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  • counter

    2019-04-21 22:03:00
    Counter 集成于 dict 类,因此也可以使用字典的方法,此类返回一个以元素为 key 、元素个数为 value 的 Counter 对象集合 >>> from collections import Counter >>> s = "hello pinsily" >...

    Counter 集成于 dict 类,因此也可以使用字典的方法,此类返回一个以元素为 key 、元素个数为 value 的 Counter 对象集合

    >>> from collections import Counter
    >>> s = "hello pinsily"
    >>> d = Counter(s)
    >>> d
    Counter({'l': 3, 'i': 2, 'h': 1, 'e': 1, 'o': 1, ' ': 1, 'p': 1, 'n': 1, 's': 1, 'y': 1})

    转载于:https://www.cnblogs.com/xxupup/p/10747315.html

    展开全文
  • Counter

    2016-05-06 16:23:58
    #python counter object from collections import * import os def get_counter():  '''get the Counter object'''  return Counter() def str_to_list(s):  '''  a string covert
    #python counter object

    from collections import *
    import os

    def get_counter():
        '''get the Counter object'''
        return Counter()

    def str_to_list(s):
        '''
        a string covert to list,
        return an empty list if the string equal None
        '''
        if s != None:
            return [x for x in s]
        else:
            return []

    def counter(c, l):
        '''统计列表l中每个单词的出现次数,最后返回一个Counter对象'''
        for word in l:
            c[word] += 1
        return c

    def get_file_str(path):
        '''打开指定的文件,并且把文件中的内容以字符串的形式返回'''
        if os.path.exists(path):
            temp_str = ''
            with open(path, 'r') as pf:
                for line in pf:
                    temp_str += line
                return temp_str
        else:
            print('the file [{}] is not exist!'.format(path))

    def test_str():
        #使用自定义字符串测试
        #统计自定义字符串中每个字符出现的次数
        cnt = get_counter()
        temp_str = 'hello,i\'m Hongten,welcome to my space!'
        temp_list = str_to_list(temp_str)
        cnt = counter(cnt, temp_list)
        print(cnt)

    def test_file():
        '''
        读取一个文件,把文件中的内容转化为字符串
        统计该字符串中每个字符串出现的次数
        '''
        cnt = get_counter()
        temp_path = 'c:\\temp.txt'
        temp_str = get_file_str(temp_path)
        temp_list = str_to_list(temp_str)
        cnt = counter(cnt, temp_list)
        print(cnt)
        
    def main():
        test_str()
        print('#' * 50)
        test_file()

    if __name__ == '__main__':
        main()
    展开全文
  • Counter goodie

    2020-12-28 03:53:09
    counter will show you that you first need to skim through lots and lots of search engine results to find a website which provides you a simple counter. <p>This IA should provide a simple interface for...
  • SourceCounter

    2019-03-22 14:15:02
    SourceCounter统计代码工具,可以统计应用程序代码的总行数,文件数量,资源文件大小等
  • 在这里为大家介绍一下Python非常实用的Counter、defaultdict、map、reduce、filter、groupby的函数使用,提高大家在平时实用Python的效率计数器函数 Counter带默认值的字典 defaultdictmap函数reduce函数filter函数 ...

    在这里为大家介绍一下Python非常实用的Counter、defaultdict、map、reduce、filter的函数使用,提高大家在平时使用Python的效率

    计数器函数 Counter

    相信在大家在平时使用python这门语言的时候都会遇见需要计算出一个字符在列表或者字典里面出现的次数吧!
    在没遇见这个函数前相信大家都是这样的(计算一个列表里字符a出现的次数):
    在这里插入图片描述
    但是!现在我们如果使用Counter这个高级函数就不一样啦!效果如下:
    在这里插入图片描述
    哇噢!不止帮我们计算出了a字符,而且在列表中出现的字符b,c都以字典的形式给我们返回了回来!
    重点!!这还没完,这函数还可以进行更新!!!
    在这里插入图片描述
    棒吧 计数器函数Counter!快拿小本本记上

    带默认值的字典 defaultdict

    为什么要用这个函数:大家在使用python语言创建字典的时候直接访问字典里面不存在的key是会报错的。
    在这里插入图片描述所以呢,这个defaultdict函数就很好的解决了这个问题
    格式为dict = defaultdict(factory_function)
    在这里插入图片描述
    也可以传入列表类型噢
    在这里插入图片描述

    注意:facotry_function可以为str,int,list,set,可以省略初始化噢

    map函数

    在这里插入图片描述

    reduce函数

    在这里插入图片描述

    filter函数

    在这里插入图片描述

    这篇文章乃本人睡觉突然想到的几个感觉最近用得比较多的实用的函数,和大家共勉!睡啦!希望和大家一起加油!

