python-Day3-set 集合-counter计数器-默认字典(defaultdict) -可命名元组(namedtuple)-有序字典(orderedDict)-双向队列(deque)--Qu...

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C语言为什么比起他语言块,因为C 会把代码变异成机器码
Pyhton 的 .pyc文件是什么
python 把.py文件编译成的.pyc文件是Python的字节码,

字符串本质是 字符数组,

python 一切事物都是对象,对象是类创建的,像 增加删除更改 都存在于类里边,也可以称作类的成员

 

set集合

set是一个无序且不重复的元素集合

  1 class set(object):
  2     """
  3     set() -> new empty set object
  4     set(iterable) -> new set object
  5     
  6     Build an unordered collection of unique elements.
  7     """
  8     def add(self, *args, **kwargs): # real signature unknown
  9         """ 添加 """
 10         """
 11         Add an element to a set.
 12         
 13         This has no effect if the element is already present.
 14         """
 15         pass
 16 
 17     def clear(self, *args, **kwargs): # real signature unknown
 18         """ Remove all elements from this set. """
 19         pass
 20 
 21     def copy(self, *args, **kwargs): # real signature unknown
 22         """ Return a shallow copy of a set. """
 23         pass
 24 
 25     def difference(self, *args, **kwargs): # real signature unknown
 26         """
 27         Return the difference of two or more sets as a new set.
 28         
 29         (i.e. all elements that are in this set but not the others.)
 30         """
 31         pass
 32 
 33     def difference_update(self, *args, **kwargs): # real signature unknown
 34         """ 删除当前set中的所有包含在 new set 里的元素 """
 35         """ Remove all elements of another set from this set. """
 36         pass
 37 
 38     def discard(self, *args, **kwargs): # real signature unknown
 39         """ 移除元素 """
 40         """
 41         Remove an element from a set if it is a member.
 42         
 43         If the element is not a member, do nothing.
 44         """
 45         pass
 46 
 47     def intersection(self, *args, **kwargs): # real signature unknown
 48         """ 取交集，新创建一个set """
 49         """
 50         Return the intersection of two or more sets as a new set.
 51         
 52         (i.e. elements that are common to all of the sets.)
 53         """
 54         pass
 55 
 56     def intersection_update(self, *args, **kwargs): # real signature unknown
 57         """ 取交集，修改原来set """
 58         """ Update a set with the intersection of itself and another. """
 59         pass
 60 
 61     def isdisjoint(self, *args, **kwargs): # real signature unknown
 62         """ 如果没有交集，返回true  """
 63         """ Return True if two sets have a null intersection. """
 64         pass
 65 
 66     def issubset(self, *args, **kwargs): # real signature unknown
 67         """ 是否是子集 """
 68         """ Report whether another set contains this set. """
 69         pass
 70 
 71     def issuperset(self, *args, **kwargs): # real signature unknown
 72         """ 是否是父集 """
 73         """ Report whether this set contains another set. """
 74         pass
 75 
 76     def pop(self, *args, **kwargs): # real signature unknown
 77         """ 移除 """
 78         """
 79         Remove and return an arbitrary set element.
 80         Raises KeyError if the set is empty.
 81         """
 82         pass
 83 
 84     def remove(self, *args, **kwargs): # real signature unknown
 85         """ 移除 """
 86         """
 87         Remove an element from a set; it must be a member.
 88         
 89         If the element is not a member, raise a KeyError.
 90         """
 91         pass
 92 
 93     def symmetric_difference(self, *args, **kwargs): # real signature unknown
 94         """ 差集，创建新对象"""
 95         """
 96         Return the symmetric difference of two sets as a new set.
 97         
 98         (i.e. all elements that are in exactly one of the sets.)
 99         """
100         pass
101 
102     def symmetric_difference_update(self, *args, **kwargs): # real signature unknown
103         """ 差集，改变原来 """
104         """ Update a set with the symmetric difference of itself and another. """
105         pass
106 
107     def union(self, *args, **kwargs): # real signature unknown
108         """ 并集 """
109         """
110         Return the union of sets as a new set.
111         
112         (i.e. all elements that are in either set.)
113         """
114         pass
115 
116     def update(self, *args, **kwargs): # real signature unknown
117         """ 更新 """
118         """ Update a set with the union of itself and others. """
119         pass
120 
121     def __and__(self, y): # real signature unknown; restored from __doc__
122         """ x.__and__(y) <==> x&y """
123         pass
124 
125     def __cmp__(self, y): # real signature unknown; restored from __doc__
126         """ x.__cmp__(y) <==> cmp(x,y) """
127         pass
128 
129     def __contains__(self, y): # real signature unknown; restored from __doc__
130         """ x.__contains__(y) <==> y in x. """
131         pass
132 
133     def __eq__(self, y): # real signature unknown; restored from __doc__
134         """ x.__eq__(y) <==> x==y """
135         pass
136 
137     def __getattribute__(self, name): # real signature unknown; restored from __doc__
138         """ x.__getattribute__('name') <==> x.name """
139         pass
140 
141     def __ge__(self, y): # real signature unknown; restored from __doc__
142         """ x.__ge__(y) <==> x>=y """
143         pass
144 
145     def __gt__(self, y): # real signature unknown; restored from __doc__
146         """ x.__gt__(y) <==> x>y """
147         pass
148 
149     def __iand__(self, y): # real signature unknown; restored from __doc__
150         """ x.__iand__(y) <==> x&=y """
151         pass
152 
153     def __init__(self, seq=()): # known special case of set.__init__
154         """
155         set() -> new empty set object
156         set(iterable) -> new set object
157         
158         Build an unordered collection of unique elements.
159         # (copied from class doc)
160         """
161         pass
162 
163     def __ior__(self, y): # real signature unknown; restored from __doc__
164         """ x.__ior__(y) <==> x|=y """
165         pass
166 
167     def __isub__(self, y): # real signature unknown; restored from __doc__
168         """ x.__isub__(y) <==> x-=y """
169         pass
170 
171     def __iter__(self): # real signature unknown; restored from __doc__
172         """ x.__iter__() <==> iter(x) """
173         pass
174 
175     def __ixor__(self, y): # real signature unknown; restored from __doc__
176         """ x.__ixor__(y) <==> x^=y """
177         pass
178 
179     def __len__(self): # real signature unknown; restored from __doc__
180         """ x.__len__() <==> len(x) """
181         pass
182 
183     def __le__(self, y): # real signature unknown; restored from __doc__
184         """ x.__le__(y) <==> x<=y """
185         pass
186 
187     def __lt__(self, y): # real signature unknown; restored from __doc__
188         """ x.__lt__(y) <==> x"""
189         pass
190 
191     @staticmethod # known case of __new__
192     def __new__(S, *more): # real signature unknown; restored from __doc__
193         """ T.__new__(S, ...) -> a new object with type S, a subtype of T """
194         pass
195 
196     def __ne__(self, y): # real signature unknown; restored from __doc__
197         """ x.__ne__(y) <==> x!=y """
198         pass
199 
200     def __or__(self, y): # real signature unknown; restored from __doc__
201         """ x.__or__(y) <==> x|y """
202         pass
203 
204     def __rand__(self, y): # real signature unknown; restored from __doc__
205         """ x.__rand__(y) <==> y&x """
206         pass
207 
208     def __reduce__(self, *args, **kwargs): # real signature unknown
209         """ Return state information for pickling. """
210         pass
211 
212     def __repr__(self): # real signature unknown; restored from __doc__
213         """ x.__repr__() <==> repr(x) """
214         pass
215 
216     def __ror__(self, y): # real signature unknown; restored from __doc__
217         """ x.__ror__(y) <==> y|x """
218         pass
219 
220     def __rsub__(self, y): # real signature unknown; restored from __doc__
221         """ x.__rsub__(y) <==> y-x """
222         pass
223 
224     def __rxor__(self, y): # real signature unknown; restored from __doc__
225         """ x.__rxor__(y) <==> y^x """
226         pass
227 
228     def __sizeof__(self): # real signature unknown; restored from __doc__
229         """ S.__sizeof__() -> size of S in memory, in bytes """
230         pass
231 
232     def __sub__(self, y): # real signature unknown; restored from __doc__
233         """ x.__sub__(y) <==> x-y """
234         pass
235 
236     def __xor__(self, y): # real signature unknown; restored from __doc__
237         """ x.__xor__(y) <==> x^y """
238         pass
239 
240     __hash__ = None
241 
242 set

set集合

集合里不允许重复的元素存在
对象是由类创建的
要创建一个set

创建一个 set无序集合
列表有两种创建方法:
a1 = []
a2 = list()

set 通过类创建对象、
s1 = set() 这就是创建了一个集合的对象
现在可以往里边添加对象

 

用途:
#比如说在写爬虫的时候访问一个电商网站,访问第一个页面的时候收集到了一个商品名称,在访问第二个页面的时候又收集了一个商品名称,这个时候集合就起作用了,集合里不会有重复的元素

#访问速度快
#天生解决了重复问题

 

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 #定义一个空的集合
 4 s1 = set()
 5 #给集合添加对象
 6 s1.add('amd')
 7 #打印集合
 8 print(s1)
 9 #打印类型
10 print(type(s1))
11 --------------------------------------------------------------------------------
12 #打印添加对象后的集合
13 {'amd'}
14 #打印显示所属类型为集合
15 <class 'set'>
16 
17 --------------------------------------------------------------------------------
18 __author__ = 'Administrator'
19 # -*- coding:utf-8 -*-
20 s1 = set()
21 #添加对象
22 s1.add('amd')
23 #添加对象
24 s1.add('amd')
25 print(s1)
26 print(s1)
27 print(type(s1))
28 --------------------------------------------------------------------------------
29 输出:
30 #这里表明了 集合里不允许重复的元素存在所以只打印了一个
31 {'amd'}
32 {'amd'}
33 <class 'set'>

创建set集合

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 s1 = set()
 4 s1.add('amd')
 5 s1.add('amd')
 6 print(s1)
 7 #打印清空数据
 8 print(s1.clear())
 9 -----------------------------------------------------------------------------------
10 输出:
11 #数据存在的时候
12 {'amd'}
13 #清空后会显示None
14 None

set清空数据clear()

 1 '''
 2 #找到不同的创建一个新的集合，
 3 #注意:             而不是修改原来的集合
 4  def difference(self, *args, **kwargs): # real signature unknown
 5         """
 6 '''
 7 #set()内可以传入一个列表,传入的参数set会自动的将列表转为集合,并且把重复的去掉
 8 aa = set(['a','b','c','c'])
 9 print(type(aa))
10 print(aa)
11 ww = set(['a','c'])
12 a1 = aa.difference(ww)
13 print(a1)

difference(self, *args, **kwargs):对比两个集合找到不同后生成一个新的集合

 1 '''
 2 #删除当前set中的所有包含在参数里的元素
 3 #在原有的集合里删除所传入的元素
 4 #注意:    是在原有的集合里删除,不是生成信的集合
 5 def difference_update(self, *args, **kwargs): # real signature unknown
 6         """ Remove all elements of another set from this set. """
 7         pass
 8 '''
 9 aa = set(['a','b','c','c'])
10 a1 = set(['a','c'])
11 #difference_update 没有生成信的集合而是修改了原有的集合
12 a2 = aa.difference_update(a1)
13 print(aa)
14 print(a2)

difference_update(self, *args, **kwargs):删除当前set集合中的所有包含在参数里的元素

#取交集,取两个集合中相同的交集,
#注意:  并且生成一个新的集合,不是修改原来的集合
   def intersection(self, *args, **kwargs): # real signature unknown
        """
        Return the intersection of two sets as a new set.

