########################################################################

###  Counter

########################################################################

class Counter(dict):

    '''Dict subclass for counting hashable items.  Sometimes called a bag

    or multiset.  Elements are stored as dictionary keys and their counts

    are stored as dictionary values.

    >>> c = Counter('abcdeabcdabcaba')  # count elements from a string

    >>> c.most_common(3)                # three most common elements

    [('a', 5), ('b', 4), ('c', 3)]

    >>> sorted(c)                       # list all unique elements

    ['a', 'b', 'c', 'd', 'e']

    >>> ''.join(sorted(c.elements()))   # list elements with repetitions

    'aaaaabbbbcccdde'

    >>> sum(c.values())                 # total of all counts

    >>> c['a']                          # count of letter 'a'

    >>> for elem in 'shazam':           # update counts from an iterable

    ...     c[elem] += 1                # by adding 1 to each element's count

    >>> c['a']                          # now there are seven 'a'

    >>> del c['b']                      # remove all 'b'

    >>> c['b']                          # now there are zero 'b'

    >>> d = Counter('simsalabim')       # make another counter

    >>> c.update(d)                     # add in the second counter

    >>> c['a']                          # now there are nine 'a'

    >>> c.clear()                       # empty the counter

    >>> c

    Counter()

    Note:  If a count is set to zero or reduced to zero, it will remain

    in the counter until the entry is deleted or the counter is cleared:

    >>> c = Counter('aaabbc')

    >>> c['b'] -= 2                     # reduce the count of 'b' by two

    >>> c.most_common()                 # 'b' is still in, but its count is zero

    [('a', 3), ('c', 1), ('b', 0)]

    '''

    # References:

    #   http://en.wikipedia.org/wiki/Multiset

    #   http://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html

    #   http://www.demo2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm

    #   http://code.activestate.com/recipes/259174/

    #   Knuth, TAOCP Vol. II section 4.6.3

    def __init__(self, iterable=None, **kwds):

        '''Create a new, empty Counter object.  And if given, count elements

        from an input iterable.  Or, initialize the count from another mapping

        of elements to their counts.

        >>> c = Counter()                           # a new, empty counter

        >>> c = Counter('gallahad')                 # a new counter from an iterable

        >>> c = Counter({'a': 4, 'b': 2})           # a new counter from a mapping

        >>> c = Counter(a=4, b=2)                   # a new counter from keyword args

        '''

        super(Counter, self).__init__()

        self.update(iterable, **kwds)

    def __missing__(self, key):

        """ 对于不存在的元素，返回计数器为0 """

        'The count of elements not in the Counter is zero.'

        # Needed so that self[missing_item] does not raise KeyError

        return 0

    def most_common(self, n=None):

        """ 数量大于等n的所有元素和计数器 """

        '''List the n most common elements and their counts from the most

        common to the least.  If n is None, then list all element counts.

        >>> Counter('abcdeabcdabcaba').most_common(3)

        [('a', 5), ('b', 4), ('c', 3)]

        '''

        # Emulate Bag.sortedByCount from Smalltalk

        if n is None:

            return sorted(self.iteritems(), key=_itemgetter(1), reverse=True)

        return _heapq.nlargest(n, self.iteritems(), key=_itemgetter(1))

    def elements(self):

        """ 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 """

        '''Iterator over elements repeating each as many times as its count.

        >>> c = Counter('ABCABC')

        >>> sorted(c.elements())

        ['A', 'A', 'B', 'B', 'C', 'C']

        # Knuth's example for prime factors of 1836:  2**2 * 3**3 * 17**1

        >>> prime_factors = Counter({2: 2, 3: 3, 17: 1})

        >>> product = 1

        >>> for factor in prime_factors.elements():     # loop over factors

        ...     product *= factor                       # and multiply them

        >>> product

        Note, if an element's count has been set to zero or is a negative

        number, elements() will ignore it.

