Day 3 Python之循序渐进3
1.Python集合Set
set 是一个无序且不重复的元素集合，访问速度快，自动解决重复问题
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
练习测试2.Python计数器
ounter是对字典类型的补充，用于追踪值的出现次数。
ps：具备字典的所有功能 + 自己类的功能
1 #! /usr/bin/env python 2 # -*- coding:utf-8 -*- 3 4 import collections 5 obj = collections.Counter('abdahdjkahdsa;d') 6 print(obj) 7 ret = obj.most_common(4) 8 print(ret) 9 for k in obj.elements(): 10 print(k) 11 for k,v in obj.items(): 12 print(k,v) 13 obj = collections.Counter(['11','22','22','22','33','44','55']) #计数出现次数 14 print(obj) 15 obj.update(['leon','11','55','55']) ##更新计数出现次数 16 print(obj) 17 obj.subtract(['11','55']) #删除出现的次数 18 print(obj) 19 20 输出： 21 C:\Users\Administrator\AppData\Local\Programs\Python\Python35\python.exe "D:/PythonTraining/PythonCode/Python35/Day 4/test.py" 22 Counter({'d': 4, 'a': 4, 'h': 2, 'k': 1, ';': 1, 'b': 1, 's': 1, 'j': 1}) 23 [('d', 4), ('a', 4), ('h', 2), ('k', 1)] 24 h 25 h 26 d 27 d 28 d 29 d 30 k 31 ; 32 b 33 s 34 a 35 a 36 a 37 a 38 j 39 h 2 40 d 4 41 k 1 42 ; 1 43 b 1 44 s 1 45 a 4 46 j 1 47 Counter({'22': 3, '33': 1, '11': 1, '55': 1, '44': 1}) 48 Counter({'55': 3, '22': 3, '11': 2, '33': 1, 'leon': 1, '44': 1}) 49 Counter({'22': 3, '55': 2, '33': 1, 'leon': 1, '11': 1, '44': 1}) 50 51 Process finished with exit code 0
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
3.Python有序字典OrderedDict
orderdDict是对字典类型的补充，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
有序字典：
#! /usr/bin/env python
# -*- coding:utf-8 -*-
import collections
"""
# 字典 dic = {'k1':'v1','k2':'v2'}
# 列表 li = [k1]
for i in li:
print(dic[i]) #构造有序字典
"""
dic = collections.OrderedDict()
# dic = dict() 无序的字典集合
dic['k1'] = 'v1'
dic['k2'] = 'v2'
dic['k3'] = 'v3'
# print(dic)
# 输出OrderedDict([('k1', 'v1'), ('k2', 'v2'), ('k3', 'v3')])
dic.move_to_end('k1') #把K1放到最后
print(dic)
输出：OrderedDict([('k2', 'v2'), ('k3', 'v3'), ('k1', 'v1')])
dic.popitem()
print(dic) #内存栈，后进先出
输出：rderedDict([('k2', 'v2'), ('k3', 'v3')])
ret = dic.pop('k2')
print(dic)
print(ret)
# 输出：v2
# dic['k4'] = None 等同于 dic.setdefault('k4','66') 如果没有66就是None
dic.update({'k1':'v111','k10':'v222'})
print(dic)
# 更新数据，没有就插入，有就更新值
4.Python默认字典defaultdict
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
#! /usr/bin/env python
# -*- coding:utf-8 -*-
# 默认字典defaultdict ：定义一个字典，让字典的值默认是个什么类型
import collections
# 有如下值集合 [11,22,33,44,55,66,77,88,99,90...]，将所有大于 66 的值保存至字典的第一个key中，将小于 66 的值保存至第二个key的值中。
# 即： {'k1': 大于66 , 'k2': 小于66}
'''
******************************************************************
values = [11,22,33,44,55,66,77,88,90]
my_dict = {}
for value in values:
if value>66:
if my_dict.has_key('k1'):
my_dict['k1'].append(value)
else:
my_dict['k1'] = [value]
else:
if my_dict.has_key('k2'):
my_dict['k2'].append(value)
else:
my_dict['k2'] = ['value']
******************************************************************
'''
from collections import defaultdict
values = [11, 22, 33,44,55,66,77,88,99,90]
my_dict = defaultdict(list) #设置一个默认字典，类型为列表
for value in values:
if value>66:
my_dict['k1'].append(value)
else:
my_dict['k2'].append(value)
print(my_dict)