        (i.e. all elements that are in both sets.)
        """
        pass
        '''
a = set(['a','c','d'])
a1 = set(['g','w','a'])
ww = a.intersection(a1)
print(ww)
print(type(ww))
-----------------------------------------------------------------------------------
输出:
{'a'}

 

 1 '''
 2 #对比两个集合取交集,
 3 #注意: 这里是取到的交集修改原来的集合,不是生成一个新的集合
 4  def intersection_update(self, *args, **kwargs): # real signature unknown
 5         """ Update a set with the intersection of itself and another. """
 6         pass
 7                 '''
 8 a = set(['a','c','d'])
 9 a1 = set(['g','w','a'])
10 ww = a.intersection_update(a1)
11 print(a)
12 print(type(a))
13 print(ww)
14 print(type(ww))
15 ------------------------------------------------------------------------------------
16 输出:
17 {'a'}
18 <class 'set'>
19 None
20 <class 'NoneType'>

 

 1 '''
 2 #对比两个集合的交集,如果没有交集 返回True
 3 def isdisjoint(self, *args, **kwargs): # real signature unknown
 4         """ Return True if two sets have a null intersection. """
 5         pass
 6                 '''
 7 a = set(['a','c','d'])
 8 a1 = set(['g','w',])
 9 ww = a.isdisjoint(a1)
10 print(ww)
11 -----------------------------------------------------------------------------------
12 输出:
13 True
14 ==============================================
15 a = set(['a','c','d',])
16 a1 = set(['g','w','a',])
17 ww = a.isdisjoint(a1)
18 print(ww)
19 ----------------------------------------------------------------------------------
20 输出:
21 False

isdisjoint(self, *args, **kwargs):对比两个集合的交集,如果没有交集 返回True

 

 1 '''
 2 #是否是子集的
 3 def issubset(self, *args, **kwargs): # real signature unknown
 4         """ Report whether another set contains this set. """
 5         pass
 6                 '''
 7 a = set(['a','c','d',])
 8 a1 = set(['a','c','d',])
 9 #测试是否 a 中的每一个元素都在 a1 中
10 ww = a.issubset(a1)
11 print(ww)
12 ----------------------------------------------------------------------------------
13 输出:
14 True

issubset(self, *args, **kwargs):是否是子集的

 

 1 '''
 2 #是否是父集
 3  def issuperset(self, *args, **kwargs): # real signature unknown
 4         """ Report whether this set contains another set. """
 5         pass
 6                 '''
 7 a = set(['a','c','d',])
 8 a1 = set(['a','c','d',])
 9 #测试是否 a1 中的每一个元素都在 a 中
10 ee = a.issuperset(a1)
11 print(ee)
12 -----------------------------------------------------------------------------------
13 输出:
14 True

def issuperset(self, *args, **kwargs):

 

 1 '''
 2 #pop是去一个元素里随机取一个值并且赋给一个新的变量
 3  def pop(self, *args, **kwargs): # real signature unknown
 4         """
 5         Remove and return an arbitrary set element.
 6         Raises KeyError if the set is empty.
 7         """
 8         pass
 9                 '''
10 a = set(['a','c','d',])
11 a1 = set(['a','c','d',])
12 w1 = a.pop()
13 print(w1)

def pop(self, *args, **kwargs):

 

 1 '''
 2 #移除一个元素
 3 def remove(self, *args, **kwargs): # real signature unknown
 4         """
 5         Remove an element from a set; it must be a member.
 6         
 7         If the element is not a member, raise a KeyError.
 8         """
 9         pass
10 
11                 '''
12 a = set(['a','c','d',])
13 a.remove('c')
14 print(a)
15 ------------------------------------------------------------------------------------
16 输出：
17 {'d', 'a'}

def remove(self, *args, **kwargs):#移除一个元素

 

 1 '''
 2 #计算两个集合的 差集
 3 #注意: 计算两个几个的差集 并创建新的集合
 4 def symmetric_difference(self, *args, **kwargs): # real signature unknown
 5         """
 6         Return the symmetric difference of two sets as a new set.
 7 
 8         (i.e. all elements that are in exactly one of the sets.)
 9         """
10         pass
11 
12                 '''
13 a = set(['a','c','d',])
14 b = set(['a','c','w',])
15 ww = a.symmetric_difference(b)
16 print(ww)
17 ----------------------------------------------------------------------------------
18 输出:
19 {'w', 'd'}

def symmetric_difference(self, *args, **kwargs):计算两个集合的 差集，并生成新的集合

 

 1 '''
 2 #计算两个集合的 差集
 3 #注意: 计算两个几个的差集 并修改原来的集合
 4 def symmetric_difference_update(self, *args, **kwargs): # real signature unknown
 5         """ Update a set with the symmetric difference of itself and another. """
 6         pass
 7 
 8                 '''
 9 a = set(['a','c','d',])
10 b = set(['a','c','w',])
11 a.symmetric_difference_update(b)
12 #打印两个几个的差集
13 print(a)
14 ----------------------------------------------------------------------------------
15 输出:
16 {'d', 'w'}
17 ==============================================
18 a = set(['a','c','d',])
19 b = set(['a','c','w',])
20 a.symmetric_difference_update(b)
21 #打印两个集合的交集
22 print(b)
23 ------------------------------------------------------------------------------
24 输出:
25 {'c', 'a', 'w'}

def symmetric_difference_update(self, *args, **kwargs):计算两个几个的差集 并修改原来的集合

 1 '''
 2 #取两个集合的并集
 3 #注意:将两个集合去除重复,并合并生成一个新的变量
 4 def union(self, *args, **kwargs): # real signature unknown
 5         """
 6         Return the union of sets as a new set.
 7 
 8         (i.e. all elements that are in either set.)
 9         """
10         pass
11 
12                 '''
13 a = set(['a','c','d',])
14 b = set(['a','c','w','wer'])
15 bb = a.union(b)
16 print(bb)
17 ----------------------------------------------------------------------------------
18 输出:
19 {'wer', 'a', 'c', 'w', 'd'}

def union(self, *args, **kwargs):#注意:将两个集合去除重复,并合并生成一个新的变量

 1 '''
 2 #更新一个集合
 3 #注意:这里更新的原有的集合,不是更新后新生成一个集合
 4 def update(self, *args, **kwargs): # real signature unknown
 5         """ Update a set with the union of itself and others. """
 6         pass
 7 
 8                 '''
 9 a = set(['a','c','d',])
10 b = set(['a','c','w','wer'])
11 a.update(set(['wewewe']))
12 print(a)
13 a.update(b)
14 print(a)
15 ----------------------------------------------------------------------------------
16 输出:
17 {'wewewe', 'a', 'd', 'c'}
18 {'a', 'c', 'wewewe', 'wer', 'd', 'w'}

def update(self, *args, **kwargs): 更新一个集合

 

练习：寻找差异

 1 # 数据库中原有
 2 old_dict = {
 3     "#1":{ 'hostname':c1, 'cpu_count': 2, 'mem_capicity': 80 },
 4     "#2":{ 'hostname':c1, 'cpu_count': 2, 'mem_capicity': 80 }
 5     "#3":{ 'hostname':c1, 'cpu_count': 2, 'mem_capicity': 80 }
 6 }
 7   
 8 # cmdb 新汇报的数据
 9 new_dict = {
10     "#1":{ 'hostname':c1, 'cpu_count': 2, 'mem_capicity': 800 },
11     "#3":{ 'hostname':c1, 'cpu_count': 2, 'mem_capicity': 80 }
12     "#4":{ 'hostname':c2, 'cpu_count': 2, 'mem_capicity': 80 }
13 }

注意：1.无需考虑内部元素是否改变，只要原来存在，新汇报也存在，就是需要更新

　　　2.原来的不存在就插入,新汇报的就插入

　　　3.原来的存在,新汇报的不存在就删除

　　　4.只需要打印出 更新的有哪些,删除的有哪些,插入的有哪些

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 old_dict = {
 4     "#1":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 },
 5     "#2":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 },
 6     "#3":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 },
 7 }
 8 
 9 new_dict = {
10     "#1":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 800 },
11     "#3":{ 'hostname':'c1', 'cpu_count': 2, 'mem_capicity': 80 },
12     "#4":{ 'hostname':'c2', 'cpu_count': 2, 'mem_capicity': 80 },
13 }
14 #用set集合中的取交集来判断字典的key是否都存在,如果都存在的生成一个新的变量,并且定义为集合
15 update_dict = set(old_dict.keys()).intersection(set(new_dict.keys()))
16 #print(update_dict)
17 #定义一个空的要插入的列表
18 new_list = []
19 #定义一个空的要删除的列表
20 delete_list = []
21 #这里是把原来的数据old_dict 的key赋值给i
22 for i in old_dict.keys():
23 #这里判断循环中的 i 如果不在update_dict集合里,就添加到删除列表里
24     if i not in update_dict:
25         delete_list.append(i)
26 #这里是把汇报上来的的数据new_dict 的key赋值给i
27 for i in new_dict.keys():
28 #这里判断 i 如果不在更新的集合中,就添加到插入的列表里
29     if i not in update_dict:
30         new_list.append(i)
31 #一下是前几天提到的格式化输出,下面列出了两种方法,
32 msg = '''
33 更新:%s
34 插入:%s
35 删除:%s
36 ''' %(update_dict,new_list,delete_list)
37 print("更新:%s\n删除:%s\n插入:%s" %(update_dict,delete_list,new_list))
38 print(msg)

找差异源代码

 collections系列

Counter功能在 collections模块里所有在使用 Counter功能的时候需要导入 collections 模块(import collections)

一.计数器(counter)

Counter是对字典类型的补充,用于追踪值得出现次数.

PS:具备字典的所有功能 加上 自己的功能

 

collections 在Python里是一个文件夹 python 在导入的时候 是导入的 collections 的文件夹,导入之后 Python 会在导入的文件夹内查找Counter,找到Counter之后就可以创建对象

 

collections.Counter() 的功能是将元素出现的次数做一个统计
例:

1 __author__ = 'Administrator'
2 import collections
3 aa = collections.Counter('aabbccddeeffgg')
4 print(aa)
5 print(type(aa))
6 -----------------------------------------------------------------------------------
7 输出:
8 Counter({'g': 2, 'd': 2, 'b': 2, 'c': 2, 'f': 2, 'a': 2, 'e': 2})
9 <class 'collections.Counter'>

