Python3 元组

Python 的元组与列表类似，不同之处在于元组的元素不能修改。

元组使用小括号，列表使用方括号。

元组创建很简单，只需要在括号中添加元素，并使用逗号隔开即可。

不可变的tuple有什么意义？因为tuple不可变，所以代码更安全。如果可能，能用tuple代替list就尽量用tuple。

定义：与列表类似，只不过［］改成（）特性：

1.可存放多个值2.不可变3.按照从左到右的顺序定义元组元素，下标从0开始顺序访问，有序

基本操作：

• 索引
• 切片
• 循环
• 长度
• 包含

lass tuple(object):
    """
    tuple() -> empty tuple
    tuple(iterable) -> tuple initialized from iterable‘s items

    If the argument is a tuple, the return value is the same object.
    """
    def count(self, value): # real signature unknown; restored from __doc__
        """ T.count(value) -> integer -- return number of occurrences of value """
        return 0

    def index(self, value, start=None, stop=None): # real signature unknown; restored from __doc__
        """
        T.index(value, [start, [stop]]) -> integer -- return first index of value.
        Raises ValueError if the value is not present.
        """
        return 0

    def __add__(self, y): # real signature unknown; restored from __doc__
        """ x.__add__(y) <==> x+y """
        pass

    def __contains__(self, y): # real signature unknown; restored from __doc__
        """ x.__contains__(y) <==> y in x """
        pass

    def __eq__(self, y): # real signature unknown; restored from __doc__
        """ x.__eq__(y) <==> x==y """
        pass

    def __getattribute__(self, name): # real signature unknown; restored from __doc__
        """ x.__getattribute__(‘name‘) <==> x.name """
        pass

    def __getitem__(self, y): # real signature unknown; restored from __doc__
        """ x.__getitem__(y) <==> x[y] """
        pass

    def __getnewargs__(self, *args, **kwargs): # real signature unknown
        pass

    def __getslice__(self, i, j): # real signature unknown; restored from __doc__
        """
        x.__getslice__(i, j) <==> x[i:j]

                   Use of negative indices is not supported.
        """
        pass

    def __ge__(self, y): # real signature unknown; restored from __doc__
        """ x.__ge__(y) <==> x>=y """
        pass

    def __gt__(self, y): # real signature unknown; restored from __doc__
        """ x.__gt__(y) <==> x>y """
        pass

    def __hash__(self): # real signature unknown; restored from __doc__
        """ x.__hash__() <==> hash(x) """
        pass

    def __init__(self, seq=()): # known special case of tuple.__init__
        """
        tuple() -> empty tuple
        tuple(iterable) -> tuple initialized from iterable‘s items

        If the argument is a tuple, the return value is the same object.
        # (copied from class doc)
        """
        pass

    def __iter__(self): # real signature unknown; restored from __doc__
        """ x.__iter__() <==> iter(x) """
        pass

    def __len__(self): # real signature unknown; restored from __doc__
        """ x.__len__() <==> len(x) """
        pass

    def __le__(self, y): # real signature unknown; restored from __doc__
        """ x.__le__(y) <==> x<=y """
        pass

    def __lt__(self, y): # real signature unknown; restored from __doc__
        """ x.__lt__(y) <==> x<y """
        pass

    def __mul__(self, n): # real signature unknown; restored from __doc__
        """ x.__mul__(n) <==> x*n """
        pass

    @staticmethod # known case of __new__
    def __new__(S, *more): # real signature unknown; restored from __doc__
        """ T.__new__(S, ...) -> a new object with type S, a subtype of T """
        pass

    def __ne__(self, y): # real signature unknown; restored from __doc__
        """ x.__ne__(y) <==> x!=y """
        pass

    def __repr__(self): # real signature unknown; restored from __doc__
        """ x.__repr__() <==> repr(x) """
        pass

    def __rmul__(self, n): # real signature unknown; restored from __doc__
        """ x.__rmul__(n) <==> n*x """
        pass

    def __sizeof__(self): # real signature unknown; restored from __doc__
        """ T.__sizeof__() -- size of T in memory, in bytes """
        pass

tuple

如下实例：

tup1 = (‘Google‘, ‘Runoob‘, 1997, 2000);
tup2 = (1, 2, 3, 4, 5 );
tup3 = "a", "b", "c", "d";

创建空元组

tup1 = ();

元组中只包含一个元素时，需要在元素后面添加逗号

tup1 = (50,);

元组与字符串类似，下标索引从0开始，可以进行截取，组合等。

访问元组

元组可以使用下标索引来访问元组中的值，如下实例:

