kmpath,