Python学习笔记——基础篇2【第三周】——计数器、有序字典、元组、单(双)向队列、深浅拷贝、函数、装饰器
目录
1、Python计数器Counter
2、Python有序字典OrderredDict
3、Python默认字典default
4、python可命名元组namedtuple
5、Python双向队列deque
6、Python单向队列deque
7、Python深浅拷贝原理
8、Python深浅拷贝应用
9、python函数的基本定义（open、lambda、递归、装饰器）
collections系列
1、Python计数器Counter
1、计数器（counter）
Counter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 + 自己的功能
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c = Counter('abcdeabcdabcaba') print c输出：Counter({'a': 5, 'b': 4, 'c': 3, 'd': 2, 'e': 1}) |
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
import collections
# obj = collections.Counter('aaddwersdfdf')
# print(obj)
# ret = obj.most_common(4) #查看前四位
# print(ret)
# for item in obj.elements():
# print(item)
# for k in obj.elements():
# print(k)
# for k,v in obj.items():
# print(k,v)
obj = collections.Counter(['11','22','22','33'])
print(obj)
obj.update(['eric','11','11'])
print(obj)
obj.subtract(['eric','11','11'])
print(obj)
2、Python有序字典OrderredDict
2、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)
用for循环做一个有序字典
dic = collections.OrderedDict()
# dic = dict()
dic['k1']='v1'
dic['k2']='v2'
dic['k3']='v3'
dic['k2']='v2'
# dic['k4']=None
# dic.setdefault('k4','66') #与上一步等同
print(dic)
#将k1移到结尾
# dic.move_to_end('k1')
# print(dic)
# dic.popitem()
# print(dic)
# dic.popitem()
# print(dic)
# ret = dic.pop('k2')
# print(dic)
# print(ret)
dic.update({'k1':'v111','k10':'v10'})
print(dic)
3、Python默认字典default
3、默认字典(defaultdict)
学前需求：
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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} |
1 values = [11, 22, 33,44,55,66,77,88,99,90] 2 3 my_dict = {} 4 5 for value in values: 6 if value>66: 7 if my_dict.has_key('k1'): 8 my_dict['k1'].append(value) 9 else: 10 my_dict['k1'] = [value] 11 else: 12 if my_dict.has_key('k2'): 13 my_dict['k2'].append(value) 14 else: 15 my_dict['k2'] = [value] 16 17 原生字典解决方法
1 from collections import defaultdict 2 3 values = [11, 22, 33,44,55,66,77,88,99,90] 4 5 my_dict = defaultdict(list) 6 7 for value in values: 8 if value>66: 9 my_dict['k1'].append(value) 10 else: 11 my_dict['k2'].append(value)
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__()."""
# dic = {'k1':[]}
# dic['k1'].append('alex')
# print(dic)
dic=collections.defaultdict(list)
dic['k1'].append('alex')
print(dic)
4、python可命名元组namedtuple
4、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。
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import collectionsMytuple = collections.namedtuple('Mytuple',['x', 'y', 'z']) |
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
# t = (11,22,33,44)
# #name age gender address
# print(t[0])
# print(t[2])
# t.name
# t.age
import collections
#创建类，等同于defaultdict
MytupleClass = collections.namedtuple('MytupleClass',['x', 'y', 'z'])
print(help(MytupleClass))
obj = MytupleClass(11,22,33)
print(obj.x)
print(obj.y)
print(obj.z)
5、Python双向队列deque
5、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
注：既然有双向队列，也有单项队列（先进先出 FIFO ）
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()
#双向队列
d = collections.deque()
d.append('1')
d.appendleft('10')
d.appendleft('1')
print(d)
r = d.count('1')
print(r)
d.extend(['yy','uu','ii'])
d.extendleft(['y1y','u1u','i1i'])
print(d)
d.rotate(5)
print(d)
6、Python单向队列deque
#单向队列
import queue
#d = collections.deque()
q = queue.Queue()
q.put('123')
q.put('789')
print(q.qsize()) #个数
print(q.get()) #拿数据
7、Python深浅拷贝原理
为什么要拷贝？
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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？ （深浅拷贝不同的终极原因）
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在修改数据时： 数字字符串：在内存中新建一份数据 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？
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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？
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深拷贝 |
