mirror of https://github.com/python/cpython
350 lines
14 KiB
Python
350 lines
14 KiB
Python
__all__ = ['deque', 'defaultdict', 'namedtuple']
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# For bootstrapping reasons, the collection ABCs are defined in _abcoll.py.
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# They should however be considered an integral part of collections.py.
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from _abcoll import *
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import _abcoll
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__all__ += _abcoll.__all__
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from _collections import deque, defaultdict
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from operator import itemgetter as _itemgetter
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from keyword import iskeyword as _iskeyword
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import sys as _sys
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import heapq as _heapq
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import itertools as _itertools
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########################################################################
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### namedtuple #######################################################
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def namedtuple(typename, field_names, verbose=False):
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"""Returns a new subclass of tuple with named fields.
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>>> Point = namedtuple('Point', 'x y')
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>>> Point.__doc__ # docstring for the new class
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'Point(x, y)'
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>>> p = Point(11, y=22) # instantiate with positional args or keywords
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>>> p[0] + p[1] # indexable like a plain tuple
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33
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>>> x, y = p # unpack like a regular tuple
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>>> x, y
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(11, 22)
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>>> p.x + p.y # fields also accessable by name
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33
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>>> d = p._asdict() # convert to a dictionary
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>>> d['x']
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11
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>>> Point(**d) # convert from a dictionary
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Point(x=11, y=22)
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>>> p._replace(x=100) # _replace() is like str.replace() but targets named fields
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Point(x=100, y=22)
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"""
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# Parse and validate the field names. Validation serves two purposes,
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# generating informative error messages and preventing template injection attacks.
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if isinstance(field_names, basestring):
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field_names = field_names.replace(',', ' ').split() # names separated by whitespace and/or commas
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field_names = tuple(map(str, field_names))
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for name in (typename,) + field_names:
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if not all(c.isalnum() or c=='_' for c in name):
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raise ValueError('Type names and field names can only contain alphanumeric characters and underscores: %r' % name)
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if _iskeyword(name):
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raise ValueError('Type names and field names cannot be a keyword: %r' % name)
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if name[0].isdigit():
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raise ValueError('Type names and field names cannot start with a number: %r' % name)
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seen_names = set()
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for name in field_names:
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if name.startswith('_'):
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raise ValueError('Field names cannot start with an underscore: %r' % name)
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if name in seen_names:
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raise ValueError('Encountered duplicate field name: %r' % name)
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seen_names.add(name)
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# Create and fill-in the class template
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numfields = len(field_names)
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argtxt = repr(field_names).replace("'", "")[1:-1] # tuple repr without parens or quotes
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reprtxt = ', '.join('%s=%%r' % name for name in field_names)
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dicttxt = ', '.join('%r: t[%d]' % (name, pos) for pos, name in enumerate(field_names))
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template = '''class %(typename)s(tuple):
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'%(typename)s(%(argtxt)s)' \n
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__slots__ = () \n
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_fields = %(field_names)r \n
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def __new__(cls, %(argtxt)s):
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return tuple.__new__(cls, (%(argtxt)s)) \n
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@classmethod
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def _make(cls, iterable, new=tuple.__new__, len=len):
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'Make a new %(typename)s object from a sequence or iterable'
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result = new(cls, iterable)
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if len(result) != %(numfields)d:
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raise TypeError('Expected %(numfields)d arguments, got %%d' %% len(result))
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return result \n
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def __repr__(self):
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return '%(typename)s(%(reprtxt)s)' %% self \n
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def _asdict(t):
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'Return a new dict which maps field names to their values'
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return {%(dicttxt)s} \n
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def _replace(self, **kwds):
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'Return a new %(typename)s object replacing specified fields with new values'
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result = self._make(map(kwds.pop, %(field_names)r, self))
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if kwds:
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raise ValueError('Got unexpected field names: %%r' %% kwds.keys())
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return result \n
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def __getnewargs__(self):
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return tuple(self) \n\n''' % locals()
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for i, name in enumerate(field_names):
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template += ' %s = property(itemgetter(%d))\n' % (name, i)
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if verbose:
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print template
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# Execute the template string in a temporary namespace and
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# support tracing utilities by setting a value for frame.f_globals['__name__']
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namespace = dict(itemgetter=_itemgetter, __name__='namedtuple_%s' % typename)
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try:
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exec template in namespace
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except SyntaxError, e:
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raise SyntaxError(e.message + ':\n' + template)
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result = namespace[typename]
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# For pickling to work, the __module__ variable needs to be set to the frame
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# where the named tuple is created. Bypass this step in enviroments where
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# sys._getframe is not defined (Jython for example).
