-- collection是对内置数据类型的一种扩充，其主要扩充类型包括：
1.namedtuple(): 生成可以使用名字来访问元素内容的tuple子类，以增强可读性。
def namedtuple(typename, field_names, verbose=False, rename=False):
"""Returns a new subclass of tuple with named fields.
返回一个新的命名域元组子类，typename为类型名，field_names为数据变量域名
>>> Point = namedtuple('Point', ['x', 'y']) #定义一个命名元组，类型为Point，数据变量域为['x','y']
>>> Point.__doc__ # docstring for the new class
'Point(x, y)'
>>> p = Point(11, y=22) # 定义一个Point,x=11,y=22，（instantiate with positional args or keywords）
>>> p[0] + p[1] # 也可以用下标，p[0]即x,p[1]即y，(indexable like a plain tuple)
33
>>> x, y = p # 也可以这样赋值，p即p[0]和p[1]或p.x和p.y，（unpack like a regular tuple）
>>> x, y
(11, 22)
>>> p.x + p.y # fields also accessable 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)
2.deque: 双端队列，可以快速的从另外一侧追加和推出对象。deque其实是 double-ended queue 的缩写，翻译过来就是双端队列，它最大的好处就是实现了从队列 头部快速增加和取出对象: .popleft(), .appendleft() 。
从_collection模块得到：
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
""" Add an element to the right side of the deque.从队列右边增加一个元素
如：
d
=
deque()
d.append(
'1'
)
d.append(
'2'
)
d.append(
'3'
)
len
(d)
d[
0
]
d[
-
1
]
print(d)
print("d[0]=%s,d[1]=%s,d[2]=%s"%(d[0],d[1],d[2]))
结果
deque(['1', '2', '3'])
d[0]=1,d[1]=2,d[2]=3
"""
pass
def appendleft(self, *args, **kwargs): # real signature unknown
""" Add an element to the left side of the deque. 从队列左边增加一个元素"""
pass
def clear(self, *args, **kwargs): # real signature unknown
""" Remove all elements from the deque. 清除所有队列数据"""
pass
def copy(self, *args, **kwargs): # real signature unknown
""" Return a shallow copy of a deque. 返回一个浅拷贝队列"""
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 从右边扩充队列值"""
pass
def extendleft(self, *args, **kwargs): # real signature unknown
""" 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__
"""
D.index(value, [start, [stop]]) -> integer -- return first index of value.返回值得第一个下标
Raises ValueError if the value is not present.
"""
return 0
def insert(self, index, p_object): # real signature unknown; restored from __doc__
""" D.insert(index, object) -- insert object before index """
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
3.Counter: 计数器，主要用来计数,是对字典的一种扩充。
下面是Counter类，从dict继承而来。
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') # 从字串中计算元素个数
Counter({'a': 5, 'b': 4, 'c': 3, 'd': 2, 'e': 1})
>>> c.most_common(3) # 选出3个元素最多的值
[('a', 5), ('b', 4), ('c', 3)]
>>> sorted(c) # 对每个独立的元素进行列表排序
['a', 'b', 'c', 'd', 'e']
>>> ''.join(sorted(c.elements())) # 按排序列出重复元素
'aaaaabbbbcccdde'
>>> sum(c.values()) # 求出字串元素的总个数
15
>>> c['a'] # 计算c字串中a元素的个数
5
#遍历'shazam'字串，为每个遍历到的元素数量加1，所以总的a元素数量为7
>>> 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'] # 删除所有的b元素
>>> c['b'] # now there are zero 'b'
0
>>> d = Counter('simsalabim') # 生成一个新的计数器
>>> c.update(d) # 将新的计数器d加到原来的计数器c中
>>> c['a'] # 此时计算的a元素为9个
9
>>> c.clear() # 清空计数器
>>> 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 # 将b元素减少2个
>>> c.most_common() # 此时b仍然存在，但计数数量为0
[('a', 3), ('c', 1), ('b', 0)]
'''
4.OrderedDict: 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 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
