###########################################################################################################################################Counter            *            字典(dict)的子類用來統計可哈希對象的值                                    *      new in py 2.7   *deque              *            雙端隊列，兩端都可以作為隊列的結束，方便前端插入需求                         *      new in py 2.4   *namedtuple         *            tuple的子類，可以用于按名字標識元組                                       *      new in py 2.6   *OrderedDict        *            dict的子類，創建一個可哈希的有序字典                                      *      new in py 2.7   *defaultdict        *            dict的子類，當某個key不存在時，一共一個默認值，而不是報KeyError              *      new in py 2.5   *

from collections import Countercnt = Counter()for Word in ['1','2','3','1','2','1']:    cnt[word] +=1cnt#Counter({'1':3,'2':2,'3':1})######################################統計一段話里出現次數最多的10個詞和各自的次數text = ['a', 'an', 'and', 'are', 'as', 'at', 'be', 'by', 'can','for', 'from', 'have', 'if', 'in', 'is', 'it', 'may','not', 'of', 'on', 'or', 'tbd', 'that', 'the', 'this','to', 'us', 'we', 'when', 'will', 'with', 'yet','you', 'your', '的', '了', '和','or', 'tbd', 'that', 'the', 'this','to', 'us', 'we', 'when', 'will','when']Counter(text).most_common(10)#[('when', 3), ('to', 2), ('we', 2), ('that', 2), ('tbd', 2), ('this', 2), ('us',2), ('will', 2), ('the', 2), ('or', 2)]

c = Counter()     #一個新的空的Counterc = Counter('kwejrkhdskf')    #以可迭代對象'kwejrkhdskf'為基礎創建Counterc = Counter({'red': 4, 'blue': 2})    #以mapping{'red': 4, 'blue': 2}為基礎創建Counterc = Counter(cats=4, dogs=8)    #以keywords args為基礎創建Counter

>>> c = Counter(['eggs', 'ham','eggs'])>>> c['bacon'] 0    #在c.keys中不存在'bacon'，故返回0>>> c['eggs'] 2    #在c.keys中存在'bacon'，故返回對應的value

>>> c['sausage'] = 0  #設置'sausage'的個數為0>>> del c['sausage']    #從Counter中刪除'sausage'

 ##########elements()    Return an iterator over elements repeating each as many times as its count. Elements are returned in arbitrary order. If an element’s count is less than one, elements() will ignore it.##########most_common([n])Return a list of the n most common elements and their counts from the most common to the least. If n is omitted or None, most_common() returns all elements in the counter. Elements with equal counts are ordered arbitrarily:#########################subtract([iterable-or-mapping])Elements are subtracted from an iterable or from another mapping (or counter). Like dict.update() but subtracts counts instead of replacing them. Both inputs and outputs may be zero or negative.##########################sum(c.values())                 # 求和c.clear()                       # 重置list(c)                         # 轉換為listset(c)                          # 轉換為setdict(c)                         # 轉換為dictc.items()                       # 類似dict的items()c += Counter()                  # 刪除掉值為0和負數的count

>>> c = Counter(a=3, b=1)>>> d = Counter(a=1, b=2)>>> c + d                       # 相加:  c[x] + d[x]Counter({'a': 4, 'b': 3})>>> c - d                       # 相減 (舍掉非整數值)Counter({'a': 2})>>> c & d                       # 取最小值:  min(c[x], d[x])Counter({'a': 1, 'b': 1})>>> c | d                       # 取最大值:  max(c[x], d[x])Counter({'a': 3, 'b': 2})

