collections模塊簡介

除python提供的內置數據類型（int、float、str、list、tuple、dict）外，collections模塊還提供了其餘數據類型，使用以下功能需先導入collections模塊（import collections）：

• 計數器（counter）
• 有序字典（orderedDict）
• 默認字典（defaultdict）
• 可命名元組（namedtuple）
• 雙向隊列（deque）

1、 計數器（Counter）：統計元素的個數，並以字典形式返回{元素：元素個數}

class Counter(dict):
# class Counter(dict) 表示Counter類繼承dict類，既子類繼承父類全部功能
    '''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
    15

    >>> c['a']                          # count of letter 'a'
    5
    >>> 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'
    7
    >>> del c['b']                      # remove all 'b'
    >>> c['b']                          # now there are zero 'b'
    0

    >>> d = Counter('simsalabim')       # make another counter
    >>> c.update(d)                     # add in the second counter
    >>> c['a']                          # now there are nine 'a'
    9

    >>> 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__(*args, **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

        '''
        if not args:
            raise TypeError("descriptor '__init__' of 'Counter' object "
                            "needs an argument")
        self, *args = args
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        super(Counter, self).__init__()
        self.update(*args, **kwds)

    def __missing__(self, key):
        '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):
        '''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.items(), key=_itemgetter(1), reverse=True)
        return _heapq.nlargest(n, self.items(), key=_itemgetter(1))

    def elements(self):
        '''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
        1836

        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.items()))

    # 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(*args, **kwds):
        '''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
        4

        '''
        # 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 not args:
            raise TypeError("descriptor 'update' of 'Counter' object "
                            "needs an argument")
        self, *args = args
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        iterable = args[0] if args else None
        if iterable is not None:
            if isinstance(iterable, Mapping):
                if self:
                    self_get = self.get
                    for elem, count in iterable.items():
                        self[elem] = count + self_get(elem, 0)
                else:
                    super(Counter, self).update(iterable) # fast path when counter is empty
            else:
                _count_elements(self, iterable)
        if kwds:
            self.update(kwds)

    def subtract(*args, **kwds):
        '''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
        0
        >>> c['w']                          # 1 in which, minus 1 in witch, minus 1 in watch
        -1

        '''
        if not args:
            raise TypeError("descriptor 'subtract' of 'Counter' object "
                            "needs an argument")
        self, *args = args
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        iterable = args[0] if args else None
        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):
        'Return a shallow copy.'
        return self.__class__(self)

    def __reduce__(self):
        return self.__class__, (dict(self),)

    def __delitem__(self, elem):
        'Like dict.__delitem__() but does not raise KeyError for missing values.'
        if elem in self:
            super().__delitem__(elem)

    def __repr__(self):
        if not self:
            return '%s()' % self.__class__.__name__
        try:
            items = ', '.join(map('%r: %r'.__mod__, self.most_common()))
            return '%s({%s})' % (self.__class__.__name__, items)
        except TypeError:
            # handle case where values are not orderable
            return '{0}({1!r})'.format(self.__class__.__name__, dict(self))

    # 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

    def __pos__(self):
        'Adds an empty counter, effectively stripping negative and zero counts'
        result = Counter()
        for elem, count in self.items():
            if count > 0:
                result[elem] = count
        return result

    def __neg__(self):
        '''Subtracts from an empty counter.  Strips positive and zero counts,
        and flips the sign on negative counts.

        '''
        result = Counter()
        for elem, count in self.items():
            if count < 0:
                result[elem] = 0 - count
        return result

    def _keep_positive(self):
        '''Internal method to strip elements with a negative or zero count'''
        nonpositive = [elem for elem, count in self.items() if not count > 0]
        for elem in nonpositive:
            del self[elem]
        return self

    def __iadd__(self, other):
        '''Inplace add from another counter, keeping only positive counts.

        >>> c = Counter('abbb')
        >>> c += Counter('bcc')
        >>> c
        Counter({'b': 4, 'c': 2, 'a': 1})

        '''
        for elem, count in other.items():
            self[elem] += count
        return self._keep_positive()

    def __isub__(self, other):
        '''Inplace subtract counter, but keep only results with positive counts.

        >>> c = Counter('abbbc')
        >>> c -= Counter('bccd')
        >>> c
        Counter({'b': 2, 'a': 1})

        '''
        for elem, count in other.items():
            self[elem] -= count
        return self._keep_positive()

    def __ior__(self, other):
        '''Inplace union is the maximum of value from either counter.