#!/usr/bin/python3

tup1 = (‘Google‘, ‘Runoob‘, 1997, 2000)
tup2 = (1, 2, 3, 4, 5, 6, 7 )

print ("tup1[0]: ", tup1[0])
print ("tup2[1:5]: ", tup2[1:5])

以上实例输出结果：

tup1[0]:  Google
tup2[1:5]:  (2, 3, 4, 5)

修改元组

元组中的元素值是不允许修改的，但我们可以对元组进行连接组合，如下实例:

#!/usr/bin/python3

tup1 = (12, 34.56);
tup2 = (‘abc‘, ‘xyz‘)

# 以下修改元组元素操作是非法的。
# tup1[0] = 100

# 创建一个新的元组
tup3 = tup1 + tup2;
print (tup3)

以上实例输出结果：

(12, 34.56, ‘abc‘, ‘xyz‘)

删除元组

元组中的元素值是不允许删除的，但我们可以使用del语句来删除整个元组，如下实例:

#!/usr/bin/python3

tup = (‘Google‘, ‘Runoob‘, 1997, 2000)

print (tup)
del tup;
print ("删除后的元组 tup : ")
print (tup)

以上实例元组被删除后，输出变量会有异常信息，输出如下所示：

删除后的元组 tup :
Traceback (most recent call last):
  File "test.py", line 8, in <module>
    print (tup)
NameError: name ‘tup‘ is not defined

元组运算符

与字符串一样，元组之间可以使用 + 号和 * 号进行运算。这就意味着他们可以组合和复制，运算后会生成一个新的元组。

元组索引，截取

因为元组也是一个序列，所以我们可以访问元组中的指定位置的元素，也可以截取索引中的一段元素，如下所示：

元组：

L = (‘Google‘, ‘Taobao‘, ‘Runoob‘)

Python 表达式

运行实例如下：

>>> L = (‘Google‘, ‘Taobao‘, ‘Runoob‘)
>>> L[2]
‘Runoob‘
>>> L[-2]
‘Taobao‘
>>> L[1:]
(‘Taobao‘, ‘Runoob‘)

元组内置函数

Python元组包含了以下内置函数

>>> tuple1 = (‘Google‘, ‘Runoob‘, ‘Taobao‘)
>>> len(tuple1)
3
>>>

>>> tuple2 = (‘5‘, ‘4‘, ‘8‘)
>>> max(tuple2)
‘8‘
>>>

>>> tuple2 = (‘5‘, ‘4‘, ‘8‘)
>>> min(tuple2)
‘4‘
>>>

>>> list1= [‘Google‘, ‘Taobao‘, ‘Runoob‘, ‘Baidu‘]
>>> tuple1=tuple(list1)
>>> tuple1
(‘Google‘, ‘Taobao‘, ‘Runoob‘, ‘Baidu‘)

Python在显示只有1个元素的tuple时，也会加一个逗号,，以免你误解成数学计算意义上的括号。

最后来看一个“可变的”tuple：

>>> t = (‘a‘, ‘b‘, [‘A‘, ‘B‘])
>>> t[2][0] = ‘X‘
>>> t[2][1] = ‘Y‘
>>> t
(‘a‘, ‘b‘, [‘X‘, ‘Y‘])

这个tuple定义的时候有3个元素，分别是‘a‘，‘b‘和一个list。不是说tuple一旦定义后就不可变了吗？怎么后来又变了？

别急，我们先看看定义的时候tuple包含的3个元素：

当我们把list的元素‘A‘和‘B‘修改为‘X‘和‘Y‘后，tuple变为：

表面上看，tuple的元素确实变了，但其实变的不是tuple的元素，而是list的元素。tuple一开始指向的list并没有改成别的list，所以，tuple所谓的“不变”是说，tuple的每个元素，指向永远不变。即指向‘a‘，就不能改成指向‘b‘，指向一个list，就不能改成指向其他对象，但指向的这个list本身是可变的！

理解了“指向不变”后，要创建一个内容也不变的tuple怎么做？那就必须保证tuple的每一个元素本身也不能变。

Python3 字典

字典是另一种可变容器模型，且可存储任意类型对象。

Python内置了字典：dict的支持，dict全称dictionary，在其他语言中也称为map，使用键-值（key-value）存储，具有极快的查找速度。

常用操作：

• 索引
• 新增
• 删除
• 键、值、键值对
• 循环
• 长度

class dict(object):
    """
    dict() -> new empty dictionary
    dict(mapping) -> new dictionary initialized from a mapping object‘s
        (key, value) pairs
    dict(iterable) -> new dictionary initialized as if via:
        d = {}
        for k, v in iterable:
            d[k] = v
    dict(**kwargs) -> new dictionary initialized with the name=value pairs
        in the keyword argument list.  For example:  dict(one=1, two=2)
    """

    def clear(self): # real signature unknown; restored from __doc__
        """ 清除内容 """
        """ D.clear() -> None.  Remove all items from D. """
        pass

    def copy(self): # real signature unknown; restored from __doc__
        """ 浅拷贝 """
        """ D.copy() -> a shallow copy of D """
        pass