>>> from collections import deque>>> d = deque('ghi')                 # 創建實例>>> for elem in d:                   # 迭代d...     PRint elem.upper()GHI>>> d.append('j')                    # 在最右邊加>>> d.appendleft('f')                # 在最左邊加>>> d                                # showdeque(['f', 'g', 'h', 'i', 'j'])>>> d.pop()                          # 在右邊pop'j'>>> d.popleft()                      #在左邊pop'f'>>> list(d)                          # 轉換為list['g', 'h', 'i']>>> d[0]                             #用下標獲取元素'g'>>> d[-1]                            # 類比list語法'i'>>> list(reversed(d))                ['i', 'h', 'g']>>> 'h' in d                         True>>> d.extend('jkl')                  # 拼接一個可迭代對象>>> ddeque(['g', 'h', 'i', 'j', 'k', 'l'])>>> d.rotate(1)                      #順時針旋轉>>> ddeque(['l', 'g', 'h', 'i', 'j', 'k'])>>> d.rotate(-1)                     #逆時針旋轉>>> ddeque(['g', 'h', 'i', 'j', 'k', 'l'])>>> deque(reversed(d))               deque(['l', 'k', 'j', 'i', 'h', 'g'])>>> d.clear()                        # 清空>>> d.pop()                          # 沒有元素不可以popTraceback (most recent call last):  File "<pyshell#6>", line 1, in -toplevel-    d.pop()IndexError: pop from an empty deque>>> d.extendleft('abc')              # reverse input>>> ddeque(['c', 'b', 'a'])

def del_(d,n):    d.rorate(-n)    d.popleft()    d.rorate(n)

#####################算法：    例如：[40, 30, 50, 46, 39, 44] --> 40.0 42.0 45.0 43.0計算公式： MA = (C1+C2+C3+C4+C5+....+Cn)/n C 為收盤價，n 為移動平均周期數例如，現貨黃金的 5 日移動平均價格計算方法為： MA 5 = （前四天收盤價+前三天收盤價+前天收盤價+昨天收盤價+今天收盤價）/5 #####################  def moving_average(iterable, n=3):    # http://en.wikipedia.org/wiki/Moving_average    it = iter(iterable)    d = deque(itertools.islice(it, n-1))    d.appendleft(0)    s = sum(d)    for elem in it:        s += elem - d.popleft()        d.append(elem)        yield s / float(n)

>>> Point = namedtuple('Point', ['x', 'y'], verbose=True)class Point(tuple):    'Point(x, y)'    __slots__ = ()    _fields = ('x', 'y')    def __new__(_cls, x, y):        'Create a new instance of Point(x, y)'        return _tuple.__new__(_cls, (x, y))    @classmethod    def _make(cls, iterable, new=tuple.__new__, len=len):        'Make a new Point object from a sequence or iterable'        result = new(cls, iterable)        if len(result) != 2:            raise TypeError('Expected 2 arguments, got %d' % len(result))        return result    def __repr__(self):        'Return a nicely formatted representation string'        return 'Point(x=%r, y=%r)' % self    def _asdict(self):        'Return a new OrderedDict which maps field names to their values'        return OrderedDict(zip(self._fields, self))    def _replace(_self, **kwds):        'Return a new Point object replacing specified fields with new values'        result = _self._make(map(kwds.pop, ('x', 'y'), _self))        if kwds:            raise ValueError('Got unexpected field names: %r' % kwds.keys())        return result    def __getnewargs__(self):        'Return self as a plain tuple.   Used by copy and pickle.'        return tuple(self)    __dict__ = _property(_asdict)    def __getstate__(self):        'Exclude the OrderedDict from pickling'        pass    x = _property(_itemgetter(0), doc='Alias for field number 0')    y = _property(_itemgetter(1), doc='Alias for field number 1')>>> p = Point(11, y=22)     # 實例化一個點對象>>> p[0] + p[1]             # 索引方式相加33>>> x, y = p                # unpack like a regular tuple>>> x, y(11, 22)>>> p.x + p.y               # 屬性方式相加33>>> p                       # __repr__實例的值Point(x=11, y=22)