        '''

        # Emulate Bag.do from Smalltalk and Multiset.begin from C++.

        return _chain.from_iterable(_starmap(_repeat, self.iteritems()))

    # Override dict methods where necessary

    @classmethod

    def fromkeys(cls, iterable, v=None):

        # There is no equivalent method for counters because setting v=1

        # means that no element can have a count greater than one.

        raise NotImplementedError(

            'Counter.fromkeys() is undefined.  Use Counter(iterable) instead.')

    def update(self, iterable=None, **kwds):

        """ 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 """

        '''Like dict.update() but add counts instead of replacing them.

        Source can be an iterable, a dictionary, or another Counter instance.

        >>> c = Counter('which')

        >>> c.update('witch')           # add elements from another iterable

        >>> d = Counter('watch')

        >>> c.update(d)                 # add elements from another counter

        >>> c['h']                      # four 'h' in which, witch, and watch

        '''

        # The regular dict.update() operation makes no sense here because the

        # replace behavior results in the some of original untouched counts

        # being mixed-in with all of the other counts for a mismash that

        # doesn't have a straight-forward interpretation in most counting

        # contexts.  Instead, we implement straight-addition.  Both the inputs

        # and outputs are allowed to contain zero and negative counts.

        if iterable is not None:

            if isinstance(iterable, Mapping):

                if self:

                    self_get = self.get

                    for elem, count in iterable.iteritems():

                        self[elem] = self_get(elem, 0) + count

                else:

                    super(Counter, self).update(iterable) # fast path when counter is empty

            else:

                self_get = self.get

                for elem in iterable:

                    self[elem] = self_get(elem, 0) + 1

        if kwds:

            self.update(kwds)

    def subtract(self, iterable=None, **kwds):

        """ 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 """

        '''Like dict.update() but subtracts counts instead of replacing them.

        Counts can be reduced below zero.  Both the inputs and outputs are

        allowed to contain zero and negative counts.

        Source can be an iterable, a dictionary, or another Counter instance.

        >>> c = Counter('which')

        >>> c.subtract('witch')             # subtract elements from another iterable

        >>> c.subtract(Counter('watch'))    # subtract elements from another counter

        >>> c['h']                          # 2 in which, minus 1 in witch, minus 1 in watch

        >>> c['w']                          # 1 in which, minus 1 in witch, minus 1 in watch

        -1

        '''

        if iterable is not None:

            self_get = self.get

            if isinstance(iterable, Mapping):

                for elem, count in iterable.items():

                    self[elem] = self_get(elem, 0) - count

            else:

                for elem in iterable:

                    self[elem] = self_get(elem, 0) - 1

        if kwds:

            self.subtract(kwds)

    def copy(self):

        """ 拷贝 """

        'Return a shallow copy.'

        return self.__class__(self)

    def __reduce__(self):

        """ 返回一个元组（类型，元组） """

        return self.__class__, (dict(self),)

    def __delitem__(self, elem):

        """ 删除元素 """

        'Like dict.__delitem__() but does not raise KeyError for missing values.'

        if elem in self:

            super(Counter, self).__delitem__(elem)

    def __repr__(self):

        if not self:

            return '%s()' % self.__class__.__name__

        items = ', '.join(map('%r: %r'.__mod__, self.most_common()))

        return '%s({%s})' % (self.__class__.__name__, items)

    # Multiset-style mathematical operations discussed in:

    #       Knuth TAOCP Volume II section 4.6.3 exercise 19

    #       and at http://en.wikipedia.org/wiki/Multiset

    #

    # Outputs guaranteed to only include positive counts.

    #

    # To strip negative and zero counts, add-in an empty counter:

    #       c += Counter()

    def __add__(self, other):

        '''Add counts from two counters.

        >>> Counter('abbb') + Counter('bcc')

        Counter({'b': 4, 'c': 2, 'a': 1})

        '''

        if not isinstance(other, Counter):

            return NotImplemented

        result = Counter()

        for elem, count in self.items():

            newcount = count + other[elem]

            if newcount > 0:

                result[elem] = newcount

        for elem, count in other.items():

            if elem not in self and count > 0:

                result[elem] = count

        return result

    def __sub__(self, other):

        ''' Subtract count, but keep only results with positive counts.

