Pythonic与Python杂记

一、用字典映射代替switch case语句

    1、switch case语句：        

switch (day){ case 0: dayName = "Sunday"; ... ... break; case 1: dayName = "Monday"; ... ... break; case 2: dayName = "Tuesday"; ... ... break; ... default: dayName = "Unknow"; ... ... break; }

    2、字典映射示例一：    

switcher = { 0: "Sunday", 1: "Monday", 2: "Tuesday" } day = 0 day_name = switcher.get(day, "Unknow") print(day_name) 运行结果： Sunday day = 1 day_name = switcher.get(day, "Unknow") print(day_name) 运行结果： Monday day = 2 day_name = switcher.get(day, "Unknow") print(day_name) 运行结果： Tuesday day = 3 day_name = switcher.get(day, "Unknow") print(day_name) 运行结果： Unknow

    3、字典映射示例二：        

def getSunday(): return "Sunday" def getMonday(): return "Monday" def getTuesday(): return "Tuesday" def getDefault(): return "Unknow" switcher = { 0: getSunday, 1: getMonday, 2: getTuesday } day = 0 day_name = switcher.get(day, getDefault)() print(day_name) 运行结果： Sunday day = 1 day_name = switcher.get(day, getDefault)() print(day_name) 运行法结果： Monday day = 2 day_name = switcher.get(day, getDefault)() print(day_name) 运行结果： Tuesday day = 3 day_name = switcher.get(day, getDefault)() print(day_name) 运行结果： Unknow

二、列表推导式

    1、示例一：    

a = [1, 2, 3, 4, 5, 6, 7, 8] list = [i*i for i in a] print(list) 运行结果： [1, 4, 9, 16, 25, 36, 49, 64]

    2、示例二：    

a = [1, 2, 3, 4, 5, 6, 7, 8] list = [i**2 for i in a] print(list) 运行结果： [1, 4, 9, 16, 25, 36, 49, 64]

    3、示例三：

a = [1, 2, 3, 4, 5, 6, 7, 8] list = [i**3 for i in a] print(list) 运行结果： [1, 8, 27, 64, 125, 216, 343, 512]

    4、示例四：    

a = [1, 2, 3, 4, 5, 6, 7, 8] list = [i**2 for i in a if i > 5] print(list) 运行结果： [36, 49, 64]

    5、示例五：       

a = {1, 2, 3, 4, 5, 6, 7, 8} list = {i**2 for i in a if i > 5} print(list) 运行结果： {64, 49, 36}

    6、示例六：    

a = (1, 2, 3, 4, 5, 6, 7, 8) list = (i**2 for i in a if i > 5) print(type(list)) 运行结果： <class 'generator'> for item in list: print(item) 运行结果： 36 49 64

三、字典如何编写推导式

    1、示例一：

students = { "喜小乐": 18, "石敢当": 20, "孙悟空": 15 } list = [key for key, value in students.items()] print(list) 运行结果： ['喜小乐', '石敢当', '孙悟空']

    2、示例二：    

students = { "喜小乐": 18, "石敢当": 20, "孙悟空": 15 } list = [value for key, value in students.items()] print(list) 运行结果： [18, 20, 15]

    3、示例三：

students = { "喜小乐": 18, "石敢当": 20, "孙悟空": 15 } list = {key: value for key, value in students.items()} print(list) 运行结果： {'喜小乐': 18, '石敢当': 20, '孙悟空': 15}

四、iterator(迭代器)与generator(发生器)

    1、iterator:

        (1) 定义：

            a、迭代器是一个可以记住遍历的位置的对象；

            b、迭代器对象从集合的第一个元素开始访问，直到所有的元素被访问完结束。迭代器只能往前不能后退；

            c、迭代器有两个基本方法：iter() 和 next()。

        (2) 示例一：       

class BookCollection: def __init__(self): self.data = ["往事", "回味", "朝花夕拾"] self.cur = 0 def __iter__(self): return self def __next__(self): if self.cur >= len(self.data): raise StopIteration r = self.data[self.cur] self.cur += 1 return r books = BookCollection() for book in books: print(book) 运行结果： 往事 回味 朝花夕拾

        (3) 示例二：可以使用next()函数     

import sys class BookCollection: def __init__(self): self.data = ["往事", "回味", "朝花夕拾"] self.cur = 0 def __iter__(self): return self def __next__(self): if self.cur >= len(self.data): raise StopIteration r = self.data[self.cur] self.cur += 1 return r books = BookCollection() while True: try: print(next(books)) except StopIteration: sys.exit() 运行结果： 往事 回味 朝花夕拾

