lambda、map、reduce、filter函数讲解

# coding:utf-8

"""
几个特殊的函数：
    lambda
        lambda后面直接跟变量
        变量后面是冒号
        冒号后面是表达式，表达式计算结果就是本函数的返回值
        作用：没有给程序带来性能上的提升，带来的是代码的简洁
    map
        格式：map(func, seq) func是一个函数，seq是一个序列对象
        最终结果得到一个list
        执行时，序列对象中的每个元素，从左到右的顺序，一次被取出来，并塞入到func那个函数中
        map是上下运算
    reduce
        reduce是横向逐个元素进行运算
    filter
        过滤器
"""

# lambda 功能的三种实现方式

# 最原始方式
def lambda_test():
    def add(x):
        x += 3
        return x
    numbers = range(10)
    new_numbers = []
    for i in numbers:
        new_numbers.append(add(i))
    return new_numbers

# 列表解析的方式，推荐使用
def lambda_test2():
    return [i+3 for i in range(10)]

# lambda方式实现
def lambda_test3():
    lam = lambda x:x+3    # 一行表示了add方法
    numbers = range(10)
    n2 = []
    for i in numbers:
        n2.append(lam(i))
    return n2

# lambda 多参数
def lambda_test4(x,y):
    g =  lambda x,y:x+y #计算x+y
    print g #返回的是方法名地址 <function <lambda> at 0x0000000002A2AB38>
    return g(x,y)

# lambda多参改进
def lambda_test5(x,y):
    return (lambda x,y:x+y)(x,y)
    
"""
map
"""
# lambda_test的功能也能通过map实现
def map_test():
    def add(x):
        x += 3
        return x
    numbers = range(10)
    return map(add, numbers)

# map改进,lambda实现函数
def map_test2():
    numbers = range(10)
    return map(lambda x:x+3, numbers)

# 列表解析实现map的功能
def map_test3():
    return [i+3 for i in range(10)]

# map的优雅（多参）
def map_test4():
    list1 = range(1,6)
    list2 = range(6,11)
    return map(lambda x,y:x+y, list1, list2)

# zip方式实现map_test4功能
def map_test5():
    list1 = range(1,6)
    list2 = range(6,11)
    lst = zip(list1, list2)
    return [x+y for x,y in lst]
    
# reduce
def reduce_test():
    return reduce(lambda x,y:x+y, range(10))

# for循环实现
def reduce_test2():
    lam = lambda x,y:x+y
    numbers = range(10)
    sum_number = 0
    for i in numbers:
        sum_number += i
    return sum_number

# 列表解析器操作,不能复用，函数发生变化，列表解析器就失效了
def reduce_test3():
    return sum([x for x in range(10)])

#练习
#两个list，a=[3,9,8,5,2],b=[1,4,9,2,6].计算a[0]b[0]+a[1]b[1]+...的结果
#方法1：
def test():
    a,b = [3,9,8,5,2],[1,4,9,2,6]
    lst = zip(a,b)
    return sum(x*y for x,y in lst)
#方法2    
def test2():
    a,b = [3,9,8,5,2],[1,4,9,2,6]
    lst = zip(a,b)
    return reduce(lambda x,y:x+y, [m*n for m,n in lst])
# 方法3, lambda、map、reduce都使用上了
def test3():
    a,b = [3,9,8,5,2],[1,4,9,2,6]
    return reduce(lambda x,y:x+y,map(lambda x,y:x*y, a,b))

#filter
def filter_test():
    numbers = range(-5,5)
    print numbers
    return filter(lambda x:x>0, numbers)

# 列表解析器执行filter
def filter_test2():
    numbers = range(-5,5)
    return [x for x in numbers if x>0]

if __name__ =="__main__":
    print "----lambda-------"
    print lambda_test()
    print lambda_test2()
    print lambda_test3()
    print lambda_test4(3,4)
    print lambda_test5(5,6)
    print "-----map-----"
    print map_test()
    print map_test2()
    print map_test3()
    print map_test4()
    print map_test5()
    print "-------reduce-------"
    print reduce_test()
    print reduce_test2()
    print reduce_test3()
    print "----exercise--------"
    print test()
    print test2()
    print test3()
    print "-----filter----------"
    print filter_test()
    print filter_test2()

执行的结果是：

----lambda-------
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
<function <lambda> at 0x0000000002A792E8>
7
11
-----map-----
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
[7, 9, 11, 13, 15]
[7, 9, 11, 13, 15]
-------reduce-------
45
45
45
----exercise--------
133
133
133
-----filter----------
[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4]
[1, 2, 3, 4]
[1, 2, 3, 4]