1、装饰器
2、生成器
3、迭代器
4、内置方法
5、可序列化
6、项目规范化
1、装饰器
# -*- coding:utf-8 -*- # Author:Wong Du ### 原代码 def home(): print("Welcome to home...") def shoe(): print("Welcome to shoe...") def clothes(): print("Welcome to clothes...") def gift(): print("Welcome to gift...") home() shoe() clothes() gift() #################需求:为程序的购物专区增加认证功能################# ### Part1:添加认证函数login(),加入到需要认证模块的函数当中 user = 'Wong' passwd = 'Wong123' def login(): count = 0 while count < 3: username = input('User login: ') password = input('Password: ') if username == user and password == passwd: print("Login successful...") break else: print("Invalid username or password...") count += 1 def home(): print("Welcome to home...") def shoe(): login() print("Welcome to shoe...") def clothes(): login() print("Welcome to clothes...") def gift(): login() print("Welcome to gift...") home() shoe() clothes() gift() #################需求:为程序的购物专区增加认证功能################# ### Part2:添加认证函数login(func),在login()中调用需要添加认证功能的函数 user = 'Wong' passwd = 'Wong123' def login(func): count = 0 while count < 3: username = input('User login: ') password = input('Password: ') if username == user and password == passwd: print("Login successful...") func() break else: print("Invalid username or password...") count += 1 def home(): print("Welcome to home...") def shoe(): print("Welcome to shoe...") def clothes(): print("Welcome to clothes...") def gift(): print("Welcome to gift...") home() # shoe() # clothes() # gift() login(shoe) login(clothes) login(gift) #################需求:为程序的购物专区增加认证功能################# ### Part3:添加认证函数login(func),函数赋值,再调用 user = 'Wong' passwd = 'Wong123' def login(func): count = 0 while count < 3: username = input('User login: ') password = input('Password: ') if username == user and password == passwd: print("Login successful...") func() break else: print("Invalid username or password...") count += 1 return login #高阶函数,返回login的内存地址 def home(): print("Welcome to home...") def shoe(): print("Welcome to shoe...") def clothes(): print("Welcome to clothes...") def gift(): print("Welcome to gift...") home() # shoe() # clothes() # gift() # shoe = login(shoe) # clothes = login(clothes) # gift = login(gift) # shoe() # clothes() # gift() #################需求:为程序的购物专区增加认证功能################# ### Part4:添加认证函数login(func),嵌套函数+高阶函数,函数赋值,再调用 user = 'Wong' passwd = 'Wong123' def login(func): def auth(): count = 0 while count < 3: username = input('User login: ') password = input('Password: ') if username == user and password == passwd: print("Login successful...") func() break else: print("Invalid username or password...") count += 1 return auth #高阶函数,返回login的内存地址 def home(): print("Welcome to home...") def shoe(): print("Welcome to shoe...") def clothes(name): print("%s,Welcome to clothes..." %name) def gift(): print("Welcome to gift...") home() shoe = login(shoe) clothes = login(clothes) gift = login(gift) shoe() clothes() gift() ### Part5:添加不固定参数,增加装饰器的可扩展性 user = 'Wong' passwd = 'Wong123' def login(func,*args,**kwargs): def auth(*args,**kwargs): count = 0 while count < 3: username = input('User login: ') password = input('Password: ') if username == user and password == passwd: print("Login successful...") func(*args,**kwargs) break else: print("Invalid username or password...") count += 1 return auth #高阶函数,返回login的内存地址 def home(): print("Welcome