link_prev.next = link_next
link_next.prev = link_prev
root = self.__root
if last:
last = root.prev
link.prev = last
link.next = root
last.next = root.prev = link
else:
first = root.next
link.prev = root
link.next = first
root.next = first.prev = 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
5.defaultdict: 带有默认值的字典
我们都知道，在使用Python原生的数据结构dict的时候，如果用 d[key] 这样的方式访问， 当指定的key不存在时，是会抛出KeyError异常的。
但是，如果使用defaultdict，只要你传入一个默认的工厂方法，那么请求一个不存在的key时， 便会调用这个工厂方法使用其结果来作为这个key的默认值。
默认值可以很方便
众所周知，在Python中如果访问字典中不存在的键，会引发KeyError异常（JavaScript中如果对象中不存在某个属性，则返回undefined）。但是有时候，字典中的每个键都存在默认值是非常方便的。例如下面的例子：
strings = ('puppy', 'kitten', 'puppy', 'puppy', 'weasel', 'puppy', 'kitten', 'puppy') counts = {} for kw in strings: counts[kw] += 1该例子统计strings中某个单词出现的次数，并在counts字典中作记录。单词每出现一次，在counts相对应的键所存的值数字加1。但是事实上，运行这段代码会抛出KeyError异常，出现的时机是每个单词第一次统计的时候，因为Python的dict中不存在默认值的说法，可以在Python命令行中验证：
>>> counts = dict() >>> counts {} >>> counts['puppy'] += 1 Traceback (most recent call last): File "<stdin>", line 1, in <module> KeyError: 'puppy'
使用判断语句检查
既然如此，首先可能想到的方法是在单词第一次统计的时候，在counts中相应的键存下默认值1。这需要在处理的时候添加一个判断语句：
strings = ('puppy', 'kitten', 'puppy', 'puppy', 'weasel', 'puppy', 'kitten', 'puppy') counts = {} for kw in strings: if kw not in counts: counts[kw] = 1 else: counts[kw] += 1 # counts: # {'puppy': 5, 'weasel': 1, 'kitten': 2}使用dict.setdefault()方法
也可以通过dict.setdefault()方法来设置默认值：
strings = ('puppy', 'kitten', 'puppy', 'puppy', 'weasel', 'puppy', 'kitten', 'puppy') counts = {} for kw in strings: counts.setdefault(kw, 0) counts[kw] += 1 # 原PPT中这里有一个笔误dict.setdefault()方法接收两个参数，第一个参数是健的名称，第二个参数是默认值。假如字典中不存在给定的键，则返回参数中提供的默认值；反之，则返回字典中保存的值。利用dict.setdefault()方法的返回值可以重写for循环中的代码，使其更加简洁：
strings = ('puppy', 'kitten', 'puppy', 'puppy', 'weasel', 'puppy', 'kitten', 'puppy') counts = {} for kw in strings: counts[kw] = counts.setdefault(kw, 0) + 1使用collections.defaultdict类
以上的方法虽然在一定程度上解决了dict中不存在默认值的问题，但是这时候我们会想，有没有一种字典它本身提供了默认值的功能呢？答案是肯定的，那就是collections.defaultdict。
defaultdict类就好像是一个dict，但是它是使用一个类型来初始化的：
>>> from collections import defaultdict >>> dd = defaultdict(list) >>> dd defaultdict(<type 'list'>, {})defaultdict类的初始化函数接受一个类型作为参数，当所访问的键不存在的时候，可以实例化一个值作为默认值：
>>> dd['foo'] [] >>> dd defaultdict(<type 'list'>, {'foo': []}) >>> dd['bar'].append('quux') >>> dd defaultdict(<type 'list'>, {'foo': [], 'bar': ['quux']})需要注意的是，这种形式的默认值只有在通过dict[key]或者dict.__getitem__(key)访问的时候才有效，这其中的原因在下文会介绍。
>>> from collections import defaultdict >>> dd = defaultdict(list) >>> 'something' in dd False >>> dd.pop('something') Traceback (most recent call last): File "<stdin>", line 1, in <module> KeyError: 'pop(): dictionary is empty' >>> dd.get('something') >>> dd['something'] []defaultdict类除了接受类型名称作为初始化函数的参数之外，还可以使用任何不带参数的可调用函数，到时该函数的返回结果作为默认值，这样使得默认值的取值更加灵活。下面用一个例子来说明，如何用自定义的不带参数的函数zero()作为defaultdict类的初始化函数的参数：
>>> from collections import defaultdict >>> def zero(): ... return 0 ... >>> dd = defaultdict(zero) >>> dd defaultdict(<function zero at 0xb7ed2684>, {}) >>> dd['foo'] 0 >>> dd defaultdict(<function zero at 0xb7ed2684>, {'foo': 0})利用collections.defaultdict来解决最初的单词统计问题，代码如下：