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。
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import copy# ######### 数字、字符串 #########n1 = 123# n1 = "i am alex age 10"print(id(n1))# ## 赋值 ##n2 = n1print(id(n2))# ## 浅拷贝 ##n2 = copy.copy(n1)print(id(n2))# ## 深拷贝 ##n3 = copy.deepcopy(n1)print(id(n3)) |
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。
赋值，只是创建一个变量，该变量指向原来内存地址，如：
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n1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}n2 = n1 |
浅拷贝，在内存中只额外创建第一层数据
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import copyn1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}n3 = copy.copy(n1) |
深拷贝，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）
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import copyn1 = {"k1": "wu", "k2": 123, "k3": ["alex", 456]}n4 = copy.deepcopy(n1) |
8、Python深浅拷贝应用
import copy
# # #浅拷贝
# copy.copy()
# #深拷贝
# copy.deepcopy()
# #赋值
# # =
#字符串，数字
# a1 = "asdasda"
# #a2 = 123123
# a2 = a1
# print(id(a1))
# print(id(a2))
# a3 = copy.copy(a1)
# print(id(a1))
# print(id(a3))
#
# a3 = copy.deepcopy(a1)
# print(id(a1))
# print(id(a3))
# #字符串和数字读取的是内存的地址
#其他，元祖，列表，字典
# n1 = {"k1":"wu","k2":123,"k3":["alex",456]}
# n2=n1
# print(id(n1))
# print(id(n2))
# n3 = copy.copy(n1)
# n3 = copy.deepcopy(n1)
# print(id(n1))
# print(id(n3))
#
# print(id(n1['k3']))
# print(id(n3['k3']))
#实例应用：
dic = {
"CPU":[80,],
"mem0":[80,],
"disk":[80,]
}
print('brefore',dic)
new_dic = copy.deepcopy(dic)
new_dic['CPU'][0] = 50
print(dic)
print(new_dic)
9、python函数的基本定义
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：
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while True： if cpu利用率 > 90%: #发送邮件提醒 连接邮箱服务器 发送邮件 关闭连接 if 硬盘使用空间 > 90%: #发送邮件提醒 连接邮箱服务器 发送邮件 关闭连接 if 内存占用 > 80%: #发送邮件提醒 连接邮箱服务器 发送邮件 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：
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def 发送邮件(内容) #发送邮件提醒 连接邮箱服务器 发送邮件 关闭连接 while True： if cpu利用率 > 90%: 发送邮件('CPU报警') if 硬盘使用空间 > 90%: 发送邮件('硬盘报警') 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
二、定义和使用
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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，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：
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。
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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... |
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（）
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。")
函数的有三中不同的参数：
- 普通参数
- 默认参数
- 动态参数
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 # 'wupeiqi' 叫做函数func的实际参数，简称：实参 9 func('wupeiqi')
1 def func(name, age = 18): 2 3 print "%s:%s" %(name,age) 4 5 # 指定参数 6 func('wupeiqi', 19) 7 # 使用默认参数 8 func('alex') 9 10 注：默认参数需要放在参数列表最后
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)
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)
1 def func(*args, **kwargs): 2 3 print args 4 print kwargs
扩展：发送邮件实例
import smtplib
from email.mime.text import MIMEText
from email.utils import formataddr
msg = MIMEText('邮件内容', 'plain', 'utf-8')
msg['From'] = formataddr(["武沛齐",'wptawy@126.com'])
msg['To'] = formataddr(["走人",'424662508@qq.com'])
msg['Subject'] = "主题"
server = smtplib.SMTP("smtp.126.com", 25)
server.login("wptawy@126.com", "邮箱密码")
server.sendmail('wptawy@126.com', ['424662508@qq.com',], msg.as_string())
server.quit()
内置函数
注：查看详细猛击这里
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
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文件句柄 = open('文件路径', '模式') |
打开文件时，需要指定文件路径和以何等方式打开文件，打开后，即可获取该文件句柄，日后通过此文件句柄对该文件操作。
打开文件的模式有：
- r，只读模式（默认）。
- w，只写模式。【不可读；不存在则创建；存在则删除内容；】
- a，追加模式。【可读； 不存在则创建；存在则只追加内容；】
"+" 表示可以同时读写某个文件
- r+，可读写文件。【可读；可写；可追加】
- w+，写读
- a+，同a
"U"表示在读取时，可以将 \r \n \r\n自动转换成 \n （与 r 或 r+ 模式同使用）
- rU