  1 ########################################################################
  2 ###  Counter
  3 ########################################################################
  4 
  5 class Counter(dict):
  6     '''Dict subclass for counting hashable items.  Sometimes called a bag
  7     or multiset.  Elements are stored as dictionary keys and their counts
  8     are stored as dictionary values.
  9 
 10     >>> c = Counter('abcdeabcdabcaba')  # count elements from a string
 11 
 12     >>> c.most_common(3)                # three most common elements
 13     [('a', 5), ('b', 4), ('c', 3)]
 14     >>> sorted(c)                       # list all unique elements
 15     ['a', 'b', 'c', 'd', 'e']
 16     >>> ''.join(sorted(c.elements()))   # list elements with repetitions
 17     'aaaaabbbbcccdde'
 18     >>> sum(c.values())                 # total of all counts
 19 
 20     >>> c['a']                          # count of letter 'a'
 21     >>> for elem in 'shazam':           # update counts from an iterable
 22     ...     c[elem] += 1                # by adding 1 to each element's count
 23     >>> c['a']                          # now there are seven 'a'
 24     >>> del c['b']                      # remove all 'b'
 25     >>> c['b']                          # now there are zero 'b'
 26 
 27     >>> d = Counter('simsalabim')       # make another counter
 28     >>> c.update(d)                     # add in the second counter
 29     >>> c['a']                          # now there are nine 'a'
 30 
 31     >>> c.clear()                       # empty the counter
 32     >>> c
 33     Counter()
 34 
 35     Note:  If a count is set to zero or reduced to zero, it will remain
 36     in the counter until the entry is deleted or the counter is cleared:
 37 
 38     >>> c = Counter('aaabbc')
 39     >>> c['b'] -= 2                     # reduce the count of 'b' by two
 40     >>> c.most_common()                 # 'b' is still in, but its count is zero
 41     [('a', 3), ('c', 1), ('b', 0)]
 42 
 43     '''
 44     # References:
 45     #   http://en.wikipedia.org/wiki/Multiset
 46     #   http://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html
 47     #   http://www.demo2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm
 48     #   http://code.activestate.com/recipes/259174/
 49     #   Knuth, TAOCP Vol. II section 4.6.3
 50 
 51     def __init__(self, iterable=None, **kwds):
 52         '''Create a new, empty Counter object.  And if given, count elements
 53         from an input iterable.  Or, initialize the count from another mapping
 54         of elements to their counts.
 55 
 56         >>> c = Counter()                           # a new, empty counter
 57         >>> c = Counter('gallahad')                 # a new counter from an iterable
 58         >>> c = Counter({'a': 4, 'b': 2})           # a new counter from a mapping
 59         >>> c = Counter(a=4, b=2)                   # a new counter from keyword args
 60 
 61         '''
 62         super(Counter, self).__init__()
 63         self.update(iterable, **kwds)
 64 
 65     def __missing__(self, key):
 66         """ 对于不存在的元素，返回计数器为0 """
 67         'The count of elements not in the Counter is zero.'
 68         # Needed so that self[missing_item] does not raise KeyError
 69         return 0
 70 
 71     def most_common(self, n=None):
 72         """ 数量大于等n的所有元素和计数器 """
 73         '''List the n most common elements and their counts from the most
 74         common to the least.  If n is None, then list all element counts.
 75 
 76         >>> Counter('abcdeabcdabcaba').most_common(3)
 77         [('a', 5), ('b', 4), ('c', 3)]
 78 
 79         '''
 80         # Emulate Bag.sortedByCount from Smalltalk
 81         if n is None:
 82             return sorted(self.iteritems(), key=_itemgetter(1), reverse=True)
 83         return _heapq.nlargest(n, self.iteritems(), key=_itemgetter(1))
 84 
 85     def elements(self):
 86         """ 计数器中的所有元素，注：此处非所有元素集合，而是包含所有元素集合的迭代器 """
 87         '''Iterator over elements repeating each as many times as its count.
 88 
 89         >>> c = Counter('ABCABC')
 90         >>> sorted(c.elements())
 91         ['A', 'A', 'B', 'B', 'C', 'C']
 92 
 93         # Knuth's example for prime factors of 1836:  2**2 * 3**3 * 17**1
 94         >>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
 95         >>> product = 1
 96         >>> for factor in prime_factors.elements():     # loop over factors
 97         ...     product *= factor                       # and multiply them
 98         >>> product
 99 
100         Note, if an element's count has been set to zero or is a negative
101         number, elements() will ignore it.
102 
103         '''
104         # Emulate Bag.do from Smalltalk and Multiset.begin from C++.
105         return _chain.from_iterable(_starmap(_repeat, self.iteritems()))
106 
107     # Override dict methods where necessary
108 
109     @classmethod
110     def fromkeys(cls, iterable, v=None):
111         # There is no equivalent method for counters because setting v=1
112         # means that no element can have a count greater than one.
113         raise NotImplementedError(
114             'Counter.fromkeys() is undefined.  Use Counter(iterable) instead.')
115 
116     def update(self, iterable=None, **kwds):
117         """ 更新计数器，其实就是增加；如果原来没有，则新建，如果有则加一 """
118         '''Like dict.update() but add counts instead of replacing them.
119 
120         Source can be an iterable, a dictionary, or another Counter instance.
121 
122         >>> c = Counter('which')
123         >>> c.update('witch')           # add elements from another iterable
124         >>> d = Counter('watch')
125         >>> c.update(d)                 # add elements from another counter
126         >>> c['h']                      # four 'h' in which, witch, and watch
127 
128         '''
129         # The regular dict.update() operation makes no sense here because the
130         # replace behavior results in the some of original untouched counts
131         # being mixed-in with all of the other counts for a mismash that
132         # doesn't have a straight-forward interpretation in most counting
133         # contexts.  Instead, we implement straight-addition.  Both the inputs
134         # and outputs are allowed to contain zero and negative counts.
135 
136         if iterable is not None:
137             if isinstance(iterable, Mapping):
138                 if self:
139                     self_get = self.get
140                     for elem, count in iterable.iteritems():
141                         self[elem] = self_get(elem, 0) + count
142                 else:
143                     super(Counter, self).update(iterable) # fast path when counter is empty
144             else:
145                 self_get = self.get
146                 for elem in iterable:
147                     self[elem] = self_get(elem, 0) + 1
148         if kwds:
149             self.update(kwds)
150 
151     def subtract(self, iterable=None, **kwds):
152         """ 相减，原来的计数器中的每一个元素的数量减去后添加的元素的数量 """
153         '''Like dict.update() but subtracts counts instead of replacing them.
154         Counts can be reduced below zero.  Both the inputs and outputs are
155         allowed to contain zero and negative counts.
156 
157         Source can be an iterable, a dictionary, or another Counter instance.
158 
159         >>> c = Counter('which')
160         >>> c.subtract('witch')             # subtract elements from another iterable
161         >>> c.subtract(Counter('watch'))    # subtract elements from another counter
162         >>> c['h']                          # 2 in which, minus 1 in witch, minus 1 in watch
163         >>> c['w']                          # 1 in which, minus 1 in witch, minus 1 in watch
164         -1
165 
166         '''
167         if iterable is not None:
168             self_get = self.get
169             if isinstance(iterable, Mapping):
170                 for elem, count in iterable.items():
171                     self[elem] = self_get(elem, 0) - count
172             else:
173                 for elem in iterable:
174                     self[elem] = self_get(elem, 0) - 1
175         if kwds:
176             self.subtract(kwds)
177 
178     def copy(self):
179         """ 拷贝 """
180         'Return a shallow copy.'
181         return self.__class__(self)
182 
183     def __reduce__(self):
184         """ 返回一个元组（类型，元组） """
185         return self.__class__, (dict(self),)
186 
187     def __delitem__(self, elem):
188         """ 删除元素 """
189         'Like dict.__delitem__() but does not raise KeyError for missing values.'
190         if elem in self:
191             super(Counter, self).__delitem__(elem)
192 
193     def __repr__(self):
194         if not self:
195             return '%s()' % self.__class__.__name__
196         items = ', '.join(map('%r: %r'.__mod__, self.most_common()))
197         return '%s({%s})' % (self.__class__.__name__, items)
198 
199     # Multiset-style mathematical operations discussed in:
200     #       Knuth TAOCP Volume II section 4.6.3 exercise 19
201     #       and at http://en.wikipedia.org/wiki/Multiset
202     #
203     # Outputs guaranteed to only include positive counts.
204     #
205     # To strip negative and zero counts, add-in an empty counter:
206     #       c += Counter()
207 
208     def __add__(self, other):
209         '''Add counts from two counters.
210 
211         >>> Counter('abbb') + Counter('bcc')
212         Counter({'b': 4, 'c': 2, 'a': 1})
213 
214         '''
215         if not isinstance(other, Counter):
216             return NotImplemented
217         result = Counter()
218         for elem, count in self.items():
219             newcount = count + other[elem]
220             if newcount > 0:
221                 result[elem] = newcount
222         for elem, count in other.items():
223             if elem not in self and count > 0:
224                 result[elem] = count
225         return result
226 
227     def __sub__(self, other):
228         ''' Subtract count, but keep only results with positive counts.
229 
230         >>> Counter('abbbc') - Counter('bccd')
231         Counter({'b': 2, 'a': 1})
232 
233         '''
234         if not isinstance(other, Counter):
235             return NotImplemented
236         result = Counter()
237         for elem, count in self.items():
238             newcount = count - other[elem]
239             if newcount > 0:
240                 result[elem] = newcount
241         for elem, count in other.items():
242             if elem not in self and count < 0:
243                 result[elem] = 0 - count
244         return result
245 
246     def __or__(self, other):
247         '''Union is the maximum of value in either of the input counters.
248 
249         >>> Counter('abbb') | Counter('bcc')
250         Counter({'b': 3, 'c': 2, 'a': 1})
251 
252         '''
253         if not isinstance(other, Counter):
254             return NotImplemented
255         result = Counter()
256         for elem, count in self.items():
257             other_count = other[elem]
258             newcount = other_count if count < other_count else count
259             if newcount > 0:
260                 result[elem] = newcount
261         for elem, count in other.items():
262             if elem not in self and count > 0:
263                 result[elem] = count
264         return result
265 
266     def __and__(self, other):
267         ''' Intersection is the minimum of corresponding counts.
268 
269         >>> Counter('abbb') & Counter('bcc')
270         Counter({'b': 1})
271 
272         '''
273         if not isinstance(other, Counter):
274             return NotImplemented
275         result = Counter()
276         for elem, count in self.items():
277             other_count = other[elem]
278             newcount = count if count < other_count else other_count
279             if newcount > 0:
280                 result[elem] = newcount
281         return result
282 
283 Counter

collections方法

方法:most_common 是按照元素出现的次数 从多到少取 前4位 "we = aa.most_common(4)"

__author__ = 'Administrator'
import collections
aa = collections.Counter('aabbcccddddeeeeeffffffggggggg')

we = aa.most_common(4)

print(we)
print(type(aa))
----------------------------------------------------------------------------------
输出:
[('g', 7), ('f', 6), ('e', 5), ('d', 4)]
<class 'collections.Counter'>

 elements

 items

__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import collections
aa = collections.Counter('aabbccddeeffgg')
for item in aa.elements():
    print(item)
for k,v in aa.items():
    print(k,v)
---------------------------------------------------------------------------------------------
输出:
b
b
e
e
f
f
c
c
a
a
d
d
g
g
b 2
e 2
f 2
c 2
a 2
d 2
g 2

　　

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import collections
 4 aa = collections.Counter(['11','22','33','44'])
 5 print(aa)
 6 aa.update(['aa','33','ff'])
 7 print(aa)
 8 --------------------------------------------------------------
 9 输出:
10 Counter({'11': 1, '44': 1, '22': 1, '33': 1})
11 Counter({'33': 2, '11': 1, 'aa': 1, '22': 1, '44': 1, 'ff': 1})

update更新计数器,增加元素出现的次数

__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import collections
aa = collections.Counter(['11','22','33','44'])
print(aa)
aa.update(['aa','33','ff'])
print(aa)

aa.subtract(['aa','33'])
print(aa)
--------------------------------------
输出:
Counter({'11': 1, '44': 1, '33': 1, '22': 1})
                #原来33 出现了两次
Counter({'33': 2, 'aa': 1, '44': 1, '22': 1, 'ff': 1, '11': 1})
                                                             #通过subtract 33变成了一次
Counter({'44': 1, '22': 1, 'ff': 1, '11': 1, '33': 1, 'aa': 0})    

subtract 减少元素出现的次数

 