from collections import defaultdict
strings = ('puppy', 'kitten', 'puppy', 'puppy', 'weasel', 'puppy', 'kitten', 'puppy') counts = defaultdict(lambda: 0) # 使用lambda来定义简单的函数 for s in strings: counts[s] += 1defaultdict类是如何实现的
通过上面的内容，想必大家已经了解了defaultdict类的用法，那么在defaultdict类中又是如何来实现默认值的功能呢？这其中的关键是使用了看__missing__()这个方法：
>>> from collections import defaultdict >>> print defaultdict.__missing__.__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通过查看__missing__()方法的docstring，可以看出当使用__getitem__()方法访问一个不存在的键时(dict[key]这种形式实际上是__getitem__()方法的简化形式)，会调用__missing__()方法获取默认值，并将该键添加到字典中去。
关于__missing__()方法的具体介绍可以参考Python官方文档中的"Mapping Types — dict"一节。
文档中介绍，从2.5版本开始，如果派生自dict的子类定义了__missing__()方法，当访问不存在的键时，dict[key]会调用__missing__()方法取得默认值。
从中可以看出，虽然dict支持__missing__()方法，但是在dict本身是不存在这个方法的，而是需要在派生的子类中自行实现这个方法。可以简单的验证这一点：
>>> print dict.__missing__.__doc__ Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: type object 'dict' has no attribute '__missing__'同时，我们可以进一步的做实验，定义一个子类Missing并实现__missing__()方法:
>>> class Missing(dict): ... def __missing__(self, key): ... return 'missing' ... >>> d = Missing() >>> d {} >>> d['foo'] 'missing' >>> d {}返回结果反映了__missing__()方法确实发挥了作用。在此基础上，我们稍许修改__missing__()方法,使得该子类同defautldict类一样为不存在的键设置一个默认值：
>>> class Defaulting(dict): ... def __missing__(self, key): ... self[key] = 'default' ... return 'default' ... >>> d = Defaulting() >>> d {} >>> d['foo'] 'default' >>> d {'foo': 'default'}在旧版本的Python中实现类defaultdict的功能
defaultdict类是从2.5版本之后才添加的，在一些旧版本中并不支持它，因此为旧版本实现一个兼容的defaultdict类是必要的。这其实很简单，虽然性能可能未必如2.5版本中自带的defautldict类好，但在功能上是一样的。
首先，__getitem__()方法需要在访问键失败时，调用__missing__()方法：
class defaultdict(dict): def __getitem__(self, key): try: return dict.__getitem__(self, key) except KeyError: return self.__missing__(key)其次，需要实现__missing__()方法用来设置默认值：
class defaultdict(dict): def __getitem__(self, key): try: return dict.__getitem__(self, key) except KeyError: return self.__missing__(key) def __missing__(self, key): self[key] = value = self.default_factory() return value然后，defaultdict类的初始化函数__init__()需要接受类型或者可调用函数参数:
class defaultdict(dict): def __init__(self, default_factory=None, *a, **kw): dict.__init__(self, *a, **kw) self.default_factory = default_factory def __getitem__(self, key): try: return dict.__getitem__(self, key) except KeyError: return self.__missing__(key) def __missing__(self, key): self[key] = value = self.default_factory() return value最后，综合以上内容，通过以下方式完成兼容新旧Python版本的代码：
try:
from collections import defaultdict except ImportError: class defaultdict(dict): def __init__(self, default_factory=None, *a, **kw): dict.__init__(self, *a, **kw) self.default_factory = default_factory def __getitem__(self, key): try: return dict.__getitem__(self, key) except KeyError: return self.__missing__(key) def __missing__(self, key): self[key] = value = self.default_factory() return value
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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