装饰器
1，知识储备
一 *args，**kwargs
def index(name,age):
print(name,age)
def wrapper(*args,**kwargs):
#args=(1,2,2,3,4,4,5),kwargs={'x':1,'y':2}
index(*args,**kwargs) #index(1,2,2,3,4,4,5,y=2,x=1)
wrapper('egon',age=18)
二 函数对象：函数可被当做数据传递
- 函数可以当做参数传给另外一个函数
- 一个函数的返回值也可以是一个函数(打破函数的层级限制)
def f1():
def f2():
print('f2')
return f2
f=f1()
f()
三 名称空间与作用域
名称空间
- 分三种
内置名称空间：python解释器启动则生效
全局名称空间：执行python文件时生效
局部名称空间：调用函数时，临时生效，函调用结束则失效
- 加载顺序：先内置，再全局，最后有可能产生局部
- 查找名字的顺序：先局部，再全局，最后内置
作用：
- 分两种
全局作用域：全局存活，全局有效
局部作用域：临时存活，局部有效
强调：作用关系在函数定义阶段就已经固定，与调用位置无关
2，闭包函数
二 #闭包函数定义：定义在函数内部的函数，特点是：包含对外部作用域而不是对全局作用域名字的引用，该函数就称之为闭包函数
# x=1
# def outter():
# x=2
# def inner():
# print(x)
# return inner
#
#
# f=outter()
#
# def f1():
# x=1000000000
# f()
#
# f1()
from urllib.request import urlopen
#函数体内内部需要一个变量，有两种解决方案
#一种是：以参数的形式传入
def get(url):
return urlopen(url).read()
# get('http://www.baidu.com')
# get('http://www.baidu.com')
# get('http://www.baidu.com')
#另外一种：包起来
# def get(url): #url='http://www.baidu.com'
# # url='http://www.baidu.com'
# def inner():
# return urlopen(url).read()
# return inner
#
# baidu=get('http://www.baidu.com')
# print(baidu)
# res=baidu()
# baidu()
# baidu()
# baidu()
# baidu()
# def get(x,y):
# def inner():
# print(x,y)
# return inner
#
# baidu=get('a','b')
#
# print(baidu.__closure__[0].cell_contents)
# print(baidu.__closure__[1].cell_contents)
x,y=1,2
def get():
y=111111
def inner():
print(x,y)
return inner
baidu=get()
print(baidu.__closure__)
3，简单装饰器
'''
1、为什么要用装饰器：开放封闭原则，对扩展是开放的，对修改是封闭的
2、什么是装饰器
- 用来装饰它人，装饰器本身可以是任意可调用对象，被装饰器的对象也可以是任意可调用对象
- 遵循的原则：1、不修改被装饰对象的源代码 2、不修改被装饰对象的调用方式
- 目标是：在遵循原则1和2的前提，为被装饰器对象添加上新功能
'''
import time
def timmer(func):
# func=index #最原始的index函数的内存地址
def inner():
start_time=time.time()
func()
stop_time=time.time()
print('run time is :[%s]' %(stop_time-start_time))
return inner
@timmer #index=timmer(index)
def index():
time.sleep(3)
print('welcome to index page')
index()
三
4，装饰器修订
import time
from functools import wraps
def timmer(func):
@wraps(func)
def inner(*args,**kwargs):
start_time=time.time()
res=func(*args,**kwargs)
stop_time=time.time()
print('run time is :[%s]' %(stop_time-start_time))
return res
return inner
@timmer
def index():
'''
index function
:return:
'''
time.sleep(3)
print('welcome to index page')
return 123
@timmer #home=timmer(home) #home=inner
def home(name):
time.sleep(2)
print('welcome %s to home page' %name)
return 456
# res=index() # res=inner()
# print(res)
#
# res=home('egon') #inner('egon')
# print(res)
# print(index.__doc__)
print(help(index))
5，有参装饰器
# import time
# current_status={'user':None,'login_status':False}
#
#
# def auth(func):
# def inner(*args,**kwargs):
# if current_status['user'] and current_status['login_status']:
# res = func(*args, **kwargs)
# return res
# name=input('username>>:').strip()
# pwd=input('password>>:').strip()
# if name == 'egon' and pwd == '123':
# print('login successfull')
# current_status['user']=name
# current_status['login_status']=True
# res=func(*args,**kwargs)
# return res
# return inner
#
# @auth #index=auth(index)
# def index():
# time.sleep(3)
# print('welcome to index page')
# return 123
#
# @auth
# def home(name):
# time.sleep(2)
# print('welcome %s to home page' %name)
# return 456
# index()
# home('egon')
import time
current_status={'user':None,'login_status':False}
def auth(egine='file'):
# egine='file'
def wrapper(func):
def inner(*args,**kwargs):
if current_status['user'] and current_status['login_status']:
res = func(*args, **kwargs)
return res
if egine == 'file':
u='egon'
p='123'
elif egine == 'mysql':
print('mysql auth')