        >>> c = Counter('abbb')
        >>> c |= Counter('bcc')
        >>> c
        Counter({'b': 3, 'c': 2, 'a': 1})

        '''
        for elem, other_count in other.items():
            count = self[elem]
            if other_count > count:
                self[elem] = other_count
        return self._keep_positive()

    def __iand__(self, other):
        '''Inplace intersection is the minimum of corresponding counts.

        >>> c = Counter('abbb')
        >>> c &= Counter('bcc')
        >>> c
        Counter({'b': 1})

        '''
        for elem, count in self.items():
            other_count = other[elem]
            if other_count < count:
                self[elem] = other_count
        return self._keep_positive()

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Counter類包含方法以下：

1.  most_common：將元素出現的次數按照從高到低進行排序，並返回前N個元素，若多個元素統計數相同，按照字母順序排列，N若未指定，則返回全部元素

    def most_common(self, n=None):
        '''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.items(), key=_itemgetter(1), reverse=True)
        return _heapq.nlargest(n, self.items(), key=_itemgetter(1))

 2. elements：返回一個迭代器，元素被重複多少次，在迭代器中就包含多少個此元素，全部元素按字母序排列，個數<1的不羅列

def elements(self):
        '''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
        1836

        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.items()))

3. update：增長元素的重複次數

def update(*args, **kwds):
        '''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
        4

        '''
        # 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 not args:
            raise TypeError("descriptor 'update' of 'Counter' object "
                            "needs an argument")
        self, *args = args
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        iterable = args[0] if args else None
        if iterable is not None:
            if isinstance(iterable, Mapping):
                if self:
                    self_get = self.get
                    for elem, count in iterable.items():
                        self[elem] = count + self_get(elem, 0)
                else:
                    super(Counter, self).update(iterable) # fast path when counter is empty
            else:
                _count_elements(self, iterable)
        if kwds:
            self.update(kwds)

View Code

4. subtract：減小元素重複次數

def subtract(*args, **kwds):
        '''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
        0
        >>> c['w']                          # 1 in which, minus 1 in witch, minus 1 in watch
        -1

        '''
        if not args:
            raise TypeError("descriptor 'subtract' of 'Counter' object "
                            "needs an argument")
        self, *args = args
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        iterable = args[0] if args else None
        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)

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2、有序字典（orderedDict）：繼承了dict的全部功能，dict是無序的，orderedDict恰好對dict做了補充，記錄了鍵值對插入的順序，是有序字典

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).
    # The sentinel is in self.__hardroot with a weakref proxy in self.__root.
    # The prev links are weakref proxies (to prevent circular references).
    # Individual links are kept alive by the hard reference in self.__map.
    # Those hard references disappear when a key is deleted from an OrderedDict.

    def __init__(*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 not args:
            raise TypeError("descriptor '__init__' of 'OrderedDict' object "
                            "needs an argument")
        self, *args = args
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        try:
            self.__root
        except AttributeError:
            self.__hardroot = _Link()
            self.__root = root = _proxy(self.__hardroot)
            root.prev = root.next = root
            self.__map = {}
        self.__update(*args, **kwds)

    def __setitem__(self, key, value,
                    dict_setitem=dict.__setitem__, proxy=_proxy, Link=_Link):
        '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:
            self.__map[key] = link = Link()
            root = self.__root
            last = root.prev
            link.prev, link.next, link.key = last, root, key
            last.next = link
            root.prev = proxy(link)
        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 = self.__map.pop(key)
        link_prev = link.prev
        link_next = link.next
        link_prev.next = link_next
        link_next.prev = link_prev
        link.prev = None
        link.next = None

    def __iter__(self):
        'od.__iter__() <==> iter(od)'
        # Traverse the linked list in order.
        root = self.__root
        curr = root.next
        while curr is not root:
            yield curr.key
            curr = curr.next

    def __reversed__(self):
        'od.__reversed__() <==> reversed(od)'
        # Traverse the linked list in reverse order.
        root = self.__root
        curr = root.prev
        while curr is not root:
            yield curr.key
            curr = curr.prev

    def clear(self):
        'od.clear() -> None.  Remove all items from od.'
        root = self.__root
        root.prev = root.next = root
        self.__map.clear()
        dict.clear(self)

    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')
        root = self.__root
        if last:
            link = root.prev
            link_prev = link.prev
            link_prev.next = root
            root.prev = link_prev
        else:
            link = root.next
            link_next = link.next
            root.next = link_next
            link_next.prev = root
        key = link.key
        del self.__map[key]
        value = dict.pop(self, key)
        return key, value

    def move_to_end(self, key, last=True):
        '''Move an existing element to the end (or beginning if last==False).

