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__all__ = ['Counter', 'deque', 'defaultdict', 'namedtuple', 'OrderedDict']
# For bootstrapping reasons, the collection ABCs are defined in _abcoll.py.
# They should however be considered an integral part of collections.py.
from _abcoll import *
import _abcoll
__all__ += _abcoll.__all__
from _collections import deque, defaultdict
from operator import itemgetter as _itemgetter, eq as _eq
from keyword import iskeyword as _iskeyword
import sys as _sys
import heapq as _heapq
from weakref import proxy as _proxy
from itertools import repeat as _repeat, chain as _chain, starmap as _starmap, \
ifilter as _ifilter, imap as _imap, izip as _izip
################################################################################
### OrderedDict
################################################################################
class _Link(object):
__slots__ = 'prev', 'next', 'key', '__weakref__'
class OrderedDict(dict, MutableMapping):
'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 for regular dictionaries.
# The internal self.__map dictionary 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 prev/next 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__(self, *args, **kwds):
'''Initialize an ordered dictionary. Signature is the same as for
regular dictionaries, but keyword arguments are not recommended
because their insertion order is arbitrary.
'''
if len(args) > 1:
raise TypeError('expected at most 1 arguments, got %d' % len(args))
try:
self.__root
except AttributeError:
self.__root = root = _Link() # sentinel node for the doubly linked list
root.prev = root.next = root
self.__map = {}
self.update(*args, **kwds)
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 __setitem__(self, key, value):
'od.__setitem__(i, y) <==> od[i]=y'
# Setting a new item creates a new link which goes 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 = root.prev = _proxy(link)
dict.__setitem__(self, key, value)
def __delitem__(self, key):
'od.__delitem__(y) <==> del od[y]'
# Deleting an existing item uses self.__map to find the link which is
# then removed by updating the links in the predecessor and successor nodes.
dict.__delitem__(self, key)
link = self.__map.pop(key)
link.prev.next = link.next
link.next.prev = link.prev
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 __reduce__(self):
'Return state information for pickling'
items = [[k, self[k]] for k in self]
tmp = self.__map, self.__root
del self.__map, self.__root
inst_dict = vars(self).copy()
self.__map, self.__root = tmp
if inst_dict:
return (self.__class__, (items,), inst_dict)
return self.__class__, (items,)
setdefault = MutableMapping.setdefault
update = MutableMapping.update
pop = MutableMapping.pop
keys = MutableMapping.keys
values = MutableMapping.values
items = MutableMapping.items
iterkeys = MutableMapping.iterkeys
itervalues = MutableMapping.itervalues
iteritems = MutableMapping.iteritems
__ne__ = MutableMapping.__ne__
def popitem(self, last=True):
'''od.popitem() -> (k, v), return and remove a (key, value) pair.
Pairs are returned in LIFO order if last is true or FIFO order if false.
'''
if not self:
raise KeyError('dictionary is empty')
key = next(reversed(self) if last else iter(self))
value = self.pop(key)
return key, value
def __repr__(self):
'od.__repr__() <==> repr(od)'
if not self:
return '%s()' % (self.__class__.__name__,)
return '%s(%r)' % (self.__class__.__name__, 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
and values equal to v (which defaults to None).
'''
d = cls()
for key in iterable:
d[key] = value
return d
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 len(self)==len(other) and \
all(_imap(_eq, self.iteritems(), other.iteritems()))
return dict.__eq__(self, other)
################################################################################
### namedtuple
################################################################################
def namedtuple(typename, field_names, verbose=False, rename=False):
"""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)
"""
