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c c s: | j } | j } x! | | k r5 | j V| j } q Wd S( u# od.__reversed__() <==> reversed(od)N( u _OrderedDict__rootu prevu key( u selfu rootu curr( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __reversed__[ s
c C s7 | j } | | _ | _ | j j � t j | � d S( u. od.clear() -> None. Remove all items from od.N( u _OrderedDict__rootu prevu nextu _OrderedDict__mapu clearu dict( u selfu root( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu cleard s
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__sizeof__� s c C sC | | k r! | | } | | =| S| | j k r? t | � � n | S( u� od.pop(k[,d]) -> v, remove specified key and return the corresponding
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c C s7 | s d | j j f Sd | j j t | j � � f S( u od.__repr__() <==> repr(od)u %s()u %s(%r)( u __class__u __name__u listu items( u self( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __repr__� s c s{ � f d � � D� } t � � j � } x' t t � � D] } | j | d � q8 W| rk � j | f | f S� j | f f S( u% Return state information for picklingc s g | ] } | � | g � q S( ( ( u .0u k( u self( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu
<listcomp>� s N( u varsu copyu OrderedDictu popu Noneu __class__( u selfu itemsu inst_dictu k( ( u selfu2 /usr/local/python-3.2/lib/python3.2/collections.pyu
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c C s` t | t � rP t | � t | � k oO t d � t | j � | j � � D� � St j | | � S( u� od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive
while comparison to a regular mapping is order-insensitive.
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u3 from builtins import property as _property, tuple as _tuple
from operator import itemgetter as _itemgetter
from collections import OrderedDict
class {typename}(tuple):
'{typename}({arg_list})'
__slots__ = ()
_fields = {field_names!r}
def __new__(_cls, {arg_list}):
'Create new instance of {typename}({arg_list})'
return _tuple.__new__(_cls, ({arg_list}))
@classmethod
def _make(cls, iterable, new=tuple.__new__, len=len):
'Make a new {typename} object from a sequence or iterable'
result = new(cls, iterable)
if len(result) != {num_fields:d}:
raise TypeError('Expected {num_fields:d} arguments, got %d' % len(result))
return result
def __repr__(self):
'Return a nicely formatted representation string'
return self.__class__.__name__ + '({repr_fmt})' % self
def _asdict(self):
'Return a new OrderedDict which maps field names to their values'
return OrderedDict(zip(self._fields, self))
__dict__ = property(_asdict)
def _replace(_self, **kwds):
'Return a new {typename} object replacing specified fields with new values'
result = _self._make(map(kwds.pop, {field_names!r}, _self))
if kwds:
raise ValueError('Got unexpected field names: %r' % list(kwds))
return result
def __getnewargs__(self):
'Return self as a plain tuple. Used by copy and pickle.'
return tuple(self)
def __getstate__(self):
'Exclude the OrderedDict from pickling'
return None
{field_defs}
u {name}=%ruW {name} = _property(_itemgetter({index:d}), doc='Alias for field number {index:d}')
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r�} z t | j d | � � WYd d } ~ Xn X| | }
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r Yn X|
S( uC 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 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)
u ,u c s s' | ] } | j � p | d k Vq d S( u _N( u isalnum( u .0u c( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu <genexpr>I s i u _u _%dc s s' | ] } | j � p | d k Vq d S( u _N( u isalnum( u .0u c( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu <genexpr>R s uW Type names and field names can only contain alphanumeric characters and underscores: %ru2 Type names and field names cannot be a keyword: %ru9 Type names and field names cannot start with a number: %ru/ Field names cannot start with an underscore: %ru$ Encountered duplicate field name: %ru typenameu field_namesu
num_fieldsu arg_listu 'u i u repr_fmtu , c s s! | ] } t j d | � Vq d S( u nameN( u _repr_templateu format( u .0u name( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu <genexpr>f s u
field_defsu
c s s- | ]# \ } } t j d | d | � Vq d S( u indexu nameN( u _field_templateu format( u .0u indexu name( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu <genexpr>g s u __name__u
namedtuple_%su :
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namedtuple) sb
( *
%c C s5 | j } x% | D] } | | d � d | | <q Wd S( u! Tally elements from the iterable.i i N( u get( u mappingu iterableu mapping_getu elem( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu _count_elements� s
( u _count_elementsc s� | Ee Z d Z d � f d � Z d � Z d d � Z d � Z e d d � � Z d � f d � Z
d d � Z d � Z d � Z
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� Z d � Z d � Z � S( u� 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)]
c s! t � j � | j | | � d S( u 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
N( u superu __init__u update( u selfu iterableu kwds( u __class__( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __init__� s
c C s d S( u1 The count of elements not in the Counter is zero.i ( ( u selfu key( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __missing__� s c C sP | d k r. t | j � d t d � d d �St j | | j � d t d � �S( u� 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)]
u keyi u reverseNT( u Noneu sortedu itemsu _itemgetteru Trueu _heapqu nlargest( u selfu n( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu most_common� s "c C s t j t t | j � � � S( u� 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.