    @staticmethod # known case
    def fromkeys(S, v=None): # real signature unknown; restored from __doc__
        """
        dict.fromkeys(S[,v]) -> New dict with keys from S and values equal to v.
        v defaults to None.
        """
        pass

    def get(self, k, d=None): # real signature unknown; restored from __doc__
        """ 根据key获取值，d是默认值 """
        """ D.get(k[,d]) -> D[k] if k in D, else d.  d defaults to None. """
        pass

    def has_key(self, k): # real signature unknown; restored from __doc__
        """ 是否有key """
        """ D.has_key(k) -> True if D has a key k, else False """
        return False

    def items(self): # real signature unknown; restored from __doc__
        """ 所有项的列表形式 """
        """ D.items() -> list of D‘s (key, value) pairs, as 2-tuples """
        return []

    def iteritems(self): # real signature unknown; restored from __doc__
        """ 项可迭代 """
        """ D.iteritems() -> an iterator over the (key, value) items of D """
        pass

    def iterkeys(self): # real signature unknown; restored from __doc__
        """ key可迭代 """
        """ D.iterkeys() -> an iterator over the keys of D """
        pass

    def itervalues(self): # real signature unknown; restored from __doc__
        """ value可迭代 """
        """ D.itervalues() -> an iterator over the values of D """
        pass

    def keys(self): # real signature unknown; restored from __doc__
        """ 所有的key列表 """
        """ D.keys() -> list of D‘s keys """
        return []

    def pop(self, k, d=None): # real signature unknown; restored from __doc__
        """ 获取并在字典中移除 """
        """
        D.pop(k[,d]) -> v, remove specified key and return the corresponding value.
        If key is not found, d is returned if given, otherwise KeyError is raised
        """
        pass

    def popitem(self): # real signature unknown; restored from __doc__
        """ 获取并在字典中移除 """
        """
        D.popitem() -> (k, v), remove and return some (key, value) pair as a
        2-tuple; but raise KeyError if D is empty.
        """
        pass

    def setdefault(self, k, d=None): # real signature unknown; restored from __doc__
        """ 如果key不存在，则创建，如果存在，则返回已存在的值且不修改 """
        """ D.setdefault(k[,d]) -> D.get(k,d), also set D[k]=d if k not in D """
        pass

    def update(self, E=None, **F): # known special case of dict.update
        """ 更新
            {‘name‘:‘alex‘, ‘age‘: 18000}
            [(‘name‘,‘sbsbsb‘),]
        """
        """
        D.update([E, ]**F) -> None.  Update D from dict/iterable E and F.
        If E present and has a .keys() method, does:     for k in E: D[k] = E[k]
        If E present and lacks .keys() method, does:     for (k, v) in E: D[k] = v
        In either case, this is followed by: for k in F: D[k] = F[k]
        """
        pass

    def values(self): # real signature unknown; restored from __doc__
        """ 所有的值 """
        """ D.values() -> list of D‘s values """
        return []

    def viewitems(self): # real signature unknown; restored from __doc__
        """ 所有项，只是将内容保存至view对象中 """
        """ D.viewitems() -> a set-like object providing a view on D‘s items """
        pass

    def viewkeys(self): # real signature unknown; restored from __doc__
        """ D.viewkeys() -> a set-like object providing a view on D‘s keys """
        pass

    def viewvalues(self): # real signature unknown; restored from __doc__
        """ D.viewvalues() -> an object providing a view on D‘s values """
        pass

    def __cmp__(self, y): # real signature unknown; restored from __doc__
        """ x.__cmp__(y) <==> cmp(x,y) """
        pass

    def __contains__(self, k): # real signature unknown; restored from __doc__
        """ D.__contains__(k) -> True if D has a key k, else False """
        return False

    def __delitem__(self, y): # real signature unknown; restored from __doc__
        """ x.__delitem__(y) <==> del x[y] """
        pass

    def __eq__(self, y): # real signature unknown; restored from __doc__
        """ x.__eq__(y) <==> x==y """
        pass

    def __getattribute__(self, name): # real signature unknown; restored from __doc__
        """ x.__getattribute__(‘name‘) <==> x.name """
        pass

    def __getitem__(self, y): # real signature unknown; restored from __doc__
        """ x.__getitem__(y) <==> x[y] """
        pass