二、有序字典(orderedDict)
orderdDict是对字典类型的补充，他记住了字典元素添加的顺序

  1 class OrderedDict(dict):
  2     'Dictionary that remembers insertion order'
  3     # An inherited dict maps keys to values.
  4     # The inherited dict provides __getitem__, __len__, __contains__, and get.
  5     # The remaining methods are order-aware.
  6     # Big-O running times for all methods are the same as regular dictionaries.
  7 
  8     # The internal self.__map dict maps keys to links in a doubly linked list.
  9     # The circular doubly linked list starts and ends with a sentinel element.
 10     # The sentinel element never gets deleted (this simplifies the algorithm).
 11     # Each link is stored as a list of length three:  [PREV, NEXT, KEY].
 12 
 13     def __init__(self, *args, **kwds):
 14         '''Initialize an ordered dictionary.  The signature is the same as
 15         regular dictionaries, but keyword arguments are not recommended because
 16         their insertion order is arbitrary.
 17 
 18         '''
 19         if len(args) > 1:
 20             raise TypeError('expected at most 1 arguments, got %d' % len(args))
 21         try:
 22             self.__root
 23         except AttributeError:
 24             self.__root = root = []                     # sentinel node
 25             root[:] = [root, root, None]
 26             self.__map = {}
 27         self.__update(*args, **kwds)
 28 
 29     def __setitem__(self, key, value, dict_setitem=dict.__setitem__):
 30         'od.__setitem__(i, y) <==> od[i]=y'
 31         # Setting a new item creates a new link at the end of the linked list,
 32         # and the inherited dictionary is updated with the new key/value pair.
 33         if key not in self:
 34             root = self.__root
 35             last = root[0]
 36             last[1] = root[0] = self.__map[key] = [last, root, key]
 37         return dict_setitem(self, key, value)
 38 
 39     def __delitem__(self, key, dict_delitem=dict.__delitem__):
 40         'od.__delitem__(y) <==> del od[y]'
 41         # Deleting an existing item uses self.__map to find the link which gets
 42         # removed by updating the links in the predecessor and successor nodes.
 43         dict_delitem(self, key)
 44         link_prev, link_next, _ = self.__map.pop(key)
 45         link_prev[1] = link_next                        # update link_prev[NEXT]
 46         link_next[0] = link_prev                        # update link_next[PREV]
 47 
 48     def __iter__(self):
 49         'od.__iter__() <==> iter(od)'
 50         # Traverse the linked list in order.
 51         root = self.__root
 52         curr = root[1]                                  # start at the first node
 53         while curr is not root:
 54             yield curr[2]                               # yield the curr[KEY]
 55             curr = curr[1]                              # move to next node
 56 
 57     def __reversed__(self):
 58         'od.__reversed__() <==> reversed(od)'
 59         # Traverse the linked list in reverse order.
 60         root = self.__root
 61         curr = root[0]                                  # start at the last node
 62         while curr is not root:
 63             yield curr[2]                               # yield the curr[KEY]
 64             curr = curr[0]                              # move to previous node
 65 
 66     def clear(self):
 67         'od.clear() -> None.  Remove all items from od.'
 68         root = self.__root
 69         root[:] = [root, root, None]
 70         self.__map.clear()
 71         dict.clear(self)
 72 
 73     # -- the following methods do not depend on the internal structure --
 74 
 75     def keys(self):
 76         'od.keys() -> list of keys in od'
 77         return list(self)
 78 
 79     def values(self):
 80         'od.values() -> list of values in od'
 81         return [self[key] for key in self]
 82 
 83     def items(self):
 84         'od.items() -> list of (key, value) pairs in od'
 85         return [(key, self[key]) for key in self]
 86 
 87     def iterkeys(self):
 88         'od.iterkeys() -> an iterator over the keys in od'
 89         return iter(self)
 90 
 91     def itervalues(self):
 92         'od.itervalues -> an iterator over the values in od'
 93         for k in self:
 94             yield self[k]
 95 
 96     def iteritems(self):
 97         'od.iteritems -> an iterator over the (key, value) pairs in od'
 98         for k in self:
 99             yield (k, self[k])
100 
101     update = MutableMapping.update
102 
103     __update = update # let subclasses override update without breaking __init__
104 
105     __marker = object()
106 
107     def pop(self, key, default=__marker):
108         '''od.pop(k[,d]) -> v, remove specified key and return the corresponding
109         value.  If key is not found, d is returned if given, otherwise KeyError
110         is raised.
111 
112         '''
113         if key in self:
114             result = self[key]
115             del self[key]
116             return result
117         if default is self.__marker:
118             raise KeyError(key)
119         return default
120 
121     def setdefault(self, key, default=None):
122         'od.setdefault(k[,d]) -> od.get(k,d), also set od[k]=d if k not in od'
123         if key in self:
124             return self[key]
125         self[key] = default
126         return default
127 
128     def popitem(self, last=True):
129         '''od.popitem() -> (k, v), return and remove a (key, value) pair.
130         Pairs are returned in LIFO order if last is true or FIFO order if false.
131 
132         '''
133         if not self:
134             raise KeyError('dictionary is empty')
135         key = next(reversed(self) if last else iter(self))
136         value = self.pop(key)
137         return key, value
138 
139     def __repr__(self, _repr_running={}):
140         'od.__repr__() <==> repr(od)'
141         call_key = id(self), _get_ident()
142         if call_key in _repr_running:
143             return '...'
144         _repr_running[call_key] = 1
145         try:
146             if not self:
147                 return '%s()' % (self.__class__.__name__,)
148             return '%s(%r)' % (self.__class__.__name__, self.items())
149         finally:
150             del _repr_running[call_key]
151 
152     def __reduce__(self):
153         'Return state information for pickling'
154         items = [[k, self[k]] for k in self]
155         inst_dict = vars(self).copy()
156         for k in vars(OrderedDict()):
157             inst_dict.pop(k, None)
158         if inst_dict:
159             return (self.__class__, (items,), inst_dict)
160         return self.__class__, (items,)
161 
162     def copy(self):
163         'od.copy() -> a shallow copy of od'
164         return self.__class__(self)
165 
166     @classmethod
167     def fromkeys(cls, iterable, value=None):
168         '''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S.
169         If not specified, the value defaults to None.
170 
171         '''
172         self = cls()
173         for key in iterable:
174             self[key] = value
175         return self
176 
177     def __eq__(self, other):
178         '''od.__eq__(y) <==> od==y.  Comparison to another OD is order-sensitive
179         while comparison to a regular mapping is order-insensitive.
180 
181         '''
182         if isinstance(other, OrderedDict):
183             return dict.__eq__(self, other) and all(_imap(_eq, self, other))
184         return dict.__eq__(self, other)
185 
186     def __ne__(self, other):
187         'od.__ne__(y) <==> od!=y'
188         return not self == other
189 
190     # -- the following methods support python 3.x style dictionary views --
191 
192     def viewkeys(self):
193         "od.viewkeys() -> a set-like object providing a view on od's keys"
194         return KeysView(self)
195 
196     def viewvalues(self):
197         "od.viewvalues() -> an object providing a view on od's values"
198         return ValuesView(self)
199 
200     def viewitems(self):
201         "od.viewitems() -> a set-like object providing a view on od's items"
202         return ItemsView(self)
203 
204 OrderedDict

orderedDict

 1 dic = collections.OrderedDict()
 2 dic['k1'] = 'v1'
 3 dic['k2'] = 'v2'
 4 dic['k3'] = 'v3'
 5 print(dic)
 6 print(dic)
 7 print(dic)
 8 print(type(dic))
 9 ----------------------------------------------------------------------------------
10 输出:
11 OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
12 OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
13 OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
14 <class 'collections.OrderedDict'>
15 
16 
17 ----------------------------------------------------------------------------------
18 无需字典:
19 __author__ = 'Administrator'
20 # -*- coding:utf-8 -*-
21 import collections
22 # dic = collections.OrderedDict()
23 dic = dict()
24 dic['k1'] = 'v1'
25 dic['k2'] = 'v2'
26 dic['k3'] = 'v3'
27 print(dic)
28 print(dic)
29 print(dic)
30 print(type(dic))
31 --------------------------------------------------------
32 #这里就会变成无序字典了
33 输出:
34 {'k2': 'v2', 'k3': 'v3', 'k1': 'v1'}
35 {'k2': 'v2', 'k3': 'v3', 'k1': 'v1'}
36 {'k2': 'v2', 'k3': 'v3', 'k1': 'v1'}
37 <class 'dict'>

OrderedDict有序字典与无序字典dict

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import collections
 4 dic = collections.OrderedDict()
 5 # dic = dict()
 6 dic['k1'] = 'v1'
 7 dic['k2'] = 'v2'
 8 dic['k3'] = 'v3'
 9 print(dic)
10 dic.move_to_end('k1')
11 print(dic)
12 -----------------------------------------------
13 输出:
14 OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
15 OrderedDict([('k2', 'v2'), ('k3', 'v3'), ('k1', 'v1')])

move_to_end:把第一个拿到最后

__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import collections
dic = collections.OrderedDict()
# dic = dict()
dic['k1'] = 'v1'
dic['k2'] = 'v2'
dic['k3'] = 'v3'
print(dic)

dic.popitem()
print(dic)
dic.popitem()
print(dic)
--------------------------------------------------------------------------------
输出:
OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
OrderedDict([('k1', 'v1'), ('k2', 'v2')])
OrderedDict([('k1', 'v1')])



在看一组例子；
__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import collections
dic = collections.OrderedDict()
# dic = dict()
dic['k1'] = 'v1'
dic['k2'] = 'v2'
dic['k3'] = 'v3'
print(dic)

a7 = dic.popitem()
print(a7)
a8 = dic.popitem()
print(a8)
a9 = dic.popitem()
print(a9)
print(dic)
---------------------------------------------------------------------
输出；
OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
('k3', 'v3')
('k2', 'v2')
('k1', 'v1')
OrderedDict()


---------------------------
__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import collections
dic = collections.OrderedDict()
# dic = dict()
dic['k1'] = 'v1'
dic['k2'] = 'v2'
dic['k3'] = 'v3'
print(dic)
a1 = dic.pop('k1')
print(a1)
print(dic)
------------------------------------------------
输出:
OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
v1
OrderedDict([('k2', 'v2'), ('k3', 'v3')])

popitem:是按照后进先出的方法,拿到一个值赋予新的变量

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import collections
 4 dic = collections.OrderedDict()
 5 # dic = dict()
 6 dic['k1'] = 'v1'
 7 dic['k2'] = 'v2'
 8 dic['k3'] = 'v3'
 9 print(dic)
10 dic.update({'k1':'v111','k10':'v10'})
11 print(dic)
12 --------------------------------
13 OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
14 OrderedDict([('k1', 'v111'), ('k2', 'v2'), ('k3', 'v3'), ('k10', 'v10')])

update:更新原来的字典,如果原来字典没有则添加

 