        (4) 示例三：（第二次遍历迭代器的时候不会打印值，如需多次遍历解决方案：1、实例化一个新的对象；2、使用对象拷贝的方式）

示例一： class BookCollection: def __init__(self): self.data = ["往事", "回味", "朝花夕拾"] self.cur = 0 def __iter__(self): return self def __next__(self): if self.cur >= len(self.data): raise StopIteration r = self.data[self.cur] self.cur += 1 return r books = BookCollection() for book in books: print(book) for book in books: print(book) 运行结果： 往事 回味 朝花夕拾 示例二： import sys class BookCollection: def __init__(self): self.data = ["往事", "回味", "朝花夕拾"] self.cur = 0 def __iter__(self): return self def __next__(self): if self.cur >= len(self.data): raise StopIteration r = self.data[self.cur] self.cur += 1 return r books = BookCollection() while True: try: print(next(books)) except StopIteration: sys.exit() while True: try: print(next(books)) except StopIteration: sys.exit() 运行结果： 往事 回味 朝花夕拾 示例三： import sys class BookCollection: def __init__(self): self.data = ["往事", "回味", "朝花夕拾"] self.cur = 0 def __iter__(self): return self def __next__(self): if self.cur >= len(self.data): raise StopIteration r = self.data[self.cur] self.cur += 1 return r books = BookCollection() for book in books: print(book) while True: try: print(next(books)) except StopIteration: sys.exit() 运行结果： 往事 回味 朝花夕拾 示例四：(新实例化一个对象) import sys class BookCollection: def __init__(self): self.data = ["往事", "回味", "朝花夕拾"] self.cur = 0 def __iter__(self): return self def __next__(self): if self.cur >= len(self.data): raise StopIteration r = self.data[self.cur] self.cur += 1 return r books = BookCollection() books_two = BookCollection() for book in books: print(book) 运行结果： 往事 回味 朝花夕拾 while True: try: print(next(books_two)) except StopIteration: sys.exit() 运行结果： 往事 回味 朝花夕拾 示例五：(对象拷贝) import sys class BookCollection: def __init__(self): self.data = ["往事", "回味", "朝花夕拾"] self.cur = 0 def __iter__(self): return self def __next__(self): if self.cur >= len(self.data): raise StopIteration r = self.data[self.cur] self.cur += 1 return r books = BookCollection() import copy books_two = copy.copy(books) for book in books: print(book) 运行结果： 往事 回味 朝花夕拾 while True: try: print(next(books_two)) except StopIteration: sys.exit() 运行结果： 往事 回味 朝花夕拾

    2、generator:

        (1) 在python中，使用yield的函数被称为生成器；

        (2) 生成器是一个返回迭代器的函数，只能用于迭代器操作，更简单点理解生成器就是一个迭代器；

        (3) 在调用生成器的过程中，每次遇到yield时函数会暂停并保存当前所有的运行信息，返回yield的值，并在下一次执行next()方法时从当前位置继续运行；

        (4) 调用一个生成器函数，返回的是一个迭代器对象。

        (5) 示例一：            

import sys def feibonacci(n): # 生成器函数 - 斐波那契 a, b, counter = 0, 1, 0 while True: if counter > n: return yield a a, b = b, a + b counter += 1 f = feibonacci(10) while True: try: print(next(f), end=" ") except StopIteration: sys.exit() 运行结果： 0 1 1 2 3 5 8 13 21 34 55

        (6) 示例二：    

def feibonacci(n): # 生成器函数 - 斐波那契 a, b, counter = 0, 1, 0 while True: if counter > n: return yield a a, b = b, a + b counter += 1 f = feibonacci(10) for i in f: print(i) 运行结果： 0 1 1 2 3 5 8 13 21 34 55

五、None

    1、""、[]、{}、()不等于None:

a = "" b = [] c = {} d = () print(a == None) print(b == None) print(c == None) print(d == None) 运行结果： False False False False print(a is None) print(b is None) print(c is None) print(d is None) 运行结果： False False False False print(type(None)) 运行结果： <class 'NoneType'>

    2、示例一：    

def fun(): return None a = fun() if not a: print("S") else: print("F") if a is None: print("S") else: print("F") 运行结果： S S

    3、判断不为空操作建议的两种方式：(1) if a:  ；(2) if not a: 。

六、对象存在并不一定是True

    1、示例一：

class Test(): pass test = Test() print(bool(test)) 运行结果： True

    2、示例二：    

class Test(): def __len__(self): return 0 test = Test() print(bool(test)) 运行结果： False

七、__len__与__bool__内置方法

    1、示例一：        

class Test(): def __len__(self): print("len called") return True test = Test() print(bool(test)) 运行结果： len called True

    2、示例二：    

class Test(): def __bool__(self): print("boll called") return False def __len__(self): print("len called") return True test = Test() print(bool(test)) 运行结果： boll called False

八、装饰器的副作用

    1、 示例一：打印函数名

# 不带装饰器 from datetime import datetime def decorator(func): def wrapper(): print(datetime.now()) func() return wrapper def f1(): print(f1.__name__) f1() 运行结果： f1 # 带装饰器 from datetime import datetime def decorator(func): def wrapper(): print(datetime.now()) func() return wrapper @decorator def f1(): print(f1.__name__) f1() 运行结果： 2019-10-02 23:17:15.278430 wrapper

    2、示例二：打印help函数    

# 不带装饰器 from datetime import datetime def decorator(func): def wrapper(): print(datetime.now()) func() return wrapper def f1(): """ This is f1 :return: """ print(f1.__name__) print(help(f1)) 运行结果： Help on function f1 in module __main__: f1() This is f1 :return: None # 带装饰器 from datetime import datetime def decorator(func): def wrapper(): print(datetime.now()) func() return wrapper @decorator def f1(): """ This is f1 :return: """ print(f1.__name__) print(help(f1)) 运行结果： Help on function wrapper in module __main__: wrapper() None

    3、解决方案：使用wraps装饰器

from datetime import datetime from functools import wraps def decorator(func): @wraps(func) def wrapper(): print(datetime.now()) func() return wrapper @decorator def f1(): """ This is f1 :return: """ print(f1.__name__) print(help(f1)) 运行结果： Help on function f1 in module __main__: f1() This is f1 :return: None