        Raises KeyError if the element does not exist.
        When last=True, acts like a fast version of self[key]=self.pop(key).

        '''
        link = self.__map[key]
        link_prev = link.prev
        link_next = link.next
        soft_link = link_next.prev
        link_prev.next = link_next
        link_next.prev = link_prev
        root = self.__root
        if last:
            last = root.prev
            link.prev = last
            link.next = root
            root.prev = soft_link
            last.next = link
        else:
            first = root.next
            link.prev = root
            link.next = first
            first.prev = soft_link
            root.next = link

    def __sizeof__(self):
        sizeof = _sys.getsizeof
        n = len(self) + 1                       # number of links including root
        size = sizeof(self.__dict__)            # instance dictionary
        size += sizeof(self.__map) * 2          # internal dict and inherited dict
        size += sizeof(self.__hardroot) * n     # link objects
        size += sizeof(self.__root) * n         # proxy objects
        return size

    update = __update = MutableMapping.update

    def keys(self):
        "D.keys() -> a set-like object providing a view on D's keys"
        return _OrderedDictKeysView(self)

    def items(self):
        "D.items() -> a set-like object providing a view on D's items"
        return _OrderedDictItemsView(self)

    def values(self):
        "D.values() -> an object providing a view on D's values"
        return _OrderedDictValuesView(self)

    __ne__ = MutableMapping.__ne__

    __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

    @_recursive_repr()
    def __repr__(self):
        'od.__repr__() <==> repr(od)'
        if not self:
            return '%s()' % (self.__class__.__name__,)
        return '%s(%r)' % (self.__class__.__name__, list(self.items()))

    def __reduce__(self):
        'Return state information for pickling'
        inst_dict = vars(self).copy()
        for k in vars(OrderedDict()):
            inst_dict.pop(k, None)
        return self.__class__, (), inst_dict or None, None, iter(self.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(map(_eq, self, other))
        return dict.__eq__(self, other)


try:
    from _collections import OrderedDict
except ImportError:
    # Leave the pure Python version in place.
    pass

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說明：python v3.6以前的版本dict是無序的，3.6版本以後（含v3.6）dict是有序的，目測爲了兼容性以及100%有序性考慮，建議實現有序功能時使用orderedDict

orderedDict類補充方法：

1. clear：清空字典

 def clear(self):
        'od.clear() -> None.  Remove all items from od.'
        root = self.__root
        root.prev = root.next = root
        self.__map.clear()
        dict.clear(self)

2. popitem：有序刪除，相似於棧，按照後進先出的順序依次刪除

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')
        root = self.__root
        if last:
            link = root.prev
            link_prev = link.prev
            link_prev.next = root
            root.prev = link_prev
        else:
            link = root.next
            link_next = link.next
            root.next = link_next
            link_next.prev = root
        key = link.key
        del self.__map[key]
        value = dict.pop(self, key)
        return key, value

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3. pop：刪除指定鍵值對

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

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4. move_to_end：將指定鍵值對移到最後位置

def move_to_end(self, key, last=True):
        '''Move an existing element to the end (or beginning if last==False).

        Raises KeyError if the element does not exist.
        When last=True, acts like a fast version of self[key]=self.pop(key).

        '''
        link = self.__map[key]
        link_prev = link.prev
        link_next = link.next
        soft_link = link_next.prev
        link_prev.next = link_next
        link_next.prev = link_prev
        root = self.__root
        if last:
            last = root.prev
            link.prev = last
            link.next = root
            root.prev = soft_link
            last.next = link
        else:
            first = root.next
            link.prev = root
            link.next = first
            first.prev = soft_link
            root.next = link

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5. setdefault：設置默認值，默認爲None，也可指定值

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

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6. update：更新字典，有則更新，無則添加

3、默認字典（defaultdict）：設置values默認類型，如list、tuple

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, *args, **kwargs): # real signature unknown
        """ Return getattr(self, 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, *args, **kwargs): # real signature unknown
        """ Return repr(self). """
        pass

    default_factory = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default
    """Factory for default value called by __missing__()."""