三、默认字典(defaultdict) 

defaultdict是对字典的类型的补充，他默认给字典的值设置了一个类型。

 1 class defaultdict(dict):
 2     """
 3     defaultdict(default_factory[, ...]) --> dict with default factory
 4     
 5     The default factory is called without arguments to produce
 6     a new value when a key is not present, in __getitem__ only.
 7     A defaultdict compares equal to a dict with the same items.
 8     All remaining arguments are treated the same as if they were
 9     passed to the dict constructor, including keyword arguments.
10     """
11     def copy(self): # real signature unknown; restored from __doc__
12         """ D.copy() -> a shallow copy of D. """
13         pass
14 
15     def __copy__(self, *args, **kwargs): # real signature unknown
16         """ D.copy() -> a shallow copy of D. """
17         pass
18 
19     def __getattribute__(self, name): # real signature unknown; restored from __doc__
20         """ x.__getattribute__('name') <==> x.name """
21         pass
22 
23     def __init__(self, default_factory=None, **kwargs): # known case of _collections.defaultdict.__init__
24         """
25         defaultdict(default_factory[, ...]) --> dict with default factory
26         
27         The default factory is called without arguments to produce
28         a new value when a key is not present, in __getitem__ only.
29         A defaultdict compares equal to a dict with the same items.
30         All remaining arguments are treated the same as if they were
31         passed to the dict constructor, including keyword arguments.
32         
33         # (copied from class doc)
34         """
35         pass
36 
37     def __missing__(self, key): # real signature unknown; restored from __doc__
38         """
39         __missing__(key) # Called by __getitem__ for missing key; pseudo-code:
40           if self.default_factory is None: raise KeyError((key,))
41           self[key] = value = self.default_factory()
42           return value
43         """
44         pass
45 
46     def __reduce__(self, *args, **kwargs): # real signature unknown
47         """ Return state information for pickling. """
48         pass
49 
50     def __repr__(self): # real signature unknown; restored from __doc__
51         """ x.__repr__() <==> repr(x) """
52         pass
53 
54     default_factory = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default
55     """Factory for default value called by __missing__()."""
56 
57 defaultdict

defaultdict

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import collections
 4 #这里定义了一个字典输入的类型为list
 5 dic = collections.defaultdict(list)
 6 dic['k1'].append('asdf')
 7 print(dic['k1'])
 8 
 9 ---------------
10 输出:
11 ['asdf']

defaultdict(list):设置一个字典输入的默认类型

四、可命名元组(namedtuple) 

根据nametuple可以创建一个包含tuple所有功能以及其他功能的类型。

  1 class Mytuple(__builtin__.tuple)
  2  |  Mytuple(x, y)
  3  |  
  4  |  Method resolution order:
  5  |      Mytuple
  6  |      __builtin__.tuple
  7  |      __builtin__.object
  8  |  
  9  |  Methods defined here:
 10  |  
 11  |  __getnewargs__(self)
 12  |      Return self as a plain tuple.  Used by copy and pickle.
 13  |  
 14  |  __getstate__(self)
 15  |      Exclude the OrderedDict from pickling
 16  |  
 17  |  __repr__(self)
 18  |      Return a nicely formatted representation string
 19  |  
 20  |  _asdict(self)
 21  |      Return a new OrderedDict which maps field names to their values
 22  |  
 23  |  _replace(_self, **kwds)
 24  |      Return a new Mytuple object replacing specified fields with new values
 25  |  
 26  |  ----------------------------------------------------------------------
 27  |  Class methods defined here:
 28  |  
 29  |  _make(cls, iterable, new=in method __new__ of type object>, len=in function len>) from __builtin__.type
 30  |      Make a new Mytuple object from a sequence or iterable
 31  |  
 32  |  ----------------------------------------------------------------------
 33  |  Static methods defined here:
 34  |  
 35  |  __new__(_cls, x, y)
 36  |      Create new instance of Mytuple(x, y)
 37  |  
 38  |  ----------------------------------------------------------------------
 39  |  Data descriptors defined here:
 40  |  
 41  |  __dict__
 42  |      Return a new OrderedDict which maps field names to their values
 43  |  
 44  |  x
 45  |      Alias for field number 0
 46  |  
 47  |  y
 48  |      Alias for field number 1
 49  |  
 50  |  ----------------------------------------------------------------------
 51  |  Data and other attributes defined here:
 52  |  
 53  |  _fields = ('x', 'y')
 54  |  
 55  |  ----------------------------------------------------------------------
 56  |  Methods inherited from __builtin__.tuple:
 57  |  
 58  |  __add__(...)
 59  |      x.__add__(y) <==> x+y
 60  |  
 61  |  __contains__(...)
 62  |      x.__contains__(y) <==> y in x
 63  |  
 64  |  __eq__(...)
 65  |      x.__eq__(y) <==> x==y
 66  |  
 67  |  __ge__(...)
 68  |      x.__ge__(y) <==> x>=y
 69  |  
 70  |  __getattribute__(...)
 71  |      x.__getattribute__('name') <==> x.name
 72  |  
 73  |  __getitem__(...)
 74  |      x.__getitem__(y) <==> x[y]
 75  |  
 76  |  __getslice__(...)
 77  |      x.__getslice__(i, j) <==> x[i:j]
 78  |      
 79  |      Use of negative indices is not supported.
 80  |  
 81  |  __gt__(...)
 82  |      x.__gt__(y) <==> x>y
 83  |  
 84  |  __hash__(...)
 85  |      x.__hash__() <==> hash(x)
 86  |  
 87  |  __iter__(...)
 88  |      x.__iter__() <==> iter(x)
 89  |  
 90  |  __le__(...)
 91  |      x.__le__(y) <==> x<=y
 92  |  
 93  |  __len__(...)
 94  |      x.__len__() <==> len(x)
 95  |  
 96  |  __lt__(...)
 97  |      x.__lt__(y) <==> x<y
 98  |  
 99  |  __mul__(...)
100  |      x.__mul__(n) <==> x*n
101  |  
102  |  __ne__(...)
103  |      x.__ne__(y) <==> x!=y
104  |  
105  |  __rmul__(...)
106  |      x.__rmul__(n) <==> n*x
107  |  
108  |  __sizeof__(...)
109  |      T.__sizeof__() -- size of T in memory, in bytes
110  |  
111  |  count(...)
112  |      T.count(value) -> integer -- return number of occurrences of value
113  |  
114  |  index(...)
115  |      T.index(value, [start, [stop]]) -> integer -- return first index of value.
116  |      Raises ValueError if the value is not present.
117 
118 Mytuple

nametuple

1 import  collections
2 #创建类,等同于defaultdict
3 #根据类创建对象
4 MytupleClass = collections.namedtuple('Mytuple',['x', 'y', 'z'])
5 aa = MytupleClass(11,22,33)
6 print(aa.x,aa.y,aa.z)
7 -----------------------------------
8 输出:
9 11 22 33

namedtuple

五、双向队列(deque)

一个线程安全的双向队列

  1 class deque(object):
  2     """
  3     deque([iterable[, maxlen]]) --> deque object
  4     
  5     Build an ordered collection with optimized access from its endpoints.
  6     """
  7     def append(self, *args, **kwargs): # real signature unknown
  8         """ Add an element to the right side of the deque. """
  9         pass
 10 
 11     def appendleft(self, *args, **kwargs): # real signature unknown
 12         """ Add an element to the left side of the deque. """
 13         pass
 14 
 15     def clear(self, *args, **kwargs): # real signature unknown
 16         """ Remove all elements from the deque. """
 17         pass
 18 
 19     def count(self, value): # real signature unknown; restored from __doc__
 20         """ D.count(value) -> integer -- return number of occurrences of value """
 21         return 0
 22 
 23     def extend(self, *args, **kwargs): # real signature unknown
 24         """ Extend the right side of the deque with elements from the iterable """
 25         pass
 26 
 27     def extendleft(self, *args, **kwargs): # real signature unknown
 28         """ Extend the left side of the deque with elements from the iterable """
 29         pass
 30 
 31     def pop(self, *args, **kwargs): # real signature unknown
 32         """ Remove and return the rightmost element. """
 33         pass
 34 
 35     def popleft(self, *args, **kwargs): # real signature unknown
 36         """ Remove and return the leftmost element. """
 37         pass
 38 
 39     def remove(self, value): # real signature unknown; restored from __doc__
 40         """ D.remove(value) -- remove first occurrence of value. """
 41         pass
 42 
 43     def reverse(self): # real signature unknown; restored from __doc__
 44         """ D.reverse() -- reverse *IN PLACE* """
 45         pass
 46 
 47     def rotate(self, *args, **kwargs): # real signature unknown
 48         """ Rotate the deque n steps to the right (default n=1).  If n is negative, rotates left. """
 49         pass
 50 
 51     def __copy__(self, *args, **kwargs): # real signature unknown
 52         """ Return a shallow copy of a deque. """
 53         pass
 54 
 55     def __delitem__(self, y): # real signature unknown; restored from __doc__
 56         """ x.__delitem__(y) <==> del x[y] """
 57         pass
 58 
 59     def __eq__(self, y): # real signature unknown; restored from __doc__
 60         """ x.__eq__(y) <==> x==y """
 61         pass
 62 
 63     def __getattribute__(self, name): # real signature unknown; restored from __doc__
 64         """ x.__getattribute__('name') <==> x.name """
 65         pass
 66 
 67     def __getitem__(self, y): # real signature unknown; restored from __doc__
 68         """ x.__getitem__(y) <==> x[y] """
 69         pass
 70 
 71     def __ge__(self, y): # real signature unknown; restored from __doc__
 72         """ x.__ge__(y) <==> x>=y """
 73         pass
 74 
 75     def __gt__(self, y): # real signature unknown; restored from __doc__
 76         """ x.__gt__(y) <==> x>y """
 77         pass
 78 
 79     def __iadd__(self, y): # real signature unknown; restored from __doc__
 80         """ x.__iadd__(y) <==> x+=y """
 81         pass
 82 
 83     def __init__(self, iterable=(), maxlen=None): # known case of _collections.deque.__init__
 84         """
 85         deque([iterable[, maxlen]]) --> deque object
 86         
 87         Build an ordered collection with optimized access from its endpoints.
 88         # (copied from class doc)
 89         """
 90         pass
 91 
 92     def __iter__(self): # real signature unknown; restored from __doc__
 93         """ x.__iter__() <==> iter(x) """
 94         pass
 95 
 96     def __len__(self): # real signature unknown; restored from __doc__
 97         """ x.__len__() <==> len(x) """
 98         pass
 99 
100     def __le__(self, y): # real signature unknown; restored from __doc__
101         """ x.__le__(y) <==> x<=y """
102         pass
103 
104     def __lt__(self, y): # real signature unknown; restored from __doc__
105         """ x.__lt__(y) <==> x"""
106         pass
107 
108     @staticmethod # known case of __new__
109     def __new__(S, *more): # real signature unknown; restored from __doc__
110         """ T.__new__(S, ...) -> a new object with type S, a subtype of T """
111         pass
112 
113     def __ne__(self, y): # real signature unknown; restored from __doc__
114         """ x.__ne__(y) <==> x!=y """
115         pass
116 
117     def __reduce__(self, *args, **kwargs): # real signature unknown
118         """ Return state information for pickling. """
119         pass
120 
121     def __repr__(self): # real signature unknown; restored from __doc__
122         """ x.__repr__() <==> repr(x) """
123         pass
124 
125     def __reversed__(self): # real signature unknown; restored from __doc__
126         """ D.__reversed__() -- return a reverse iterator over the deque """
127         pass
128 
129     def __setitem__(self, i, y): # real signature unknown; restored from __doc__
130         """ x.__setitem__(i, y) <==> x[i]=y """
131         pass
132 
133     def __sizeof__(self): # real signature unknown; restored from __doc__
134         """ D.__sizeof__() -- size of D in memory, in bytes """
135         pass
136 
137     maxlen = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default
138     """maximum size of a deque or None if unbounded"""
139 
140 
141     __hash__ = None
142 
143 deque
144 
145 deque

deque

1 def append(self, *args, **kwargs): # real signature unknown
2         """ Add an element to the right side of the deque. """
3         pass

append--往右边添加一个

1 def appendleft(self, *args, **kwargs): # real signature unknown
2         """ Add an element to the left side of the deque. """
3         pass

appendleft--往左边添加

1 def clear(self, *args, **kwargs): # real signature unknown
2         """ Remove all elements from the deque. """
3         pass

clear--清空这个队列

1 def count(self, value): # real signature unknown; restored from __doc__
2         """ D.count(value) -> integer -- return number of occurrences of value """
3         return 0

count--计算队列的元素出现了多少次

 1 import collections
 2 
 3 a = collections.deque()
 4 #在最后插入一个队列
 5 a.append('1')
 6 #在最左边插入一个队列
 7 a.appendleft('10')
 8 #在最左边插入一个队列
 9 a.appendleft('3')
10 a.appendleft('1')
11 #打印插入的队列
12 print(a)
13 #统计这个队列里有几个1
14 b= a.count('1')
15 #打印上边count统计到的有多少个1 的结果
16 print("出现",b)
17 --------------------------------------------------------
18 输出:
19 deque(['1', '3', '10', '1'])
20 出现 2

