上节内容回顾:
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<y """ 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
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'>
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
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)
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)
#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'} <class 'set'>
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
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
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
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)
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'}
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'}
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'}
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'}
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'}
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 删除:%s 插入:%s" %(update_dict,delete_list,new_list)) 38 print(msg)
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
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})
__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})
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
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'>
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')])
__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')])
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')])
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
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']
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=<built-in method __new__ of type object>, len=<built-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
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
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<y """ 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
1 def append(self, *args, **kwargs): # real signature unknown 2 """ Add an element to the right side of the deque. """ 3 pass
1 def appendleft(self, *args, **kwargs): # real signature unknown 2 """ Add an element to the left side of the deque. """ 3 pass
1 def clear(self, *args, **kwargs): # real signature unknown 2 """ Remove all elements from the deque. """ 3 pass
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
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'])
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
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'])
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
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
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]}
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]}
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_***_you@126.com']) 15 msg['To'] = formataddr(["没事",'352***7864@qq.com']) 16 msg['Subject'] = "主题啊啊啊啊啊啊" 17 server = smtplib.SMTP("smtp.126.com", 25) 18 server.login("hu_***_you@126.com", "password") 19 server.sendmail('hu_***_you@126.com', ['352***7864@qq.com',], 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",'wptawy@126.com']) 8 msg['To'] = formataddr(["走人",'424662508@qq.com']) 9 msg['Subject'] = "主题" 10 11 server = smtplib.SMTP("smtp.126.com", 25) 12 server.login("wptawy@126.com", "邮箱密码") 13 server.sendmail('wptawy@126.com', ['424662508@qq.com',], msg.as_string()) 14 server.quit()
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
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
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***7864@qq.com' 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_***_you@126.com']) 17 msg['To'] = formataddr(["没事",'352***7864@qq.com']) 18 msg['Subject'] = "主题啊啊啊啊啊啊" 19 server = smtplib.SMTP("smtp.126.com", 25) 20 server.login("hu_***_you@126.com", "***") 21 server.sendmail('hu_***_you@126.com', [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***7864@qq.com') 30 ret = mail('hu_***_you@126.com') 31 if ret: 32 print("发送成功...") 33 else: 34 print("发送失败!!!") 35 36 普通函数
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," 我特啊游,弄啥嘞") 15 -------------------------------------- 16 输出: 17 11 18 我特啊游,弄啥嘞
1 def show(a1,a2): 2 print(a1,a2) 3 show(a2=123,a1=999) 4 ----------------------------------------------------------------------------------- 5 输出: 6 999 123
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)," ",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'>
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
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
#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
1 #bin 是 返回一个二进制 2 a3 = bin(8,) 3 print(a3) 4 ----------------------------------------------------------------- 5 0b1000
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'xe7x8cxaaxe5x85xabxe6x88x92')
1 print(ord('A')) 2 ---------------------- 3 打印 4 65 5 6 7 =================== 8 print(chr(65)) 9 --------------------------- 10 打印: 11 A
1 #验证码 2 import random 3 print(random.randint(1,9999))
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 自动转换成 （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
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, '', ' ', ' ', and ' '. It works as follows: * On input, if newline is None, universal newlines mode is enabled. Lines in the input can end in ' ', ' ', or ' ', and these are translated into ' ' 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 ' ' characters written are translated to the system default line separator, os.linesep. If newline is '' or ' ', no translation takes place. If newline is any of the other legal values, any ' ' 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