Examples of python ancestors, dictionaries and collections

The following editor will bring you a brief understanding of Python's ancestors, dictionaries and collections. The editor thinks it’s pretty good, so I’ll share it with you now and give it as a reference. Let’s follow the editor and take a look.

1. Tuple

1. Tuple cannot be modified and is usually written in parentheses A series of items in, with ordered positions and fixed length

2. In fact, the tuple supports general sequence operations of strings and lists. "+", "*" and slicing operations will be returned when applied to the tuple. New Yuanzu

print（（1，2）+（3，4））>>>>（1，2，3，4）
print（（1，2）*4）>>>>（1，2，1，2，1，2，1，2）
T=（1，2，3，4）
print（T【0】，T【1：3】）>>>>（1，（2，3））

3. Yuanzu does not provide string, list and dictionary methods. If you want to sort the Yuanzu, you usually have to convert it into a list before you can get it. Calls using the sort method

T=（“z”,"b"."c"）
tem= list(T)
tem.sort()
print(tem)>>>> ["b","c","z"]
T=tuple(tem)
print(T) >>>>("b","c","z")

But the list inside the ancestor can be modified as usual

T=(1,[2,3],4)
T[1].[0] ="ABC"
print(T)>>>>>(1,["ABC",3],4)

2. Dictionary (dict)

1. The dictionary is unordered, that is, the order of the result data you query each time is not certain, because it is the key- Value type data does not need to be indexed by subscript

2. Dictionary operations:

D1={} #表示空字典
D2=｛“spam”:1,"app":2｝#两项目字典
D3={"food":{"spam":1,"egg":2}}#嵌套
D2["app"]#通过键进行查找
D3["food"]["spam"]
"egg" in D3 #判断egg是否存在在D3中，存在则返回True
D2.keys（）#查询key值
D2.values（）#查询value值
D2[key]=44#表示新增或者修改，当字典中不存在这个key则新增，存在则是修改
del D2[key]#删除

D2 = ｛"egg",1,"app",2｝
print(D2["app"])
>>>>>>>2
print(D2)
>>>>>>>{"egg",1,"app",2}
len(D2)
>>>>>>>2#返回的时keys的列表的长度

合并的方法：
D2 = ｛"egg",1,"app",2｝
D3 = ｛"egg",1,"app",2｝
D2.update(D3)
print（D2）
>>>>>>>｛"egg",1,"app",2,"egg",1,"app",2｝
pop删除的方法：能够删除字典一个键并返回它的值
D2 = ｛"egg",1,"app",2｝
D2.pop（“egg”）
>>>>>>>>1
print(D2)
>>>>>>>>{"app",2}


另一种创建方法：条件是所有的key的值都是一样的
dict.fromkeys（["a","b"],0）
>>>>>>>>>{"a":0,"b":0}

3. Set

A set is an unordered, non-duplicate data overlap. The main function is to

(1) remove duplicates; turn a list into a set and automatically remove duplicates

(2) relationship testing; test the intersection and union of two sets of data, etc. Relationship

Related operations

s1= set([1,2,3,4,5,6,7])
s2 = set([2,5,4,6,3,9])
print(s1.intersection(s2))#表示取交集
>>>>>>>>{2,4,5,6,3}
print（s1.union(s2)）#表示取并集
>>>>>>>>{1,2,3,4,5,6,7,9}
print(s1.difference(s2))#表示差集
>>>>>>>>{7,9}
print(s1.isdisjiont(s2))#表示s与s2是否有交集
>>>>>>>>True
s1.add(10)#添加1个项
s1.update([8,9,10])#添加多个项
s1.remove(1)#删除一项，值为1（指定删除哪个，没有指定会报错）
s1.pop()#随机删除一个数

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