 

 1 import collections
 2 #定义一个队列
 3 a = collections.deque()
 4 #在最后插入一个队列
 5 a.append('1')
 6 #在最左边插入一个队列
 7 a.appendleft('10')
 8 #在最左边插入一个队列
 9 a.appendleft('3')
10 a.appendleft('1')
11 #打印插入的队列
12 print(a)
13 #统计这个队列里有几个1
14 b= a.count('1')
15 #打印上边count统计到的有多少个1 的结果
16 print("出现",b)
17 #从右边扩展队列
18 a.extend(['yy','uu','ii'])
19 print(a)
20 #从左边扩展队列
21 a.extendleft(['w','ee','pp'])
22 print(a)
23 ------------------------------------------------------
24 deque(['1', '3', '10', '1'])
25 出现 2
26 deque(['1', '3', '10', '1', 'yy', 'uu', 'ii'])
27 deque(['pp', 'ee', 'w', '1', '3', '10', '1', 'yy', 'uu', 'ii'])

extendleft:左边队列扩展,extend--右边队列扩展

 1 import collections
 2 #定义一个队列
 3 a = collections.deque()
 4 #在最后插入一个队列
 5 a.append('1')
 6 #在最左边插入一个队列
 7 a.appendleft('10')
 8 #在最左边插入一个队列
 9 a.appendleft('3')
10 a.appendleft('1')
11 #打印插入的队列
12 #print(a)
13 #统计这个队列里有几个1
14 b= a.count('1')
15 #打印上边count统计到的有多少个1 的结果
16 #print("出现",b)
17 #从右边扩展队列
18 a.extend(['yy','uu','ii'])
19 #print(a)
20 #从左边扩展队列
21 a.extendleft(['w','ee','pp'])
22 #print(a)
23 #取这个索引值得位置
24 ww = a.index('ii')
25 print(ww)
26 --------------------------------------
27 输出:
28 9

index--取这个索引值在队列里的位置

 1 import collections
 2 #定义一个队列
 3 a = collections.deque()
 4 #在最后插入一个队列
 5 a.append('1')
 6 #在最左边插入一个队列
 7 a.appendleft('10')
 8 #在最左边插入一个队列
 9 a.appendleft('3')
10 print(a)
11 a.rotate(2)
12 print(a)
13 ----------------------------------------------------------------------------------
14 输出:
15 deque(['3', '10', '1'])
16 deque(['10', '1', '3'])

rotate--转圈

注：既然有双向队列，也有单项队列（先进先出 FIFO ）

Queue.Queue单项队列

  1 class Queue:
  2     """Create a queue object with a given maximum size.
  3 
  4     If maxsize is <= 0, the queue size is infinite.
  5     """
  6     def __init__(self, maxsize=0):
  7         self.maxsize = maxsize
  8         self._init(maxsize)
  9         # mutex must be held whenever the queue is mutating.  All methods
 10         # that acquire mutex must release it before returning.  mutex
 11         # is shared between the three conditions, so acquiring and
 12         # releasing the conditions also acquires and releases mutex.
 13         self.mutex = _threading.Lock()
 14         # Notify not_empty whenever an item is added to the queue; a
 15         # thread waiting to get is notified then.
 16         self.not_empty = _threading.Condition(self.mutex)
 17         # Notify not_full whenever an item is removed from the queue;
 18         # a thread waiting to put is notified then.
 19         self.not_full = _threading.Condition(self.mutex)
 20         # Notify all_tasks_done whenever the number of unfinished tasks
 21         # drops to zero; thread waiting to join() is notified to resume
 22         self.all_tasks_done = _threading.Condition(self.mutex)
 23         self.unfinished_tasks = 0
 24 
 25     def task_done(self):
 26         """Indicate that a formerly enqueued task is complete.
 27 
 28         Used by Queue consumer threads.  For each get() used to fetch a task,
 29         a subsequent call to task_done() tells the queue that the processing
 30         on the task is complete.
 31 
 32         If a join() is currently blocking, it will resume when all items
 33         have been processed (meaning that a task_done() call was received
 34         for every item that had been put() into the queue).
 35 
 36         Raises a ValueError if called more times than there were items
 37         placed in the queue.
 38         """
 39         self.all_tasks_done.acquire()
 40         try:
 41             unfinished = self.unfinished_tasks - 1
 42             if unfinished <= 0:
 43                 if unfinished < 0:
 44                     raise ValueError('task_done() called too many times')
 45                 self.all_tasks_done.notify_all()
 46             self.unfinished_tasks = unfinished
 47         finally:
 48             self.all_tasks_done.release()
 49 
 50     def join(self):
 51         """Blocks until all items in the Queue have been gotten and processed.
 52 
 53         The count of unfinished tasks goes up whenever an item is added to the
 54         queue. The count goes down whenever a consumer thread calls task_done()
 55         to indicate the item was retrieved and all work on it is complete.
 56 
 57         When the count of unfinished tasks drops to zero, join() unblocks.
 58         """
 59         self.all_tasks_done.acquire()
 60         try:
 61             while self.unfinished_tasks:
 62                 self.all_tasks_done.wait()
 63         finally:
 64             self.all_tasks_done.release()
 65 
 66     def qsize(self):
 67         """Return the approximate size of the queue (not reliable!)."""
 68         self.mutex.acquire()
 69         n = self._qsize()
 70         self.mutex.release()
 71         return n
 72 
 73     def empty(self):
 74         """Return True if the queue is empty, False otherwise (not reliable!)."""
 75         self.mutex.acquire()
 76         n = not self._qsize()
 77         self.mutex.release()
 78         return n
 79 
 80     def full(self):
 81         """Return True if the queue is full, False otherwise (not reliable!)."""
 82         self.mutex.acquire()
 83         n = 0 < self.maxsize == self._qsize()
 84         self.mutex.release()
 85         return n
 86 
 87     def put(self, item, block=True, timeout=None):
 88         """Put an item into the queue.
 89 
 90         If optional args 'block' is true and 'timeout' is None (the default),
 91         block if necessary until a free slot is available. If 'timeout' is
 92         a non-negative number, it blocks at most 'timeout' seconds and raises
 93         the Full exception if no free slot was available within that time.
 94         Otherwise ('block' is false), put an item on the queue if a free slot
 95         is immediately available, else raise the Full exception ('timeout'
 96         is ignored in that case).
 97         """
 98         self.not_full.acquire()
 99         try:
100             if self.maxsize > 0:
101                 if not block:
102                     if self._qsize() == self.maxsize:
103                         raise Full
104                 elif timeout is None:
105                     while self._qsize() == self.maxsize:
106                         self.not_full.wait()
107                 elif timeout < 0:
108                     raise ValueError("'timeout' must be a non-negative number")
109                 else:
110                     endtime = _time() + timeout
111                     while self._qsize() == self.maxsize:
112                         remaining = endtime - _time()
113                         if remaining <= 0.0:
114                             raise Full
115                         self.not_full.wait(remaining)
116             self._put(item)
117             self.unfinished_tasks += 1
118             self.not_empty.notify()
119         finally:
120             self.not_full.release()
121 
122     def put_nowait(self, item):
123         """Put an item into the queue without blocking.
124 
125         Only enqueue the item if a free slot is immediately available.
126         Otherwise raise the Full exception.
127         """
128         return self.put(item, False)
129 
130     def get(self, block=True, timeout=None):
131         """Remove and return an item from the queue.
132 
133         If optional args 'block' is true and 'timeout' is None (the default),
134         block if necessary until an item is available. If 'timeout' is
135         a non-negative number, it blocks at most 'timeout' seconds and raises
136         the Empty exception if no item was available within that time.
137         Otherwise ('block' is false), return an item if one is immediately
138         available, else raise the Empty exception ('timeout' is ignored
139         in that case).
140         """
141         self.not_empty.acquire()
142         try:
143             if not block:
144                 if not self._qsize():
145                     raise Empty
146             elif timeout is None:
147                 while not self._qsize():
148                     self.not_empty.wait()
149             elif timeout < 0:
150                 raise ValueError("'timeout' must be a non-negative number")
151             else:
152                 endtime = _time() + timeout
153                 while not self._qsize():
154                     remaining = endtime - _time()
155                     if remaining <= 0.0:
156                         raise Empty
157                     self.not_empty.wait(remaining)
158             item = self._get()
159             self.not_full.notify()
160             return item
161         finally:
162             self.not_empty.release()
163 
164     def get_nowait(self):
165         """Remove and return an item from the queue without blocking.
166 
167         Only get an item if one is immediately available. Otherwise
168         raise the Empty exception.
169         """
170         return self.get(False)
171 
172     # Override these methods to implement other queue organizations
173     # (e.g. stack or priority queue).
174     # These will only be called with appropriate locks held
175 
176     # Initialize the queue representation
177     def _init(self, maxsize):
178         self.queue = deque()
179 
180     def _qsize(self, len=len):
181         return len(self.queue)
182 
183     # Put a new item in the queue
184     def _put(self, item):
185         self.queue.append(item)
186 
187     # Get an item from the queue
188     def _get(self):
189         return self.queue.popleft()
190 
191 Queue.Queue

Queue.Queue

 

 1 import queue
 2 #创建一个单项队列
 3 a = queue.Queue()
 4 #插入数据
 5 a.put('999')
 6 ww = a.put('asdf')
 7 #qsize统计队列里有几个数据
 8 print(a.qsize())
 9 #到队列里通过get取数据
10 print(a.get())
11 #到队列里取数据
12 print(a.get())
13 #取数据的过程中是遵循 先进先出的规则来拿数据的
14 ---------------------------------------------------------------------
15 输出:
16 2
17 999
18 asdf

queue--单项队列

 

深浅拷贝

对于 数字 和 字符串 而言，赋值、浅拷贝和深拷贝无意义，因为其永远指向同一个内存地址。

拷贝是通过copy模块的copy.copy()方法来实现的拷贝

浅拷贝:copy.copy()

深拷贝:copy.deepcopy()

赋值 = 

Python分为两类:

　　#字符串数字 属于一类

　　#其他的属于一类

查看一个变量的id地址

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import copy
 4 a1 = 1
 5 a2 = 1
 6 print(id(a1))
 7 print(id(a2))
 8 ----------------------------------------------------------------------------
 9 输出:
10 1583410992
11 1583410992

浅拷贝

__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import copy
a1 = 'asdfasdf'
#浅拷贝
a2 = copy.copy(a1)
print(id(a1))
print(id(a2))
----------------------------------------------------------------------------
输出:
17973616
17973616

-------------------------------------------------------------------
深拷贝:__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import copy
a1 = 'asdfasdf'
a2 = copy.deepcopy(a1)
print(id(a1))
print(id(a2))
------------------------------------------------------------------
17908080
17908080

PS:对于数字和字符串来说无论是赋值、深拷贝还是浅拷贝 都是使用的内存里的同一个地址,所以对于数字和字符串来说深浅拷贝是无用的.

 

#下面来看一下列表、元祖以及字典其他...

