What are the practical operations of Python?
1)映射代理(不可变字典)
映射代理是创建后无法更改的字典。如果我们不希望用户能够更改我们的值,就可以使用它。
from types import MappingProxyType mp = MappingProxyType({'apple':4, 'orange':5}) print(mp) # {'apple': 4, 'orange': 5}
如果我们尝试更改映射代理中的内容,就会出现错误。
from types import MappingProxyType mp = MappingProxyType({'apple':4, 'orange':5}) print(mp) ''' Traceback (most recent call last): File "some/path/a.py", line 4, in <module> mp['apple'] = 10 ~~^^^^^^^^^ TypeError: 'mappingproxy' object does not support item assignment '''
2) dict 对于类和对象是不同的
class Dog: def __init__(self, name, age): self.name = name self.age = age rocky = Dog('rocky', 5) print(type(rocky.__dict__)) # <class 'dict'> print(rocky.__dict__) # {'name': 'rocky', 'age': 5} print(type(Dog.__dict__)) # <class 'mappingproxy'> print(Dog.__dict__) # {'__module__': '__main__', # '__init__': <function Dog.__init__ at 0x108f587c0>, # '__dict__': <attribute '__dict__' of 'Dog' objects>, # '__weakref__': <attribute '__weakref__' of 'Dog' objects>, # '__doc__': None}
对象的 dict 属性是普通字典,而类的 dict 属性是映射代理,它们本质上是不可变字典(无法更改)。
3) any() 和 all()
any([True, False, False]) # True any([False, False, False]) # False all([True, False, False]) # False all([True, True, True]) # True
any() 和 all() 函数都接受可迭代对象(例如列表)。
any() 如果至少有一个元素为 True,则返回 True。
all() 只有当所有元素都为 True 时才返回 True。
4) divmod()
内置的divmod()函数可以同时执行//和%运算符。
quotient, remainder = divmod(27, 10) print(quotient) # 2 print(remainder) # 7
这里,27 // 10 的值为2,而 27 % 10 的值为7。因此,返回元组2,7。
5) 使用格式化字符串轻松检查变量
name = 'rocky' age = 5 string = f'{name=} {age=}' print(string) # name='rocky' age=5
在格式化字符串中,我们可以在变量后面添加 = 以使用 var_name=var_value 的语法打印它。
6) 我们可以将浮点数转换为比率
print(float.as_integer_ratio(0.5)) # (1, 2) print(float.as_integer_ratio(0.25)) # (1, 4) print(float.as_integer_ratio(1.5)) # (3, 2)
内置的 float.as_integer_ratio() 函数允许我们将浮点数转换为表示分数的元组。但有时它会表现得很奇怪。
print(float.as_integer_ratio(0.1)) # (3602879701896397, 36028797018963968) print(float.as_integer_ratio(0.2)) # (3602879701896397, 18014398509481984)
7) 用globals()和locals()显示现有的全局/本地变量
x = 1 print(globals()) # {'__name__': '__main__', '__doc__': None, ..., 'x': 1}
内置的 globals() 函数返回一个包含所有全局变量及其值的字典。
def test(): x = 1 y = 2 print(locals()) test() # {'x': 1, 'y': 2}
内置函数 locals() 返回一个包含所有局部变量及其值的字典。
8) import() 函数
import numpy as np import pandas as pd
^ 导入模块的常规方式。
np = __import__('numpy') pd = __import__('pandas')
^ 这与上面的代码块执行相同的操作。
9) Python中的无限值
a = float('inf') b = float('-inf')
^ 我们可以定义正无穷和负无穷。 正无穷大于所有其他数字,而负无穷小于所有其他数字。
10) 我们可以使用 ‘pprint’ 来漂亮地打印东西
from pprint import pprint d = {"A":{"apple":1, "orange":2, "pear":3}, "B":{"apple":4, "orange":5, "pear":6}, "C":{"apple":7, "orange":8, "pear":9}} pprint(d)
11) 我们可以在Python中打印彩色输出
我们需要先安装colorama。
from colorama import Fore print(Fore.RED + "hello world") print(Fore.BLUE + "hello world") print(Fore.GREEN + "hello world")
12) 创建字典的更快方法
d1 = {'apple':'pie', 'orange':'juice', 'pear':'cake'}
^ 正常的方式
d2 = dict(apple='pie', orange='juice', pear='cake')
^更快的方法。这与上面的代码块完全相同,但我们输入较少的引号。
13) 我们可以在Python中取消打印的内容
CURSOR_UP = '\033[1A' CLEAR = '\x1b[2K' print('apple') print('orange') print('pear') print((CURSOR_UP + CLEAR)*2, end='') # this unprints 2 lines print('pineapple')
14) 对象中的私有变量并不是真正的私有
class Dog: def __init__(self, name): self.__name = name @property def name(self): return self.__name
这里,self.__name变量应该是私有的。我们不应该能够从类外部访问它。但实际上我们可以。
rocky = Dog('rocky') print(rocky.__dict__) # {'_Dog__name': 'rocky'}
我们可以使用 dict 属性来访问或编辑这些属性。
15) 我们可以使用’type()'创建类
classname = type(name, bases, dict)
name 是一个字符串,代表类的名称
bases 是包含类父类的元组
dict 是包含属性和方法的字典
class Dog: def __init__(self, name, age): self.name = name self.age = age def bark(self): print(f'Dog({self.name}, {self.age})')
^ 以正常方式创建一个 Dog 类
def __init__(self, name, age): self.name = name self.age = age def bark(self): print(f'Dog({self.name}, {self.age})') Dog = type('Dog', (), {'__init__':__init__, 'bark':bark})
^ 使用 type() 创建与上面完全相同的 Dog 类
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