Python中map、filter和reduce的使用总结

sxxbxh 2020-11-14 13:27:38
Python .NET Framework def


在Python中我们常常会遇到需要使用map、filter和reduce三大函数的情况,大家知道分别在什么情况下使用它们吗?下面我们来逐一学习并理解Python中map、filter和reduce的使用,一起来看看吧!

1、map函数

map函数的规范是,将⼀个函数映射到⼀个输⼊列表的所有元素上。

map(function_to_apply, list_of_inputs)

⼤多数时候,我们要把列表中所有元素⼀个个地传递给⼀个函数,并收集输出。比如:

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

squared = []

for i in items:

squared.append(i**2)

而Map函数可以让我们⽤⼀种简单⽽漂亮得多的⽅式来实现,如下:

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

squared = list(map(lambda x: x**2, items))

⼤多数时候,我们使⽤匿名函数lambdas来配合map函数,不仅⽤于⼀列表的输⼊, 我们甚⾄可以⽤于⼀列表的函数!

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))

# Output:

# [0, 0]

# [1, 2]

# [4, 4]

# [9, 6]

# [16, 8]

2、Filter函数

Filter函数很好理解,就是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。下面具一个简单的例子来帮助大家理解:

number_list = range(-5, 5)

less_than_zero = filter(lambda x: x < 0, number_list)

print(list(less_than_zero))

# 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。

3、Reduce函数

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

Python中map、filter和reduce的使用总结就讲到这里了,大家都掌握精华的内容了吗?总的来说,map、filter和reduce三大函数对函数式编程来讲,是极为方便快捷的,推荐大家都尝试着多使用看看,一定能发现新的大陆!郑州同济不孕不育医院:http://jbk.39.net/yiyuanzaixian/zztjyy/郑州男妇科医院在线咨询:http://news.39.net/ylzx/zztjyy/郑州妇科医院那里好:http://jbk.39.net/yiyuanzaixian/sysdfkyy/

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