    def __ge__(self, y): # real signature unknown; restored from __doc__
        """ x.__ge__(y) <==> x>=y """
        pass

    def __gt__(self, y): # real signature unknown; restored from __doc__
        """ x.__gt__(y) <==> x>y """
        pass

    def __init__(self, seq=None, **kwargs): # known special case of dict.__init__
        """
        dict() -> new empty dictionary
        dict(mapping) -> new dictionary initialized from a mapping object‘s
            (key, value) pairs
        dict(iterable) -> new dictionary initialized as if via:
            d = {}
            for k, v in iterable:
                d[k] = v
        dict(**kwargs) -> new dictionary initialized with the name=value pairs
            in the keyword argument list.  For example:  dict(one=1, two=2)
        # (copied from class doc)
        """
        pass

    def __iter__(self): # real signature unknown; restored from __doc__
        """ x.__iter__() <==> iter(x) """
        pass

    def __len__(self): # real signature unknown; restored from __doc__
        """ x.__len__() <==> len(x) """
        pass

    def __le__(self, y): # real signature unknown; restored from __doc__
        """ x.__le__(y) <==> x<=y """
        pass

    def __lt__(self, y): # real signature unknown; restored from __doc__
        """ x.__lt__(y) <==> x<y """
        pass

    @staticmethod # known case of __new__
    def __new__(S, *more): # real signature unknown; restored from __doc__
        """ T.__new__(S, ...) -> a new object with type S, a subtype of T """
        pass

    def __ne__(self, y): # real signature unknown; restored from __doc__
        """ x.__ne__(y) <==> x!=y """
        pass

    def __repr__(self): # real signature unknown; restored from __doc__
        """ x.__repr__() <==> repr(x) """
        pass

    def __setitem__(self, i, y): # real signature unknown; restored from __doc__
        """ x.__setitem__(i, y) <==> x[i]=y """
        pass

    def __sizeof__(self): # real signature unknown; restored from __doc__
        """ D.__sizeof__() -> size of D in memory, in bytes """
        pass

    __hash__ = None

dict

定义：｛key1:value1,key2:value2｝,key-value结构，key必须可hash特性：

1.可存放多个值2.可修改指定key对应的值，可变3.无序

如果用dict实现，只需要一个“名字”-“成绩”的对照表，直接根据名字查找成绩，无论这个表有多大，查找速度都不会变慢。用Python写一个dict如下：

>>> d = {‘Michael‘: 95, ‘Bob‘: 75, ‘Tracy‘: 85}
>>> d[‘Michael‘]
95

为什么dict查找速度这么快？因为dict的实现原理和查字典是一样的。假设字典包含了1万个汉字，我们要查某一个字，一个办法是把字典从第一页往后翻，直到找到我们想要的字为止，这种方法就是在list中查找元素的方法，list越大，查找越慢。

第二种方法是先在字典的索引表里（比如部首表）查这个字对应的页码，然后直接翻到该页，找到这个字。无论找哪个字，这种查找速度都非常快，不会随着字典大小的增加而变慢。

dict就是第二种实现方式，给定一个名字，比如‘Michael‘，dict在内部就可以直接计算出Michael对应的存放成绩的“页码”，也就是95这个数字存放的内存地址，直接取出来，所以速度非常快。

你可以猜到，这种key-value存储方式，在放进去的时候，必须根据key算出value的存放位置，这样，取的时候才能根据key直接拿到value。

由于一个key只能对应一个value，所以，多次对一个key放入value，后面的值会把前面的值冲掉：

>>> d[‘Jack‘] = 90
>>> d[‘Jack‘]
90
>>> d[‘Jack‘] = 88
>>> d[‘Jack‘]
88

如果key不存在，dict就会报错：

>>> d[‘Thomas‘]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
KeyError: ‘Thomas‘

要避免key不存在的错误，有两种办法，一是通过in判断key是否存在：

>>> ‘Thomas‘ in d
False

二是通过dict提供的get方法，如果key不存在，可以返回None，或者自己指定的value：

>>> d.get(‘Thomas‘)
>>> d.get(‘Thomas‘, -1)
-1

注意：返回None的时候Python的交互式命令行不显示结果。

要删除一个key，用pop(key)方法，对应的value也会从dict中删除：

>>> d.pop(‘Bob‘)
75
>>> d
{‘Michael‘: 95, ‘Tracy‘: 85}

请务必注意，dict内部存放的顺序和key放入的顺序是没有关系的。

和list比较，dict有以下几个特点：

1. 查找和插入的速度极快，不会随着key的增加而变慢；
2. 需要占用大量的内存，内存浪费多。

而list相反：

1. 查找和插入的时间随着元素的增加而增加；
2. 占用空间小，浪费内存很少。

所以，dict是用空间来换取时间的一种方法。

dict可以用在需要高速查找的很多地方，在Python代码中几乎无处不在，正确使用dict非常重要，需要牢记的第一条就是dict的key必须是不可变对象。

这是因为dict根据key来计算value的存储位置，如果每次计算相同的key得出的结果不同，那dict内部就完全混乱了。这个通过key计算位置的算法称为哈希算法（Hash）。