# Parse and validate the field names. Validation serves two purposes,
# generating informative error messages and preventing template injection attacks.
if isinstance(field_names, basestring):
field_names = field_names.replace(',', ' ').split() # names separated by whitespace and/or commas
field_names = tuple(map(str, field_names))
if rename:
names = list(field_names)
seen = set()
for i, name in enumerate(names):
if (not all(c.isalnum() or c=='_' for c in name) or _iskeyword(name)
or not name or name[0].isdigit() or name.startswith('_')
or name in seen):
names[i] = '_%d' % i
seen.add(name)
field_names = tuple(names)
for name in (typename,) + field_names:
if not all(c.isalnum() or c=='_' for c in name):
raise ValueError('Type names and field names can only contain alphanumeric characters and underscores: %r' % name)
if _iskeyword(name):
raise ValueError('Type names and field names cannot be a keyword: %r' % name)
if name[0].isdigit():
raise ValueError('Type names and field names cannot start with a number: %r' % name)
seen_names = 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_names:
raise ValueError('Encountered duplicate field name: %r' % name)
seen_names.add(name)
# Create and fill-in the class template
numfields = len(field_names)
argtxt = repr(field_names).replace("'", "")[1:-1] # tuple repr without parens or quotes
reprtxt = ', '.join('%s=%%r' % name for name in field_names)
template = '''class %(typename)s(tuple):
'%(typename)s(%(argtxt)s)' \n
__slots__ = () \n
_fields = %(field_names)r \n
def __new__(_cls, %(argtxt)s):
return _tuple.__new__(_cls, (%(argtxt)s)) \n
@classmethod
def _make(cls, iterable, new=tuple.__new__, len=len):
'Make a new %(typename)s object from a sequence or iterable'
result = new(cls, iterable)
if len(result) != %(numfields)d:
raise TypeError('Expected %(numfields)d arguments, got %%d' %% len(result))
return result \n
def __repr__(self):
return '%(typename)s(%(reprtxt)s)' %% self \n
def _asdict(self):
'Return a new OrderedDict which maps field names to their values'
return OrderedDict(zip(self._fields, self)) \n
def _replace(_self, **kwds):
'Return a new %(typename)s 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' %% kwds.keys())
return result \n
def __getnewargs__(self):
return tuple(self) \n\n''' % locals()
for i, name in enumerate(field_names):
template += ' %s = _property(_itemgetter(%d))\n' % (name, i)
if verbose:
print template
# Execute the template string in a temporary namespace and
# support tracing utilities by setting a value for frame.f_globals['__name__']
namespace = dict(_itemgetter=_itemgetter, __name__='namedtuple_%s' % typename,
OrderedDict=OrderedDict, _property=property, _tuple=tuple)
try:
exec template in namespace
except SyntaxError, e:
raise SyntaxError(e.message + ':\n' + template)
result = namespace[typename]
# For pickling to work, the __module__ variable needs to be set to the frame
# where the named tuple is created. Bypass this step in enviroments where
# sys._getframe is not defined (Jython for example) or sys._getframe is not
# defined for arguments greater than 0 (IronPython).
try:
result.__module__ = _sys._getframe(1).f_globals.get('__name__', '__main__')
except (AttributeError, ValueError):
pass
return result
########################################################################
### Counter
########################################################################
class Counter(dict):
'''Dict subclass for counting hashable items. Sometimes called a bag
or multiset. Elements are stored as dictionary keys and their counts
are stored as dictionary values.
>>> c = Counter('abracadabra') # count elements from a string
>>> c.most_common(3) # three most common elements
[('a', 5), ('r', 2), ('b', 2)]
>>> sorted(c) # list all unique elements
['a', 'b', 'c', 'd', 'r']
>>> ''.join(sorted(c.elements())) # list elements with repetitions
'aaaaabbcdrr'
>>> sum(c.values()) # total of all counts
11
>>> 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['r'] # remove all 'r'
>>> c['r'] # now there are zero 'r'
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__(self, iterable=None, **kwds):
'''Create a new, empty Counter object. And if given, count elements
from an input iterable. Or, initialize the count from another mapping
of elements to their counts.
