Analyze examples of four main data types in Python

Basic data types

Numeric type

The data in Python are all objects, such as the well-known int integer object, float double precision floating point type, bool logical object, they are all is a single element. Give two examples.

Prefix with 0x to create a hexadecimal integer:

0xa5 # 等于十进制的 165

Use e to create a floating point number represented in scientific notation:

1.05e3 # 1050.0

Container type

A container object that can accommodate multiple elements. Commonly used ones include: list list object, tuple tuple object, dict dictionary object, and set collection object. Python defines these types of variables with a very concise syntax.

Examples are as follows.

Use a pair of square brackets [] to create a list variable:

lst = [1,3,5] # list 变量

As can be seen from the diagram, the container on the right is open-loop, which means that the container can Adding and deleting elements in:

Use a pair of brackets () to create a tuple object:

tup = (1,3,5) # tuple 变量

As shown in the diagram , the container on the right is closed, which means that once a tuple is created, elements cannot be added or deleted from the container:

But it should be noted that tuples containing a single element A comma must be left behind to be interpreted as a tuple.

tup = (1,) # 必须保留逗号

Otherwise it will be considered the element itself:

In [14]: tup=(1)
   ...: print(type(tup)) 
<class &#39;int&#39;>

Use a pair of curly braces {} and use a colon : to create a dict object:

dic = {'a':1, 'b':3, 'c':5} # dict变量

The dictionary is a hash table. The following diagram vividly expresses the "shape" of the dictionary.

Use only a pair of curly braces {} to create a set object:

s = {1,3,5} # 集合变量

Python container type, list, dict , tuple, set, etc. can easily implement powerful functions. Here are a few cases.

1. Find the average

After removing a minimum value and a maximum value in the list, calculate the average of the remaining elements.

def score_mean(lst):
   lst.sort()
   lst2=lst[1:-1]
   return round((sum(lst2)/len(lst2)),1)

lst=[9.1, 9.0,8.1, 9.7, 19,8.2, 8.6,9.8]
score_mean(lst) # 9.1

Code execution process, animation demonstration:

2. Print 99 multiplication table

Print out the following The multiplication table in the format:

1*1=1
1*2=2   2*2=4
1*3=3   2*3=6   3*3=9
1*4=4   2*4=8   3*4=12  4*4=16
1*5=5   2*5=10  3*5=15  4*5=20  5*5=25
1*6=6   2*6=12  3*6=18  4*6=24  5*6=30  6*6=36
1*7=7   2*7=14  3*7=21  4*7=28  5*7=35  6*7=42  7*7=49
1*8=8   2*8=16  3*8=24  4*8=32  5*8=40  6*8=48  7*8=56  8*8=64
1*9=9   2*9=18  3*9=27  4*9=36  5*9=45  6*9=54  7*9=63  8*9=72  9*9=81

has 10 rows in total. The j-th column of the i-th row is equal to: j*i, where:

• i Value range: 1<=i<=9

• j Value range: 1<=j<=i

According to the language description of "example analysis", it is converted into the following code:

In [13]: for i in range(1,10):
   ...:     for j in range(1,i+1):
   ...:         print('%d*%d=%d'%(j,i,j*i),end='\t')
   ...:     print()

3. Sample sampling

Use sample sampling , the following example randomly samples 10 samples from 100.

from random import randint,sample
lst = [randint(0,50) for _ in range(100)]
print(lst[:5])# [38, 19, 11, 3, 6]
lst_sample = sample(lst,10)
print(lst_sample) # [33, 40, 35, 49, 24, 15, 48, 29, 37, 24]

String

Note that there is no character type (char) like C in Python, and all characters or strings are unified into str objects. For example, the type of a single character c is also str.

The str type will be frequently used. Let’s first list 5 frequently used methods.

strip is used to remove spaces before and after a string:

In [1]: '  I love python\t\n  '.strip()
Out[1]: 'I love python'

replace is used to replace strings:

In [2]: 'i love python'.replace(' ','_')
Out[2]: 'i_love_python'

join is used to merge strings:

In [3]: '_'.join(['book', 'store','count'])
Out[3]: 'book_store_count'

title is used to capitalize the first character of a word:

In [4]: 'i love python'.title()
Out[4]: 'I Love Python'

find is used to return the starting position index of the matching string:

In [5]: 'i love python'.find('python')
Out[5]: 7

As an example of applying strings, determine whether str1 is composed of str2 is rotated.