要保证hash的正确性，作为key的对象就不能变。在Python中，字符串、整数等都是不可变的，因此，可以放心地作为key。而list是可变的，就不能作为key：

>>> key = [1, 2, 3]
>>> d[key] = ‘a list‘
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unhashable type: ‘list‘

字典的每个键值(key=>value)对用冒号(:)分割，每个对之间用逗号(,)分割，整个字典包括在花括号({})中 ,格式如下所示：

d = {key1 : value1, key2 : value2 }

键必须是唯一的，但值则不必。

值可以取任何数据类型，但键必须是不可变的，如字符串，数字或元组。

一个简单的字典实例：

dict = {‘Alice‘: ‘2341‘, ‘Beth‘: ‘9102‘, ‘Cecil‘: ‘3258‘}

也可如此创建字典：

dict1 = { ‘abc‘: 456 };
dict2 = { ‘abc‘: 123, 98.6: 37 };

访问字典里的值

把相应的键放入熟悉的方括弧，如下实例:

#!/usr/bin/python3

dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Class‘: ‘First‘}

print ("dict[‘Name‘]: ", dict[‘Name‘])
print ("dict[‘Age‘]: ", dict[‘Age‘])

以上实例输出结果：

dict[‘Name‘]:  Runoob
dict[‘Age‘]:  7

如果用字典里没有的键访问数据，会输出错误如下：

#!/usr/bin/python3

dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Class‘: ‘First‘};

print ("dict[‘Alice‘]: ", dict[‘Alice‘])

以上实例输出结果：

Traceback (most recent call last):
  File "test.py", line 5, in <module>
    print ("dict[‘Alice‘]: ", dict[‘Alice‘])
KeyError: ‘Alice‘

修改字典

向字典添加新内容的方法是增加新的键/值对，修改或删除已有键/值对如下实例:

#!/usr/bin/python3

dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Class‘: ‘First‘}

dict[‘Age‘] = 8;               # 更新 Age
dict[‘School‘] = "python教程"  # 添加信息

print ("dict[‘Age‘]: ", dict[‘Age‘])
print ("dict[‘School‘]: ", dict[‘School‘])

以上实例输出结果：

dict[‘Age‘]:  8
dict[‘School‘]:  python教程

删除字典元素

能删单一的元素也能清空字典，清空只需一项操作。

显示删除一个字典用del命令，如下实例：

#!/usr/bin/python3

dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Class‘: ‘First‘}

del dict[‘Name‘] # 删除键 ‘Name‘
dict.clear()     # 删除字典
del dict         # 删除字典

print ("dict[‘Age‘]: ", dict[‘Age‘])
print ("dict[‘School‘]: ", dict[‘School‘])

但这会引发一个异常，因为用执行 del 操作后字典不再存在：

Traceback (most recent call last):
  File "test.py", line 9, in <module>
    print ("dict[‘Age‘]: ", dict[‘Age‘])
TypeError: ‘type‘ object is not subscriptable

注：del() 方法后面也会讨论。

字典键的特性

字典值可以没有限制地取任何python对象，既可以是标准的对象，也可以是用户定义的，但键不行。

两个重要的点需要记住：

1）不允许同一个键出现两次。创建时如果同一个键被赋值两次，后一个值会被记住，如下实例：

#!/usr/bin/python3

dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Name‘: ‘小菜鸟‘}

print ("dict[‘Name‘]: ", dict[‘Name‘])

以上实例输出结果：

dict[‘Name‘]:  小菜鸟

2）键必须不可变，所以可以用数字，字符串或元组充当，而用列表就不行，如下实例：

#!/usr/bin/python3

dict = {[‘Name‘]: ‘Runoob‘, ‘Age‘: 7}

print ("dict[‘Name‘]: ", dict[‘Name‘])

以上实例输出结果：

Traceback (most recent call last):
  File "test.py", line 3, in <module>
    dict = {[‘Name‘]: ‘Runoob‘, ‘Age‘: 7}
TypeError: unhashable type: ‘list‘

字典内置函数&方法

Python字典包含了以下内置函数：

>>> dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Class‘: ‘First‘}
>>> len(dict)
3