# 输出：defaultdict(<class 'list'>, {'k2': [11, 22, 33, 44, 55, 66], 'k1': [77, 88, 99, 90]})
# dic = {'k1':[]} #默认让字典的值为空列表
# dic[k1].append('leon')
dic = collections.defaultdict(list) #
dic['k1'].append('leon')
print(dic)
# 输出：defaultdict(<class 'list'>, {'k1': ['leon']})
PS:orderdDict是对字典类型的补充，他记住了字典元素添加的顺序
5.Python可命名元祖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 119 120 Mytuple
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。
没有提供类，需要自己通过namedtuple 方法创建类，创建对象
'''
t = (11,22,33,44,55,566)
t = home,age,gender,address #给元素命名
t[0]
t[2]
通过索引来取值
t.name
t.age
t.address
t.gender
两个元素就是X,Y轴形式
obj = (1,2)
obj.x
obj.y
'''
#! /usr/bin/env python
# -*- coding:utf-8 -*-
import collections
# 创建类，defaultdict
MytupleClass = collections.namedtuple('MytupleClass',['x','y','z'])
#print(help(MytupleClass)) 查看MytupleClass类里的方法
obj = MytupleClass(111,222,333)
print(obj.x)
print(obj.y)
print(obj.z)
6.Python双向队列deque
一个线程安全的双向队列
#! /usr/bin/env python
# -*- coding:utf-8 -*-
import collections
d = collections.deque()
d.append('1') #往右添加元素
d.appendleft('10')
d.appendleft('1') #往左添加元素
print(d)
ret = d.count('1') #查看元素的个数
print(ret)
d.extend(['cc','aa','rr']) #扩展元素
d.extendleft(['ff','vv'])
print(d)
d.rotate(5) #自己从队列的右边拿数据插入到左边，执行5次操作
print(d)
'''
输出：
deque(['1', '10', '1'])
2
deque(['vv', 'ff', '1', '10', '1', 'cc', 'aa', 'rr'])
deque(['10', '1', 'cc', 'aa', 'rr', 'vv', 'ff', '1'])
'''
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
7.Python单向队列queue.Queue
先进先出 FIFO；
内存栈，后进先出。
练习：
#! /usr/bin/env python
# -*- coding:utf-8 -*-
import queue # 含单向队列
import collections # 含双向队列
# d = collections.deque()
q = queue.Queue()
# q.qsize() # 查看队列个数
q.put('123')
q.put('678')
q.put('ddd')
print(q.qsize())
print(q.get())
"""
输出：
3
123
"""
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
8.Python深浅拷贝原理
深浅拷贝原理：
为什么要拷贝？
1.当进行修改时，想要保留原来的数据和修改后的数据
数字字符串 和 集合 在修改时的差异？ （深浅拷贝不同的原因）
1.在修改数据时：
2.数字字符串：在内存中新建一份数据
3.集合：修改内存中的同一份数据
对于集合，如何保留其修改前和修改后的数据？
2.在内存中拷贝一份
对于集合，如何拷贝其n层元素同时拷贝？
1 #! /usr/bin/env python 2 # -*- coding:utf-8 -*- 3 4 import copy 5 # 浅拷贝 6 # copy.copy() 7 # 深拷贝 8 # copy.deepcopy() 9 10 ''' 11 # 字符串、数字、赋值 12 a1 = 123123 13 # a2 = 123123 14 a2 = a1 15 print(id(a1)) 16 print(id(a2)) 17 ''' 18 '''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。 19 a1 = "adasfasdfasdf" 20 a3 = copy.copy(a1) 21 a4 = copy.deepcopy(a1) 22 print(id(a1)) 23 print(id(a3)) 24 print(id(a4)) 25 # 输出： 26 # 10952304 27 # 10952304 28 # 10952304 29 ''' 30 # 其他包括数字、元组、列表、字典 31 # 对于字典、元祖、列表 而言，进行赋值、浅拷贝和深拷贝时，其内存地址的变化是不同的。 32 # 赋值，只是创建一个变量，该变量指向原来内存地址，如： 33 n1 = {"k1":"wu","k2":"123","k3":["leon",456]} 34 n2 = n1 #赋值 35 n3 = copy.copy(n1) #浅拷贝只copy内存里面的列表，但不拷贝列表里的元素，只copy一层 36 n4 = copy.deepcopy(n1) #深拷贝copy拷贝了多层，在内存中将所有的数据重新创建一份（排除最后一层，即：python内部对字符串和数字的优化） 37 print(id(n1)) 38 print(id(n2)) 39 print(id(n3["k3"])) 40 print(id(n4["k3"])) 41 ''' 42 输出： 43 10470344 44 10470344 45 11318856 46 11317640 47 '''