    展开全文
  • ReSwift-CounterApp 基于ReSwift的Swift Counter应用程序
  • Counter 用法 from collections import Counter

    千次阅读 2019-12-31 16:15:55
    Counter 用法 from collections import Counter from collections import Counter a = [1,4,2,3,2,3,4,2] b = Counter(a) #求数组中每个数字出现了几次 print(b) print( b[2]) #计算每个元素出现了几次 输出...

    Counter 用法 from collections import Counter

    from collections import Counter  
    a = [1,4,2,3,2,3,4,2]  
     
    b = Counter(a) #求数组中每个数字出现了几次
    print(b)
     
    print(  b[2]) #计算每个元素出现了几次
     
    输出
    Counter({2: 3, 4: 2, 3: 2, 1: 1})
    3
    [Finished in 0.0s]
    
     
     
    更多请看库函数解释
     
     
    Help on class Counter in module collections:
     
    class Counter(builtins.dict)
     |  Counter(*args, **kwds)
     |  
     |  Dict subclass for counting hashable items.  Sometimes called a bag
     |  or multiset.  Elements are stored as dictionary keys and their counts
     |  are stored as dictionary values.
     |  
     |  >>> c = Counter('abcdeabcdabcaba')  # count elements from a string
     |  
     |  >>> c.most_common(3)                # three most common elements
     |  [('a', 5), ('b', 4), ('c', 3)]
     |  >>> sorted(c)                       # list all unique elements
     |  ['a', 'b', 'c', 'd', 'e']
     |  >>> ''.join(sorted(c.elements()))   # list elements with repetitions
     |  'aaaaabbbbcccdde'
     |  >>> sum(c.values())                 # total of all counts
     |  15
     |  
     |  >>> c['a']                          # count of letter 'a'
     |  5
     |  >>> for elem in 'shazam':           # update counts from an iterable
     |  ...     c[elem] += 1                # by adding 1 to each element's count
     |  >>> c['a']                          # now there are seven 'a'
     |  7
     |  >>> del c['b']                      # remove all 'b'
     |  >>> c['b']                          # now there are zero 'b'
     |  0
     |  
     |  >>> d = Counter('simsalabim')       # make another counter
     |  >>> c.update(d)                     # add in the second counter
     |  >>> c['a']                          # now there are nine 'a'
     |  9
     |  
     |  >>> c.clear()                       # empty the counter
     |  >>> c
     |  Counter()
     |  
     |  Note:  If a count is set to zero or reduced to zero, it will remain
     |  in the counter until the entry is deleted or the counter is cleared:
     |  
     |  >>> c = Counter('aaabbc')
     |  >>> c['b'] -= 2                     # reduce the count of 'b' by two
     |  >>> c.most_common()                 # 'b' is still in, but its count is zero
     |  [('a', 3), ('c', 1), ('b', 0)]
     |  
     |  Method resolution order:
     |      Counter
     |      builtins.dict
     |      builtins.object
     |  
     |  Methods defined here:
     |  
     |  __add__(self, other)
     |      Add counts from two counters.
     |      
     |      >>> Counter('abbb') + Counter('bcc')
     |      Counter({'b': 4, 'c': 2, 'a': 1})
     |  
     |  __and__(self, other)
     |      Intersection is the minimum of corresponding counts.
     |      
     |      >>> Counter('abbb') & Counter('bcc')
     |      Counter({'b': 1})
     |  
     |  __delitem__(self, elem)
     |      Like dict.__delitem__() but does not raise KeyError for missing values.
     |  
     |  __iadd__(self, other)
     |      Inplace add from another counter, keeping only positive counts.
     |      
     |      >>> c = Counter('abbb')
     |      >>> c += Counter('bcc')
     |      >>> c
     |      Counter({'b': 4, 'c': 2, 'a': 1})
     |  
     |  __iand__(self, other)
     |      Inplace intersection is the minimum of corresponding counts.
     |      
     |      >>> c = Counter('abbb')
     |      >>> c &= Counter('bcc')
     |      >>> c
     |      Counter({'b': 1})
     |  
     |  __init__(*args, **kwds)
