<!doctype html>python标准库之collection

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python标准库之collections

最近在工作零零散散的用到了一些collections的方法，突然有个想法来将它整理一下。

简介

collections是python中基础数据类型的容器模块，提供了更加便捷和快速的数据类型操作的方法，我们可以在合适的场景去运用他们。

常用方法

Counter()

统计序列中元素的个数：

作为输入， Counter 对象可以接受任意的由可哈希（hashable）元素构成的序列对象。 在底层实现上，一个 Counter 对象就是一个字典，将元素映射到它出现的次数上。

 
 
 

xxxxxxxxxx

 
 

 
 

from collections import Counter
​
def test_counter():
    text = "kshfkhdghskdnvknsighdsihinisdhguidhicoidsjiohfiuerhrfjsiohgi"
    words = Counter(text)
    print(words.items())  # 序列中各元素出现的次数
    print(words.most_common(3))  # 序列中出现次数最多的三个
    print(words["k"])  # 查看序列中某个元素出现的次数
    
if __name__ == '__main__':
    test_counter()
    
"""
dict_items([('k', 4), ('s', 7), ('h', 10), ('f', 3), ('d', 6), ('g', 4), ('n', 3), ('v', 1), ('i', 11), ('u', 2), ('c', 1), ('o', 3), ('j', 2), ('e', 1), ('r', 2)])
[('i', 11), ('h', 10), ('s', 7)]
4
​
"""

 
 

defaultdict()

看了很多对defaultdict的解释没有一个能完美通俗的解释清楚的，那我们就简单从字面上去理解他吧，我觉得这样反倒更清晰。

定义一个默认格式的字典，他是dict的一个子类，那怎么定义一个默认格式的字典呢，请看下面的例子

 
 
 

xxxxxxxxxx

 
 

 
 

from collections import defaultdict
def test_defaultdict():
    d = defaultdict(list)  # 创建一个value默认为list类型的字典
    d["a"].append(1)
    d["a"].append(2)
    d["a"].append(3)
    print(d)
    print(d["a"])
    print(d["b"])  # 即使没有key("b"),取值也不会报错，依然会有默认值[]
    s = defaultdict(set)  # 创建一个value默认为list类型的字典
    s["aa"].add(1)
    s["aa"].add(2)
    print(s["aa"],"__", s["bb"])
​
​
if __name__ == '__main__':
    test_defaultdict()
    
"""
defaultdict(<class 'list'>, {'a': [1, 2, 3]})
[1, 2, 3]
[]
{1, 2} __ set()
"""

 
 

OrderDict()

OrderDict()字典排序，我们知道python的基本数据类型字典是无序的，但是我们想创建一个有序的字典怎么办呢？这个时候我们就可以用OrderDict()来创建，它会保留键值插入的顺序并以此顺序排列。

OrderDict内部维护着一个根据键值插入顺序的双向链表，每当一个新的元素被插入进来的时候，它会被放到链表的尾部。对于一个已存在的键值赋值不会改变键值的顺序。

需要注意的是OrderDict是一个普通字典大小的两倍，因为它内部维护着另外一个链表。使用时要注意这点。

 
 
 

xxxxxxxxxx

 
 

 
 

>>> od = OrderedDict()
>>> od['z'] = 1
>>> od['y'] = 2
>>> od['x'] = 3
>>> od.keys() # 按照插入的Key的顺序返回
['z', 'y', 'x']

 
 

namedtuple()

namedtuple()是一个方法生成的对象是tuple的子类，用来定义一个有指定含义的元组，通常我们定义一个元组无法知道他内部元素的含义，但是使用了namedtuple()就可以很清晰的知道这个元祖的的元素是用来干什么的

 
 
 

x

 
 

 
 

from collections import deque, namedtuple
def test_namedtuple():
    Person = namedtuple("Person", ["name", "age", "gender"])
    person = Person("lily", 20, "female")
    print(person.age)
    print(person.name)
    print(person.gender)
​
​
if __name__ == '__main__':
    test_namedtuple()
    
"""
20
lily
female
"""

 
 

deque()

deque()可以创建一个队列容器，供我们消费，它与python的队列的区别在于deque()在增加元素的时候，超出设定元素个数大小时，会默认删除最早的那个;同时deque不像list是一个线性存储，deque是一个双向链表，数据量大的时候插入效率大大高于list

 
 
 

​x
 
 

 
 

from collections import deque
​
def test_deque():
    q1 = deque(maxlen=3)
    q1.append(1)
    q1.append(2)
    q1.append(3)
q1。qppend(4)
    print(q1)
​
​
if __name__ == '__main__':
    test_deque()
# deque([2, 3, 4], maxlen=3)

 
 

deque包含的方法：其中pop从队列的 尾部抛出数据，如果想从队列头部取数据则用popleft（）

python标准库之collections-风君雪科技博客