浅拷贝只拷贝一层

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import copy
 4 n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}
 5 n3 = copy.copy(n1)
 6 print(id(n1))
 7 print(id(n3))
 8 #下面输出的更深层次的元素的内存地址是没有变的
 9 print(id(n1['k1']))
10 print(id(n3['k1']))
11 ----------------------------------------------------
12 输出:
13 6607432
14 7116936
15 7071256
16 7071256

深拷贝:

__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import copy
n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}
n3 = copy.deepcopy(n1)

print(id(n1['k3']))
print(id(n3['k3']))
----------------------------------------------------------------------
输出:
12382792
12360072




-----------------------------------------------------------------------------
__author__ = 'Administrator'
# -*- coding:utf-8 -*-
import copy
n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}
n3 = copy.copy(n1)

print(id(n1['k3']))
print(id(n3['k3']))
---------------------------------
输出:

18784008
18784008

 小练习

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import copy
 4 dic = {
 5     "CPU":[90,],
 6     "mem":[80,],
 7     "disk":[70,],
 8 }
 9 dic['CPU'][0] = 10
10 #浅拷贝
11 new_dic = copy.copy(dic)
12 new_dic['mem'][0] = 100
13 print(dic)
14 print(new_dic)
15 --------------------------
16 输出:
17 {'mem': [100], 'disk': [70], 'CPU': [10]}
18 {'mem': [100], 'disk': [70], 'CPU': [10]}

浅拷贝

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 import copy
 4 dic = {
 5     "CPU":[90,],
 6     "mem":[80,],
 7     "disk":[70,],
 8 }
 9 dic['CPU'][0] = 10
10 #浅拷贝
11 new_dic = copy.deepcopy(dic)
12 new_dic['mem'][0] = 100
13 print(dic)
14 print(new_dic)
15 ----------------------------------------
16 输出:
17 {'CPU': [10], 'mem': [80], 'disk': [70]}
18 {'CPU': [10], 'mem': [100], 'disk': [70]}

深拷贝

 

函数

一、背景

在学习函数之前，一直遵循：面向过程编程，即：根据业务逻辑从上到下实现功能，其往往用一长段代码来实现指定功能，开发过程中最常见的操作就是粘贴复制，也就是将之前实现的代码块复制到现需功能处，如下：

 1 while True：
 2     if cpu利用率 > 90%:
 3         #发送邮件提醒
 4         连接邮箱服务器
 5         发送邮件
 6         关闭连接
 7    
 8     if 硬盘使用空间 > 90%:
 9         #发送邮件提醒
10         连接邮箱服务器
11         发送邮件
12         关闭连接
13    
14     if 内存占用 > 80%:
15         #发送邮件提醒
16         连接邮箱服务器
17         发送邮件
18         关闭连接

腚眼一看上述代码，if条件语句下的内容可以被提取出来公用，如下：

 1 def 发送邮件(内容)
 2     #发送邮件提醒
 3     连接邮箱服务器
 4     发送邮件
 5     关闭连接
 6    
 7 while True：
 8    
 9     if cpu利用率 > 90%:
10         发送邮件('CPU报警')
11    
12     if 硬盘使用空间 > 90%:
13         发送邮件('硬盘报警')
14    
15     if 内存占用 > 80%:

对于上述的两种实现方式，第二次必然比第一次的重用性和可读性要好，其实这就是函数式编程和面向过程编程的区别：

• 函数式：将某功能代码封装到函数中，日后便无需重复编写，仅调用函数即可
• 面向对象：对函数进行分类和封装，让开发“更快更好更强...

函数式编程最重要的是增强代码的重用性和可读性

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 #定义一个函数
 4 def mail():
 5     n = 123
 6     n += 1
 7     print(n)
 8 #函数名mail
 9 mail()
10 f = mail
11 f()

函数的定义主要有如下要点：

• def：表示函数的关键字
• 函数名：函数的名称，日后根据函数名调用函数
• 函数体：函数中进行一系列的逻辑计算，如：发送邮件、计算出 [11,22,38,888,2]中的最大数等...
• 参数：为函数体提供数据
• 返回值：当函数执行完毕后，可以给调用者返回数据。

以上要点中，比较重要有参数和返回值：

 

 

Python函数的返回值

发送邮件:

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 #定义一个函数
 4 import smtplib
 5 from email.mime.text import MIMEText
 6 from email.utils import formataddr
 7 def mail():
 8     ret = True
 9     #上边ret的内容执行完了就会执行try,try 的意思是 如果发邮件的代码不出错的情况下就会继续执行下去,如果出错的话就会执行except的内容然后return ret
10     #如果try里的内容不出错就永远不会执行except里的内容
11     try:
12         msg = MIMEText('邮件内容', 'plain', 'utf-8')
13         #
14         msg['From'] = formataddr(["aaa",'hu_***[email protected]'])
15         msg['To'] = formataddr(["没事",'352***[email protected]'])
16         msg['Subject'] = "主题啊啊啊啊啊啊"
17         server = smtplib.SMTP("smtp.126.com", 25)
18         server.login("hu_***[email protected]", "password")
19         server.sendmail('hu_***[email protected]', ['352***[email protected]',], msg.as_string())
20         server.quit()
21     except Exception:
22         ret = False
23     return ret
24 
25 #函数名mail
26 ret = mail()
27 if ret:
28     print("发送成功...")
29 else:
30     print("发送失败!!!")

 1 import smtplib
 2 from email.mime.text import MIMEText
 3 from email.utils import formataddr
 4   
 5   
 6 msg = MIMEText('邮件内容', 'plain', 'utf-8')
 7 msg['From'] = formataddr(["武沛齐",'[email protected]'])
 8 msg['To'] = formataddr(["走人",'[email protected]'])
 9 msg['Subject'] = "主题"
10   
11 server = smtplib.SMTP("smtp.126.com", 25)
12 server.login("[email protected]", "邮箱密码")
13 server.sendmail('[email protected]', ['[email protected]',], msg.as_string())
14 server.quit()

Python 邮件发送实例

1、返回值

函数是一个功能块，该功能到底执行成功与否，需要通过返回值来告知调用者

 

 1 def 发送短信():
 2       
 3     发送短信的代码...
 4   
 5     if 发送成功:
 6         return True
 7     else:
 8         return False
 9   
10   
11 while True:
12       
13     # 每次执行发送短信函数，都会将返回值自动赋值给result
14     # 之后，可以根据result来写日志，或重发等操作
15   
16     result = 发送短信()
17     if result == False:
18         记录日志，短信发送失败...

 

 

2、参数

　　为什么要有参数？

 1 def CPU报警邮件()
 2     #发送邮件提醒
 3     连接邮箱服务器
 4     发送邮件
 5     关闭连接
 6 
 7 def 硬盘报警邮件()
 8     #发送邮件提醒
 9     连接邮箱服务器
10     发送邮件
11     关闭连接
12 
13 def 内存报警邮件()
14     #发送邮件提醒
15     连接邮箱服务器
16     发送邮件
17     关闭连接
18  
19 while True：
20  
21     if cpu利用率 > 90%:
22         CPU报警邮件（）
23  
24     if 硬盘使用空间 > 90%:
25         硬盘报警邮件（）
26  
27     if 内存占用 > 80%:
28         内存报警邮件（）
29 
30 无参数实现

无参数

 1 def 发送邮件(邮件内容)
 2 
 3     #发送邮件提醒
 4     连接邮箱服务器
 5     发送邮件
 6     关闭连接
 7 
 8  
 9 while True：
10  
11     if cpu利用率 > 90%:
12         发送邮件("CPU报警了。")
13  
14     if 硬盘使用空间 > 90%:
15         发送邮件("硬盘报警了。")
16  
17     if 内存占用 > 80%:
18         发送邮件("内存报警了。")
19 
20 有参数实现

有参数

函数的有三中不同的参数：

• 普通参数
• 默认参数
• 动态参数

 1 __author__ = 'Administrator'
 2 # -*- coding:utf-8 -*-
 3 #定义一个函数
 4 import smtplib
 5 from email.mime.text import MIMEText
 6 from email.utils import formataddr
 7 #形式参数
 8 #user = '352***[email protected]'
 9 def mail(user):
10     ret = True
11     #上边ret的内容执行完了就会执行try,try 的意思是 如果发邮件的代码不出错的情况下就会继续执行下去,如果出错的话就会执行except的内容然后return ret
12     #如果try里的内容不出错就永远不会执行except里的内容
13     try:
14         msg = MIMEText('邮件内容', 'plain', 'utf-8')
15         #发件箱
16         msg['From'] = formataddr(["aaa",'hu_***[email protected]'])
17         msg['To'] = formataddr(["没事",'352***[email protected]'])
18         msg['Subject'] = "主题啊啊啊啊啊啊"
19         server = smtplib.SMTP("smtp.126.com", 25)
20         server.login("hu_***[email protected]", "***")
21         server.sendmail('hu_***[email protected]', [user,], msg.as_string())
22         server.quit()
23     except Exception:
24         ret = False
25     return ret
26 
27 #函数名mail
28 #括号内为实际参数
29 ret = mail('352***[email protected]')
30 ret = mail('hu_***[email protected]')
31 if ret:
32     print("发送成功...")
33 else:
34     print("发送失败!!!")
35 
36 普通函数

普通参数

多个普通参数传参

 1 #默认情况下a2=99,
 2 def show(a1,a2=99):
 3     print(a1,a2)
 4 #执行函数的时候第一个值是赋给第一个参数,第二个值如果不定义的话函数执行的时候就会使用默认的值"99"，如果第二个值制定了的话就会使用指定的值
 5 show(11)
 6 ----------------
 7 输出:
 8 11 99
 9 ===========================================
10 #默认情况下a2=99,
11 def show(a1,a2=99):
12     print(a1,a2)
13 #执行函数的时候第一个值是赋给第一个参数,第二个值如果不定义的话函数执行的时候就会使用默认的值"99"，如果第二个值制定了的话就会使用指定的值
14 show(11,"\n我特啊游,弄啥嘞")
15 --------------------------------------
16 输出:
17 11 
18 我特啊游,弄啥嘞

默认参数

1 def show(a1,a2):
2     print(a1,a2)
3 show(a2=123,a1=999)
4 -----------------------------------------------------------------------------------
5 输出:
6 999 123

指定参数

 1 #元祖动态参数
 2 def show(*arg):
 3     print(arg,type(arg))
 4 n = [11,22,33,44]
 5 show(n)
 6 
 7 ===========================================
 8 #字典动态参数
 9 def show(**arg):
10     print(arg,type(arg))
11 show(n1 = 'ww',99 = 88)
12 ==============================================
13 
14 #如下例子会将传入的元素参数自动转换为元祖,传入的字典格式会自动转换为字典
15 def show(*args,**kwargs):
16     print(args,type(args),"\n",kwargs,type(kwargs))
17 show(11,22,33,44,55,66,77,n8 = 99)
18 
19 ----------------------------------
20 输出:
21 (11, 22, 33, 44, 55, 66, 77) <class 'tuple'> 
22  {'n8': 99} <class 'dict'>

元祖,字典动态参数

ps:注意

 1 def show(*args,**kwargs):
 2     print(args,type(args),)
 3     print(kwargs,type(kwargs))
 4 l = [11,22,33,44]
 5 d = {'n1':99,'n2':'asb'}
 6 #show(11,22,33,44,55,66,77,n8 = 99)
 7 show(l,d)
 8 -----------------------------------------
 9 输出:
10 ([11, 22, 33, 44], {'n2': 'asb', 'n1': 99}) <class 'tuple'>
11 {} <class 'dict'>
12 
13 
14 
15 
16 ============================================
17 def show(*args,**kwargs):
18     print(args,type(args),)
19     print(kwargs,type(kwargs))
20 l = [11,22,33,44]
21 d = {'n1':99,'n2':'asb'}
22 
23 show(*l,**d)
24 ----------------------------------------------
25 输出:
26 (11, 22, 33, 44) <class 'tuple'>
27 {'n1': 99, 'n2': 'asb'} <class 'dict'>