>>> dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Class‘: ‘First‘}
>>> str(dict)
"{‘Name‘: ‘Runoob‘, ‘Class‘: ‘First‘, ‘Age‘: 7}"

>>> dict = {‘Name‘: ‘Runoob‘, ‘Age‘: 7, ‘Class‘: ‘First‘}
>>> type(dict)
<class ‘dict‘>

Python字典包含了以下内置方法：

其他

1、for循环

用户按照顺序循环可迭代对象中的内容，

PS：break、continue

li = [11,22,33,44]
for item in li:
    print（item）

2、enumrate

为可迭代的对象添加序号

li = [11,22,33]
for k,v in enumerate(li, 1):
    print(k,v)

3、range和xrange

指定范围，生成指定的数字

print range(1, 10)
# 结果：[1, 2, 3, 4, 5, 6, 7, 8, 9]

print（range(1, 10, 2)）
# 结果：[1, 3, 5, 7, 9]

print（range(30, 0, -2)）
# 结果：[30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2]　　

Set（集合）

集合（set）是一个无序不重复元素的序列。

基本功能是进行成员关系测试和删除重复元素。

可以使用大括号({})或者 set()函数创建集合，注意：创建一个空集合必须用 set() 而不是 { }，因为 { } 是用来创建一个空字典。

定义：由不同元素组成的集合，集合中是一组无序排列的可hash值，可以作为字典的key特性：1.集合的目的是将不同的值存放到一起，不同的集合间用来做关系运算，无需纠结于集合中单个值

集合常用操作：关系运算

　　 in    not in    ＝＝    ！＝    <,<=    >,>=    |,|=:合集    &.&=:交集    －,－=:差集    ^,^=:对称差分

集合工厂函数set()

class set(object):
    """
    set() -> new empty set object
    set(iterable) -> new set object

    Build an unordered collection of unique elements.
    """
    def add(self, *args, **kwargs): # real signature unknown
        """
        Add an element to a set.

        This has no effect if the element is already present.
        """
        pass

    def clear(self, *args, **kwargs): # real signature unknown
        """ Remove all elements from this set. """
        pass

    def copy(self, *args, **kwargs): # real signature unknown
        """ Return a shallow copy of a set. """
        pass

    def difference(self, *args, **kwargs): # real signature unknown
        """
        相当于s1-s2

        Return the difference of two or more sets as a new set.

        (i.e. all elements that are in this set but not the others.)
        """
        pass

    def difference_update(self, *args, **kwargs): # real signature unknown
        """ Remove all elements of another set from this set. """
        pass

    def discard(self, *args, **kwargs): # real signature unknown
        """
        与remove功能相同，删除元素不存在时不会抛出异常

        Remove an element from a set if it is a member.

        If the element is not a member, do nothing.
        """
        pass

    def intersection(self, *args, **kwargs): # real signature unknown
        """
        相当于s1&s2

        Return the intersection of two sets as a new set.

        (i.e. all elements that are in both sets.)
        """
        pass

    def intersection_update(self, *args, **kwargs): # real signature unknown
        """ Update a set with the intersection of itself and another. """
        pass

    def isdisjoint(self, *args, **kwargs): # real signature unknown
        """ Return True if two sets have a null intersection. """
        pass

    def issubset(self, *args, **kwargs): # real signature unknown
        """
        相当于s1<=s2

        Report whether another set contains this set. """
        pass

    def issuperset(self, *args, **kwargs): # real signature unknown
        """
        相当于s1>=s2

         Report whether this set contains another set. """
        pass

    def pop(self, *args, **kwargs): # real signature unknown
        """
        Remove and return an arbitrary set element.
        Raises KeyError if the set is empty.
        """
        pass

    def remove(self, *args, **kwargs): # real signature unknown
        """
        Remove an element from a set; it must be a member.

        If the element is not a member, raise a KeyError.
        """
        pass

    def symmetric_difference(self, *args, **kwargs): # real signature unknown
        """
        相当于s1^s2

        Return the symmetric difference of two sets as a new set.

        (i.e. all elements that are in exactly one of the sets.)
        """
        pass

    def symmetric_difference_update(self, *args, **kwargs): # real signature unknown
        """ Update a set with the symmetric difference of itself and another. """
        pass

    def union(self, *args, **kwargs): # real signature unknown
        """
        相当于s1|s2

        Return the union of sets as a new set.