1 """Generic (shallow and deep) copying operations. 2 3 Interface summary: 4 5 import copy 6 7 x = copy.copy(y) # make a shallow copy of y 8 x = copy.deepcopy(y) # make a deep copy of y 9 10 For module specific errors, copy.Error is raised. 11 12 The difference between shallow and deep copying is only relevant for 13 compound objects (objects that contain other objects, like lists or 14 class instances). 15 16 - A shallow copy constructs a new compound object and then (to the 17 extent possible) inserts *the same objects* into it that the 18 original contains. 19 20 - A deep copy constructs a new compound object and then, recursively, 21 inserts *copies* into it of the objects found in the original. 22 23 Two problems often exist with deep copy operations that don't exist 24 with shallow copy operations: 25 26 a) recursive objects (compound objects that, directly or indirectly, 27 contain a reference to themselves) may cause a recursive loop 28 29 b) because deep copy copies *everything* it may copy too much, e.g. 30 administrative data structures that should be shared even between 31 copies 32 33 Python's deep copy operation avoids these problems by: 34 35 a) keeping a table of objects already copied during the current 36 copying pass 37 38 b) letting user-defined classes override the copying operation or the 39 set of components copied 40 41 This version does not copy types like module, class, function, method, 42 nor stack trace, stack frame, nor file, socket, window, nor array, nor 43 any similar types. 44 45 Classes can use the same interfaces to control copying that they use 46 to control pickling: they can define methods called __getinitargs__(), 47 __getstate__() and __setstate__(). See the documentation for module 48 "pickle" for information on these methods. 49 """ 50 51 import types 52 import weakref 53 from copyreg import dispatch_table 54 import builtins 55 56 class Error(Exception): 57 pass 58 error = Error # backward compatibility 59 60 try: 61 from org.python.core import PyStringMap 62 except ImportError: 63 PyStringMap = None 64 65 __all__ = ["Error", "copy", "deepcopy"] 66 67 def copy(x): 68 """Shallow copy operation on arbitrary Python objects. 69 70 See the module's __doc__ string for more info. 71 """ 72 73 cls = type(x) 74 75 copier = _copy_dispatch.get(cls) 76 if copier: 77 return copier(x) 78 79 try: 80 issc = issubclass(cls, type) 81 except TypeError: # cls is not a class 82 issc = False 83 if issc: 84 # treat it as a regular class: 85 return _copy_immutable(x) 86 87 copier = getattr(cls, "__copy__", None) 88 if copier: 89 return copier(x) 90 91 reductor = dispatch_table.get(cls) 92 if reductor: 93 rv = reductor(x) 94 else: 95 reductor = getattr(x, "__reduce_ex__", None) 96 if reductor: 97 rv = reductor(4) 98 else: 99 reductor = getattr(x, "__reduce__", None) 100 if reductor: 101 rv = reductor() 102 else: 103 raise Error("un(shallow)copyable object of type %s" % cls) 104 105 return _reconstruct(x, rv, 0) 106 107 108 _copy_dispatch = d = {} 109 110 def _copy_immutable(x): 111 return x 112 for t in (type(None), int, float, bool, str, tuple, 113 bytes, frozenset, type, range, 114 types.BuiltinFunctionType, type(Ellipsis), 115 types.FunctionType, weakref.ref): 116 d[t] = _copy_immutable 117 t = getattr(types, "CodeType", None) 118 if t is not None: 119 d[t] = _copy_immutable 120 for name in ("complex", "unicode"): 121 t = getattr(builtins, name, None) 122 if t is not None: 123 d[t] = _copy_immutable 124 125 def _copy_with_constructor(x): 126 return type(x)(x) 127 for t in (list, dict, set): 128 d[t] = _copy_with_constructor 129 130 def _copy_with_copy_method(x): 131 return x.copy() 132 if PyStringMap is not None: 133 d[PyStringMap] = _copy_with_copy_method 134 135 del d 136 137 def deepcopy(x, memo=None, _nil=[]): 138 """Deep copy operation on arbitrary Python objects. 