u = 'egon'
p = '123'
elif egine == 'ldap':
print('ldap auth')
else:
pass
name = input('username>>:').strip()
pwd = input('password>>:').strip()
if name == u and pwd == p:
print('login successfull')
current_status['user'] = name
current_status['login_status'] = True
res = func(*args, **kwargs)
return res
return inner
return wrapper
@auth(egine='ldap') #@wrapper #index=wrapper(index) #index=inner
def index():
time.sleep(3)
print('welcome to index page')
return 123
index() #inner()
6，加多个参装饰器
import time
current_status={'user':None,'login_status':False}
def timmer(func):
def inner(*args,**kwargs):
start_time=time.time()
res=func(*args,**kwargs)
stop_time=time.time()
print('run time is :[%s]' %(stop_time-start_time))
return res
return inner
def auth(egine='file'):
# egine='file'
def wrapper(func):
def inner(*args,**kwargs):
if current_status['user'] and current_status['login_status']:
res = func(*args, **kwargs)
return res
if egine == 'file':
u='egon'
p='123'
elif egine == 'mysql':
u = 'egon'
p = '123'
elif egine == 'ldap':
u = 'egon'
p = '123'
else:
pass
name = input('username>>:').strip()
pwd = input('password>>:').strip()
if name == u and pwd == p:
print('login successfull')
current_status['user'] = name
current_status['login_status'] = True
res = func(*args, **kwargs)
return res
return inner
return wrapper
@timmer
@auth(egine='ldap') #@wrapper #index=wrapper(timmer_inner)
# @timmer #timmer_inner=timmer(index)
def index():
time.sleep(3)
print('welcome to index page')
return 123
index() #inner()
迭代器
'''
1 什么叫迭代：迭代是一个重复过程，每次重复都是基于上一次的结果来的
2 为什么要用迭代器？
l=['a','b','c']
n=0
while n < len(l):
print(l[n])
n+=1
- 对于序列类型：字符串，列表，元组，可以使用基于索引的迭代取值方式，而对于没有索引的类型，如字典，
集合、文件，这种方式不再适用，于是我们必须找出一种能不依赖于索引的取值方式，这就是迭代器
3 可迭代的对象：只要对象内置有__iter__方法，obj.__iter__
4 迭代器对象：对象既内置有__iter__方法，又内置有__next__，如文件对象
注意：可迭代对象不一定是迭代器对象，而迭代器对象一定是可迭代的对象
'''
#可迭代的对象
# 'hello'.__iter__
# [1,2].__iter__
# (1,2).__iter__
# {'a':1}.__iter__
# {1,2,3}.__iter__
#
#既是可迭代对象，又是迭代器对象
# open('a.txt','w').__iter__
# open('a.txt','w').__next__
# 迭代器对象执行__iter__得到的仍然是它本身
# dic={'a':1,'b':2,'c':3}
# iter_dic=dic.__iter__()
#
# print(iter_dic.__iter__() is iter_dic)
# f=open('a.txt','w')
# print(f is f.__iter__())
#迭代器对象的用处
# dic={'a':1,'b':2,'c':3}
# iter_dic=dic.__iter__()
# print(iter_dic.__next__())
# print(next(iter_dic))
# print(next(iter_dic))
# print(next(iter_dic)) #StopIteration
# with open('a.txt','r') as f:
# print(next(f))
# print(next(f))
# print(next(f))
# l=[1,2,3,4,5]
# iter_l=l.__iter__()
# print(iter_l)
# print(next(iter_l))
# print(next(iter_l))
# print(next(iter_l))
#基于迭代器对象的迭代取值（不依赖索引）
dic={'a':1,'b':2,'c':3}
iter_dic=dic.__iter__()
obj=range(1000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000)
# list(obj)
# while True:
# try:
# i=next(iter_dic)
# print(i)
# except StopIteration:
# break
#
# for i in dic: #iter_dic=dic.__iter__()
# print(i)
'''
迭代器的优缺点：
- 优点：
提供了一种统一的迭代取值方式，该方式不再依赖于索引
更节省内存
- 缺点：
无法统计长度
一次性的，只能往后走，不能往前退，无法获取指定位置的值
'''
from collections import Iterable,Iterator
print(isinstance('hello',Iterable))
print(isinstance('hello',Iterator))
生成器
'''
定义：只要函数内部出现yield关键字，那么再调用该函数，将不会立即执行函数体代码，会到到一个结果
该结果就是生成器对象
'''
#
# def func():
# print('===>first')
# yield 1
# print('===>second')
# yield 2
# print('====>third')
# yield 3
#
#
# g=func()
# print(g)
#生成器本质就是迭代器
# print(next(g))
# print(next(g))
# print(next(g))
# print(next(g))
# print(next(func()))
# print(next(func()))
# print(next(func()))
# for i in g:
# print(i)
#
# for i in g:
# print(i)
#
# for i in g:
# print(i)
'''
yield的功能：
- 为我们提供了一种自定义迭代器的方式
- 对比return，可以返回多次值，挂起函数的运行状态
'''
