函数作用域
函数的作用域只跟函数声明时定义的作用域有关,跟函数的调用位置无任何关系
1 name=‘alex‘ 2 3 def foo(): 4 name=‘lhf‘ 5 def bar(): 6 name=‘wupeiqi‘ 7 print(name) 8 def tt(): 9 print(name) 10 return tt 11 return bar 12 13 # bar=foo() 14 # tt=bar() 15 # print(tt) 16 # tt() 17 r1 = foo() 18 r2 = r1() # tt 19 r3 = r2() 20 foo()()()
1 高阶函数(满足一个条件) 2 1.函数接收的参数是一个函数名 2.返回值中包含函数 3 把函数当作参数传给另外一个函数 4 def foo(n): #n=bar 5 print(n) 6 7 def bar(name): 8 print(‘my name is %s‘ %name) 9 10 # foo(bar) 11 # foo(bar()) 12 foo(bar(‘alex‘)) 13 14 #返回值中包含函数 15 def bar(): 16 print(‘from bar‘) 17 def foo(): 18 print(‘from foo‘) 19 return bar 20 n=foo() 21 n() 22 def hanle(): 23 print(‘from handle‘) 24 return hanle 25 h=hanle() 26 h() 27 28 29 30 def test1(): 31 print(‘from test1‘) 32 def test2(): 33 print(‘from handle‘) 34 return test1()
尾调用:https://blog.csdn.net/wusecaiyun/article/details/46531891
在递归函数的最后一步return自身(),会直接调到下一层函数,因为如果是return x +函数(),
那么这个x+ 会一直等着函数()执行返回的结果。如果是尾调用,直接进函数,没有任何res在
等待函数()返回值
匿名函数lambda
1 # lambda x:x+1 2 3 4 def calc(x): 5 return x+1 6 7 res=calc(10) 8 print(res) 9 print(calc) 10 11 print(lambda x:x+1) 12 func=lambda x:x+1 13 print(func(10)) 14 15 16 17 18 name=‘alex‘ #name=‘alex_sb‘ 19 def change_name(x): 20 return name+‘_sb‘ 21 22 res=change_name(name) 23 print(res) 24 25 func=lambda x:x+‘_sb‘ 26 res=func(name) 27 print(‘匿名函数的运行结果‘,res) 28 29 30 # func=lambda x,y,z:x+y+z 31 # print(func(1,2,3)) 32 33 name1=‘alex‘ 34 name2=‘sbalex‘ 35 name1=‘supersbalex‘ 36 37 38 39 # def test(x,y,z): 40 # return x+1,y+1 #----->(x+1,y+1) 41 42 # lambda x,y,z:(x+1,y+1,z+1)
map()
匿名函数可以与map,filter,reduce结合使用,精简代码
map处理的是一个可迭代对象,内部用for遍历可迭代对象的每一条数据,数据被传入的函数处理,
得到的结果也是一个可迭代对象,用list处理,得到列表,并且该‘列表’元素个数及位置与原来一样
1 # num_l=[1,2,10,5,3,7] 2 # num1_l=[1,2,10,5,3,7] 3 4 # ret=[] 5 # for i in num_l: 6 # ret.append(i**2) 7 # 8 # print(ret) 9 10 # def map_test(array): 11 # ret=[] 12 # for i in num_l: 13 # ret.append(i**2) 14 # return ret 15 # 16 # ret=map_test(num_l) 17 # rett=map_test(num1_l) 18 # print(ret) 19 # print(rett) 20 21 num_l=[1,2,10,5,3,7] 22 #lambda x:x+1 23 def add_one(x): 24 return x+1 25 26 #lambda x:x-1 27 def reduce_one(x): 28 return x-1 29 30 #lambda x:x**2 31 def pf(x): 32 return x**2 33 34 def map_test(func,array): 35 ret=[] 36 for i in num_l: 37 res=func(i) #add_one(i) 38 ret.append(res) 39 return ret 40 # print(map_test(add_one,num_l)) 41 # print(map_test(lambda x:x+1,num_l)) 42 43 # print(map_test(reduce_one,num_l)) 44 # print(map_test(lambda x:x-1,num_l)) 45 46 # print(map_test(pf,num_l)) 47 # print(map_test(lambda x:x**2,num_l)) 48 49 50 51 #终极版本 52 def map_test(func,array): #func=lambda x:x+1 arrary=[1,2,10,5,3,7] 53 ret=[] 54 for i in array: 55 res=func(i) #add_one(i) 56 ret.append(res) 57 return ret 58 59 print(map_test(lambda x:x+1,num_l)) 60 res=map(lambda x:x+1,num_l) 61 print(‘内置函数map,处理结果‘,res) 62 # for i in res: 63 # print(i) 64 print(list(res)) 65 print(‘传的是有名函数‘,list(map(reduce_one,num_l))) 66 67 68 msg=‘linhaifeng‘ 69 print(list(map(lambda x:x.upper(),msg)))