- r+U
"b"表示处理二进制文件（如：FTP发送上传ISO镜像文件，linux可忽略，windows处理二进制文件时需标注）
- rb
- wb
- ab
1 class file(object) 2 def close(self): # real signature unknown; restored from __doc__ 3 关闭文件 4 """ 5 close() -> None or (perhaps) an integer. Close the file. 6 7 Sets data attribute .closed to True. A closed file cannot be used for 8 further I/O operations. close() may be called more than once without 9 error. Some kinds of file objects (for example, opened by popen()) 10 may return an exit status upon closing. 11 """ 12 13 def fileno(self): # real signature unknown; restored from __doc__ 14 文件描述符 15 """ 16 fileno() -> integer "file descriptor". 17 18 This is needed for lower-level file interfaces, such os.read(). 19 """ 20 return 0 21 22 def flush(self): # real signature unknown; restored from __doc__ 23 刷新文件内部缓冲区 24 """ flush() -> None. Flush the internal I/O buffer. """ 25 pass 26 27 28 def isatty(self): # real signature unknown; restored from __doc__ 29 判断文件是否是同意tty设备 30 """ isatty() -> true or false. True if the file is connected to a tty device. """ 31 return False 32 33 34 def next(self): # real signature unknown; restored from __doc__ 35 获取下一行数据，不存在，则报错 36 """ x.next() -> the next value, or raise StopIteration """ 37 pass 38 39 def read(self, size=None): # real signature unknown; restored from __doc__ 40 读取指定字节数据 41 """ 42 read([size]) -> read at most size bytes, returned as a string. 43 44 If the size argument is negative or omitted, read until EOF is reached. 45 Notice that when in non-blocking mode, less data than what was requested 46 may be returned, even if no size parameter was given. 47 """ 48 pass 49 50 def readinto(self): # real signature unknown; restored from __doc__ 51 读取到缓冲区，不要用，将被遗弃 52 """ readinto() -> Undocumented. Don't use this; it may go away. """ 53 pass 54 55 def readline(self, size=None): # real signature unknown; restored from __doc__ 56 仅读取一行数据 57 """ 58 readline([size]) -> next line from the file, as a string. 59 60 Retain newline. A non-negative size argument limits the maximum 61 number of bytes to return (an incomplete line may be returned then). 62 Return an empty string at EOF. 63 """ 64 pass 65 66 def readlines(self, size=None): # real signature unknown; restored from __doc__ 67 读取所有数据，并根据换行保存值列表 68 """ 69 readlines([size]) -> list of strings, each a line from the file. 70 71 Call readline() repeatedly and return a list of the lines so read. 72 The optional size argument, if given, is an approximate bound on the 73 total number of bytes in the lines returned. 74 """ 75 return [] 76 77 def seek(self, offset, whence=None): # real signature unknown; restored from __doc__ 78 指定文件中指针位置 79 """ 80 seek(offset[, whence]) -> None. Move to new file position. 81 82 Argument offset is a byte count. Optional argument whence defaults to 83 (offset from start of file, offset should be >= 0); other values are 1 84 (move relative to current position, positive or negative), and 2 (move 85 relative to end of file, usually negative, although many platforms allow 86 seeking beyond the end of a file). If the file is opened in text mode, 87 only offsets returned by tell() are legal. Use of other offsets causes 88 undefined behavior. 89 Note that not all file objects are seekable. 90 """ 91 pass 92 93 def tell(self): # real signature unknown; restored from __doc__ 94 获取当前指针位置 95 """ tell() -> current file position, an integer (may be a long integer). """ 96 pass 97 98 def truncate(self, size=None): # real signature unknown; restored from __doc__ 99 截断数据，仅保留指定之前数据 100 """ 101 truncate([size]) -> None. Truncate the file to at most size bytes. 102 103 Size defaults to the current file position, as returned by tell(). 104 """ 105 pass 106 107 def write(self, p_str): # real signature unknown; restored from __doc__ 108 写内容 109 """ 110 write(str) -> None. Write string str to file. 111 112 Note that due to buffering, flush() or close() may be needed before 113 the file on disk reflects the data written. 