to home...") def shoe(): print("Welcome to shoe...") def clothes(name,*args,**kwargs): print("%s,Welcome to clothes..." %name) def gift(): print("Welcome to gift...") home() # shoe = login(shoe) clothes = login(clothes) # gift = login(gift) # shoe() clothes('Wong') # gift() ### Part6:函数赋值的方式看起来太low了,用装饰器专用调用方法 user = 'Wong' passwd = 'Wong123' def login(func,*args,**kwargs): def auth(*args,**kwargs): count = 0 while count < 3: username = input('User login: ') password = input('Password: ') if username == user and password == passwd: print("Login successful...") func(*args,**kwargs) break else: print("Invalid username or password...") count += 1 return auth #高阶函数,返回login的内存地址 def home(): print("Welcome to home...") @login #相当于shoe = login(shoe) def shoe(): print("Welcome to shoe...") @login #相当于shoe = login(clothes) def clothes(name,*args,**kwargs): print("%s,Welcome to clothes..." %name) @login #相当于shoe = login(gift) def gift(): print("Welcome to gift...") home() # shoe() clothes('Wong') # gift() ### Part7:为函数添加不同平台qq/wechat/weibo等认证功能 user = 'Wong' passwd = 'Wong123' def login(auth_type,*args,**kwargs): def auth(func,*args,**kwargs): def inner(*args,**kwargs): if auth_type == 'qq': count = 0 while count < 3: username = input('User login: ') password = input('Password: ') if username == user and password == passwd: print("Login successful...") func(*args,**kwargs) break else: print("Invalid username or password...") count += 1 else: print("Sorry,Only support qq login...") return inner #高阶函数,返回login的内存地址 return auth def home(): print("Welcome to home...") @login('qq') #相当于shoe = login(shoe) def shoe(): print("Welcome to shoe...") @login('weibo') #相当于shoe = login(clothes) def clothes(name,*args,**kwargs): print("%s,Welcome to clothes..." %name) @login('wechat') #相当于shoe = login(gift) def gift(): print("Welcome to gift...") home() shoe() clothes('Wong') gift()
2、生成器
# -*- coding:utf-8 -*- # Author:Wong Du ''' 生成器 generator 生成器最直观的效果就是节省内存 1.传统的列表等集合体是把所有元素存在内存里,当我们需要某个元素时,再从集合体里调用,此方式耗费内存,效率低下 2.生成器可以理解为是把一套计算方法和一个内存地址绑定在一起,这个内存地址里面没有生成元素,当我们需要某个元素时,再通过内存地址里面的算法一个一个生成元素 制造生成器: 1.g = (x*2 for x in range(10)) 2.用yield在函数中定义,把整个函数制造成一个生成器 特性: 生成器只能向后生成元素 生成器有两种调用方式 1. __next__方法 g.__next__() 2. for循环调用 for i in g: print(i) ''' ### 制造生成器和类型说明 g = (x*2 for x in range(10)) print(type(g)) print(g) ''' 输出: <class 'generator'> <generator object <genexpr> at 0x0000000000A2A938> ''' ### 生成器的调用特点 print(g.__next__()) print(next(g)) print("走走神。。。") print(next(g)) print(g.__next__()) print("发发呆。。。") for i in g: print(i) ### 函数生成器, ## 生成器的send方法可以给yield赋值 print('华丽分割线'.center(40,'*')) # def fib(max): #普通函数 # n,a,b = 0,0,1 # while max > n: # print(b) # a,b = b,a+b # n += 1 # return 'done' # print(type(fib)) def fib(max): #函数生成器 n,a,b = 0,0,1 while max > n: # print(b) yield b a,b = b,a+b n += 1 return 'done' print(type(fib(5))) for i in fib(5): print(i) ### 单线程并行效果 import time def foo(name): print("%s 要开始吃包子了" %name) while True: baozi = yield print("包子 %s 被 %s 吃了" %(baozi,name)) def war(): a1 = foo('A') a2 = foo('B') a1.__next__() a2.__next__() print("我要准备做包子啦...") for i in range(5): time.sleep(1) print("做了2个包子...") a1.send(i) a2.send(i) war()
3、迭代器