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4、可命名元組（namedtuple）: 可經過名稱訪問元組中的元素，提升代碼可讀性

def namedtuple(typename, field_names, *, verbose=False, rename=False, module=None):
    """Returns a new subclass of tuple with named fields.

    >>> Point = namedtuple('Point', ['x', 'y'])
    >>> Point.__doc__                   # docstring for the new class
    'Point(x, y)'
    >>> p = Point(11, y=22)             # instantiate with positional args or keywords
    >>> p[0] + p[1]                     # indexable like a plain tuple
    33
    >>> x, y = p                        # unpack like a regular tuple
    >>> x, y
    (11, 22)
    >>> p.x + p.y                       # fields also accessible by name
    33
    >>> d = p._asdict()                 # convert to a dictionary
    >>> d['x']
    11
    >>> Point(**d)                      # convert from a dictionary
    Point(x=11, y=22)
    >>> p._replace(x=100)               # _replace() is like str.replace() but targets named fields
    Point(x=100, y=22)

    """

    # Validate the field names.  At the user's option, either generate an error
    # message or automatically replace the field name with a valid name.
    if isinstance(field_names, str):
        field_names = field_names.replace(',', ' ').split()
    field_names = list(map(str, field_names))
    typename = str(typename)
    if rename:
        seen = set()
        for index, name in enumerate(field_names):
            if (not name.isidentifier()
                or _iskeyword(name)
                or name.startswith('_')
                or name in seen):
                field_names[index] = '_%d' % index
            seen.add(name)
    for name in [typename] + field_names:
        if type(name) is not str:
            raise TypeError('Type names and field names must be strings')
        if not name.isidentifier():
            raise ValueError('Type names and field names must be valid '
                             'identifiers: %r' % name)
        if _iskeyword(name):
            raise ValueError('Type names and field names cannot be a '
                             'keyword: %r' % name)
    seen = set()
    for name in field_names:
        if name.startswith('_') and not rename:
            raise ValueError('Field names cannot start with an underscore: '
                             '%r' % name)
        if name in seen:
            raise ValueError('Encountered duplicate field name: %r' % name)
        seen.add(name)

    # Fill-in the class template
    class_definition = _class_template.format(
        typename = typename,
        field_names = tuple(field_names),
        num_fields = len(field_names),
        arg_list = repr(tuple(field_names)).replace("'", "")[1:-1],
        repr_fmt = ', '.join(_repr_template.format(name=name)
                             for name in field_names),
        field_defs = '\n'.join(_field_template.format(index=index, name=name)
                               for index, name in enumerate(field_names))
    )

    # Execute the template string in a temporary namespace and support
    # tracing utilities by setting a value for frame.f_globals['__name__']
    namespace = dict(__name__='namedtuple_%s' % typename)
    exec(class_definition, namespace)
    result = namespace[typename]
    result._source = class_definition
    if verbose:
        print(result._source)

    # For pickling to work, the __module__ variable needs to be set to the frame
    # where the named tuple is created.  Bypass this step in environments where
    # sys._getframe is not defined (Jython for example) or sys._getframe is not
    # defined for arguments greater than 0 (IronPython), or where the user has
    # specified a particular module.
    if module is None:
        try:
            module = _sys._getframe(1).f_globals.get('__name__', '__main__')
        except (AttributeError, ValueError):
            pass
    if module is not None:
        result.__module__ = module

    return result

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【示例】
>>> import colletcions                      #導入collections模塊
>>> TupleName=collections.namedtuple('TupleName',['a','b','c'])  #經過namedtuple自定義一個TupleName類
>>> obj=TupleName(11,22,33)                 #經過類建立對象obj
>>> obj.a        
>>> 11                                      #經過名稱訪問元組中的元素
>>> obj.b
>>> 22      
>>> obj.a*obj.c  
>>> 363 