114 """ 115 pass 116 117 def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__ 118 将一个字符串列表写入文件 119 """ 120 writelines(sequence_of_strings) -> None. Write the strings to the file. 121 122 Note that newlines are not added. The sequence can be any iterable object 123 producing strings. This is equivalent to calling write() for each string. 124 """ 125 pass 126 127 def xreadlines(self): # real signature unknown; restored from __doc__ 128 可用于逐行读取文件，非全部 129 """ 130 xreadlines() -> returns self. 131 132 For backward compatibility. File objects now include the performance 133 optimizations previously implemented in the xreadlines module. 134 """ 135 pass
1 class file(object) 2 def close(self): # real signature unknown; restored from __doc__ 3 关闭文件 4 """ 5 close() -> None or (perhaps) an integer. Close the file. 6 7 Sets data attribute .closed to True. A closed file cannot be used for 8 further I/O operations. close() may be called more than once without 9 error. Some kinds of file objects (for example, opened by popen()) 10 may return an exit status upon closing. 11 """ 12 13 def fileno(self): # real signature unknown; restored from __doc__ 14 文件描述符 15 """ 16 fileno() -> integer "file descriptor". 17 18 This is needed for lower-level file interfaces, such os.read(). 19 """ 20 return 0 21 22 def flush(self): # real signature unknown; restored from __doc__ 23 刷新文件内部缓冲区 24 """ flush() -> None. Flush the internal I/O buffer. """ 25 pass 26 27 28 def isatty(self): # real signature unknown; restored from __doc__ 29 判断文件是否是同意tty设备 30 """ isatty() -> true or false. True if the file is connected to a tty device. """ 31 return False 32 33 34 def next(self): # real signature unknown; restored from __doc__ 35 获取下一行数据，不存在，则报错 36 """ x.next() -> the next value, or raise StopIteration """ 37 pass 38 39 def read(self, size=None): # real signature unknown; restored from __doc__ 40 读取指定字节数据 41 """ 42 read([size]) -> read at most size bytes, returned as a string. 43 44 If the size argument is negative or omitted, read until EOF is reached. 45 Notice that when in non-blocking mode, less data than what was requested 46 may be returned, even if no size parameter was given. 47 """ 48 pass 49 50 def readinto(self): # real signature unknown; restored from __doc__ 51 读取到缓冲区，不要用，将被遗弃 52 """ readinto() -> Undocumented. Don't use this; it may go away. """ 53 pass 54 55 def readline(self, size=None): # real signature unknown; restored from __doc__ 56 仅读取一行数据 57 """ 58 readline([size]) -> next line from the file, as a string. 59 60 Retain newline. A non-negative size argument limits the maximum 61 number of bytes to return (an incomplete line may be returned then). 62 Return an empty string at EOF. 63 """ 64 pass 65 66 def readlines(self, size=None): # real signature unknown; restored from __doc__ 67 读取所有数据，并根据换行保存值列表 68 """ 69 readlines([size]) -> list of strings, each a line from the file. 70 71 Call readline() repeatedly and return a list of the lines so read. 72 The optional size argument, if given, is an approximate bound on the 73 total number of bytes in the lines returned. 74 """ 75 return [] 76 77 def seek(self, offset, whence=None): # real signature unknown; restored from __doc__ 78 指定文件中指针位置 79 """ 80 seek(offset[, whence]) -> None. Move to new file position. 81 82 Argument offset is a byte count. Optional argument whence defaults to 83 (offset from start of file, offset should be >= 0); other values are 1 84 (move relative to current position, positive or negative), and 2 (move 85 relative to end of file, usually negative, although many platforms allow 86 seeking beyond the end of a file). If the file is opened in text mode, 87 only offsets returned by tell() are legal. Use of other offsets causes 88 undefined behavior. 