cpython/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
try:
    from thread import get_ident
except AttributeError:
    from dummy_thread import get_ident

def _recursive_repr(user_function):
    'Decorator to make a repr function return "..." for a recursive call'
    repr_running = set()

    def wrapper(self):
        key = id(self), get_ident()
        if key in repr_running:
            return '...'
        repr_running.add(key)
        try:
            result = user_function(self)
        finally:
            repr_running.discard(key)
        return result

    # Can't use functools.wraps() here because of bootstrap issues
    wrapper.__module__ = getattr(user_function, '__module__')
    wrapper.__doc__ = getattr(user_function, '__doc__')
    wrapper.__name__ = getattr(user_function, '__name__')
    return wrapper


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

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).
    # Each link is stored as a list of length three:  [PREV, NEXT, KEY].

    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 = [None, None, None]     # sentinel node
            PREV = 0
            NEXT = 1
            root[PREV] = root[NEXT] = root
            self.__map = {}
        self.update(*args, **kwds)

    def __setitem__(self, key, value, PREV=0, NEXT=1, dict_setitem=dict.__setitem__):
        '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:
            root = self.__root
            last = root[PREV]
            last[NEXT] = root[PREV] = self.__map[key] = [last, root, key]
        dict_setitem(self, key, value)

    def __delitem__(self, key, PREV=0, NEXT=1, dict_delitem=dict.__delitem__):
        '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 = link[PREV]
        link_next = link[NEXT]
        link_prev[NEXT] = link_next
        link_next[PREV] = link_prev

    def __iter__(self, NEXT=1, KEY=2):
        '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, PREV=0, KEY=2):
        '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,)

    def clear(self):
        'od.clear() -> None.  Remove all items from od.'
        try:
            for node in self.__map.itervalues():
                del node[:]
            self.__root[:] = [self.__root, self.__root, None]
            self.__map.clear()
        except AttributeError:
            pass
        dict.clear(self)

    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 viewkeys(self):
        "od.viewkeys() -> a set-like object providing a view on od's keys"
        return KeysView(self)

    def viewvalues(self):
        "od.viewvalues() -> an object providing a view on od's values"
        return ValuesView(self)

    def viewitems(self):
        "od.viewitems() -> a set-like object providing a view on od's items"
        return ItemsView(self)

    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

    @_recursive_repr
    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):
            'Create new instance of %(typename)s(%(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 a nicely formatted representation string'
            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 self as a plain tuple.  Used by copy and pickle.'
            return tuple(self) \n\n''' % locals()
    for i, name in enumerate(field_names):
        template += "        %s = _property(_itemgetter(%d), doc='Alias for field number %d')\n" % (name, i, 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 subtract(self, iterable=None, **kwds):
        '''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

        '''
        if iterable is not None:
            self_get = self.get
            if isinstance(iterable, Mapping):
                for elem, count in iterable.items():
                    self[elem] = self_get(elem, 0) - count
            else:
                for elem in iterable:
                    self[elem] = self_get(elem, 0) - 1
        if kwds:
            self.subtract(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())