     |      Create a new, empty Counter object.  And if given, count elements
     |      from an input iterable.  Or, initialize the count from another mapping
     |      of elements to their counts.
     |      
     |      >>> c = Counter()                           # a new, empty counter
     |      >>> c = Counter('gallahad')                 # a new counter from an iterable
     |      >>> c = Counter({'a': 4, 'b': 2})           # a new counter from a mapping
     |      >>> c = Counter(a=4, b=2)                   # a new counter from keyword args
     |  
     |  __ior__(self, other)
     |      Inplace union is the maximum of value from either counter.
     |      
     |      >>> c = Counter('abbb')
     |      >>> c |= Counter('bcc')
     |      >>> c
     |      Counter({'b': 3, 'c': 2, 'a': 1})
     |  
     |  __isub__(self, other)
     |      Inplace subtract counter, but keep only results with positive counts.
     |      
     |      >>> c = Counter('abbbc')
     |      >>> c -= Counter('bccd')
     |      >>> c
     |      Counter({'b': 2, 'a': 1})
     |  
     |  __missing__(self, key)
     |      The count of elements not in the Counter is zero.
     |  
     |  __neg__(self)
     |      Subtracts from an empty counter.  Strips positive and zero counts,
     |      and flips the sign on negative counts.
     |  
     |  __or__(self, other)
     |      Union is the maximum of value in either of the input counters.
     |      
     |      >>> Counter('abbb') | Counter('bcc')
     |      Counter({'b': 3, 'c': 2, 'a': 1})
     |  
     |  __pos__(self)
     |      Adds an empty counter, effectively stripping negative and zero counts
     |  
     |  __reduce__(self)
     |      Helper for pickle.
     |  
     |  __repr__(self)
     |      Return repr(self).
     |  
     |  __sub__(self, other)
     |      Subtract count, but keep only results with positive counts.
     |      
     |      >>> Counter('abbbc') - Counter('bccd')
     |      Counter({'b': 2, 'a': 1})
     |  
     |  copy(self)
     |      Return a shallow copy.
     |  
     |  elements(self)
     |      Iterator over elements repeating each as many times as its count.
     |      
     |      >>> c = Counter('ABCABC')
     |      >>> sorted(c.elements())
     |      ['A', 'A', 'B', 'B', 'C', 'C']
     |      
     |      # Knuth's example for prime factors of 1836:  2**2 * 3**3 * 17**1
     |      >>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
     |      >>> product = 1
     |      >>> for factor in prime_factors.elements():     # loop over factors
     |      ...     product *= factor                       # and multiply them
     |      >>> product
     |      1836
     |      
     |      Note, if an element's count has been set to zero or is a negative
     |      number, elements() will ignore it.
     |  
     |  most_common(self, n=None)
     |      List the n most common elements and their counts from the most
     |      common to the least.  If n is None, then list all element counts.
     |      
     |      >>> Counter('abcdeabcdabcaba').most_common(3)
     |      [('a', 5), ('b', 4), ('c', 3)]
     |  
     |  subtract(*args, **kwds)
     |      Like dict.update() but subtracts counts instead of replacing them.
     |      Counts can be reduced below zero.  Both the inputs and outputs are
     |      allowed to contain zero and negative counts.
     |      
     |      Source can be an iterable, a dictionary, or another Counter instance.
     |      
     |      >>> c = Counter('which')
     |      >>> c.subtract('witch')             # subtract elements from another iterable
     |      >>> c.subtract(Counter('watch'))    # subtract elements from another counter
     |      >>> c['h']                          # 2 in which, minus 1 in witch, minus 1 in watch
     |      0