        >>> Counter('abbbc') - Counter('bccd')

        Counter({'b': 2, 'a': 1})

        '''

        if not isinstance(other, Counter):

            return NotImplemented

        result = Counter()

        for elem, count in self.items():

            newcount = count - other[elem]

            if newcount > 0:

                result[elem] = newcount

        for elem, count in other.items():

            if elem not in self and count < 0:

                result[elem] = 0 - count

        return result

    def __or__(self, other):

        '''Union is the maximum of value in either of the input counters.

        >>> Counter('abbb') | Counter('bcc')

        Counter({'b': 3, 'c': 2, 'a': 1})

        '''

        if not isinstance(other, Counter):

            return NotImplemented

        result = Counter()

        for elem, count in self.items():

            other_count = other[elem]

            newcount = other_count if count < other_count else count

            if newcount > 0:

                result[elem] = newcount

        for elem, count in other.items():

            if elem not in self and count > 0:

                result[elem] = count

        return result

    def __and__(self, other):

        ''' Intersection is the minimum of corresponding counts.

        >>> Counter('abbb') & Counter('bcc')

        Counter({'b': 1})

        '''

        if not isinstance(other, Counter):

            return NotImplemented

        result = Counter()

        for elem, count in self.items():

            other_count = other[elem]

            newcount = count if count < other_count else other_count

            if newcount > 0:

                result[elem] = newcount

        return result

Counter

Counter

class OrderedDict(dict):

    'Dictionary that remembers insertion order'

    # An inherited dict maps keys to values.

    # The inherited dict provides __getitem__, __len__, __contains__, and get.

    # The remaining methods are order-aware.

    # Big-O running times for all methods are the same as regular dictionaries.

    # The internal self.__map dict maps keys to links in a doubly linked list.

    # The circular doubly linked list starts and ends with a sentinel element.

    # The sentinel element never gets deleted (this simplifies the algorithm).

    # Each link is stored as a list of length three:  [PREV, NEXT, KEY].

    def __init__(self, *args, **kwds):

        '''Initialize an ordered dictionary.  The signature is the same as

        regular dictionaries, but keyword arguments are not recommended because

        their insertion order is arbitrary.

        '''

        if len(args) > 1:

            raise TypeError('expected at most 1 arguments, got %d' % len(args))

        try:

            self.__root

        except AttributeError:

            self.__root = root = []                     # sentinel node

            root[:] = [root, root, None]

            self.__map = {}

        self.__update(*args, **kwds)

    def __setitem__(self, key, value, dict_setitem=dict.__setitem__):

        'od.__setitem__(i, y) <==> od[i]=y'

        # Setting a new item creates a new link at the end of the linked list,

        # and the inherited dictionary is updated with the new key/value pair.

        if key not in self:

            root = self.__root

            last = root[0]

            last[1] = root[0] = self.__map[key] = [last, root, key]

        return dict_setitem(self, key, value)

    def __delitem__(self, key, dict_delitem=dict.__delitem__):

        'od.__delitem__(y) <==> del od[y]'

        # Deleting an existing item uses self.__map to find the link which gets

        # removed by updating the links in the predecessor and successor nodes.

        dict_delitem(self, key)

        link_prev, link_next, _ = self.__map.pop(key)

        link_prev[1] = link_next                        # update link_prev[NEXT]

        link_next[0] = link_prev                        # update link_next[PREV]

    def __iter__(self):

        'od.__iter__() <==> iter(od)'

        # Traverse the linked list in order.

        root = self.__root

        curr = root[1]                                  # start at the first node

        while curr is not root:

            yield curr[2]                               # yield the curr[KEY]

            curr = curr[1]                              # move to next node

    def __reversed__(self):

        'od.__reversed__() <==> reversed(od)'

        # Traverse the linked list in reverse order.

        root = self.__root

        curr = root[0]                                  # start at the last node

        while curr is not root:

            yield curr[2]                               # yield the curr[KEY]

            curr = curr[0]                              # move to previous node

    def clear(self):

        'od.clear() -> None.  Remove all items from od.'

        root = self.__root

        root[:] = [root, root, None]

        self.__map.clear()

        dict.clear(self)

    # -- the following methods do not depend on the internal structure --

    def keys(self):

        'od.keys() -> list of keys in od'

        return list(self)

    def values(self):

