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Detailed explanation of python functions map, filter, and reduce
Detailed explanation of python functions map, filter, and reduce
This article shares with you a detailed explanation of the python functions map, filter, and reduce. The content is quite good. I hope it can help friends in need
##1 .map
Map will map a function to all elements of an input list. This is its specification:
map(function_to_apply, list_of_inputs)
items = [1, 2, 3, 4, 5] squared = []for i in items: squared.append(i**2)
Map allows us to achieve it in a much simpler and more beautiful way. That's it:
items = [1, 2, 3, 4, 5] squared = list(map(lambda x: x**2, items))
map,
So I did the same thing above. Not only for a list of inputs, we can even use it for a list of functions!
def multiply(x): return (x*x)def add(x): return (x+x) funcs = [multiply, add]for i in range(5): value = map(lambda x: x(i), funcs) print(list(value)) # 译者注：上面print时，加了list转换，是为了python2/3的兼容性 # 在python2中map直接返回列表，但在python3中返回迭代器 # 因此为了兼容python3, 需要list转换一下 # Output: # [0, 0] # [1, 2] # [4, 4] # [9, 6] # [16, 8]
2.Filter
顾名思义，filter过滤列表中的元素，并且返回一个由所有符合要求的元素所构成的列表，符合要求即函数映射到该元素时返回值为True. 这里是一个简短的例子：
number_list = range(-5, 5) less_than_zero = filter(lambda x: x < 0, number_list) print(list(less_than_zero)) # 译者注：上面print时，加了list转换，是为了python2/3的兼容性 # 在python2中filter直接返回列表，但在python3中返回迭代器 # 因此为了兼容python3, 需要list转换一下 # Output: [-5, -4, -3, -2, -1]
这个filter类似于一个for循环，但它是一个内置函数，并且更快。
注意：如果map和filter对你来说看起来并不优雅的话，那么你可以看看另外一章：列表/字典/元组推导式。
3.Reduce
当需要对一个列表进行一些计算并返回结果时，Reduce 是个非常有用的函数。举个例子，当你需要计算一个整数列表的乘积时。
通常在 python 中你可能会使用基本的 for 循环来完成这个任务。
现在我们来试试 reduce：
from functools import reduce product = reduce( (lambda x, y: x * y), [1, 2, 3, 4] ) # Output: 24
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