from collections.abc import Mapping, MutableMapping
#dict属于mapping类型

a = {}
print (isinstance(a, MutableMapping))
# True

a = {"lewen1": {"company": "imooc"},
     "lewen2": {"company": "imooc2"}
     }
# clear   Remove all items from D.
# a.clear()
# pass
​
# copy, 返回浅拷贝
new_dict = a.copy()
new_dict["lewen1"]["company"] = "imooc3"  # 浅拷贝，只是拷贝了指向。这里修改会修改了a 中原来的值
print(new_dict)
print(a)
​
​---
{'lewen1': {'company': 'imooc3'}, 'lewen2': {'company': 'imooc2'}}
{'lewen1': {'company': 'imooc3'}, 'lewen2': {'company': 'imooc2'}}

---

import copy
a = {"lewen1": {"company": "imooc"},
     "lewen2": {"company": "imooc2"}
     }
new_dict = copy.deepcopy(a)               # 深拷贝，开辟独立的内存空间，并复制值
new_dict["lewen1"]["company"] = "imooc3"  # 这里修改，并不会影响字典a的值
print(new_dict)
print(a)

---
{'lewen1': {'company': 'imooc3'}, 'lewen2': {'company': 'imooc2'}}
{'lewen1': {'company': 'imooc'}, 'lewen2': {'company': 'imooc2'}}

---

# formkeys
new_list = ["lewen1", "lewen2"]
new_dict = dict.fromkeys(new_list, {"company": "imooc"})
print(new_dict)
​
# new_dict["kevin"]  # KeyError 不存在会抛异常
ret = new_dict.get("kevin","None") # 
print(ret)
​
# items 方法
for key,value in new_dict.items():
    print(key,value)

ret_set = new_dict.setdefault("kevin","new mem")  # 不存在key,就设置并返回值
print(ret_set)
print(new_dict)
​
​new_dict.update(      # update（） 括号里面添加为可迭代对象
    (("lewen", "imooc"),)
    )
---
{'lewen1': {'company': 'imooc'}, 'lewen2': {'company': 'imooc'}}
None
lewen1 {'company': 'imooc'}
lewen2 {'company': 'imooc'}
new mem
{'lewen1': {'company': 'imooc'}, 'lewen2': {'company': 'imooc'}, 'kevin': 'new mem'}
​

#不建议继承list和dict
class Mydict(dict):
    def __setitem__(self, key, value):
        super().__setitem__(key, value*2)

my_dict = Mydict(one=1)   # value*2 没有生效
# my_dict["one"] = 1      # 生效了
print (my_dict)
{'one': 1}

---

from collections import UserDict
class Mydict(UserDict):
    def __setitem__(self, key, value):
        super().__setitem__(key, value*2)

my_dict = Mydict(one=1)
# my_dict["one"] = 1
print (my_dict)
{'one': 2}

---

# defaultdict 
from collections import defaultdict

my_dict = defaultdict(dict)
my_value = my_dict["bobby"]  # 没有则返回空字典
print(my_value)
{}

#set 集合 fronzenset (不可变集合) 无序， 不重复
s = set('abcdee')
print(s)

s2 = set(['a','b','c','d','e'])
print(s2)

s3 = {'a','b', 'c'}
print(type(s3))

s = frozenset("abcde") #frozenset 不可变，以作为dict的key
                       # 不能添加值
print(s)
# ---
{'a', 'e', 'c', 'd', 'b'}
{'a', 'e', 'c', 'd', 'b'}
<class 'set'>
frozenset({'a', 'e', 'c', 'd', 'b'})

# ---

#向set添加数据
s = set('abcdee')
another_set = set("cef")
s.update(another_set)
print(s)

re_set = s.difference(another_set)  # {'b', 'd', 'a'}
re_set = s - another_set            # {'b', 'd', 'a'}
re_set = s & another_set            # {'c', 'f', 'e'}
re_set = s | another_set              # {'a', 'f', 'c', 'e', 'd', 'b'}

#set性能很高
# | & -  #集合运算
print(re_set)

print (s.issubset(re_set))
if "c" in re_set:
    print ("i am in set")
# ---
{'a', 'f', 'e', 'c', 'd', 'b'}
{'a', 'f', 'c', 'e', 'd', 'b'}
True
i am in set

    #dict查找的性能远远大于list
    #在list中随着list数据的增大 查找时间会增大
    #在dict中查找元素不会随着dict的增大而增大
    print(last_time)

#1.dict的key或者set的值 都必须是可以hash的
#不可变对象 都是可hash的， str， fronzenset， tuple，自己实现的类 __hash__
#2. dict的内存花销大（有大量空余的表元），但是查询速度快， 自定义的对象 或者python内部的对象都是用dict包装的
# 3. dict的存储顺序和元素添加顺序有关
# 4. 添加数据有可能改变已有数据的顺序