139 140 See the module's __doc__ string for more info. 141 """ 142 143 if memo is None: 144 memo = {} 145 146 d = id(x) 147 y = memo.get(d, _nil) 148 if y is not _nil: 149 return y 150 151 cls = type(x) 152 153 copier = _deepcopy_dispatch.get(cls) 154 if copier: 155 y = copier(x, memo) 156 else: 157 try: 158 issc = issubclass(cls, type) 159 except TypeError: # cls is not a class (old Boost; see SF #502085) 160 issc = 0 161 if issc: 162 y = _deepcopy_atomic(x, memo) 163 else: 164 copier = getattr(x, "__deepcopy__", None) 165 if copier: 166 y = copier(memo) 167 else: 168 reductor = dispatch_table.get(cls) 169 if reductor: 170 rv = reductor(x) 171 else: 172 reductor = getattr(x, "__reduce_ex__", None) 173 if reductor: 174 rv = reductor(4) 175 else: 176 reductor = getattr(x, "__reduce__", None) 177 if reductor: 178 rv = reductor() 179 else: 180 raise Error( 181 "un(deep)copyable object of type %s" % cls) 182 y = _reconstruct(x, rv, 1, memo) 183 184 # If is its own copy, don't memoize. 185 if y is not x: 186 memo[d] = y 187 _keep_alive(x, memo) # Make sure x lives at least as long as d 188 return y 189 190 _deepcopy_dispatch = d = {} 191 192 def _deepcopy_atomic(x, memo): 193 return x 194 d[type(None)] = _deepcopy_atomic 195 d[type(Ellipsis)] = _deepcopy_atomic 196 d[int] = _deepcopy_atomic 197 d[float] = _deepcopy_atomic 198 d[bool] = _deepcopy_atomic 199 try: 200 d[complex] = _deepcopy_atomic 201 except NameError: 202 pass 203 d[bytes] = _deepcopy_atomic 204 d[str] = _deepcopy_atomic 205 try: 206 d[types.CodeType] = _deepcopy_atomic 207 except AttributeError: 208 pass 209 d[type] = _deepcopy_atomic 210 d[range] = _deepcopy_atomic 211 d[types.BuiltinFunctionType] = _deepcopy_atomic 212 d[types.FunctionType] = _deepcopy_atomic 213 d[weakref.ref] = _deepcopy_atomic 214 215 def _deepcopy_list(x, memo): 216 y = [] 217 memo[id(x)] = y 218 for a in x: 219 y.append(deepcopy(a, memo)) 220 return y 221 d[list] = _deepcopy_list 222 223 def _deepcopy_tuple(x, memo): 224 y = [deepcopy(a, memo) for a in x] 225 # We're not going to put the tuple in the memo, but it's still important we 226 # check for it, in case the tuple contains recursive mutable structures. 227 try: 228 return memo[id(x)] 229 except KeyError: 230 pass 231 for k, j in zip(x, y): 232 if k is not j: 233 y = tuple(y) 234 break 235 else: 236 y = x 237 return y 238 d[tuple] = _deepcopy_tuple 239 240 def _deepcopy_dict(x, memo): 241 y = {} 242 memo[id(x)] = y 243 for key, value in x.items(): 244 y[deepcopy(key, memo)] = deepcopy(value, memo) 245 return y 246 d[dict] = _deepcopy_dict 247 if PyStringMap is not None: 248 d[PyStringMap] = _deepcopy_dict 249 250 def _deepcopy_method(x, memo): # Copy instance methods 251 return type(x)(x.__func__, deepcopy(x.