        'od.values() -> list of values in od'

        return [self[key] for key in self]

    def items(self):

        'od.items() -> list of (key, value) pairs in od'

        return [(key, self[key]) for key in self]

    def iterkeys(self):

        'od.iterkeys() -> an iterator over the keys in od'

        return iter(self)

    def itervalues(self):

        'od.itervalues -> an iterator over the values in od'

        for k in self:

            yield self[k]

    def iteritems(self):

        'od.iteritems -> an iterator over the (key, value) pairs in od'

        for k in self:

            yield (k, self[k])

    update = MutableMapping.update

    __update = update # let subclasses override update without breaking __init__

    __marker = object()

    def pop(self, key, default=__marker):

        '''od.pop(k[,d]) -> v, remove specified key and return the corresponding

        value.  If key is not found, d is returned if given, otherwise KeyError

        is raised.

        '''

        if key in self:

            result = self[key]

            del self[key]

            return result

        if default is self.__marker:

            raise KeyError(key)

        return default

    def setdefault(self, key, default=None):

        'od.setdefault(k[,d]) -> od.get(k,d), also set od[k]=d if k not in od'

        if key in self:

            return self[key]

        self[key] = default

        return default

    def popitem(self, last=True):

        '''od.popitem() -> (k, v), return and remove a (key, value) pair.

        Pairs are returned in LIFO order if last is true or FIFO order if false.

        '''

        if not self:

            raise KeyError('dictionary is empty')

        key = next(reversed(self) if last else iter(self))

        value = self.pop(key)

        return key, value

    def __repr__(self, _repr_running={}):

        'od.__repr__() <==> repr(od)'

        call_key = id(self), _get_ident()

        if call_key in _repr_running:

            return '...'

        _repr_running[call_key] = 1

        try:

            if not self:

                return '%s()' % (self.__class__.__name__,)

            return '%s(%r)' % (self.__class__.__name__, self.items())

        finally:

            del _repr_running[call_key]

    def __reduce__(self):

        'Return state information for pickling'

        items = [[k, self[k]] for k in self]

        inst_dict = vars(self).copy()

        for k in vars(OrderedDict()):

            inst_dict.pop(k, None)

        if inst_dict:

            return (self.__class__, (items,), inst_dict)

        return self.__class__, (items,)

    def copy(self):

        'od.copy() -> a shallow copy of od'

        return self.__class__(self)

    @classmethod

    def fromkeys(cls, iterable, value=None):

        '''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S.

        If not specified, the value defaults to None.

        '''

        self = cls()

        for key in iterable:

            self[key] = value

        return self

    def __eq__(self, other):

        '''od.__eq__(y) <==> od==y.  Comparison to another OD is order-sensitive

        while comparison to a regular mapping is order-insensitive.

        '''

        if isinstance(other, OrderedDict):

            return dict.__eq__(self, other) and all(_imap(_eq, self, other))

        return dict.__eq__(self, other)

    def __ne__(self, other):

        'od.__ne__(y) <==> od!=y'

        return not self == other

    # -- the following methods support python 3.x style dictionary views --

    def viewkeys(self):

        "od.viewkeys() -> a set-like object providing a view on od's keys"

        return KeysView(self)

    def viewvalues(self):

        "od.viewvalues() -> an object providing a view on od's values"

        return ValuesView(self)

    def viewitems(self):

        "od.viewitems() -> a set-like object providing a view on od's items"

        return ItemsView(self)

OrderedDict

class defaultdict(dict):

    """

    defaultdict(default_factory[, ...]) --> dict with default factory

    The default factory is called without arguments to produce

    a new value when a key is not present, in __getitem__ only.

    A defaultdict compares equal to a dict with the same items.

    All remaining arguments are treated the same as if they were

    passed to the dict constructor, including keyword arguments.