5、雙向隊列（deque）：相似於list，容許兩端操做元素

class deque(object):
    """
    deque([iterable[, maxlen]]) --> deque object
    
    A list-like sequence optimized for data accesses near its endpoints.
    """
    def append(self, *args, **kwargs): # real signature unknown
       # 添加元素至雙向隊列右側
        """ Add an element to the right side of the deque. """
        pass

    def appendleft(self, *args, **kwargs): # real signature unknown
       # 添加元素至雙向隊列左側
        """ Add an element to the left side of the deque. """
        pass

    def clear(self, *args, **kwargs): # real signature unknown
        # 清空隊列
        """ Remove all elements from the deque. """
        pass

    def copy(self, *args, **kwargs): # real signature unknown
       # 淺拷貝
        """ Return a shallow copy of a deque. """
        pass

    def count(self, value): # real signature unknown; restored from __doc__
        # 統計隊列中元素出現的次數
        """ D.count(value) -> integer -- return number of occurrences of value """
        return 0

    def extend(self, *args, **kwargs): # real signature unknown
       # 從隊列右側擴展，能夠是list、tuple、dict（取keys）
        """ Extend the right side of the deque with elements from the iterable """
        pass

    def extendleft(self, *args, **kwargs): # real signature unknown
        # 從隊列左側擴展多個元素
        """ Extend the left side of the deque with elements from the iterable """
        pass

    def index(self, value, start=None, stop=None): # real signature unknown; restored from __doc__
       # 默認從左取值的索引位置，也可指定查詢範圍，如有多個相同值，則取第一個值的索引位置
        """
        D.index(value, [start, [stop]]) -> integer -- return first index of value.
        Raises ValueError if the value is not present.
        """
        return 0

    def insert(self, index, p_object): # real signature unknown; restored from __doc__
        # 任意往指定索引位置插入值
        """ D.insert(index, object) -- insert object before index """
        pass

    def pop(self, *args, **kwargs): # real signature unknown
        # 默認從隊列右側取值並移除
        """ Remove and return the rightmost element. """
        pass

    def popleft(self, *args, **kwargs): # real signature unknown
       # 從隊列左側取值並移除
        """ Remove and return the leftmost element. """
        pass

    def remove(self, value): # real signature unknown; restored from __doc__
       # 移除指定值
        """ D.remove(value) -- remove first occurrence of value. """
        pass

    def reverse(self): # real signature unknown; restored from __doc__
       # 反轉排序
        """ D.reverse() -- reverse *IN PLACE* """
        pass

    def rotate(self, *args, **kwargs): # real signature unknown
       # 移動隊列中的元素，若n<0，則將左側n個元素依次移至隊列最右側，反之，若n>0，則將隊列右側n個元素依次移至隊列最左側
        """ Rotate the deque n steps to the right (default n=1).  If n is negative, rotates left. """
        pass

    def __add__(self, *args, **kwargs): # real signature unknown
        """ Return self+value. """
        pass

    def __bool__(self, *args, **kwargs): # real signature unknown
        """ self != 0 """
        pass

    def __contains__(self, *args, **kwargs): # real signature unknown
        """ Return key in self. """
        pass

    def __copy__(self, *args, **kwargs): # real signature unknown
        """ Return a shallow copy of a deque. """
        pass

    def __delitem__(self, *args, **kwargs): # real signature unknown
        """ Delete self[key]. """
        pass

    def __eq__(self, *args, **kwargs): # real signature unknown
        """ Return self==value. """
        pass

    def __getattribute__(self, *args, **kwargs): # real signature unknown
        """ Return getattr(self, name). """
        pass

    def __getitem__(self, *args, **kwargs): # real signature unknown
        """ Return self[key]. """
        pass

    def __ge__(self, *args, **kwargs): # real signature unknown
        """ Return self>=value. """
        pass

    def __gt__(self, *args, **kwargs): # real signature unknown
        """ Return self>value. """
        pass

    def __iadd__(self, *args, **kwargs): # real signature unknown
        """ Implement self+=value. """
        pass

    def __imul__(self, *args, **kwargs): # real signature unknown
        """ Implement self*=value. """
        pass

    def __init__(self, iterable=(), maxlen=None): # known case of _collections.deque.__init__
        """
        deque([iterable[, maxlen]]) --> deque object
        
        A list-like sequence optimized for data accesses near its endpoints.
        # (copied from class doc)
        """
        pass

    def __iter__(self, *args, **kwargs): # real signature unknown
        """ Implement iter(self). """
        pass

    def __len__(self, *args, **kwargs): # real signature unknown
        """ Return len(self). """
        pass

    def __le__(self, *args, **kwargs): # real signature unknown
        """ Return self<=value. """
        pass

    def __lt__(self, *args, **kwargs): # real signature unknown
        """ Return self<value. """
        pass

    def __mul__(self, *args, **kwargs): # real signature unknown
        """ Return self*value.n """
        pass

