# 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 
     
      
        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]    # reducedef 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))#filterdef filter_test():    numbers = range(-5,5)    print numbers    return filter(lambda x:x>0, numbers)# 列表解析器执行filterdef 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]
     
      
        at 0x0000000002A792E8>711-----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-------454545----exercise--------133133133-----filter----------[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4][1, 2, 3, 4][1, 2, 3, 4]