String stringbook is rotated to obtain bookstring. Write a code to verify whether str1 is str2 obtained by rotation.

Convert to judgment: whether str1 is a substring of str2 str2.

下面函数原型中，注明了每个参数的类型、返回值的类型，增强代码的可读性和可维护性。

def is_rotation(s1: str, s2: str) -> bool:
   if s1 is None or s2 is None:
       return False
   if len(s1) != len(s2):
       return False

   def is_substring(s1: str, s2: str) -> bool:
       return s1 in s2
   return is_substring(s1, s2 + s2)

测试函数 is_rotation：

r = is_rotation('stringbook', 'bookstring')
print(r)  # True

r = is_rotation('greatman', 'maneatgr')
print(r)  # False

代码执行过程，动画演示：

55555

字符串的匹配操作除了使用 str 封装的方法外，Python 的 re 正则模块功能更加强大，写法更为简便，广泛适用于爬虫、数据分析等。

下面这个案例实现：密码安全检查，使用正则表达式非常容易实现。

密码安全要求：

• 要求密码为 6 到 20 位；

• 密码只包含英文字母和数字。

import re
pat = re.compile(r'\w{6,20}') # 这是错误的，因为 \w 通配符匹配的是字母，数字和下划线，题目要求不能含有下划线
# 使用最稳的方法：\da-zA-Z 满足“密码只包含英文字母和数字”
# \d匹配数字 0-9
# a-z 匹配所有小写字符；A-Z 匹配所有大写字符
pat = re.compile(r'[\da-zA-Z]{6,20}')

选用最保险的 fullmatch 方法，查看是否整个字符串都匹配。

以下测试例子都返回 None，原因都在解释里。

pat.fullmatch('qaz12') # 返回 None，长度小于 6
pat.fullmatch('qaz12wsxedcrfvtgb67890942234343434') # None 长度大于 22
pat.fullmatch('qaz_231') # None 含有下划线

下面这个字符串 n0passw0Rd 完全符合：

In [20]: pat.fullmatch('n0passw0Rd')
Out[20]: <re.Match object; span=(0, 10), match=&#39;n0passw0Rd&#39;>

自定义类型

Python 使用关键字 class 定制自己的类，self 表示类实例对象本身。

一个自定义类内包括属性、方法，其中有些方法是自带的。

类（对象）：

class Dog(object):
   pass

以上定义一个 Dog 对象，它继承于根类 object，pass 表示没有自定义任何属性和方法。

下面创建一个 Dog 类型的实例：

wangwang = Dog()

Dog 类现在没有定义任何方法，但是刚才说了，它会有自带的方法，使用 dir() 查看这些自带方法：

In [26]: wangwang.__dir__()
Out[26]:
['__module__',
'__dict__',
'__weakref__',
'__doc__',
'__repr__',
'__hash__',
'__str__',
'__getattribute__',
'__setattr__',
'__delattr__',
'__lt__',
'__le__',
'__eq__',
'__ne__',
'__gt__',
'__ge__',
'__init__',
'__new__',
'__reduce_ex__',
'__reduce__',
'__subclasshook__',
'__init_subclass__',
'__format__',
'__sizeof__',
'__dir__',
'__class__']

有些地方称以上方法为魔法方法，它们与创建类时自定义个性化行为有关。比如：

• init 方法能定义一个带参数的类；

• new 方法自定义实例化类的行为；

• getattribute 方法自定义读取属性的行为；

• setattr 自定义赋值与修改属性时的行为。

类的属性：

def __init__(self, name, dtype):
    self.name = name
    self.dtype = dtype

通过 init，定义 Dog 对象的两个属性：name、dtype。

类的实例：

wangwang = Dog('wangwang','cute_type')

wangwang 是 Dog 类的实例。

类的方法：

def shout(self):
   print('I\'m %s, type: %s' % (self.name, self.dtype))