__self__, memo)) 252 _deepcopy_dispatch[types.MethodType] = _deepcopy_method 253 254 def _keep_alive(x, memo): 255 """Keeps a reference to the object x in the memo. 256 257 Because we remember objects by their id, we have 258 to assure that possibly temporary objects are kept 259 alive by referencing them. 260 We store a reference at the id of the memo, which should 261 normally not be used unless someone tries to deepcopy 262 the memo itself... 263 """ 264 try: 265 memo[id(memo)].append(x) 266 except KeyError: 267 # aha, this is the first one :-) 268 memo[id(memo)]=[x] 269 270 def _reconstruct(x, info, deep, memo=None): 271 if isinstance(info, str): 272 return x 273 assert isinstance(info, tuple) 274 if memo is None: 275 memo = {} 276 n = len(info) 277 assert n in (2, 3, 4, 5) 278 callable, args = info[:2] 279 if n > 2: 280 state = info[2] 281 else: 282 state = {} 283 if n > 3: 284 listiter = info[3] 285 else: 286 listiter = None 287 if n > 4: 288 dictiter = info[4] 289 else: 290 dictiter = None 291 if deep: 292 args = deepcopy(args, memo) 293 y = callable(*args) 294 memo[id(x)] = y 295 296 if state: 297 if deep: 298 state = deepcopy(state, memo) 299 if hasattr(y, '__setstate__'): 300 y.__setstate__(state) 301 else: 302 if isinstance(state, tuple) and len(state) == 2: 303 state, slotstate = state 304 else: 305 slotstate = None 306 if state is not None: 307 y.__dict__.update(state) 308 if slotstate is not None: 309 for key, value in slotstate.items(): 310 setattr(y, key, value) 311 312 if listiter is not None: 313 for item in listiter: 314 if deep: 315 item = deepcopy(item, memo) 316 y.append(item) 317 if dictiter is not None: 318 for key, value in dictiter: 319 if deep: 320 key = deepcopy(key, memo) 321 value = deepcopy(value, memo) 322 y[key] = value 323 return y 324 325 del d 326 327 del types 328 329 # Helper for instance creation without calling __init__ 330 class _EmptyClass: 331 pass
# 监控数据更新例子：
dic = {
"cpu":[80,],
"mem":[80,],
"disk":[80,],
}
print('before',dic)
# new_dic = copy.copy(dic)
new_dic = copy.deepcopy(dic)
new_dic['cpu'][0] = 50
print(dic)
# print(new_dic)
print(new_dic)
'''
copy.copy输出：会修改原来的数据
before {'disk': [80], 'cpu': [80], 'mem': [80]}
{'disk': [80], 'cpu': [50], 'mem': [80]}
{'disk': [80], 'cpu': [50], 'mem': [80]}
'''
'''
copy.deepcopy输出：不会修改原来的数据，仅update数据
before {'mem': [80], 'cpu': [80], 'disk': [80]}
{'mem': [80], 'cpu': [80], 'disk': [80]}
{'mem': [80], 'cpu': [50], 'disk': [80]}
'''
9.Python函数基本定义
9.1 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 19 20 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： 21 22 def 发送邮件(内容) 23 #发送邮件提醒 24 连接邮箱服务器 25 发送邮件 26 关闭连接 27 28 while True： 29 30 if cpu利用率 > 90%: 31 发送邮件('CPU报警') 32 33 if 硬盘使用空间 > 90%: 34 发送邮件('硬盘报警') 35 36 if 内存占用 > 80%: 37 发送邮件('内存报警') 38 39 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： 40 41 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 42 面向对象：对函数进行分类和封装，让开发“更快更好更强...” 43 函数式编程最重要的是增强代码的重用性和可读性
#! /usr/bin/env python
# -*- coding:utf-8 -*-
def mail():
n = 123
n += 1
print(n)
mail() #执行函数代码块，mail执行内存地址函数
f = mail
f()
"""
输出：
124
124
"""
9.2 定义和使用
def 函数名(参数):
...
函数体
...