    """

    def copy(self): # real signature unknown; restored from __doc__

        """ D.copy() -> a shallow copy of D. """

        pass

    def __copy__(self, *args, **kwargs): # real signature unknown

        """ D.copy() -> a shallow copy of D. """

        pass

    def __getattribute__(self, name): # real signature unknown; restored from __doc__

        """ x.__getattribute__('name') <==> x.name """

        pass

    def __init__(self, default_factory=None, **kwargs): # known case of _collections.defaultdict.__init__

        """

        defaultdict(default_factory[, ...]) --> dict with default factory

        The default factory is called without arguments to produce

        a new value when a key is not present, in __getitem__ only.

        A defaultdict compares equal to a dict with the same items.

        All remaining arguments are treated the same as if they were

        passed to the dict constructor, including keyword arguments.

        # (copied from class doc)

        """

        pass

    def __missing__(self, key): # real signature unknown; restored from __doc__

        """

        __missing__(key) # Called by __getitem__ for missing key; pseudo-code:

          if self.default_factory is None: raise KeyError((key,))

          self[key] = value = self.default_factory()

          return value

        """

        pass

    def __reduce__(self, *args, **kwargs): # real signature unknown

        """ Return state information for pickling. """

        pass

    def __repr__(self): # real signature unknown; restored from __doc__

        """ x.__repr__() <==> repr(x) """

        pass

    default_factory = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    """Factory for default value called by __missing__()."""

defaultdict

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

class Queue:

    """Create a queue object with a given maximum size.

    If maxsize is <= 0, the queue size is infinite.

    """

    def __init__(self, maxsize=0):

        self.maxsize = maxsize

        self._init(maxsize)

        # mutex must be held whenever the queue is mutating.  All methods

        # that acquire mutex must release it before returning.  mutex

        # is shared between the three conditions, so acquiring and

        # releasing the conditions also acquires and releases mutex.

        self.mutex = _threading.Lock()

        # Notify not_empty whenever an item is added to the queue; a

        # thread waiting to get is notified then.

        self.not_empty = _threading.Condition(self.mutex)

        # Notify not_full whenever an item is removed from the queue;

        # a thread waiting to put is notified then.

        self.not_full = _threading.Condition(self.mutex)

        # Notify all_tasks_done whenever the number of unfinished tasks

        # drops to zero; thread waiting to join() is notified to resume

        self.all_tasks_done = _threading.Condition(self.mutex)

        self.unfinished_tasks = 0

    def task_done(self):

        """Indicate that a formerly enqueued task is complete.

        Used by Queue consumer threads.  For each get() used to fetch a task,

        a subsequent call to task_done() tells the queue that the processing

        on the task is complete.

        If a join() is currently blocking, it will resume when all items

        have been processed (meaning that a task_done() call was received

        for every item that had been put() into the queue).

        Raises a ValueError if called more times than there were items

        placed in the queue.

        """

        self.all_tasks_done.acquire()

        try:

            unfinished = self.unfinished_tasks - 1

            if unfinished <= 0:

                if unfinished < 0:

                    raise ValueError('task_done() called too many times')

                self.all_tasks_done.notify_all()

            self.unfinished_tasks = unfinished

        finally:

            self.all_tasks_done.release()

    def join(self):

        """Blocks until all items in the Queue have been gotten and processed.

        The count of unfinished tasks goes up whenever an item is added to the

        queue. The count goes down whenever a consumer thread calls task_done()

        to indicate the item was retrieved and all work on it is complete.

        When the count of unfinished tasks drops to zero, join() unblocks.

        """

        self.all_tasks_done.acquire()

        try:

            while self.unfinished_tasks:

                self.all_tasks_done.wait()

        finally:

            self.all_tasks_done.release()

    def qsize(self):

        """Return the approximate size of the queue (not reliable!)."""

        self.mutex.acquire()

        n = self._qsize()

        self.mutex.release()

        return n

    def empty(self):

        """Return True if the queue is empty, False otherwise (not reliable!)."""

        self.mutex.acquire()

        n = not self._qsize()

        self.mutex.release()

        return n

    def full(self):

        """Return True if the queue is full, False otherwise (not reliable!)."""

        self.mutex.acquire()

        n = 0 < self.maxsize == self._qsize()

        self.mutex.release()

        return n

    def put(self, item, block=True, timeout=None):

        """Put an item into the queue.