注意：

• 自定义方法的第一个参数必须是 self，它指向实例本身，如 Dog 类型的实例 dog；

• 引用属性时，必须前面添加 self，比如 self.name 等。

总结以上代码：

In [40]: class Dog(object):
   ...:     def __init__(self,name,dtype):
   ...:         self.name=name
   ...:         self.dtype=dtype
   ...:     def shout(self):
   ...:         print('I\'m %s, type: %s' % (self.name, self.dtype))

In [41]: wangwang = Dog('wangwang','cute_type')

In [42]: wangwang.name
Out[42]: 'wangwang'

In [43]: wangwang.dtype
Out[43]: 'cute_type'

In [44]: wangwang.shout()
I'm wangwang, type: cute_type

看到创建的两个属性和一个方法都被暴露在外面，可被 wangwang 调用。这样的话，这些属性就会被任意修改：

In [49]: wangwang.name='wrong_name'
   
In [50]: wangwang.name
Out[50]: 'wrong_name'

如果想避免属性 name 被修改，可以将它变为私有变量。改动方法：属性前加 2 个 _ 后，变为私有属性。如：

In [51]: class Dog(object):
   ...:     def __init__(self,name,dtype):
   ...:         self.__name=name
   ...:         self.__dtype=dtype
   ...:     def shout(self):
   ...:         print('I\'m %s, type: %s' % (self.name, self.dtype))

同理，方法前加 2 个 _ 后，方法变为“私有方法”，只能在 Dog 类内被共享使用。

但是这样改动后，属性 name 不能被访问了，也就无法得知 wangwang 的名字叫啥。不过，这个问题有一种简单的解决方法，直接新定义一个方法就行：

def get_name(self):
   return self.__name

综合代码：

In [52]: class Dog(object):
   ...:     def __init__(self,name,dtype):
   ...:         self.__name=name
   ...:         self.__dtype=dtype
   ...:     def shout(self):
   ...:         print('I\'m %s, type: %s' % (self.name, self.dtype))
   ...:     def get_name(self):
   ...:         return self.__name
   ...:

In [53]: wangwang = Dog('wangwang','cute_type')

In [54]: wangwang.get_name()
Out[54]: 'wangwang'

但是，通过此机制，改变属性的可读性或可写性，怎么看都不太优雅！因为无形中增加一些冗余的方法，如 get_name。

下面，通过另一个例子，解释如何更优雅地改变某个属性为只读或只写。

自定义一个最精简的 Book 类，它继承于系统的根类 object：

class Book(object):
   def __init__(self,name,sale):
       self.__name = name
       self.__sale = sale

使用 Python 自带的 property 类，就会优雅地将 name 变为只读的。

   @property
   def name(self):
       return self.__name

使用 @property 装饰后 name 变为属性，意味着 .name 就会返回这本书的名字，而不是通过 .name() 这种函数调用的方法。这样变为真正的属性后，可读性更好。

In [101]: class Book(object):
    ...:     def __init__(self,name,sale):
    ...:         self.__name = name
    ...:         self.__sale = sale
    ...:     @property
    ...:     def name(self):
    ...:         return self.__name

In [102]: a_book = Book('magic_book',100000)

In [103]: a_book.name
Out[103]: 'magic_book'

property 是 Python 自带的类，前三个参数都是函数类型。更加详细的讨论放在后面讨论装饰器时再展开。

In [104]: help(property)
Help on class property in module builtins:

class property(object)
|  property(fget=None, fset=None, fdel=None, doc=None)

如果使 name 既可读又可写，就再增加一个装饰器 @name.setter。

In [105]: class Book(object):
    ...:     def __init__(self,name,sale):
    ...:         self.__name = name
    ...:         self.__sale = sale
    ...:     @property
    ...:     def name(self):
    ...:         return self.__name
    ...:     @name.setter
    ...:     def name(self,new_name):
    ...:         self.__name = new_name

In [106]: a_book = Book('magic_book',100000)

In [107]: a_book.name = 'magic_book_2.0'

In [108]: a_book.name
Out[108]: 'magic_book_2.0'

注意这种装饰器写法：name.setter，name 已经被包装为 property 实例，调用实例上的 setter 函数再包装 name 后就会可写。对于 Python 入门者，可以暂时不用太纠结这部分理论，使用 Python 一段时间后，再回过头来自然就会理解。

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