( u _chainu
from_iterableu _starmapu _repeatu items( u self( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu elements� s c C s t d � � d S( Nu@ Counter.fromkeys() is undefined. Use Counter(iterable) instead.( u NotImplementedError( u clsu iterableu v( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu fromkeys� s c s� | d k r� t | t � rt | ra | j } xD | j � D]# \ } } | | | d � | | <q7 Wq� t � j | � q� t | | � n | r� | j | � n d S( u� 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
i N( u Noneu
isinstanceu Mappingu getu itemsu superu updateu _count_elements( u selfu iterableu kwdsu self_getu elemu count( u __class__( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu update s c K s� | d k r� | j } t | t � r[ x\ | j � D]# \ } } | | d � | | | <q1 Wq� x( | D] } | | d � d | | <qb Wn | r� | j | � n d S( u� 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
i i N( u Noneu getu
isinstanceu Mappingu itemsu subtract( u selfu iterableu kwdsu self_getu elemu count( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu subtract$ s
c C s
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__reduce__C s c s# | | k r t � j | � n d S( uG Like dict.__delitem__() but does not raise KeyError for missing values.N( u superu __delitem__( u selfu elem( u __class__( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __delitem__F s c C s� | s d | j j Sy9 d j t d j | j � � � } d | j j | f SWn. t k
r} d j | j j t | � � SYn Xd S( Nu %s()u , u %r: %ru %s({%s})u
{0}({1!r})( u __class__u __name__u joinu mapu __mod__u most_commonu TypeErroru formatu dict( u selfu items( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __repr__K s !
c C s� t | t � s t St � } xA | j � D]3 \ } } | | | } | d k r) | | | <q) q) Wx? | j � D]1 \ } } | | k rm | d k rm | | | <qm qm W| S( u Add counts from two counters.
>>> Counter('abbb') + Counter('bcc')
Counter({'b': 4, 'c': 2, 'a': 1})
i ( u
isinstanceu Counteru NotImplementedu items( u selfu otheru resultu elemu countu newcount( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __add__^ s c C s� t | t � s t St � } xA | j � D]3 \ } } | | | } | d k r) | | | <q) q) WxC | j � D]5 \ } } | | k rm | d k rm d | | | <qm qm W| S( u� Subtract count, but keep only results with positive counts.
>>> Counter('abbbc') - Counter('bccd')
Counter({'b': 2, 'a': 1})
i ( u
isinstanceu Counteru NotImplementedu items( u selfu otheru resultu elemu countu newcount( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __sub__q s c C s� t | t � s t St � } xU | j � D]G \ } } | | } | | k rQ | n | } | d k r) | | | <q) q) Wx? | j � D]1 \ } } | | k r� | d k r� | | | <q� q� W| S( u� Union is the maximum of value in either of the input counters.
>>> Counter('abbb') | Counter('bcc')
Counter({'b': 3, 'c': 2, 'a': 1})
i ( u
isinstanceu Counteru NotImplementedu items( u selfu otheru resultu elemu countu other_countu newcount( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __or__� s
c C sx t | t � s t St � } xU | j � D]G \ } } | | } | | k rQ | n | } | d k r) | | | <q) q) W| S( u� Intersection is the minimum of corresponding counts.
>>> Counter('abbb') & Counter('bcc')
Counter({'b': 1})
i ( u
isinstanceu Counteru NotImplementedu items( u selfu otheru resultu elemu countu other_countu newcount( ( u2 /usr/local/python-3.2/lib/python3.2/collections.pyu __and__� s
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__module__u __doc__u Noneu __init__u __missing__u most_commonu elementsu classmethodu fromkeysu updateu subtractu copyu
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� � Z d � Z d � Z d � Z d � Z d � Z d S( u� A ChainMap groups multiple dicts (or other mappings) together
to create a single, updateable view.
The underlying mappings are stored in a list. That list is public and can
accessed or updated using the *maps* attribute. There is no other state.
Lookups search the underlying mappings successively until a key is found.
In contrast, writes, updates, and deletions only operate on the first
mapping.
c G s t | � p i g | _ d S( u� Initialize a ChainMap by setting *maps* to the given mappings.
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