filter() #过滤
filter处理的是一个可迭代对象,内部用for遍历每一条数据,被传入的函数判断出布尔值,如果是True则留下来,如果不是就被丢弃,最终得到的结果也是一个可迭代对象,被list处理后得到列表
1 # movie_people=[‘sb_alex‘,‘sb_wupeiqi‘,‘linhaifeng‘,‘sb_yuanhao‘] 2 # def filter_test(array): 3 # ret=[] 4 # for p in array: 5 # if not p.startswith(‘sb‘): 6 # ret.append(p) 7 # return ret 8 # 9 # res=filter_test(movie_people) 10 # print(res) 11 12 13 # movie_people=[‘alex_sb‘,‘wupeiqi_sb‘,‘linhaifeng‘,‘yuanhao_sb‘] 14 # def sb_show(n): 15 # return n.endswith(‘sb‘) 16 # 17 # def filter_test(func,array): 18 # ret=[] 19 # for p in array: 20 # if not func(p): 21 # ret.append(p) 22 # return ret 23 # 24 # res=filter_test(sb_show,movie_people) 25 # print(res) 26 27 #终极版本 28 movie_people=[‘alex_sb‘,‘wupeiqi_sb‘,‘linhaifeng‘,‘yuanhao_sb‘] 29 # def sb_show(n): 30 # return n.endswith(‘sb‘) 31 #--->lambda n:n.endswith(‘sb‘) 32 33 def filter_test(func,array): 34 ret=[] 35 for p in array: 36 if not func(p): 37 ret.append(p) 38 return ret 39 40 res=filter_test(lambda n:n.endswith(‘sb‘),movie_people) 41 print(res) 42 43 #filter函数 44 movie_people=[‘alex_sb‘,‘wupeiqi_sb‘,‘linhaifeng‘,‘yuanhao_sb‘] 45 print(filter(lambda n:not n.endswith(‘sb‘),movie_people)) 46 47 48 49 res=filter(lambda n:not n.endswith(‘sb‘),movie_people) 50 print(list(res)) 51 52 53 print(list(filter(lambda n:not n.endswith(‘sb‘),movie_people)))
reduce()
处理一个序列,然后把序列进行合并操作
1 # from functools import reduce 2 3 4 # num_l=[1,2,3,100] 5 6 # res=0 7 # for num in num_l: 8 # res+=num 9 # 10 # print(res) 11 12 # num_l=[1,2,3,100] 13 # def reduce_test(array): 14 # res=0 15 # for num in array: 16 # res+=num 17 # return res 18 # 19 # print(reduce_test(num_l)) 20 21 22 # num_l=[1,2,3,100] 23 24 # def multi(x,y): 25 # return x*y 26 #lambda x,y:x*y 27 28 # def reduce_test(func,array): 29 # res=array.pop(0) 30 # for num in array: 31 # res=func(res,num) 32 # return res 33 # 34 # print(reduce_test(lambda x,y:x*y,num_l)) 35 36 num_l=[1,2,3,100] 37 def reduce_test(func,array,init=None): 38 if init is None: 39 res=array.pop(0) 40 else: 41 res=init 42 for num in array: 43 res=func(res,num) 44 return res 45 46 print(reduce_test(lambda x,y:x*y,num_l,100)) 47 48 49 #reduce函数 50 from functools import reduce 51 num_l=[1,2,3,100] 52 print(reduce(lambda x,y:x+y,num_l,1)) 53 print(reduce(lambda x,y:x+y,num_l))
原文地址:https://www.cnblogs.com/lishuaing/p/10687014.html
时间: 2024-11-07 02:53:41