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，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：
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。
def 发送短信():
发送短信的代码...
if 发送成功:
return True
else:
return False
while True:
# 每次执行发送短信函数，都会将返回值自动赋值给result
# 之后，可以根据result来写日志，或重发等操作
result = 发送短信()
if result == False:
记录日志，短信发送失败...
def show():
print('a')
return [11,22] # 遇到函数、方法后return后，后面代码不执行
print('b')
ret = show()
# So ruturn ： 1.返回值 2.中断函数操作
9.3 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
函数的有三种不同的参数：
- 普通参数
- 默认参数
- 动态参数
1 def func(name, age = 18): 2 3 print "%s:%s" %(name,age) 4 5 # 指定参数 6 func('leon', 19) 7 # 使用默认参数 8 func('Jack') 9 10 注：默认参数需要放在参数列表最后 11 12 默认参数
1 # ######### 定义函数 ######### 2 3 # name 叫做函数func的形式参数，简称：形参 4 def func(name): 5 print name 6 7 # ######### 执行函数 ######### 8 # 'leon' 叫做函数func的实际参数，简称：实参 9 func('leon')
1 def func(*args): 2 3 print args 4 5 6 # 执行方式一 7 func(11,33,4,4454,5) 8 9 # 执行方式二 10 li = [11,2,2,3,3,4,54] 11 func(*li) 12 13 动态参数-序列
1 def func(**kwargs): 2 3 print args 4 5 6 # 执行方式一 7 func(name＝'wupeiqi',age=18) 8 9 # 执行方式二 10 li = {'name':'wupeiqi', age:18, 'gender':'male'} 11 func(**li) 12 13 动态参数-字典
1 def func(*args, **kwargs): 2 3 print args 4 print kwargs 5 6 动态参数-序列和字典
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(["Leon",'liyoung2008@163.com']) 8 msg['To'] = formataddr(["test",'176487377@qq.com']) 9 msg['Subject'] = "主题" 10 11 server = smtplib.SMTP("smtp.163.com", 25) 12 server.login("liyoung2008@163.com", "邮箱密码") 13 server.sendmail('liyoung2008@163.com', ['176487377@qq.com',], msg.as_string()) 14 server.quit()
1 #! /usr/bin/env python 2 # -*- coding:utf-8 -*- 3 """ 4 # 无参数 5 # show(): ---> show() 6 7 # 一个参数 8 def show(arg): 9 print(arg) 10 show('kkkkkk') 11 12 # 两个参数 13 def show(arg,xxx): 14 print(arg,xxx) 15 show('kkkkkk','777') 16 17 # 默认参数： 18 def show(a1,a2=999): # 指定a2 默认参数999，必须放在参数的后面 19 print(a1,a2) 20 show(111) 21 # 输出：111 999 22 23 # 指定参数 24 def show(a1,a2): 25 print(a1,a2) 26 show(a2=123,a1=999) 27 # 输出：999 123 28 """ 29 """ 30 def show(arg): 31 print(arg) 32 n = [[11,22,33]] 33 show(n) 34 """ 35 36 # 动态参数： 37 38 def show(*arg): # 带一个*将传入的参数转换成元组 39 print(arg,type(arg)) 40 show(11,22,33,44,55) 41 # 输出：(11, 22, 33, 44, 55) <class 'tuple'> 42 43 def show(**arg): # 带两个*将传入的参数转换成字典 44 print(arg,type(arg)) 45 show(n1=111,n2=222,n3=333) 46 # 输出：{'n2': 222, 'n1': 111, 'n3': 333} <class 'dict'> 47 48 def show(*args,**kwargs): #一个*的放前面，两个*放后面 49 print(args,type(args)) 50 print(kwargs,type(kwargs)) 51 show(11,22,33,44,n1=123,n2=321) 52 # 输出： 53 # (11, 22, 33, 44) <class 'tuple'> 54 # {'n1': 123, 'n2': 321} <class 'dict'> 55 56 def show(*args,**kwargs): #一个*的放前面，两个*放后面 57 print(args,type(args)) 58 print(kwargs,type(kwargs)) 59 l = [11,22,33,44] 60 d = {"n1":"123","n2":"321"} 61 show(*l,**d) #注意看这里的赋值
10.使用动态参数实现字符串格式化
# 字符串的格式化
s1 = "{0} is {1}"
l = ['leon','nb'] #传入列表
# result = s1.format('leon','nb')
result = s1.format(*l)
print(result)
s1 = "{name} is {acter}"
d = {'name':'lee','acter':'nb'} # 传入字典
# result = s1.format(name='leon',acter='nb')
result = s1.format(**d)
print(result)
11.Python lambda表达式
#! /usr/bin/env python
# -*- coding:utf-8 -*-
def func(a):