EmployeeRecord = namedtuple('EmployeeRecord', 'name, age, title, department, paygrade')import csvfor emp in map(EmployeeRecord._make, csv.reader(open("employees.csv", "rb"))):    print emp.name, emp.titleimport sqlite3conn = sqlite3.connect('/companydata')cursor = conn.cursor()cursor.execute('SELECT name, age, title, department, paygrade FROM employees')for emp in map(EmployeeRecord._make, cursor.fetchall()):    print emp.name, emp.title

>>> t = [11, 22]>>> Point._make(t)    #通過_make(可迭代對象)對實例傳值Point(x=11, y=22)>>> p._asdict()    #返回一個有序字典（py2.7更新的功能）OrderedDict([('x', 11), ('y', 22)])>>> p = Point(x=11, y=22)>>> p._replace(x=33) #_replace方法替換值Point(x=33, y=22)>>> for partnum, record in inventory.items():        inventory[partnum] = record._replace(price=newprices[partnum], timestamp=time.now())>>> p._fields            # 查看 fields名字('x', 'y')>>> Color = namedtuple('Color', 'red green blue')>>> Pixel = namedtuple('Pixel', Point._fields + Color._fields)>>> Pixel(11, 22, 128, 255, 0)Pixel(x=11, y=22, red=128, green=255, blue=0)>>> getattr(p, 'x') #獲取p實例的x的值11>>> d = {'x': 11, 'y': 22}>>> Point(**d)    #用"**"表示傳的參數是一個字典Point(x=11, y=22)>>> class Point(namedtuple('Point', 'x y')):        __slots__ = ()          @property        def hypot(self):            return (self.x ** 2 + self.y ** 2) ** 0.5        def __str__(self):            return 'Point: x=%6.3f  y=%6.3f  hypot=%6.3f' % (self.x, self.y, self.hypot)>>> Point3D = namedtuple('Point3D', Point._fields + ('z',))>>> Account = namedtuple('Account', 'owner balance transaction_count')>>> default_account = Account('<owner name>', 0.0, 0)>>> johns_account = default_account._replace(owner='John')>>> Status = namedtuple('Status', 'open pending closed')._make(range(3)) #實例化時，也可以同時初始化對象>>> Status.open, Status.pending, Status.closed(0, 1, 2)>>> class Status:        open, pending, closed = range(3)

>>> # 普通的字典>>> d = {'banana': 3, 'apple':4, 'pear': 1, 'orange': 2}>>> # 以key排序>>> OrderedDict(sorted(d.items(), key=lambda t: t[0]))OrderedDict([('apple', 4), ('banana', 3), ('orange', 2), ('pear', 1)])>>> # 以value排序>>> OrderedDict(sorted(d.items(), key=lambda t: t[1]))OrderedDict([('pear', 1), ('orange', 2), ('banana', 3), ('apple', 4)])>>> # 以key的長度排序>>> OrderedDict(sorted(d.items(), key=lambda t: len(t[0])))OrderedDict([('pear', 1), ('apple', 4), ('orange', 2), ('banana', 3)])

>>> s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]>>> d = defaultdict(list) #以list格式儲存字典values>>> for k, v in s:...     d[k].append(v)...>>> d.items()[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]

>>> d = {}>>> for k, v in s:...     d.setdefault(k, []).append(v) #另一種方式...>>> d.items()[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]

>>> s = 'mississippi'>>> d = defaultdict(int) #這種風格比較像counter>>> for k in s:...     d[k] += 1...>>> d.items()[('i', 4), ('p', 2), ('s', 4), ('m', 1)]

>>> def constant_factory(value):...     return itertools.repeat(value).next>>> d = defaultdict(constant_factory('<missing>'))>>> d.update(name='John', action='ran')>>> '%(name)s %(action)s to %(object)s' % d #key=object是缺失的值，采用默認值'John ran to <missing>'

>>> s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)]>>> d = defaultdict(set) #以集合形式存儲字典的values>>> for k, v in s:...     d[k].add(v)...>>> d.items()[('blue', set([2, 4])), ('red', set([1, 3]))]