# -*- coding:utf-8 -*- # Author:Wong Du ''' 迭代器 定义:迭代器与生成器类似,属数据流对象 可以直接作用于for循环的对象统称为可迭代对象:Iterable,如list、dict、set、tuple、str等 可以被next()函数调用并不断返回下一个值的对象称为迭代器:Iterator,生成器是迭代器 判断方法: from collections import Iterator #导入Iterator模块 from collections import Iterable #导入Iterable模块 print(isinstance(g,Iterable)) #判断g是否是一个可迭代对象 print(isinstance(g,Iterator)) #判断g是否是一个迭代器 生成迭代器: iter()方法可以把可迭代对象编程一个迭代器 如: list = (1,2,3,4) list = iter(list) ''' ### 判断是否为迭代器或可迭代对象的方法 from collections import Iterator from collections import Iterable str = '111' print(isinstance(str,Iterable)) #True print(isinstance(str,Iterator)) #False list = [1,2,3] print(isinstance(list,Iterable)) #True print(isinstance(list,Iterator)) #False g = (i*2 for i in range(5)) print(isinstance(g,Iterable)) #True print(isinstance(g,Iterator)) #True ### 可迭代对象可通过iter()方法变成一个迭代器 tup = (1,2,3,4,5,4) print(type(tup)) #tuple tup = iter(tup) print(type(tup)) #tuple_iterator
4、内置方法
# -*- coding:utf-8 -*- # Author:Wong Du def dir_object(): ## 删除对象的属性方法 ## delattr(object, name: str) delattr('Wong', 'count') ## 判断对象是否有这个属性方法 ## hasattr(object, name: str) print(hasattr('Wong', 'count1')) ## 获取对象的属性方法,如存在可直接调用执行,如不存在则可配置default返回相关信息 ## getattr(object, name: str, default) print(getattr('Wong,ggg', 'count', '不存在')) ## 为对象添加属性方法 ## setattr(object, name: str, value) def Wong(name): # 定义函数对象 print("Welcome to", name) print("I am 23 years old") return 'done' setattr(Wong, 'author', 'Wongdu') # 增加'author'属性 print(hasattr(Wong, 'author')) # 验证 # 绝对值, # abs(n),Return the absolute value of the argument. print( abs(-22) ) # 判断可迭代对象内元素是否全为真 # all(Iterable) '''Return True if bool(x) is True for all values x in the iterable. If the iterable is empty, return True.''' print( all([1,2,3,0]) ) # 判断可迭代对象内元素是否有真 # any(Iterable) '''Return True if bool(x) is True for any x in the iterable. If the iterable is empty, return False.''' print( any([1,'0','']) ) # 把对象变成可打印的字符串形式,如存在中文字符,则用二进制表示;repr则所见即所得 # ascii(object);repr(object) print(ascii({'name':'wong','age':23,'您好':''})) print([repr([1,2,3,'22','您好'])]) # 把int对象转换成二进制 # bin(number:int) '''Return the binary representation of an integer.''' print( bin(256) ) # 判断对象是否可调用,如函数是可调用的 # callable(object) def calla():print("It is callable...") print( callable(calla) ) # 使用序号i返回一个字符的Unicode字符串 # chr(i) print(chr(1111)) # 打印给定对象的所有方法 # dir(object) print( dir([1,2,3]) ) # 返回一个元组,关系:((x-x%y)/y, x%y) # divmod(number,numbre) print( divmod(22.22,23) ) #退出程序 import time time.sleep(1) exit("退出程序") # 为集合体元素进行编号一一对应 dict = {'name':'Wong','age':23,'sox':'man'} print(dict) for k,v in enumerate(dict): print(k,v,dict[v]) # 在全局和本地语境中评估给定的源。 #eval() # 在全局和本地语境中执行给定的源。 #exec() # 格式化输出 print("My name is {_name}".format(_name="Wong")) # 过滤可迭代对象中的元素生成一个迭代器 s = filter(lambda x:x==1,range(10)) # print(s) for s1 in s: print(s1) # 对可迭代对象中的元素进行计算生成一个迭代器 g = map(lambda x:x*5,range(10)) print(g) for g1 in g: print(g1) # 返回包含当前作用域全局变量的字典 print(globals()) # 返回包含当前作用域局部变量的字典 print(locals()) # 没有参数时,返回当前作用域局部变量的字典,相当于locals() print(vars()) # 返回一个对象的哈希值 # hash(object) list = [] for i in ['1','666','2','3','45',33]: print(hash(i)) list.append(hash(i)) list.sort() print(list) # 查看帮助 # help(object) help(dict) # 返回int对象的16进制 # hex(int) print(hex(111)) # 判断对象是否属于哪个类型 # isinstance(object,union) print(isinstance('11',int)) from collections import Iterator,Iterable print(isinstance('asdfg',Iterable)) print(isinstance('asdfg',Iterator)) # 用户输入 # input() name = input("您的名字是:") print(name) # 返回对象的内存地址 # id(object) print(id('name')) # 把可迭代对象变成迭代器 # iter(iterable) list = [1,2,34,5] list = iter(list) print(list) # 计算集合体的长度 # len(list)等,可迭代对象? print(len({'name':"wong",'age':23})) # 版本作者等信息 copyright() credits() license() # 取可迭代对象中的最大值 # max(Iterable) print(max({'name':'wong','age':23})) # 取可迭代对象中的最小值 # min(Iterable) print(min({'name':'wong','age':23})) # 打开文件 # open(file,mode,encoding) f = open('test','r') f.close() # 返回int对象的八进制表示 # oct(int) print(oct(64)) # 通过单个字符,返回ascii表的对应编号 # ord(str) print(ord('@') # 打印内容 # print("你想表达的内容") print("打印") # 按如下公式计算 # Equivalent to x**y (with two arguments) or x**y % z (with three arguments) # pow(int, int, *int) print(pow(2,8,127)) # 退出程序,指定退出程序code # quit(code) count = 0 while True: print("你是风儿我是沙,缠缠绵绵走天涯...") if count >1000: quit(4) count += 1 # 反转集合体内元素并生成一个迭代器 # reversed(sequence) rev_iter = reversed([1,2,33,4]) print(rev_iter) for _i in rev_iter: print(_i) # 设置数字的精确位,会四舍五入算法 # round(number, ndigits=None) print(round(23.266655555,5)) # 排序可迭代对象内的元素 # sorted(Iterable) print(sorted([1,2,44,5,66,7])) # 求和 # sum(int) print(sum([1,2,3,44,5])) # 将多个可迭代对象的元素一一对应形成一个元组,生成一个迭代器,长度以最小元素的可迭代对象为准 # zip(Iterable1,Iterable2,Iterable3...) print(zip([1,2,3,55,6])) for iz in zip([1,2,3,55,6],{'name':'wong','age':23}): print(iz)
5、可序列化
# -*- coding:utf-8 -*- # Author:Wong Du ''' 序列化 序列化可将非字符串的数据类型的数据进行存档,如字典、列表甚至是函数等等 反序列化,将通过序列化保存的文件反序列化即可得到数据原本的样子,可直接使用 python中序列化的方式: json:只可序列化简单的数据类型,如字典、列表等,其他语言也有json,即json可跨语言进行序列和反序列化 pickle:python独有的序列化,可序列化一切数据,以二进制的形式保存 python中json和pickle的用法基本上是一模一样的 ''' dict = {'name':'wong','age':'23'} # with open('test','w') as f: # f.write(dict) ### 报错:TypeError: write() argument must be str, not dict ''' ### 把字典用json序列化后写入文件 ### json.dumps(obj); json.dump(obj, fp) ### f.write(json.dumps(dict)) == json.dump(dict,f) ''' import json with open('test','w') as f: # f.write(json.dumps(dict)) json.dump(dict,f) ### 成功写入 '''pickle序列化''' import pickle def foo(): print("In the foo...") foo() with open('test2','wb') as f: #以二进制字节类型写入到文件当中,所以mode = 'wb' # f.write(pickle.dumps(foo)) pickle.dump(foo,f) ### 写入成功!注意,这里的写入是把foo函数对象写入到文件当中,反序列化后,当代码里没有foo函数对象,则会报错 list = [1,2,3,4,'name'] with open('test3','wb') as f: # f.write(pickle.dumps(list)) pickle.dump(list,f)
# -*- coding:utf-8 -*- # Author:Wong Du ''' 序列化 序列化可将非字符串的数据类型的数据进行存档,如字典、列表甚至是函数等等 反序列化,将通过序列化保存的文件反序列化即可得到数据原本的样子,可直接使用 python中序列化的方式: json:只可序列化简单的数据类型,如字典、列表等,其他语言也有json,即json可跨语言进行序列和反序列化 pickle:python独有的序列化,可序列化一切数据,以二进制的形式保存 ''' # with open('test','r') as f: # print(f.read()) # f.read()['name'] ### 报错:TypeError: string indices must be integers ''' ### json反序列化读取文件内容,可直接获取到字典,进行元素调用 ### json.loads(str); line = json.load(fp) ### line = json.loads(f.read()) == line = json.load(f) ''' import json with open('test','r') as f: # line = json.loads(f.read()) line = json.load(f) print(type(line)) print(line['age']) ### 成功调用 ''' 输出: <class 'dict'> 23 ''' import pickle def foo(): print("In the foo2...") with open('test2','rb') as f: #以二进制字节类型读取文件内容,所以mode = 'rb' # line = pickle.loads(f.read()) line = pickle.load(f) line() with open('test3','rb') as f: # line = pickle.loads(f.read()) line = pickle.load(f) print(type(line)) print(line[4])
6、项目规范化
1 App/ 2 bin/ 3 app 4 conf 5 conf.py 6 app 7 test 8 __init__.py 9 main.py 10 main.py 11 __init__.py 12 setup.py 13 requirement.txt 14 readme/README