        (i.e. all elements that are in either set.)
        """
        pass

    def update(self, *args, **kwargs): # real signature unknown
        """ Update a set with the union of itself and others. """
        pass

    def __and__(self, *args, **kwargs): # real signature unknown
        """ Return self&value. """
        pass

    def __contains__(self, y): # real signature unknown; restored from __doc__
        """ x.__contains__(y) <==> y in x. """
        pass

    def __eq__(self, *args, **kwargs): # real signature unknown
        """ Return self==value. """
        pass

    def __getattribute__(self, *args, **kwargs): # real signature unknown
        """ Return getattr(self, name). """
        pass

    def __ge__(self, *args, **kwargs): # real signature unknown
        """ Return self>=value. """
        pass

    def __gt__(self, *args, **kwargs): # real signature unknown
        """ Return self>value. """
        pass

    def __iand__(self, *args, **kwargs): # real signature unknown
        """ Return self&=value. """
        pass

    def __init__(self, seq=()): # known special case of set.__init__
        """
        set() -> new empty set object
        set(iterable) -> new set object

        Build an unordered collection of unique elements.
        # (copied from class doc)
        """
        pass

    def __ior__(self, *args, **kwargs): # real signature unknown
        """ Return self|=value. """
        pass

    def __isub__(self, *args, **kwargs): # real signature unknown
        """ Return self-=value. """
        pass

    def __iter__(self, *args, **kwargs): # real signature unknown
        """ Implement iter(self). """
        pass

    def __ixor__(self, *args, **kwargs): # real signature unknown
        """ Return self^=value. """
        pass

    def __len__(self, *args, **kwargs): # real signature unknown
        """ Return len(self). """
        pass

    def __le__(self, *args, **kwargs): # real signature unknown
        """ Return self<=value. """
        pass

    def __lt__(self, *args, **kwargs): # real signature unknown
        """ Return self<value. """
        pass

    @staticmethod # known case of __new__
    def __new__(*args, **kwargs): # real signature unknown
        """ Create and return a new object.  See help(type) for accurate signature. """
        pass

    def __ne__(self, *args, **kwargs): # real signature unknown
        """ Return self!=value. """
        pass

    def __or__(self, *args, **kwargs): # real signature unknown
        """ Return self|value. """
        pass

    def __rand__(self, *args, **kwargs): # real signature unknown
        """ Return value&self. """
        pass

    def __reduce__(self, *args, **kwargs): # real signature unknown
        """ Return state information for pickling. """
        pass

    def __repr__(self, *args, **kwargs): # real signature unknown
        """ Return repr(self). """
        pass

    def __ror__(self, *args, **kwargs): # real signature unknown
        """ Return value|self. """
        pass

    def __rsub__(self, *args, **kwargs): # real signature unknown
        """ Return value-self. """
        pass

    def __rxor__(self, *args, **kwargs): # real signature unknown
        """ Return value^self. """
        pass

    def __sizeof__(self): # real signature unknown; restored from __doc__
        """ S.__sizeof__() -> size of S in memory, in bytes """
        pass

    def __sub__(self, *args, **kwargs): # real signature unknown
        """ Return self-value. """
        pass

    def __xor__(self, *args, **kwargs): # real signature unknown
        """ Return self^value. """
        pass

    __hash__ = None

查看

查看

bytes类型

定义：存8bit整数，数据基于网络传输或内存变量存储到硬盘时需要转成bytes类型,字符串前置b代表为bytes类型

>>> x
‘hello sb‘
>>> x.encode(‘gb2312‘)
b‘hello sb‘

#!/usr/bin/python3

student = {‘Tom‘, ‘Jim‘, ‘Mary‘, ‘Tom‘, ‘Jack‘, ‘Rose‘}

print(student)   # 输出集合，重复的元素被自动去掉

# 成员测试
if(‘Rose‘ in student) :
    print(‘Rose 在集合中‘)
else :
	print(‘Rose 不在集合中‘)

# set可以进行集合运算
a = set(‘abracadabra‘)
b = set(‘alacazam‘)

print(a)

print(a - b)     # a和b的差集

print(a | b)     # a和b的并集

print(a & b)     # a和b的交集

print(a ^ b)     # a和b中不同时存在的元素

以上实例输出结果：

{‘Jack‘, ‘Rose‘, ‘Mary‘, ‘Jim‘, ‘Tom‘}
Rose 在集合中
{‘r‘, ‘b‘, ‘a‘, ‘c‘, ‘d‘}
{‘r‘, ‘b‘, ‘d‘}
{‘a‘, ‘l‘, ‘z‘, ‘b‘, ‘m‘, ‘d‘, ‘r‘, ‘c‘}
{‘a‘, ‘c‘}
{‘l‘, ‘z‘, ‘b‘, ‘m‘, ‘d‘, ‘r‘}