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if hasattr(_sys, '_getframe'):
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result.__module__ = _sys._getframe(1).f_globals['__name__']
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return result
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########################################################################
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### Counter ##########################################################
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class Counter(dict):
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'''Dict subclass for counting hashable items. Sometimes called a bag
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or multiset. Elements are stored as dictionary keys and their counts
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are stored as dictionary values.
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>>> c = Counter('abracadabra') # count elements from a string
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>>> c.most_common(3) # three most common elements
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[('a', 5), ('r', 2), ('b', 2)]
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>>> sorted(c) # list all unique elements
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['a', 'b', 'c', 'd', 'r']
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>>> ''.join(sorted(c.elements())) # list elements with repetitions
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'aaaaabbcdrr'
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>>> sum(c.values()) # total of all counts
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11
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>>> c['a'] # count of letter 'a'
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5
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>>> for elem in 'shazam': # update counts from an iterable
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... c[elem] += 1 # by adding 1 to each element's count
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>>> c['a'] # now there are seven 'a'
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7
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>>> del c['r'] # remove all 'r'
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>>> c['r'] # now there are zero 'r'
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0
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>>> d = Counter('simsalabim') # make another counter
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>>> c.update(d) # add in the second counter
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>>> c['a'] # now there are nine 'a'
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9
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>>> c.clear() # empty the counter
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>>> c
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Counter()
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Note: If a count is set to zero or reduced to zero, it will remain
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in the counter until the entry is deleted or the counter is cleared:
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>>> c = Counter('aaabbc')
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>>> c['b'] -= 2 # reduce the count of 'b' by two
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>>> c.most_common() # 'b' is still in, but its count is zero
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[('a', 3), ('c', 1), ('b', 0)]
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'''
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# References:
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# http://en.wikipedia.org/wiki/Multiset
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# http://www.gnu.org/software/smalltalk/manual-base/html_node/Bag.html
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# http://www.demo2s.com/Tutorial/Cpp/0380__set-multiset/Catalog0380__set-multiset.htm
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# http://code.activestate.com/recipes/259174/
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# Knuth, TAOCP Vol. II section 4.6.3
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def __init__(self, iterable=None, items=None):
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'''Create a new, empty Counter object. And if given, count elements
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from an input iterable. Or, initialize the count from an items list
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of (element, count) pairs.
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>>> c = Counter('hocus pocus') # count elements in an iterable
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>>> c = Counter(items=[('a', 4), ('b', 2)]) # take counts from an items list
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'''
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if iterable is not None:
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for elem in iterable:
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self[elem] += 1
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if items is not None:
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for elem, count in items:
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self[elem] += count
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def __missing__(self, key):
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'The count of elements not in the Counter is zero.'
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# Needed so that self[missing_item] does not raise KeyError
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return 0
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def most_common(self, n=None):
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'''List the n most common elements and their counts from the most
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common to the least. If n is None, then list all element counts.
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>>> Counter('abracadabra').most_common(3)
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[('a', 5), ('r', 2), ('b', 2)]
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'''
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# Emulate Bag.sortedByCount from Smalltalk
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if n is None:
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return sorted(self.iteritems(), key=_itemgetter(1), reverse=True)
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return _heapq.nlargest(n, self.iteritems(), key=_itemgetter(1))
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def elements(self):
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'''Iterator over elements repeating each as many times as its count.
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>>> c = Counter('ABCABC')
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>>> sorted(c.elements())
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['A', 'A', 'B', 'B', 'C', 'C']
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# Knuth's example of prime factors of 1836: 2**2 * 3**3 * 17**1
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>>> import operator
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>>> prime_factors = Counter(items=[(2,2), (3,3), (17,1)])
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>>> sorted(prime_factors.elements()) # list individual factors
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[2, 2, 3, 3, 3, 17]
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>>> reduce(operator.mul, prime_factors.elements(), 1) # multiply them
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1836
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Note, if an element's count has been set to zero or a negative number,
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elements() will ignore it.