 

指定参数格式化

 1 s1 = "{0} is {1}"
 2 a = ['asb','fds']
 3 s2 = s1.format(*a)
 4 print(s2)
 5 
 6 ------------------------
 7 输出:
 8 asb is fds
 9 ==================================
10 s1 = "{name} is {acter}"
11 w = s1.format(name = 'asd',acter = 'dfgh')
12 print(w)
13 ---------------------------------
14 输出:
15 asd is dfgh
16 
17 ========================================
18 
19 s1 = "{name} is {acter}"
20 d = {'name':'asd','acter':'dfgh'}
21 ret = s1.format(**d)
22 print(ret)
23 -------------------------------------------
24 输出:
25 asd is dfgh

字符串的格式化format

 

lambda表达式

 学习条件运算时，对于简单的 if else 语句，可以使用三元运算来表示，即

1 # 普通条件语句
2 if 1 == 1:
3     name = 'wupeiqi'
4 else:
5     name = 'alex'
6    
7 # 三元运算
8 name = 'wupeiqi' if 1 == 1 else 'alex'

对于简单的函数，也存在一种简便的表示方式，即：lambda表达式

 1 # ###################### 普通函数 ######################
 2 # 定义函数（普通方式）
 3 def func(arg):
 4     return arg + 1
 5    
 6 # 执行函数
 7 result = func(123)
 8    
 9 # ###################### lambda ######################
10    
11 # 定义函数（lambda表达式）
12 my_lambda = lambda arg : arg + 1
13    
14 # 执行函数
15 result = my_lambda(123)

lambda存在意义就是对简单函数的简洁表示

 

如下表中的模块不需要任何导入都可以使用

 1 #所有的元素为真则为True,所有的元素为假则为False
 2 a1 = all([None,1,2,3,4])
 3 print(a1)
 4 -------------------------------
 5 输出:
 6 False
 7 
 8 ============================================
 9 a1 = all([1,2,3,4])
10 print(a1)
11 -------------------------
12 输出:
13 True

all()

#所有元素只要有一个位真,则返回True,所有元素只要有一个位假则返回Fales
a2 = any([None,1])
print(a2)
----------------------------------------------------------
输出:
True

=============================
a2 = any([None])
print(a2)
-------------------------------------------
输出:
Fales

any()-所有元素只要有一个位真,则返回True,所有元素只要有一个位假则返回Fales

1 #bin  是 返回一个二进制
2 a3 = bin(8,)
3 print(a3)
4 -----------------------------------------------------------------
5 0b1000

bin 是 返回一个二进制

1 #一个汉字为三个字节,转换为数组
2 a4 = bytearray("猪八戒",encoding='utf-8')
3 print(a4)
4 -----------------
5 输出:
6 bytearray(b'\xe7\x8c\xaa\xe5\x85\xab\xe6\x88\x92')

bytearray:一个汉字为三个字节,转换为数组

 1 print(ord('A'))
 2 ----------------------
 3 打印
 4 65
 5 
 6 
 7 ===================
 8 print(chr(65))
 9 ---------------------------
10 打印:
11 A

# chr 是将数字转换成字符---# ord 是将字符转换成数字

1 #验证码
2 import random
3 print(random.randint(1,9999))

random:#验证码

open函数，该函数用于文件处理

操作文件时，一般需要经历如下步骤：

• 打开文件
• 操作文件

一、打开文件

 1 文件句柄 = open('文件路径', '模式') 

打开文件时，需要指定文件路径和以何等方式打开文件，打开后，即可获取该文件句柄，日后通过此文件句柄对该文件操作。

打开文件的模式有：

• r，只读模式（默认）。
• w，只写模式。【不可读；不存在则创建；存在则删除内容；】
• a，追加模式。【可读；   不存在则创建；存在则只追加内容；】

"+" 表示可以同时读写某个文件

• r+，可读写文件。【可读；可写；可追加】
• w+，写读
• a+，同a

"U"表示在读取时，可以将 \r \n \r\n自动转换成 \n （与 r 或 r+ 模式同使用）

• rU
• r+U

"b"表示处理二进制文件（如：FTP发送上传ISO镜像文件，linux可忽略，windows处理二进制文件时需标注）

• rb
• wb
• ab

二、操作

class file(object)
    def close(self): # real signature unknown; restored from __doc__
        关闭文件
        """
        close() -> None or (perhaps) an integer.  Close the file.
         
        Sets data attribute .closed to True.  A closed file cannot be used for
        further I/O operations.  close() may be called more than once without
        error.  Some kinds of file objects (for example, opened by popen())
        may return an exit status upon closing.
        """
 
    def fileno(self): # real signature unknown; restored from __doc__
        文件描述符  
         """
        fileno() -> integer "file descriptor".
         
        This is needed for lower-level file interfaces, such os.read().
        """
        return 0    
 
    def flush(self): # real signature unknown; restored from __doc__
        刷新文件内部缓冲区
        """ flush() -> None.  Flush the internal I/O buffer. """
        pass
 
 
    def isatty(self): # real signature unknown; restored from __doc__
        判断文件是否是同意tty设备
        """ isatty() -> true or false.  True if the file is connected to a tty device. """
        return False
 
 
    def next(self): # real signature unknown; restored from __doc__
        获取下一行数据，不存在，则报错
        """ x.next() -> the next value, or raise StopIteration """
        pass
 
    def read(self, size=None): # real signature unknown; restored from __doc__
        读取指定字节数据
        """
        read([size]) -> read at most size bytes, returned as a string.
         
        If the size argument is negative or omitted, read until EOF is reached.
        Notice that when in non-blocking mode, less data than what was requested
        may be returned, even if no size parameter was given.
        """
        pass
 
    def readinto(self): # real signature unknown; restored from __doc__
        读取到缓冲区，不要用，将被遗弃
        """ readinto() -> Undocumented.  Don't use this; it may go away. """
        pass
 
    def readline(self, size=None): # real signature unknown; restored from __doc__
        仅读取一行数据
        """
        readline([size]) -> next line from the file, as a string.
         
        Retain newline.  A non-negative size argument limits the maximum
        number of bytes to return (an incomplete line may be returned then).
        Return an empty string at EOF.
        """
        pass
 
    def readlines(self, size=None): # real signature unknown; restored from __doc__
        读取所有数据，并根据换行保存值列表
        """
        readlines([size]) -> list of strings, each a line from the file.
         
        Call readline() repeatedly and return a list of the lines so read.
        The optional size argument, if given, is an approximate bound on the
        total number of bytes in the lines returned.
        """
        return []
 
    def seek(self, offset, whence=None): # real signature unknown; restored from __doc__
        指定文件中指针位置
        """
        seek(offset[, whence]) -> None.  Move to new file position.
         
        Argument offset is a byte count.  Optional argument whence defaults to
(offset from start of file, offset should be >= 0); other values are 1
        (move relative to current position, positive or negative), and 2 (move
        relative to end of file, usually negative, although many platforms allow
        seeking beyond the end of a file).  If the file is opened in text mode,
        only offsets returned by tell() are legal.  Use of other offsets causes
        undefined behavior.
        Note that not all file objects are seekable.
        """
        pass
 
    def tell(self): # real signature unknown; restored from __doc__
        获取当前指针位置
        """ tell() -> current file position, an integer (may be a long integer). """
        pass
 
    def truncate(self, size=None): # real signature unknown; restored from __doc__
        截断数据，仅保留指定之前数据
        """
        truncate([size]) -> None.  Truncate the file to at most size bytes.
         
        Size defaults to the current file position, as returned by tell().
        """
        pass
 
    def write(self, p_str): # real signature unknown; restored from __doc__
        写内容
        """
        write(str) -> None.  Write string str to file.
         
        Note that due to buffering, flush() or close() may be needed before
        the file on disk reflects the data written.
        """
        pass
 
    def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__
        将一个字符串列表写入文件
        """
        writelines(sequence_of_strings) -> None.  Write the strings to the file.
         
        Note that newlines are not added.  The sequence can be any iterable object
        producing strings. This is equivalent to calling write() for each string.
        """
        pass
 
    def xreadlines(self): # real signature unknown; restored from __doc__
        可用于逐行读取文件，非全部
        """
        xreadlines() -> returns self.
         
        For backward compatibility. File objects now include the performance
        optimizations previously implemented in the xreadlines module.
        """
        pass

Python 2.x

Python2.0

class TextIOWrapper(_TextIOBase):
    """
    Character and line based layer over a BufferedIOBase object, buffer.
    
    encoding gives the name of the encoding that the stream will be
    decoded or encoded with. It defaults to locale.getpreferredencoding(False).
    
    errors determines the strictness of encoding and decoding (see
    help(codecs.Codec) or the documentation for codecs.register) and
    defaults to "strict".
    
    newline controls how line endings are handled. It can be None, '',
    '\n', '\r', and '\r\n'.  It works as follows:
    
    * On input, if newline is None, universal newlines mode is
      enabled. Lines in the input can end in '\n', '\r', or '\r\n', and
      these are translated into '\n' before being returned to the
      caller. If it is '', universal newline mode is enabled, but line
      endings are returned to the caller untranslated. If it has any of
      the other legal values, input lines are only terminated by the given
      string, and the line ending is returned to the caller untranslated.
    
    * On output, if newline is None, any '\n' characters written are
      translated to the system default line separator, os.linesep. If
      newline is '' or '\n', no translation takes place. If newline is any
      of the other legal values, any '\n' characters written are translated
      to the given string.
    
    If line_buffering is True, a call to flush is implied when a call to
    write contains a newline character.
    """
    def close(self, *args, **kwargs): # real signature unknown
        关闭文件
        pass

    def fileno(self, *args, **kwargs): # real signature unknown
        文件描述符  
        pass

    def flush(self, *args, **kwargs): # real signature unknown
        刷新文件内部缓冲区
        pass

    def isatty(self, *args, **kwargs): # real signature unknown
        判断文件是否是同意tty设备
        pass

    def read(self, *args, **kwargs): # real signature unknown
        读取指定字节数据
        pass

    def readable(self, *args, **kwargs): # real signature unknown
        是否可读
        pass

    def readline(self, *args, **kwargs): # real signature unknown
        仅读取一行数据
        pass

    def seek(self, *args, **kwargs): # real signature unknown
        指定文件中指针位置
        pass

    def seekable(self, *args, **kwargs): # real signature unknown
        指针是否可操作
        pass

    def tell(self, *args, **kwargs): # real signature unknown
        获取指针位置
        pass

    def truncate(self, *args, **kwargs): # real signature unknown
        截断数据，仅保留指定之前数据
        pass

    def writable(self, *args, **kwargs): # real signature unknown
        是否可写
        pass

    def write(self, *args, **kwargs): # real signature unknown
        写内容
        pass

    def __getstate__(self, *args, **kwargs): # real signature unknown
        pass

    def __init__(self, *args, **kwargs): # real signature unknown
        pass

    @staticmethod # known case of __new__
    def __new__(*args, **kwargs): # real signature unknown
        """ Create and return a new object.  See help(type) for accurate signature. """
        pass

    def __next__(self, *args, **kwargs): # real signature unknown
        """ Implement next(self). """
        pass

    def __repr__(self, *args, **kwargs): # real signature unknown
        """ Return repr(self). """
        pass

    buffer = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    closed = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    encoding = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    errors = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    line_buffering = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    name = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    newlines = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    _CHUNK_SIZE = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    _finalizing = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

Python 3.x

Python3.0

 

转载于:https://www.cnblogs.com/nb-blog/p/5171424.html