    @staticmethod # known case of __new__
    def __new__(*args, **kwargs): # real signature unknown
        """ Create and return a new object.  See help(type) for accurate signature. """
        pass

    def __ne__(self, *args, **kwargs): # real signature unknown
        """ Return self!=value. """
        pass

    def __reduce__(self, *args, **kwargs): # real signature unknown
        """ Return state information for pickling. """
        pass

    def __repr__(self, *args, **kwargs): # real signature unknown
        """ Return repr(self). """
        pass

    def __reversed__(self): # real signature unknown; restored from __doc__
        """ D.__reversed__() -- return a reverse iterator over the deque """
        pass

    def __rmul__(self, *args, **kwargs): # real signature unknown
        """ Return self*value. """
        pass

    def __setitem__(self, *args, **kwargs): # real signature unknown
        """ Set self[key] to value. """
        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

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deque類中包含方法：

1. append：從隊列右側添加元素

【示例】
>>> import collections
>>> deq=collections.deque('abcd')
>>> deq
>>> deque(['a','b','c','d'])
>>> deq.append(11)
>>> deq
>>> deque(['a','b','c','d',11])

2.appendleft：從隊列左側添加元素

【示例】
>>> import collections
>>> deq=collections.deque('abcd')
>>> deq
>>> deque(['a','b','c','d'])
>>> deq.appendleft(12)
>>> deq
>>> deque([12,'a','b','c','d'])

 3.clear：清空隊列

【示例】
>>> import collections
>>> deq=collections.deque('abcd')
>>> deq
>>> deque(['a','b','c','d'])
>>> deq.clear()
>>> deq
>>> deque([])

 4. count：統計隊列中元素個數

【示例】
>>> import collections
>>> deq=collections.deque('abcdaa')
>>> deq
>>> deque(['a','b','c','d','a','a'])
>>> deq.count('a')
>>> 3

 5.extend：從隊列右側擴展

【示例】
>>> import collections
>>> deq=collections.deque('abcd')
>>> deq
>>> deque(['a','b','c','d'])
>>> deq.extend(11,22,33)
>>> deq
>>> deque(['a','b','c','d',11,22,33])

6.extendleft：從隊列左側擴展

【示例】
>>> import collections
>>> deq=collections.deque('abcd')
>>> deq
>>> deque(['a','b','c','d'])
>>> deq.extendleft({'k1':'v1','k2':'v2'})   # 擴展類型爲dict，取keys
>>> deq
>>> deque(['k2','k1','a','b','c','d'])    # 取dict中的keys，並從隊列左側依次插入

7.index：取元素索引位置

【示例】
>>> import collections
>>> deq=collections.deque('abcdaa')
>>> deq
>>> deque(['a','b','c','d','a','a'])
>>> deq.index('a')              # 默認從左側開始檢索
>>> 0
>>> deq.index('a',2,5)    # 在查找範圍內如有多個相同的值，返回第一個值的索引
>>> 4

8.insert：在隊列任意位置插入值

【示例】
>>> import collections
>>> deq=collections.deque('abcd')
>>> deq
>>> deque(['a','b','c','d'])
>>> deq.insert(1,11)
>>> deq
>>> deque(['a',11,'b','c','d'])

9. pop：從隊列右側移除值

【示例】
>>> import collections
>>> deq=collections.deque('abcdef')
>>> deq
>>> deque(['a','b','c','d','e','f'])
>>> deq.pop()
>>> 'f'
>>> deq
>>> deque(['a','b','c','d','e'])

10.popleft：從隊列左側移除值

【示例】
>>> import collections
>>> deq=collections.deque('abcdef')
>>> deq
>>> deque(['a','b','c','d','e','f'])
>>> deq.popleft()
>>> 'a'
>>> deq
>>> deque(['b','c','d','e','f'])

11. remove：移除指定值

【示例】
>>> import collections
>>> deq=collections.deque('abcdef')
>>> deq
>>> deque(['a','b','c','d','e','f'])
>>> deq.remove('c')
>>> deq
>>> deque(['a','b','d','e','f'])

12.reverse：將隊列中的元素反轉

【示例】
>>> import collections
>>> deq=collections.deque('abcdef')
>>> deq
>>> deque(['a','b','c','d','e','f'])
>>> deq.reverse()
>>> deq
>>> deque(['f','e','d','c',b','a'])