a += 1
return a
result = func(4)
print(result)
# lambda表达式：简单函数的简单表示
func = lambda a:a+1 # a是形式参数，冒号前面是参数，冒号后面是函数体，自动加return值
# 创建函数参数a
# 函数内容，a+1 并把结果返回
ret = func(99)
print(ret)
12. Python 内置函数
内置函数链接地址：请点击此处链接官网说明
内置函数二讲解：
#! /usr/bin/env python
# -*- coding:utf-8 -*-
class Foo:
def __repr__(self):
return 'aaaaa'
f = Foo()
ret = ascii(f)
print(ret)
# abs(1) _abs_
# format(7) = int._format_(7)
# hex(100) '0x64' 转换16进制
# max(11,22,333,4444,,5555) 可以取到最大值
# range(0,10) 进行for循环时创建0-9区间
# round(8.9) 输出9 用于四舍五入
p = bytearray('周杰伦',encoding='utf-8')
print(p)
p = bytes('周杰伦',encoding='utf-8')
print(p)
import random # 做验证码时用到，chr（数字转换字符）和ord（字符转换数字）结合使用
f = random.randint(1,99)
print(f)
map & filter 说明：
1. map
遍历序列，对序列中每个元素进行操作，最终获取新的序列。
#每个元素增加100 li = [11, 22, 33] new_list = map(lambda a: a + 100, li)
# 两个列表对应元素相加 li = [11, 22, 33] sl = [1, 2, 3] new_list = map(lambda a, b: a + b, li, sl)
2. filter
对于序列中的元素进行筛选，最终获取符合条件的序列
# 获取到大于22的值 li = [11, 22, 33] new_list = filter(lambda arg: arg > 22, li) #filter第一个参数为空，将获取原来序列
3. reduce (3.X中已不存在)
对于序列内所有元素进行累计操作
1 li = [11, 22, 33] 2 3 result = reduce(lambda arg1, arg2: arg1 + arg2, li) 4 5 # reduce的第一个参数，函数必须要有两个参数 6 # reduce的第二个参数，要循环的序列 7 # reduce的第三个参数，初始值
13.Python 文件操作
13.1 文件操作：
1 class file(object): 2 3 def close(self): # real signature unknown; restored from __doc__ 4 关闭文件 5 """ 6 close() -> None or (perhaps) an integer. Close the file. 7 8 Sets data attribute .closed to True. A closed file cannot be used for 9 further I/O operations. close() may be called more than once without 10 error. Some kinds of file objects (for example, opened by popen()) 11 may return an exit status upon closing. 12 """ 13 14 def fileno(self): # real signature unknown; restored from __doc__ 15 文件描述符 16 """ 17 fileno() -> integer "file descriptor". 18 19 This is needed for lower-level file interfaces, such os.read(). 20 """ 21 return 0 22 23 def flush(self): # real signature unknown; restored from __doc__ 24 刷新文件内部缓冲区 25 """ flush() -> None. Flush the internal I/O buffer. """ 26 pass 27 28 29 def isatty(self): # real signature unknown; restored from __doc__ 30 判断文件是否是同意tty设备 31 """ isatty() -> true or false. True if the file is connected to a tty device. """ 32 return False 33 34 35 def next(self): # real signature unknown; restored from __doc__ 36 获取下一行数据，不存在，则报错 37 """ x.next() -> the next value, or raise StopIteration """ 38 pass 39 40 def read(self, size=None): # real signature unknown; restored from __doc__ 41 读取指定字节数据 42 """ 43 read([size]) -> read at most size bytes, returned as a string. 44 45 If the size argument is negative or omitted, read until EOF is reached. 46 Notice that when in non-blocking mode, less data than what was requested 47 may be returned, even if no size parameter was given. 48 """ 49 pass 50 51 def readinto(self): # real signature unknown; restored from __doc__ 52 读取到缓冲区，不要用，将被遗弃 53 """ readinto() -> Undocumented. Don't use this; it may go away. """ 54 pass 55 56 def readline(self, size=None): # real signature unknown; restored from __doc__ 57 仅读取一行数据 58 """ 59 readline([size]) -> next line from the file, as a string. 