一、计数器（counter）

Counter是对字典类型的补充，用于追踪值的出现次数。

具备字典的所有功能 + 自己的功能。

1 import collections
2 aa = collections.Counter("sdfdsgsdf;sdfssfd")    #把所有元素出现的次数统计下来了
3 print(aa)
4 
5 输出结果：
6 Counter({'s': 6, 'd': 5, 'f': 4, ';': 1, 'g': 1})

部分源码分析：

 1 def most_common(self, n=None):
 2         '''List the n most common elements and their counts from the most
 3         common to the least.  If n is None, then list all element counts.
 4 
 5         >>> Counter('abcdeabcdabcaba').most_common(3)
 6         [('a', 5), ('b', 4), ('c', 3)]
 7 
 8         '''
 9         # Emulate Bag.sortedByCount from Smalltalk
10         if n is None:
11             return sorted(self.items(), key=_itemgetter(1), reverse=True)
12         return _heapq.nlargest(n, self.items(), key=_itemgetter(1))
1 #获取元素出现次数多的几个
2 bb = aa.most_common(3)     #取元素次数最多的前3个
3 print(bb)
4 
5 #执行结果：
6 [('s', 6), ('d', 5), ('f', 4)]
 1 def elements(self):
 2         '''Iterator over elements repeating each as many times as its count.
 3 
 4         >>> c = Counter('ABCABC')
 5         >>> sorted(c.elements())
 6         ['A', 'A', 'B', 'B', 'C', 'C']
 7 
 8         # Knuth's example for prime factors of 1836:  2**2 * 3**3 * 17**1
 9         >>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
10         >>> product = 1
11         >>> for factor in prime_factors.elements():     # loop over factors
12         ...     product *= factor                       # and multiply them
13         >>> product
14         1836
15 
16         Note, if an element's count has been set to zero or is a negative
17         number, elements() will ignore it.
18 
19         '''
20         # Emulate Bag.do from Smalltalk and Multiset.begin from C++.
21         return _chain.from_iterable(_starmap(_repeat, self.items()))
22 
23     # Override dict methods where necessary
 1 #其他输出方式
 2 for item in aa.elements():   #迭代输出元素（同一元素出现几次，就连续输出该元素几次），无序
 3     print(item)
 4 
 5 for k,v in aa.items():     #把所有元素拿出来，再统计该元素出现次数
 6     print(k,v)
 7 
 8 #执行结果：
 9 ;
10 s
11 s
12 s
13 s
14 s
15 s
16 f
17 f
18 f
19 f
20 d
21 d
22 d
23 d
24 d
25 g
26 ; 1
27 s 6
28 f 4
29 d 5
30 g 1

 counter和elements的区别：elements处理的是原生的值；而counter处理的是已经处理完的数据

1 def update(*args, **kwds):
2         '''Like dict.update() but add counts instead of replacing them.
3 
4         Source can be an iterable, a dictionary, or another Counter instance.
 1 #更新计数器，
 2 import collections
 3 aa = collections.Counter(["11","22","33","22"])    #把所有元素出现的次数统计下来了
 4 print(aa)
 5 aa.update(["ggg","11","11"])
 6 print(aa)
 7 
 8 #执行结果:
 9 Counter({'22': 2, '33': 1, '11': 1})
10 Counter({'11': 3, '22': 2, 'ggg': 1, '33': 1})
1 def subtract(*args, **kwds):
2         '''Like dict.update() but subtracts counts instead of replacing them.
3         Counts can be reduced below zero.  Both the inputs and outputs are
4         allowed to contain zero and negative counts.
5 
6         Source can be an iterable, a dictionary, or another Counter instance.
 1 #减少元素
 2 import collections
 3 aa = collections.Counter(["11","22","33","22"])    #把所有元素出现的次数统计下来了
 4 print(aa)
 5 aa.subtract(["ggg","11","11"])   #如果不存在，也减
 6 print(aa)
 7 
 8 #执行结果：
 9 Counter({'22': 2, '11': 1, '33': 1})
10 Counter({'22': 2, '33': 1, 'ggg': -1, '11': -1})