python開發之路-第二章

第二章python基礎

1、做用域

對於變量的做用域，執行聲明並在內存中存在，該變量就能夠在下面的代碼中使用。

1 2 3

if 1 = = 1 :      name  = 'wupeiqi' print   name

下面的結論對嗎？

1，外層變量，能夠被內層變量使用

2，內層變量，沒法被外層變量使用

#在其餘語言中適用，在python中 只要在內容中存在，就能夠使用。

2、三元運算

1	result  = 值 1 if 條件  else 值 2

若是條件爲真：result = 值1
若是條件爲假：result = 值2

3、進制

• 二進制，01
• 八進制，01234567
• 十進制，0123456789
• 十六進制，0123456789ABCDE

Python基礎

對於Python，一切事物都是對象，對象基於類建立

因此，如下這些值都是對象： "wupeiqi"、3八、['北京', '上海', '深圳']，而且是根據不一樣的類生成的對象。

 

 

collection系列

 

一、計數器（counter）

 

Counter是對字典類型的補充，用於追蹤值的出現次數。

 

ps：具有字典的全部功能 + 本身的功能

1 c = Counter('abcdeabcdabcaba')
2 print c
3 輸出：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         """ 對於不存在的元素，返回計數器爲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         """ 數量大於等n的全部元素和計數器 """
 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         """ 計數器中的全部元素，注：此處非全部元素集合，而是包含全部元素集合的迭代器 """
 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         """ 更新計數器，其實就是增長；若是原來沒有，則新建，若是有則加一 """
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         """ 相減，原來的計數器中的每個元素的數量減去後添加的元素的數量 """
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         """ 拷貝 """
180         'Return a shallow copy.'
181         return self.__class__(self)
182 
183     def __reduce__(self):
184         """ 返回一個元組（類型，元組） """
185         return self.__class__, (dict(self),)
186 
187     def __delitem__(self, elem):
188         """ 刪除元素 """
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

counter

二、有序字典(orderedDict )

orderdDict是對字典類型的補充，他記住了字典元素添加的順序

  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

orderdDict

三、默認字典(defaultdict)

需求：

有以下值集合 [ 11 , 22 , 33 , 44 , 55 , 66 , 77 , 88 , 99 , 90. ..]，將全部大於 66 的值保存至字典的第一個key中，將小於 66 的值保存至第二個key的值中。

即： { 'k1' : 大於 66 , 'k2' : 小於 66 }

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]

原生字典解決方法

 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字典解決方法

defaultdict是對字典的類型的補充，他默認給字典的值設置了一個類型。

 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

四、可命名元組(namedtuple) 

根據nametuple能夠建立一個包含tuple全部功能以及其餘功能的類型。

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]

複製代碼
defaultdict字典解決方法

defaultdict是對字典的類型的補充，他默認給字典的值設置了一個類型。
defaultdict

4、可命名元組(namedtuple) 

根據nametuple能夠建立一個包含tuple全部功能以及其餘功能的類型。
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import collections
 
Mytuple = collections.namedtuple('Mytuple',['x', 'y', 'z'])
複製代碼

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

1、迭代器

對於Python 列表的 for 循環，他的內部原理：查看下一個元素是否存在，若是存在，則取出，若是不存在，則報異常 StopIteration。（python內部對異常已處理）

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

View Code

2、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)

生成器內部基於yield建立，即：對於生成器只有使用時才建立，從而不避免內存浪費

 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