#自定义功能，可以生成无穷多个值，因为同一时间在内存中只有一个值
# def my_range(start,stop,step=1):
# while start < stop:
# yield start
# start+=step
# g=my_range(1,5,2) #1 3
# print(next(g))
# print(next(g))
# print(next(g))
# print(next(g))
# print(next(g))
#
# for i in my_range(1,1000000000000000000000000000000000000000000,step=2):
# print(i)
# tail -f access.log | grep '404'
# import time
# def tail(filepath):
# with open(filepath,'rb') as f:
# f.seek(0,2)
# while True:
# line=f.readline()
# if line:
# yield line
# else:
# time.sleep(0.2)
#
# def grep(pattern,lines):
# for line in lines:
# line=line.decode('utf-8')
# if pattern in line:
# yield line
#
# g=grep('404',tail('access.log'))
# for line in g:
# print(line)
#yield的表达式形式的应用
# def eater(name):
# food_list=[]
# print('%s 开动啦' %name)
# while True:
# food=yield food_list #food=‘骨头’
# print('%s 开始吃 %s' %(name,food))
# food_list.append(food)
#
# g=eater('alex')
# g.send(None) #next(g)
# print(g.send('骨头'))
# print(g.send('shi'))
# def f1():
# while True:
# x=yield
# print(x)
#
# g=f1()
# next(g)
# g.send(1)
# g.send(1)
# g.close()
# g.send(1)
# g.send(1)
# g.send(1)
面向过程编程
'''
强调：面向过程编程绝对不是用函数编程那么简单
面向过程的编程思想：核心是过程二字，过程即解决问题的步骤，即先干什么再干什么
基于该思想去编写程序就好比在设计一条流水线，是一种机械式的编程思想
优点：复杂的问题流程化，进而简单化
缺点：可扩展性差
'''
# import os
# g=os.walk(r'C:UsersAdministratorPycharmProjects19期day4a')
# for dirname,_,files in g:
# for file in files:
# abs_file_path=r'%s\%s' %(dirname,file)
# print(abs_file_path)
#grep -rl 'root' /etc
import os
def init(func):
def inner(*args,**kwargs):
g=func(*args,**kwargs)
next(g)
return g
return inner
def search(filepath,target): #找到一个文件路径就往下个阶段传一次
g = os.walk(filepath)
for dirname, _, files in g:
for file in files:
abs_file_path = r'%s\%s' % (dirname, file)
target.send(abs_file_path)
@init
def opener(target):
while True:
abs_file_path=yield
with open(abs_file_path,'rb') as f:
target.send((f,abs_file_path))
@init
def cat(target):
while True:
f,abs_file_path=yield
for line in f:
res=target.send((line,abs_file_path))
if res:
break
@init
def grep(pattern,target):
tag=False
pattern = pattern.encode('utf-8')
while True:
line,abs_file_path=yield tag
tag=False
if pattern in line:
target.send(abs_file_path)
tag=True
@init
def printer():
while True:
abs_file_path=yield
print(abs_file_path)
search(r'C:UsersAdministratorPycharmProjects19期day4a',opener(cat(grep('你好',printer()))))
三元表达式
# name=input('>>: ')
# if name == 'alex':
# print('SB')
# else:
# print('NB')
# name = input('>>: ')
# print('SB' if name == 'alex' else 'NB')
def my_max(x,y):
return x if x > y else y
列表解析和生成器表达式
egg_list=[]
for i in range(10):
if i >= 3:
res='egg%s' %i
egg_list.append(res)
# print(egg_list)
#
#
# l=['egg%s' %i for i in range(10) if i >= 3]
# print(l)
#
# g=('egg%s' %i for i in range(10) if i >= 3)
# print(next(g))
# for i in ...:
# if ...:
# for i in ...:
# if ...:
# for ...
names=['egon','alex_sb','wupeiqi','yuanhao']
names=[name.upper() for name in names if not name.endswith('sb')]
print(names)
序列化
# user={'name':'egon','pwd':'123'}
# with open('db.txt','w',encoding='utf-8') as f:
# f.write(str(user))
# with open('db.txt','r',encoding='utf-8') as f:
# data=f.read()
# print(data)
import json
# user={'name':'egon','pwd':'123','age':18}
# with open('db.json','w',encoding='utf-8') as f:
# f.write(json.dumps(user))
# with open('db.json','r',encoding='utf-8') as f:
# data=f.read()
# dic=json.loads(data)
# print(dic['egon'])
user={'name':'egon','pwd':'123','age':18}
l=[1,2,3,'a']
json.dump(user,open('db1.json','w',encoding='utf-8'))
# dic=json.load(open('db1.json','r',encoding='utf-8'))
# print(dic,type(dic),dic['name'])