>>> c = Counter() # a new, empty counter
>>> c = Counter('gallahad') # a new counter from an iterable
>>> c = Counter({'a': 4, 'b': 2}) # a new counter from a mapping
>>> c = Counter(a=4, b=2) # a new counter from keyword args
'''
self.update(iterable, **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('abracadabra').most_common(3)
[('a', 5), ('r', 2), ('b', 2)]
'''
# Emulate Bag.sortedByCount from Smalltalk
if n is None:
return sorted(self.iteritems(), key=_itemgetter(1), reverse=True)
return _heapq.nlargest(n, self.iteritems(), key=_itemgetter(1))
def elements(self):
'''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.iteritems()))
# Override dict methods where necessary
@classmethod
def fromkeys(cls, iterable, v=None):
# There is no equivalent method for counters because setting v=1
# means that no element can have a count greater than one.
raise NotImplementedError(
'Counter.fromkeys() is undefined. Use Counter(iterable) instead.')
def update(self, iterable=None, **kwds):
'''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 iterable is not None:
if isinstance(iterable, Mapping):
if self:
self_get = self.get
for elem, count in iterable.iteritems():
self[elem] = self_get(elem, 0) + count
else:
dict.update(self, iterable) # fast path when counter is empty
else:
self_get = self.get
for elem in iterable:
self[elem] = self_get(elem, 0) + 1
if kwds:
self.update(kwds)
def copy(self):
'Like dict.copy() but returns a Counter instance instead of a dict.'
return Counter(self)
def __delitem__(self, elem):
'Like dict.__delitem__() but does not raise KeyError for missing values.'
if elem in self:
dict.__delitem__(self, elem)
def __repr__(self):
if not self:
return '%s()' % self.__class__.__name__
items = ', '.join(map('%r: %r'.__mod__, self.most_common()))
return '%s({%s})' % (self.__class__.__name__, items)
# Multiset-style mathematical operations discussed in:
# Knuth TAOCP Volume II section 4.6.3 exercise 19
# and at http://en.wikipedia.org/wiki/Multiset
#
# Outputs guaranteed to only include positive counts.
#
# To strip negative and zero counts, add-in an empty counter:
# c += Counter()
def __add__(self, other):
'''Add counts from two counters.
>>> Counter('abbb') + Counter('bcc')
Counter({'b': 4, 'c': 2, 'a': 1})
'''
if not isinstance(other, Counter):
return NotImplemented
result = Counter()
for elem in set(self) | set(other):
newcount = self[elem] + other[elem]
if newcount > 0:
result[elem] = newcount
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 in set(self) | set(other):
newcount = self[elem] - other[elem]
if newcount > 0:
result[elem] = newcount
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 in set(self) | set(other):
p, q = self[elem], other[elem]
newcount = q if p < q else p
if newcount > 0:
result[elem] = newcount
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()
if len(self) < len(other):
self, other = other, self
for elem in _ifilter(self.__contains__, other):
p, q = self[elem], other[elem]
newcount = p if p < q else q
if newcount > 0:
result[elem] = newcount
return result
if __name__ == '__main__':
# verify that instances can be pickled
from cPickle import loads, dumps
Point = namedtuple('Point', 'x, y', True)
p = Point(x=10, y=20)
assert p == loads(dumps(p))
# test and demonstrate ability to override methods
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)
for p in Point(3, 4), Point(14, 5/7.):
print p
class Point(namedtuple('Point', 'x y')):
'Point class with optimized _make() and _replace() without error-checking'
__slots__ = ()
_make = classmethod(tuple.__new__)
def _replace(self, _map=map, **kwds):
return self._make(_map(kwds.get, ('x', 'y'), self))
print Point(11, 22)._replace(x=100)
Point3D = namedtuple('Point3D', Point._fields + ('z',))
print Point3D.__doc__
import doctest
TestResults = namedtuple('TestResults', 'failed attempted')
print TestResults(*doctest.testmod())
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