     |      >>> c['w']                          # 1 in which, minus 1 in witch, minus 1 in watch
     |      -1
     |  
     |  update(*args, **kwds)
     |      Like dict.update() but add counts instead of replacing them.
     |      
     |      Source can be an iterable, a dictionary, or another Counter instance.
     |      
     |      >>> c = Counter('which')
     |      >>> c.update('witch')           # add elements from another iterable
     |      >>> d = Counter('watch')
     |      >>> c.update(d)                 # add elements from another counter
     |      >>> c['h']                      # four 'h' in which, witch, and watch
     |      4
     |  
     |  ----------------------------------------------------------------------
     |  Class methods defined here:
     |  
     |  fromkeys(iterable, v=None) from builtins.type
     |      Create a new dictionary with keys from iterable and values set to value.
     |  
     |  ----------------------------------------------------------------------
     |  Data descriptors defined here:
     |  
     |  __dict__
     |      dictionary for instance variables (if defined)
     |  
     |  __weakref__
     |      list of weak references to the object (if defined)
     |  
     |  ----------------------------------------------------------------------
     |  Methods inherited from builtins.dict:
     |  
     |  __contains__(self, key, /)
     |      True if the dictionary has the specified key, else False.
     |  
     |  __eq__(self, value, /)
     |      Return self==value.
     |  
     |  __ge__(self, value, /)
     |      Return self>=value.
     |  
     |  __getattribute__(self, name, /)
     |      Return getattr(self, name).
     |  
     |  __getitem__(...)
     |      x.__getitem__(y) <==> x[y]
     |  
     |  __gt__(self, value, /)
     |      Return self>value.
     |  
     |  __iter__(self, /)
     |      Implement iter(self).
     |  
     |  __le__(self, value, /)
     |      Return self<=value.
     |  
     |  __len__(self, /)
     |      Return len(self).
     |  
     |  __lt__(self, value, /)
     |      Return self<value.
     |  
     |  __ne__(self, value, /)
     |      Return self!=value.
     |  
     |  __setitem__(self, key, value, /)
     |      Set self[key] to value.
     |  
     |  __sizeof__(...)
     |      D.__sizeof__() -> size of D in memory, in bytes
     |  
     |  clear(...)
     |      D.clear() -> None.  Remove all items from D.
     |  
     |  get(self, key, default=None, /)
     |      Return the value for key if key is in the dictionary, else default.
     |  
     |  items(...)
     |      D.items() -> a set-like object providing a view on D's items
     |  
     |  keys(...)
     |      D.keys() -> a set-like object providing a view on D's keys
     |  
     |  pop(...)
     |      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
     |  
     |  popitem(...)
     |      D.popitem() -> (k, v), remove and return some (key, value) pair as a
     |      2-tuple; but raise KeyError if D is empty.
     |  
     |  setdefault(self, key, default=None, /)
     |      Insert key with a value of default if key is not in the dictionary.
     |      
     |      Return the value for key if key is in the dictionary, else default.
     |  
     |  values(...)
     |      D.values() -> an object providing a view on D's values
     |  
     |  ----------------------------------------------------------------------
     |  Static methods inherited from builtins.dict:
     |  
     |  __new__(*args, **kwargs) from builtins.type
     |      Create and return a new object.  See help(type) for accurate signature.
     |  
     |  ----------------------------------------------------------------------
     |  Data and other attributes inherited from builtins.dict:
     |  
     |  __hash__ = None
     