        If optional args 'block' is true and 'timeout' is None (the default),

        block if necessary until a free slot is available. If 'timeout' is

        a non-negative number, it blocks at most 'timeout' seconds and raises

        the Full exception if no free slot was available within that time.

        Otherwise ('block' is false), put an item on the queue if a free slot

        is immediately available, else raise the Full exception ('timeout'

        is ignored in that case).

        """

        self.not_full.acquire()

        try:

            if self.maxsize > 0:

                if not block:

                    if self._qsize() == self.maxsize:

                        raise Full

                elif timeout is None:

                    while self._qsize() == self.maxsize:

                        self.not_full.wait()

                elif timeout < 0:

                    raise ValueError("'timeout' must be a non-negative number")

                else:

                    endtime = _time() + timeout

                    while self._qsize() == self.maxsize:

                        remaining = endtime - _time()

                        if remaining <= 0.0:

                            raise Full

                        self.not_full.wait(remaining)

            self._put(item)

            self.unfinished_tasks += 1

            self.not_empty.notify()

        finally:

            self.not_full.release()

    def put_nowait(self, item):

        """Put an item into the queue without blocking.

        Only enqueue the item if a free slot is immediately available.

        Otherwise raise the Full exception.

        """

        return self.put(item, False)

    def get(self, block=True, timeout=None):

        """Remove and return an item from the queue.

        If optional args 'block' is true and 'timeout' is None (the default),

        block if necessary until an item is available. If 'timeout' is

        a non-negative number, it blocks at most 'timeout' seconds and raises

        the Empty exception if no item was available within that time.

        Otherwise ('block' is false), return an item if one is immediately

        available, else raise the Empty exception ('timeout' is ignored

        in that case).

        """

        self.not_empty.acquire()

        try:

            if not block:

                if not self._qsize():

                    raise Empty

            elif timeout is None:

                while not self._qsize():

                    self.not_empty.wait()

            elif timeout < 0:

                raise ValueError("'timeout' must be a non-negative number")

            else:

                endtime = _time() + timeout

                while not self._qsize():

                    remaining = endtime - _time()

                    if remaining <= 0.0:

                        raise Empty

                    self.not_empty.wait(remaining)

            item = self._get()

            self.not_full.notify()

            return item

        finally:

            self.not_empty.release()

    def get_nowait(self):

        """Remove and return an item from the queue without blocking.

        Only get an item if one is immediately available. Otherwise

        raise the Empty exception.

        """

        return self.get(False)

    # Override these methods to implement other queue organizations

    # (e.g. stack or priority queue).

    # These will only be called with appropriate locks held

    # Initialize the queue representation

    def _init(self, maxsize):

        self.queue = deque()

    def _qsize(self, len=len):

        return len(self.queue)

    # Put a new item in the queue

    def _put(self, item):

        self.queue.append(item)

    # Get an item from the queue

    def _get(self):

        return self.queue.popleft()

Queue.Queue

class deque(object):

    """

    deque([iterable[, maxlen]]) --> deque object

    Build an ordered collection with optimized access from its endpoints.

    """

    def append(self, *args, **kwargs): # real signature unknown

        """ Add an element to the right side of the deque. """

        pass

    def appendleft(self, *args, **kwargs): # real signature unknown

        """ Add an element to the left side of the deque. """

        pass

    def clear(self, *args, **kwargs): # real signature unknown

        """ Remove all elements from the deque. """

        pass

    def count(self, value): # real signature unknown; restored from __doc__

        """ D.count(value) -> integer -- return number of occurrences of value """

        return 0

    def extend(self, *args, **kwargs): # real signature unknown

        """ Extend the right side of the deque with elements from the iterable """

        pass

    def extendleft(self, *args, **kwargs): # real signature unknown

        """ Extend the left side of the deque with elements from the iterable """

        pass

    def pop(self, *args, **kwargs): # real signature unknown

        """ Remove and return the rightmost element. """

        pass

    def popleft(self, *args, **kwargs): # real signature unknown

        """ Remove and return the leftmost element. """

        pass

    def remove(self, value): # real signature unknown; restored from __doc__

        """ D.remove(value) -- remove first occurrence of value. """

