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
284
285 Counter

  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

values = [11, 22, 33,44,55,66,77,88,99,90]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]

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字典解决方法

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__()."""

defaultdict

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。

1 import collections
2
3 Mytuple = collections.namedtuple('Mytuple',['x', 'y', 'z'])

values = [11, 22, 33,44,55,66,77,88,99,90]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]复制代码
defaultdict字典解决方法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。
defaultdict4、可命名元组(namedtuple) 根据nametuple可以创建一个包含tuple所有功能以及其他功能的类型。
1
2
3import collectionsMytuple = collections.namedtuple('Mytuple',['x', 'y', 'z'])
复制代码class Mytuple(__builtin__.tuple)|  Mytuple(x, y)|  |  Method resolution order:|      Mytuple|      __builtin__.tuple|      __builtin__.object|  |  Methods defined here:|  |  __getnewargs__(self)|      Return self as a plain tuple.  Used by copy and pickle.|  |  __getstate__(self)|      Exclude the OrderedDict from pickling|  |  __repr__(self)|      Return a nicely formatted representation string|  |  _asdict(self)|      Return a new OrderedDict which maps field names to their values|  |  _replace(_self, **kwds)|      Return a new Mytuple object replacing specified fields with new values|  |  ----------------------------------------------------------------------|  Class methods defined here:|  |  _make(cls, iterable, new=<built-in method __new__ of type object>, len=<built-in function len>) from __builtin__.type|      Make a new Mytuple object from a sequence or iterable|  |  ----------------------------------------------------------------------|  Static methods defined here:|  |  __new__(_cls, x, y)|      Create new instance of Mytuple(x, y)|  |  ----------------------------------------------------------------------|  Data descriptors defined here:|  |  __dict__|      Return a new OrderedDict which maps field names to their values|  |  x|      Alias for field number 0|  |  y|      Alias for field number 1|  |  ----------------------------------------------------------------------|  Data and other attributes defined here:|  |  _fields = ('x', 'y')|  |  ----------------------------------------------------------------------|  Methods inherited from __builtin__.tuple:|  |  __add__(...)|      x.__add__(y) <==> x+y|  |  __contains__(...)|      x.__contains__(y) <==> y in x|  |  __eq__(...)|      x.__eq__(y) <==> x==y|  |  __ge__(...)|      x.__ge__(y) <==> x>=y|  |  __getattribute__(...)|      x.__getattribute__('name') <==> x.name|  |  __getitem__(...)|      x.__getitem__(y) <==> x[y]|  |  __getslice__(...)|      x.__getslice__(i, j) <==> x[i:j]|      |      Use of negative indices is not supported.|  |  __gt__(...)|      x.__gt__(y) <==> x>y|  |  __hash__(...)|      x.__hash__() <==> hash(x)|  |  __iter__(...)|      x.__iter__() <==> iter(x)|  |  __le__(...)|      x.__le__(y) <==> x<=y|  |  __len__(...)|      x.__len__() <==> len(x)|  |  __lt__(...)|      x.__lt__(y) <==> x<y|  |  __mul__(...)|      x.__mul__(n) <==> x*n|  |  __ne__(...)|      x.__ne__(y) <==> x!=y|  |  __rmul__(...)|      x.__rmul__(n) <==> n*x|  |  __sizeof__(...)|      T.__sizeof__() -- size of T in memory, in bytes|  |  count(...)|      T.count(value) -> integer -- return number of occurrences of value|  |  index(...)|      T.index(value, [start, [stop]]) -> integer -- return first index of value.|      Raises ValueError if the value is not present.Mytuple

Mytuple

迭代器和生成器

一、迭代器

对于Python 列表的 for 循环，他的内部原理：查看下一个元素是否存在，如果存在，则取出，如果不存在，则报异常 StopIteration。（python内部对异常已处理）

class listiterator(object)|  Methods defined here:|  |  __getattribute__(...)|      x.__getattribute__('name') <==> x.name|  |  __iter__(...)|      x.__iter__() <==> iter(x)|  |  __length_hint__(...)|      Private method returning an estimate of len(list(it)).|  |  next(...)|      x.next() -> the next value, or raise StopIteration

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二、生成器

range不是生成器 和 xrange 是生成器

readlines不是生成器 和 xreadlines 是生成器

1  print range(10)
2 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
3  print xrange(10)
4 xrange(10)

生成器内部基于yield创建，即：对于生成器只有使用时才创建，从而不避免内存浪费

 1 li = [13, 22, 6, 99, 11]
 2
 3 for m in range(len(li)-1):
 4
 5     for n in range(m+1, len(li)):
 6         if li[m]> li[n]:
 7             temp = li[n]
 8             li[n] = li[m]
 9             li[m] = temp
10
11 print li