    None
    [Finished in 0.1s]
    
    展开全文
  • counter项目.rar

    2021-04-26 08:44:34
    Counter V1.0 概要设计说明书.doc,Counter V1.0 详细设计说明书.doc,Counter V1.0软件需求规格说明书(评审用).doc,Counter V1.0项目工作任务书.doc
  • 关于Counter

    2020-05-05 22:51:12
    Counter Counter是一种比较简单的Meter,它是一种单值的度量类型, 或者说是一个单值计数器。Counter接口允许使用者使用一个固定值(必须为正数)进行计数。准确来说:Counter就是一个增量为正数的单值计数器。 举个很...
  • Counter

    2020-04-22 21:46:53
    Counter类是一个无序容器类型,用来跟踪值出现的次数,以字典的键值对形式存储,其中元素作为key,其计数作为value.计数值可以是任意整数 c = Counter() # 创建一个空的Counter类 c = Counter('gallahad') # 从一...
  • counter计数器

    2019-06-15 15:11:00
    计数器有三个重要的参数:counter-reset: counter-increment content counter-reset对计数器清零操作counter-increment是对计数器的自增一 content可以理解为将页面打出, 下图为执行代码和执行后的效果 转载于:...
  • python counter

    千次阅读 2018-05-28 18:33:48
    counter.most_common(n) 返回数目最多的前n个元素和对应个数a.substract(b) 返回一个Counter,Counter a减去Counter b,多的元素个数为正值,少的元素个数为负值counter.elements() 返回一个element列表,其中每个...
  • 【Jmeter】计数器Counter

    万次阅读 2017-01-14 12:18:51
    在写remote6接口候,在测试前需要进行测试分析并构造测试数据账号这些可以使用csv data config来实现还有一种不同进程需要不同的变量时,可以使用随机数 ${__Random} 其实还有一种蛮好用的Jmeter元素,即Counter...
  • counter调用Counter 类使用的方法为:from collection import CounterCounter用于计数,调用它会返回一个key为列表的值,value为该值的具体个数的对象我们首先创建一个一维数组:x=np.random.random_integers(1,10,...
  • Tailwind Counter

    2020-06-04 23:42:19
    input counter counter <link href="https://unpkg.com/tailwindcss@^1.0/dist/tailwind.min.css" rel="stylesheet"> <link href=...
  • Counter使用

    2020-01-18 12:39:22
    from collections import Counter import pandas as pd ws=pd.read_excel('F:\\项目\\2019.12.24\\20191224数据汇总\\20191224数据汇总\\2017\\分表数据\\四条数据.xlsx') wp=ws.title for i,j in Counter(wp)....
  • snmp CounterCounter 64 的区别 接受包数量的OID是多少 发送包数量OID是多少 接受字节OID是多少 发送字节OID是多少 (字节在网上找的 和大佬在程序里写的不一样)
  • motorcortex-counter-源码

    2021-03-17 04:13:49
    import Counter from "@kissmybutton/motorcortex-counter" ; 关键概念/功能 浏览器兼容性 Chrome合金 苹果浏览器 IE浏览器/边缘 火狐浏览器 歌剧 24+ 6+ 10+ 32+ 15岁以上 文献资料 导入插件并将其加载到...
  • python Counter

    2018-05-09 09:28:12
    8.3.2. Counter objects¶ A counter tool is provided to support convenient and rapid tallies. For example: >>>>>> # Tally occurrences of words in a list >>> cnt = Counter() >>> for word in ['red', '...
  • Python collections.Counter()用法

    万次阅读 多人点赞 2018-10-22 14:24:18
    Python collections.Counter用法什么是collectionsCounterCounter操作例子 什么是collections collections在python官方文档中的解释是High-performance container datatypes,直接的中文翻译解释高性能容量数据类型...
  • Counter类:Counter类的目的是用来跟踪值出现的次数。它是一个无序的容器类型,以字典的键值对形式存储,其中元素作为key,其计数作为value。计数值可以是任意的Interger(包括0和负数)。Counter类和其他语言的bags或...
  • CounterPath

    2015-11-07 02:47:46
    CounterPath
  • counter-reset:h1; dom中遇到这个就回重置计数器"h1" counter-increment:h1; dom中遇到这个就回在计数器"h1"上加1 content: counter(h1) "、"; before或after伪元素中使用...
  • collections.Counter

    2021-04-11 18:31:27
    collections.Counter
  • css counter属性被几乎所有浏览器(包括IE8)支持, 但是却不常使用, 这篇文章就带大家学习了解下这些属性 COUNTER-RESET 明译为计数器重置。形如: counter-reset: counter-name 常见写法为 /* Set counter-name ...
  • Jmeter 计数器 Counter

    2020-01-30 14:32:55
    Jmeter 计数器 Counter 一、Counter界面 Counter元素每次 Counter功能 Name 定义Counter名称 Comments 注释,描述Counter在业务中的作用 Starting value 开始值,初始值 Increment ...

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