89 Note that not all file objects are seekable. 90 """ 91 pass 92 93 def tell(self): # real signature unknown; restored from __doc__ 94 获取当前指针位置 95 """ tell() -> current file position, an integer (may be a long integer). """ 96 pass 97 98 def truncate(self, size=None): # real signature unknown; restored from __doc__ 99 截断数据，仅保留指定之前数据 100 """ 101 truncate([size]) -> None. Truncate the file to at most size bytes. 102 103 Size defaults to the current file position, as returned by tell(). 104 """ 105 pass 106 107 def write(self, p_str): # real signature unknown; restored from __doc__ 108 写内容 109 """ 110 write(str) -> None. Write string str to file. 111 112 Note that due to buffering, flush() or close() may be needed before 113 the file on disk reflects the data written. 114 """ 115 pass 116 117 def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__ 118 将一个字符串列表写入文件 119 """ 120 writelines(sequence_of_strings) -> None. Write the strings to the file. 121 122 Note that newlines are not added. The sequence can be any iterable object 123 producing strings. This is equivalent to calling write() for each string. 124 """ 125 pass 126 127 def xreadlines(self): # real signature unknown; restored from __doc__ 128 可用于逐行读取文件，非全部 129 """ 130 xreadlines() -> returns self. 131 132 For backward compatibility. File objects now include the performance 133 optimizations previously implemented in the xreadlines module. 134 """ 135
二、操作
1 class file(object) 2 def close(self): # real signature unknown; restored from __doc__ 3 关闭文件 4 """ 5 close() -> None or (perhaps) an integer. Close the file. 6 7 Sets data attribute .closed to True. A closed file cannot be used for 8 further I/O operations. close() may be called more than once without 9 error. Some kinds of file objects (for example, opened by popen()) 10 may return an exit status upon closing. 11 """ 12 13 def fileno(self): # real signature unknown; restored from __doc__ 14 文件描述符 15 """ 16 fileno() -> integer "file descriptor". 17 18 This is needed for lower-level file interfaces, such os.read(). 19 """ 20 return 0 21 22 def flush(self): # real signature unknown; restored from __doc__ 23 刷新文件内部缓冲区 24 """ flush() -> None. Flush the internal I/O buffer. """ 25 pass 26 27 28 def isatty(self): # real signature unknown; restored from __doc__ 29 判断文件是否是同意tty设备 30 """ isatty() -> true or false. True if the file is connected to a tty device. """ 31 return False 32 33 34 def next(self): # real signature unknown; restored from __doc__ 35 获取下一行数据，不存在，则报错 36 """ x.next() -> the next value, or raise StopIteration """ 37 pass 38 39 def read(self, size=None): # real signature unknown; restored from __doc__ 40 读取指定字节数据 41 """ 42 read([size]) -> read at most size bytes, returned as a string. 43 44 If the size argument is negative or omitted, read until EOF is reached. 45 Notice that when in non-blocking mode, less data than what was requested 46 may be returned, even if no size parameter was given. 47 """ 48 pass 49 50 def readinto(self): # real signature unknown; restored from __doc__ 51 读取到缓冲区，不要用，将被遗弃 52 """ readinto() -> Undocumented. Don't use this; it may go away. """ 53 pass 54 55 def readline(self, size=None): # real signature unknown; restored from __doc__ 56 仅读取一行数据 57 """ 58 readline([size]) -> next line from the file, as a string. 59 60 Retain newline. A non-negative size argument limits the maximum 61 number of bytes to return (an incomplete line may be returned then). 62 Return an empty string at EOF. 63 """ 64 pass 65 66 def readlines(self, size=None): # real signature unknown; restored from __doc__ 67 读取所有数据，并根据换行保存值列表 68 """ 69 readlines([size]) -> list of strings, each a line from the file. 70 71 Call readline() repeatedly and return a list of the lines so read. 72 The optional size argument, if given, is an approximate bound on the 73 total number of bytes in the lines returned. 