13. rotate：移動隊列中的元素，若n<0，則將隊列最左側的元素依次移動至最右側，反之，n>0，將隊列最右側元素移動至最左側

【示例】
>>> import collections
>>> deq=collections.deque('abcdef')     #建立隊列
>>> deq
>>> deque(['a','b','c','d','e','f'])
>>> deq.rotate(-2)                      # n<0，依次移動最左側2個元素至隊列最右側
>>> deq
>>> deque(['c','d','e','f','a','b'])
>>> deq.append(11)                      # 在隊列最右側插入元素
>>> deq
>>> deque(['c','d','e','f','a','b',11])
>>> deq.rotate(2)                       # n>0，依次移動右側2個元素至隊列最左側
>>> deq
>>> deque(['b',11,'c','d','e','f','a'])

 

上述既然提到了雙向隊列，那確定也存在單項隊列，雙向隊列存在於collections模塊中，容許對元素兩端進行操做，而單項隊列存在於queue模塊中，遵循先進先出原則，只能一端進，一端出

queue模塊中方法簡介：

1. empty：判斷隊列是否爲空，是返回True

def empty(self):
        '''Return True if the queue is empty, False otherwise (not reliable!).

        This method is likely to be removed at some point.  Use qsize() == 0
        as a direct substitute, but be aware that either approach risks a race
        condition where a queue can grow before the result of empty() or
        qsize() can be used.

        To create code that needs to wait for all queued tasks to be
        completed, the preferred technique is to use the join() method.
        '''
        with self.mutex:
            return not self._qsize()

【示例】
>>> import queue
>>> que=queue.Queue()         # 表示隊列的長度，即元素個數，
>>> que.empty()                 # 清空隊列，而且判斷隊列是否爲空，是返回True
>>> True

2.full：判斷隊列是否已滿，是返回True

def full(self):
        '''Return True if the queue is full, False otherwise (not reliable!).

        This method is likely to be removed at some point.  Use qsize() >= n
        as a direct substitute, but be aware that either approach risks a race
        condition where a queue can shrink before the result of full() or
        qsize() can be used.
        '''
        with self.mutex:
            return 0 < self.maxsize <= self._qsize()

【示例】
>>> import queue
>>> que=queue.Queue(2)        # 表示隊列的長度，即元素個數，
>>> que.put('a')                # 向隊列中添加元素
>>> que.full()                    # 此時隊列中有1個元素，即長度爲1
>>> False
>>> que.put('b')                     # 此時隊列中有2個元素，即長度爲2，已滿
>>> que.full()
>>> True

3. put：往隊列中放一個元素，get：依據先進先出原則，依次從隊列取元素

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).
        '''
        with self.not_full:
            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()

put

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).
        '''
        with self.not_empty:
            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

get

【示例】
>>> import queue
>>> que=queue.Queue()            # 建立隊列，表示隊列的長度，即元素個數
>>> que.put('a')                 #往隊列中放入一個元素
>>> que.put('b')                  #往隊列中再放入一個元素
>>> que.get()
>>> 'a'                          #依據先進先出原則，先取'a'，若所有取出，再次獲取元素，會wait等待生產者線程添加數據

4. put_nowait：無阻塞的向隊列中添加元素，若隊列已滿，不等待直接報錯（full）

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, block=False)

5.get_nowait：無阻塞從隊列中獲取元素，若隊列爲空，不等待直接報錯（empty）

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(block=False)

6.qsize：表示隊列長度，即元素個數

def qsize(self):
        '''Return the approximate size of the queue (not reliable!).'''
        with self.mutex:
            return self._qsize()

【示例】
>>> import queue                 #導入queue模塊
>>> que=queue.Queue()       #建立隊列
>>> que.put(11)
>>> que.put(22)                   # 往隊列中添加元素
>>> que.qsize()                    # 統計元素個數
>>> 2

7.join：阻塞調用線程，直到隊列中的全部任務都被處理完成，與task_done配合使用

def join(self):
        # 每次往隊列中添加一個元素，未完成任務數量則會增長，若是調用task_down()，未完成任務數量則會降低，代表該任務已被檢索，全部工做已完成，若未完成任務數量降到0，則join()將取消阻止
        '''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.
        '''
        with self.all_tasks_done:
            while self.unfinished_tasks:
                self.all_tasks_done.wait()

join

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.

task_down