Python中的函数与变量

def 函数名 (参数):
"函数的注释"
函数体
return x

a = ['c','d']
def test():
a = '我'
global a #报错！因为global在下面不知道去哪找a所以global应该上提
print(a)

def test(x):
return x+1#使用匿名函数：
lambda x:x+1

#若匿名函数接收多个参数，返回多个值则需加括号lambda x,y,z:(x+1,y+1,z+1)

fuc = lambda x:x+1
fuc(10)

#非函数式：
a = 1
def test():
global a
a += 1
return a
test()
print(a)

#函数式编程
a = 1
def test(n)：
return n+1
print(test(a)
print(a)

#1.函数的传入参数是一个函数名
def foo(n)
print(n)def bar(name)
print('my name is %s' %name)foo(bar('echo')) #先运行bar（）无返回值

#2.返回值中包含函数
def bar ():
print('from bar')def foo():
print('from bar ')
return bar #返回bar的内存地址n = foo()
n() #调用bar函数

array=[1,3,4,71,2]ret=[]
for i in array:
ret.append(i**2)
print(ret)#如果我们有一万个列表,那么你只能把上面的逻辑定义成函数
def map_test(array):
ret=[]
for i in array:
ret.append(i**2)
return retprint(map_test(array))#如果我们的需求变了,不是把列表中每个元素都平方,还有加1,减一,那么可以这样
def add_num(x):
return x+1
def map_test(func,array):
ret=[]
for i in array:
ret.append(func(i))
return retprint(map_test(add_num,array))
#可以使用匿名函数
print(map_test(lambda x:x-1,array))#上面就是map函数的功能,map得到的结果是可迭代对象
print(map(lambda x:x-1,range(5)))

#电影院聚集了一群看电影bb的傻逼,让我们找出他们
movie_people=['alex','wupeiqi','yuanhao','sb_alex','sb_wupeiqi','sb_yuanhao']def tell_sb(x):
return x.startswith('sb')def filter_test(func,array):
ret=[]
for i in array:
if func(i):
ret.append(i)
return retprint(filter_test(tell_sb,movie_people))#函数filter,返回可迭代对象
print(filter(lambda x:x.startswith('sb'),movie_people))

from functools import reduce
#合并,得一个合并的结果
array_test=[1,2,3,4,5,6,7]
array=range(100)#报错啊,res没有指定初始值
def reduce_test(func,array):
l=list(array)
for i in l:
res=func(res,i)
return res# print(reduce_test(lambda x,y:x+y,array))#可以从列表左边弹出第一个值
def reduce_test(func,array):
l=list(array)
res=l.pop(0)
for i in l:
res=func(res,i)
return resprint(reduce_test(lambda x,y:x+y,array))#我们应该支持用户自己传入初始值
def reduce_test(func,array,init=None):
l=list(array)
if init is None:
res=l.pop(0)
else:
res=init
for i in l:
res=func(res,i)
return resprint(reduce_test(lambda x,y:x+y,array))
print(reduce_test(lambda x,y:x+y,array,50))

当然了,map,filter,reduce,可以处理所有数据类型name_dic=[
{'name':'alex','age':1000},
{'name':'wupeiqi','age':10000},
{'name':'yuanhao','age':9000},
{'name':'linhaifeng','age':18},
]
#利用filter过滤掉千年王八,万年龟,还有一个九千岁
def func(x):
age_list=[1000,10000,9000]
return x['age'] not in age_listres=filter(func,name_dic)
for i in res:
print(i)res=filter(lambda x:x['age'] == 18,name_dic)
for i in res:
print(i)#reduce用来计算1到100的和
from functools import reduce
print(reduce(lambda x,y:x+y,range(100),100))
print(reduce(lambda x,y:x+y,range(1,101)))#用map来处理字符串列表啊,把列表中所有人都变成sb,比方alex_sb
name=['alex','wupeiqi','yuanhao']res=map(lambda x:x+'_sb',name)
for i in res:
print(i)

name = '您好‘
print(bytes(name ,encoding = 'utf-8',decode'utf-8))

#终极玩法
people= [
{'name ' ='haha', 'age' = 100}
{'name' = 'echo' , 'age' = 500}
]print(max(people,key=lambd dic:dic['age']))

l = 'hello'
s1 = slice(1,4,2)
print(l(s1))
print(s1.start)
print(s1.end)
print(s1.step) #查看步长