74 """ 75 return [] 76 77 def seek(self, offset, whence=None): # real signature unknown; restored from __doc__ 78 指定文件中指针位置 79 """ 80 seek(offset[, whence]) -> None. Move to new file position. 81 82 Argument offset is a byte count. Optional argument whence defaults to 83 (offset from start of file, offset should be >= 0); other values are 1 84 (move relative to current position, positive or negative), and 2 (move 85 relative to end of file, usually negative, although many platforms allow 86 seeking beyond the end of a file). If the file is opened in text mode, 87 only offsets returned by tell() are legal. Use of other offsets causes 88 undefined behavior. 89 Note that not all file objects are seekable. 90 """ 91 pass 92 93 def tell(self): # real signature unknown; restored from __doc__ 94 获取当前指针位置 95 """ tell() -> current file position, an integer (may be a long integer). """ 96 pass 97 98 def truncate(self, size=None): # real signature unknown; restored from __doc__ 99 截断数据，仅保留指定之前数据 100 """ 101 truncate([size]) -> None. Truncate the file to at most size bytes. 102 103 Size defaults to the current file position, as returned by tell(). 104 """ 105 pass 106 107 def write(self, p_str): # real signature unknown; restored from __doc__ 108 写内容 109 """ 110 write(str) -> None. Write string str to file. 111 112 Note that due to buffering, flush() or close() may be needed before 113 the file on disk reflects the data written. 114 """ 115 pass 116 117 def writelines(self, sequence_of_strings): # real signature unknown; restored from __doc__ 118 将一个字符串列表写入文件 119 """ 120 writelines(sequence_of_strings) -> None. Write the strings to the file. 121 122 Note that newlines are not added. The sequence can be any iterable object 123 producing strings. This is equivalent to calling write() for each string. 124 """ 125 pass 126 127 def xreadlines(self): # real signature unknown; restored from __doc__ 128 可用于逐行读取文件，非全部 129 """ 130 xreadlines() -> returns self. 131 132 For backward compatibility. File objects now include the performance 133 optimizations previously implemented in the xreadlines module. 134 """ 135 pass
1 class TextIOWrapper(_TextIOBase): 2 """ 3 Character and line based layer over a BufferedIOBase object, buffer. 4 5 encoding gives the name of the encoding that the stream will be 6 decoded or encoded with. It defaults to locale.getpreferredencoding(False). 7 8 errors determines the strictness of encoding and decoding (see 9 help(codecs.Codec) or the documentation for codecs.register) and 10 defaults to "strict". 11 12 newline controls how line endings are handled. It can be None, '', 13 '\n', '\r', and '\r\n'. It works as follows: 14 15 * On input, if newline is None, universal newlines mode is 16 enabled. Lines in the input can end in '\n', '\r', or '\r\n', and 17 these are translated into '\n' before being returned to the 18 caller. If it is '', universal newline mode is enabled, but line 19 endings are returned to the caller untranslated. If it has any of 20 the other legal values, input lines are only terminated by the given 21 string, and the line ending is returned to the caller untranslated. 22 23 * On output, if newline is None, any '\n' characters written are 24 translated to the system default line separator, os.linesep. If 25 newline is '' or '\n', no translation takes place. If newline is any 26 of the other legal values, any '\n' characters written are translated 27 to the given string. 28 29 If line_buffering is True, a call to flush is implied when a call to 30 write contains a newline character. 