set和dict类似，也是一组key的集合，但不存储value。由于key不能重复，所以，在set中，没有重复的key。

要创建一个set，需要提供一个list作为输入集合：

>>> s = set([1, 2, 3])
>>> s
{1, 2, 3}

注意，传入的参数[1, 2, 3]是一个list，而显示的{1, 2, 3}只是告诉你这个set内部有1，2，3这3个元素，显示的顺序也不表示set是有序的。。

重复元素在set中自动被过滤：

>>> s = set([1, 1, 2, 2, 3, 3])
>>> s
{1, 2, 3}

通过add(key)方法可以添加元素到set中，可以重复添加，但不会有效果：

>>> s.add(4)
>>> s
{1, 2, 3, 4}
>>> s.add(4)
>>> s
{1, 2, 3, 4}

通过remove(key)方法可以删除元素：

>>> s.remove(4)
>>> s
{1, 2, 3}

set可以看成数学意义上的无序和无重复元素的集合，因此，两个set可以做数学意义上的交集、并集等操作：

>>> s1 = set([1, 2, 3])
>>> s2 = set([2, 3, 4])
>>> s1 & s2
{2, 3}
>>> s1 | s2
{1, 2, 3, 4}

set和dict的唯一区别仅在于没有存储对应的value，但是，set的原理和dict一样，所以，同样不可以放入可变对象，因为无法判断两个可变对象是否相等，也就无法保证set内部“不会有重复元素”。试试把list放入set，看看是否会报错。

再议不可变对象

上面我们讲了，str是不变对象，而list是可变对象。

对于可变对象，比如list，对list进行操作，list内部的内容是会变化的，比如：

>>> a = [‘c‘, ‘b‘, ‘a‘]
>>> a.sort()
>>> a
[‘a‘, ‘b‘, ‘c‘]

而对于不可变对象，比如str，对str进行操作呢：

>>> a = ‘abc‘
>>> a.replace(‘a‘, ‘A‘)
‘Abc‘
>>> a
‘abc‘

虽然字符串有个replace()方法，也确实变出了‘Abc‘，但变量a最后仍是‘abc‘，应该怎么理解呢？

我们先把代码改成下面这样：

>>> a = ‘abc‘
>>> b = a.replace(‘a‘, ‘A‘)
>>> b
‘Abc‘
>>> a
‘abc‘

要始终牢记的是，a是变量，而‘abc‘才是字符串对象！有些时候，我们经常说，对象a的内容是‘abc‘，但其实是指，a本身是一个变量，它指向的对象的内容才是‘abc‘：

当我们调用a.replace(‘a‘, ‘A‘)时，实际上调用方法replace是作用在字符串对象‘abc‘上的，而这个方法虽然名字叫replace，但却没有改变字符串‘abc‘的内容。相反，replace方法创建了一个新字符串‘Abc‘并返回，如果我们用变量b指向该新字符串，就容易理解了，变量a仍指向原有的字符串‘abc‘，但变量b却指向新字符串‘Abc‘了：

所以，对于不变对象来说，调用对象自身的任意方法，也不会改变该对象自身的内容。相反，这些方法会创建新的对象并返回，这样，就保证了不可变对象本身永远是不可变的。

小结

使用key-value存储结构的dict在Python中非常有用，选择不可变对象作为key很重要，最常用的key是字符串。

tuple虽然是不变对象，但试试把(1, 2, 3)和(1, [2, 3])放入dict或set中，并解释结果。

标准数据类型特性总结

按存值个数区分

按可变不可变区分

按访问顺序区分

深浅拷贝

一、数字和字符串

对于 数字 和 字符串 而言，赋值、浅拷贝和深拷贝无意义，因为其永远指向同一个内存地址。

import copy
# ######### 数字、字符串 #########
n1 = 123
# n1 = "i am alex age 10"
print(id(n1))
# ## 赋值 ##
n2 = n1
print(id(n2))
# ## 浅拷贝 ##
n2 = copy.copy(n1)
print(id(n2))

# ## 深拷贝 ##
n3 = copy.deepcopy(n1)
print(id(n3))

其他基本数据类型

对于字典、元祖、列表 而言，进行赋值、浅拷贝和深拷贝时，其内存地址的变化是不同的。

1、赋值

赋值，只是创建一个变量，该变量指向原来内存地址，如：

n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}

n2 = n1

2、浅拷贝

浅拷贝，在内存中只额外创建第一层数据

import copy

n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}

n3 = copy.copy(n1)

3、深拷贝

深拷贝，在内存中将所有的数据重新创建一份（排除最后一层，即：python内部对字符串和数字的优化）

import copy

n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}

n4 = copy.deepcopy(n1)