        pass

    def reverse(self): # real signature unknown; restored from __doc__

        """ D.reverse() -- reverse *IN PLACE* """

        pass

    def rotate(self, *args, **kwargs): # real signature unknown

        """ Rotate the deque n steps to the right (default n=1).  If n is negative, rotates left. """

        pass

    def __copy__(self, *args, **kwargs): # real signature unknown

        """ Return a shallow copy of a deque. """

        pass

    def __delitem__(self, y): # real signature unknown; restored from __doc__

        """ x.__delitem__(y) <==> del x[y] """

        pass

    def __eq__(self, y): # real signature unknown; restored from __doc__

        """ x.__eq__(y) <==> x==y """

        pass

    def __getattribute__(self, name): # real signature unknown; restored from __doc__

        """ x.__getattribute__('name') <==> x.name """

        pass

    def __getitem__(self, y): # real signature unknown; restored from __doc__

        """ x.__getitem__(y) <==> x[y] """

        pass

    def __ge__(self, y): # real signature unknown; restored from __doc__

        """ x.__ge__(y) <==> x>=y """

        pass

    def __gt__(self, y): # real signature unknown; restored from __doc__

        """ x.__gt__(y) <==> x>y """

        pass

    def __iadd__(self, y): # real signature unknown; restored from __doc__

        """ x.__iadd__(y) <==> x+=y """

        pass

    def __init__(self, iterable=(), maxlen=None): # known case of _collections.deque.__init__

        """

        deque([iterable[, maxlen]]) --> deque object

        Build an ordered collection with optimized access from its endpoints.

        # (copied from class doc)

        """

        pass

    def __iter__(self): # real signature unknown; restored from __doc__

        """ x.__iter__() <==> iter(x) """

        pass

    def __len__(self): # real signature unknown; restored from __doc__

        """ x.__len__() <==> len(x) """

        pass

    def __le__(self, y): # real signature unknown; restored from __doc__

        """ x.__le__(y) <==> x<=y """

        pass

    def __lt__(self, y): # real signature unknown; restored from __doc__

        """ x.__lt__(y) <==> x<y """

        pass

    @staticmethod # known case of __new__

    def __new__(S, *more): # real signature unknown; restored from __doc__

        """ T.__new__(S, ...) -> a new object with type S, a subtype of T """

        pass

    def __ne__(self, y): # real signature unknown; restored from __doc__

        """ x.__ne__(y) <==> x!=y """

        pass

    def __reduce__(self, *args, **kwargs): # real signature unknown

        """ Return state information for pickling. """

        pass

    def __repr__(self): # real signature unknown; restored from __doc__

        """ x.__repr__() <==> repr(x) """

        pass

    def __reversed__(self): # real signature unknown; restored from __doc__

        """ D.__reversed__() -- return a reverse iterator over the deque """

        pass

    def __setitem__(self, i, y): # real signature unknown; restored from __doc__

        """ x.__setitem__(i, y) <==> x[i]=y """

        pass

    def __sizeof__(self): # real signature unknown; restored from __doc__

        """ D.__sizeof__() -- size of D in memory, in bytes """

        pass

    maxlen = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    """maximum size of a deque or None if unbounded"""

    __hash__ = None

deque

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

import time

def consumer(name):

    print("%s 准备吃包子啦!" %name)

    while True:

       baozi = yield                      ###接收send的变量值

       print("包子[%s]来了,被[%s]吃了!" %(baozi,name))

def producer(name):

    c = consumer('A')

    c2 = consumer('B')

    c.next()                                ###调用consumer函数

    c2.next()                               ###因yield中断函数，回到并执行c2.next

    print("老子开始准备做包子啦!")       ###因yield中断函数，并输入

    for i in range(10):

        time.sleep(1)

        print("做了2个包子!")

        c.send(i)                           ###返回i到yield

        c2.send(i)

producer("alex")

结果如下：

A 准备吃包子啦!

B 准备吃包子啦!

老子开始准备做包子啦!

做了2个包子!

包子[0]来了,被[A]吃了!

包子[0]来了,被[B]吃了!

做了2个包子!

包子[1]来了,被[A]吃了!

包子[1]来了,被[B]吃了!