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'''
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# Emulate Bag.do from Smalltalk and Multiset.begin from C++.
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return _itertools.chain.from_iterable(
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_itertools.starmap(_itertools.repeat,
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self.iteritems()))
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# Override dict methods where necessary
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@classmethod
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def fromkeys(cls, iterable, v=None):
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# There is no equivalent method for counters because setting v=1
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# means that no element can have a count greater than one.
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raise NotImplementedError(
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'Counter.fromkeys() is undefined. Use Counter(iterable) instead.')
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def update(self, mapping):
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'''Like dict.update() but add counts instead of replacing them.
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Source can be another dictionary or a Counter.instance().
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>>> c = Counter('which')
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>>> d = Counter('witch')
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>>> c.update(d) # Add counts from d to those in c
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>>> c['h'] # Count of 'h' is now three
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3
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'''
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# The regular dict.update() operation makes no sense here because the
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# replace behavior results in the some of original untouched counts
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# being mixed-in with all of the other counts for a mismash that
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# doesn't have a straight-forward interpretation in most counting
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# contexts. Instead, we look to Knuth for suggested operations on
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# multisets and implement the union-add operation discussed in
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# TAOCP Volume II section 4.6.3 exercise 19. The Wikipedia entry for
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# multisets calls that operation a sum or join.
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for elem, count in mapping.iteritems():
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self[elem] += count
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def copy(self):
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'Like dict.copy() but returns a Counter instance instead of a dict.'
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c = Counter()
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c.update(self)
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return c
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def __repr__(self):
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if not self:
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return '%s()' % self.__class__.__name__
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return '%s(items=%r)' % (self.__class__.__name__, self.most_common())
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if __name__ == '__main__':
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# verify that instances can be pickled
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from cPickle import loads, dumps
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Point = namedtuple('Point', 'x, y', True)
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p = Point(x=10, y=20)
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assert p == loads(dumps(p))
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# test and demonstrate ability to override methods
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class Point(namedtuple('Point', 'x y')):
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__slots__ = ()
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@property
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def hypot(self):
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return (self.x ** 2 + self.y ** 2) ** 0.5
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def __str__(self):
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return 'Point: x=%6.3f y=%6.3f hypot=%6.3f' % (self.x, self.y, self.hypot)
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for p in Point(3, 4), Point(14, 5/7.):
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print p
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class Point(namedtuple('Point', 'x y')):
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'Point class with optimized _make() and _replace() without error-checking'
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__slots__ = ()
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_make = classmethod(tuple.__new__)
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def _replace(self, _map=map, **kwds):
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return self._make(_map(kwds.get, ('x', 'y'), self))
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print Point(11, 22)._replace(x=100)
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Point3D = namedtuple('Point3D', Point._fields + ('z',))
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print Point3D.__doc__
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# Check that counters are copyable, deepcopyable, picklable, and have a
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# repr/eval round-trip
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import copy
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words = Counter('which witch had which witches wrist watch'.split())
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update_test = Counter()
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update_test.update(words)
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for i, dup in enumerate([
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words.copy(),
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copy.copy(words),
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copy.deepcopy(words),
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loads(dumps(words, 0)),
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loads(dumps(words, 1)),
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loads(dumps(words, 2)),
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loads(dumps(words, -1)),
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eval(repr(words)),
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update_test,
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]):
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msg = (i, dup, words)
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assert dup is not words, msg
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assert dup == words, msg
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assert len(dup) == len(words), msg
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assert type(dup) == type(words), msg
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# Verify that counters are unhashable
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try:
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hash(words)
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except TypeError:
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pass
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else:
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print 'Failed hashing test'
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# Verify that Counter.fromkeys() is disabled
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try:
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Counter.fromkeys('razmataz')
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except NotImplementedError:
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pass
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else:
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print 'Failed fromkeys() test'
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# Check ABCs
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assert issubclass(Counter, Mapping)
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assert isinstance(Counter('asdfasdf'), Mapping)
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import doctest
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TestResults = namedtuple('TestResults', 'failed attempted')
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print TestResults(*doctest.testmod())
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