Lib/collections.py

__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 itertools import repeat as _repeat, chain as _chain, starmap as _starmap, \
                      ifilter as _ifilter, imap as _imap, izip as _izip

################################################################################
### OrderedDict
################################################################################

class OrderedDict(dict, MutableMapping):
    'Dictionary that remembers insertion order'
    # The inherited dict maps keys to values.
    # The internal self.__map dictionary maps keys to links in a doubly linked list.
    # The doubly linked list starts and ends with a sentinel element.
    # The sentinel element never gets deleted.  It simplifies the algorithm.
    # Setting a new item causes a new link to append to the doubly linked list.
    # Deleting an item uses self.__map to find the link, which is then removed.
    # Iteration follows the linked list in order.
    # Reverse iteration follows the links backwards.
    # The inherited dict provides __getitem__, __len__, __contains__, and get.
    # The remaining methods are order-aware.
    # Big-Oh running times for all methods are the same as for regular dictionaries.

    def __init__(self, *args, **kwds):
        if len(args) > 1:
            raise TypeError('expected at most 1 arguments, got %d' % len(args))
        try:
            self.__end
        except AttributeError:
            self.clear()
        self.update(*args, **kwds)

    def clear(self):
        self.__end = end = []
        end += [None, end, end]         # sentinel node for doubly linked list
        self.__map = {}                 # key --> [key, prev, next]
        dict.clear(self)

    def __setitem__(self, key, value):
        if key not in self:
            end = self.__end
            curr = end[1]
            curr[2] = end[1] = self.__map[key] = [key, curr, end]
        dict.__setitem__(self, key, value)

    def __delitem__(self, key):
        dict.__delitem__(self, key)
        key, prev, next = self.__map.pop(key)
        prev[2] = next
        next[1] = prev

    def __iter__(self):
        end = self.__end
        curr = end[2]                   # start at first link
        while curr is not end:
            yield curr[0]               # yield KEY for each link
            curr = curr[2]              # goto next link

    def __reversed__(self):
        end = self.__end
        curr = end[1]                   # start at last link
        while curr is not end:
            yield curr[0]               # yield KEY for each link
            curr = curr[1]              # goto prev link

    def __reduce__(self):
        items = [[k, self[k]] for k in self]
        tmp = self.__map, self.__end
        del self.__map, self.__end
        inst_dict = vars(self).copy()
        self.__map, self.__end = 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):
        if not self:
            raise KeyError('dictionary is empty')
        key = next(reversed(self)) if last else next(iter(self))
        value = self.pop(key)
        return key, value

    def __repr__(self):
        if not self:
            return '%s()' % (self.__class__.__name__,)
        return '%s(%r)' % (self.__class__.__name__, self.items())

    def copy(self):
        return self.__class__(self)

    @classmethod
    def fromkeys(cls, iterable, value=None):
        d = cls()
        for key in iterable:
            d[key] = value
        return d

    def __eq__(self, other):
        if isinstance(other, OrderedDict):
            return len(self)==len(other) and all(_imap(_eq, self.items(), other.items()))
        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+1)
            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)
    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).
    if hasattr(_sys, '_getframe'):
        result.__module__ = _sys._getframe(1).f_globals.get('__name__', '__main__')

    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:
                    for elem, count in iterable.iteritems():
                        self[elem] += count
                else:
                    dict.update(self, iterable) # fast path when counter is empty
            else:
                for elem in iterable:
                    self[elem] += 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
        _max = max
        result = Counter()
        for elem in set(self) | set(other):
            newcount = _max(self[elem], other[elem])
            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
        _min = min
        result = Counter()
        if len(self) < len(other):
            self, other = other, self
        for elem in _ifilter(self.__contains__, other):
            newcount = _min(self[elem], other[elem])
            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())