31 """ 32 def close(self, *args, **kwargs): # real signature unknown 33 关闭文件 34 pass 35 36 def fileno(self, *args, **kwargs): # real signature unknown 37 文件描述符 38 pass 39 40 def flush(self, *args, **kwargs): # real signature unknown 41 刷新文件内部缓冲区 42 pass 43 44 def isatty(self, *args, **kwargs): # real signature unknown 45 判断文件是否是同意tty设备 46 pass 47 48 def read(self, *args, **kwargs): # real signature unknown 49 读取指定字节数据 50 pass 51 52 def readable(self, *args, **kwargs): # real signature unknown 53 是否可读 54 pass 55 56 def readline(self, *args, **kwargs): # real signature unknown 57 仅读取一行数据 58 pass 59 60 def seek(self, *args, **kwargs): # real signature unknown 61 指定文件中指针位置 62 pass 63 64 def seekable(self, *args, **kwargs): # real signature unknown 65 指针是否可操作 66 pass 67 68 def tell(self, *args, **kwargs): # real signature unknown 69 获取指针位置 70 pass 71 72 def truncate(self, *args, **kwargs): # real signature unknown 73 截断数据，仅保留指定之前数据 74 pass 75 76 def writable(self, *args, **kwargs): # real signature unknown 77 是否可写 78 pass 79 80 def write(self, *args, **kwargs): # real signature unknown 81 写内容 82 pass 83 84 def __getstate__(self, *args, **kwargs): # real signature unknown 85 pass 86 87 def __init__(self, *args, **kwargs): # real signature unknown 88 pass 89 90 @staticmethod # known case of __new__ 91 def __new__(*args, **kwargs): # real signature unknown 92 """ Create and return a new object. See help(type) for accurate signature. """ 93 pass 94 95 def __next__(self, *args, **kwargs): # real signature unknown 96 """ Implement next(self). """ 97 pass 98 99 def __repr__(self, *args, **kwargs): # real signature unknown 100 """ Return repr(self). """ 101 pass 102 103 buffer = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 104 105 closed = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 106 107 encoding = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 108 109 errors = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 110 111 line_buffering = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 112 113 name = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 114 115 newlines = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 116 117 _CHUNK_SIZE = property(lambda self: object(), lambda self, v: None, lambda self: None) # default 118 119 _finalizing = property(lambda self: object(), lambda self, v: None, lambda self: None) # default
三、管理上下文
为了避免打开文件后忘记关闭，可以通过管理上下文，即：
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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：
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with open('log1') as obj1, open('log2') as obj2: pass |
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：
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# 普通条件语句if 1 == 1: name = 'wupeiqi'else: name = 'alex' # 三元运算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
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# ###################### 普通函数 ####################### 定义函数（普通方式）def func(arg): return arg + 1 # 执行函数result = func(123) # ###################### lambda ###################### # 定义函数（lambda表达式）my_lambda = lambda arg : arg + 1 # 执行函数result = my_lambda(123) |
lambda存在意义就是对简单函数的简洁表示
递归
利用函数编写如下数列：
斐波那契数列指的是这样一个数列 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233，377，610，987，1597，2584，4181，6765，10946，17711，28657，46368...
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def func(arg1,arg2): if arg1 == 0: print arg1, arg2 arg3 = arg1 + arg2 print arg3 func(arg2, arg3)func(0,1) |
装饰器
装饰器是函数，只不过该函数可以具有特殊的含义，装饰器用来装饰函数或类，使用装饰器可以在函数执行前和执行后添加相应操作。
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def wrapper(func): def result(): print 'before' func() print 'after' return result @wrapperdef foo(): print 'foo' |
1 import functools 2 3 4 def wrapper(func): 5 @functools.wraps(func) 6 def wrapper(): 7 print 'before' 8 func() 9 print 'after' 10 return wrapper 11 12 @wrapper 13 def foo(): 14 print 'foo'
详细猛击这里