60 61 Retain newline. A non-negative size argument limits the maximum 62 number of bytes to return (an incomplete line may be returned then). 63 Return an empty string at EOF. 64 """ 65 pass 66 67 def readlines(self, size=None): # real signature unknown; restored from __doc__ 68 读取所有数据，并根据换行保存值列表 69 """ 70 readlines([size]) -> list of strings, each a line from the file. 71 72 Call readline() repeatedly and return a list of the lines so read. 73 The optional size argument, if given, is an approximate bound on the 74 total number of bytes in the lines returned. 75 """ 76 return [] 77 78 def seek(self, offset, whence=None): # real signature unknown; restored from __doc__ 79 指定文件中指针位置 80 """ 81 seek(offset[, whence]) -> None. Move to new file position. 82 83 Argument offset is a byte count. Optional argument whence defaults to 84 0 (offset from start of file, offset should be >= 0); other values are 1 85 (move relative to current position, positive or negative), and 2 (move 86 relative to end of file, usually negative, although many platforms allow 87 seeking beyond the end of a file). If the file is opened in text mode, 88 only offsets returned by tell() are legal. Use of other offsets causes 89 undefined behavior. 90 Note that not all file objects are seekable. 91 """ 92 pass 93 94 def tell(self): # real signature unknown; restored from __doc__ 95 获取当前指针位置 96 """ tell() -> current file position, an integer (may be a long integer). """ 97 pass 98 99 def truncate(self, size=None): # real signature unknown; restored from __doc__ 100 截断数据，仅保留指定之前数据 101 """ 102 truncate([size]) -> None. Truncate the file to at most size bytes. 103 104 Size defaults to the current file position, as returned by tell(). 105 """ 106 pass 107 108 def write(self, p_str): # real signature unknown; restored from __doc__ 109 写内容 110 """ 111 write(str) -> None. Write string str to file. 112 113 Note that due to buffering, flush() or close() may be needed before 114 the file on disk reflects the data written. 115 """ 116 pass 117 118 def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__ 119 将一个字符串列表写入文件 120 """ 121 writelines(sequence_of_strings) -> None. Write the strings to the file. 122 123 Note that newlines are not added. The sequence can be any iterable object 124 producing strings. This is equivalent to calling write() for each string. 125 """ 126 pass 127 128 def xreadlines(self): # real signature unknown; restored from __doc__ 129 可用于逐行读取文件，非全部 130 """ 131 xreadlines() -> returns self. 132 133 For backward compatibility. File objects now include the performance 134 optimizations previously implemented in the xreadlines module. 135 """ 136 pass
B. 基础知识点：
操作文件时，一般需要如下步骤：
- 打开文件 open
- 操作文件 r,w
read 是按照字符来读，tell按照字节来读的
f.tell #查看当前指针位置
f.seek #指定当前指针位置
13.2 打开文件
1 文件句柄 =file('文件路径', '模式')
注：python中打开文件有两种方式，即：open(...) 和 file(...) ，本质上前者在内部会调用后者来进行文件操作，推荐使用 open。
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
13.3 with使用
为了避免打开文件后忘记关闭，可以通过管理上下文，即：
with open('log','r') as f:
...
如此方式，当with代码块执行完毕时，内部会自动关闭并释放文件资源。在Python 2.7 后，with又支持同时对多个文件的上下文进行管理，即：
with open('log1') as obj1, open('log2') as obj2:
pass
部分内容引用：http://www.cnblogs.com/wupeiqi/tag/python之路 （tks）
胸怀天下，有容乃大
