563 lines
21 KiB
Python
563 lines
21 KiB
Python
__all__ = ['Counter', 'deque', 'defaultdict', 'namedtuple', 'OrderedDict']
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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, eq as _eq
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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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from weakref import proxy as _proxy
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from itertools import repeat as _repeat, chain as _chain, starmap as _starmap, \
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ifilter as _ifilter, imap as _imap
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################################################################################
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### OrderedDict
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################################################################################
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class _Link(object):
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__slots__ = 'prev', 'next', 'key', '__weakref__'
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class OrderedDict(dict, MutableMapping):
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'Dictionary that remembers insertion order'
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# An inherited dict maps keys to values.
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# The inherited dict provides __getitem__, __len__, __contains__, and get.
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# The remaining methods are order-aware.
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# Big-O running times for all methods are the same as for regular dictionaries.
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# The internal self.__map dictionary maps keys to links in a doubly linked list.
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# The circular doubly linked list starts and ends with a sentinel element.
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# The sentinel element never gets deleted (this simplifies the algorithm).
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# The prev/next links are weakref proxies (to prevent circular references).
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# Individual links are kept alive by the hard reference in self.__map.
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# Those hard references disappear when a key is deleted from an OrderedDict.
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def __init__(self, *args, **kwds):
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'''Initialize an ordered dictionary. Signature is the same as for
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regular dictionaries, but keyword arguments are not recommended
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because their insertion order is arbitrary.
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'''
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if len(args) > 1:
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raise TypeError('expected at most 1 arguments, got %d' % len(args))
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try:
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self.__root
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except AttributeError:
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self.__root = root = _Link() # sentinel node for the doubly linked list
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root.prev = root.next = root
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self.__map = {}
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self.update(*args, **kwds)
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def clear(self):
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'od.clear() -> None. Remove all items from od.'
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root = self.__root
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root.prev = root.next = root
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self.__map.clear()
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dict.clear(self)
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def __setitem__(self, key, value):
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'od.__setitem__(i, y) <==> od[i]=y'
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# Setting a new item creates a new link which goes at the end of the linked
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# list, and the inherited dictionary is updated with the new key/value pair.
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if key not in self:
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self.__map[key] = link = _Link()
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root = self.__root
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last = root.prev
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link.prev, link.next, link.key = last, root, key
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last.next = root.prev = _proxy(link)
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dict.__setitem__(self, key, value)
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def __delitem__(self, key):
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'od.__delitem__(y) <==> del od[y]'
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# Deleting an existing item uses self.__map to find the link which is
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# then removed by updating the links in the predecessor and successor nodes.
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dict.__delitem__(self, key)
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link = self.__map.pop(key)
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link.prev.next = link.next
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link.next.prev = link.prev
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def __iter__(self):
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'od.__iter__() <==> iter(od)'
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# Traverse the linked list in order.
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root = self.__root
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curr = root.next
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while curr is not root:
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yield curr.key
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curr = curr.next
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def __reversed__(self):
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'od.__reversed__() <==> reversed(od)'
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# Traverse the linked list in reverse order.
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root = self.__root
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curr = root.prev
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while curr is not root:
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yield curr.key
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curr = curr.prev
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def __reduce__(self):
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'Return state information for pickling'
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items = [[k, self[k]] for k in self]
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tmp = self.__map, self.__root
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del self.__map, self.__root
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inst_dict = vars(self).copy()
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self.__map, self.__root = tmp
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if inst_dict:
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return (self.__class__, (items,), inst_dict)
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return self.__class__, (items,)
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setdefault = MutableMapping.setdefault
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update = MutableMapping.update
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pop = MutableMapping.pop
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keys = MutableMapping.keys
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values = MutableMapping.values
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items = MutableMapping.items
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iterkeys = MutableMapping.iterkeys
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itervalues = MutableMapping.itervalues
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iteritems = MutableMapping.iteritems
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__ne__ = MutableMapping.__ne__
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def popitem(self, last=True):
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'''od.popitem() -> (k, v), return and remove a (key, value) pair.
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Pairs are returned in LIFO order if last is true or FIFO order if false.
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'''
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if not self:
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raise KeyError('dictionary is empty')
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key = next(reversed(self) if last else iter(self))
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value = self.pop(key)
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return key, value
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def __repr__(self):
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'od.__repr__() <==> repr(od)'
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if not self:
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return '%s()' % (self.__class__.__name__,)
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return '%s(%r)' % (self.__class__.__name__, self.items())
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def copy(self):
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'od.copy() -> a shallow copy of od'
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return self.__class__(self)
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@classmethod
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def fromkeys(cls, iterable, value=None):
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'''OD.fromkeys(S[, v]) -> New ordered dictionary with keys from S
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and values equal to v (which defaults to None).
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'''
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d = cls()
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for key in iterable:
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d[key] = value
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return d
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def __eq__(self, other):
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'''od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive
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while comparison to a regular mapping is order-insensitive.
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'''
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if isinstance(other, OrderedDict):
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return len(self)==len(other) and \
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all(_imap(_eq, self.iteritems(), other.iteritems()))
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return dict.__eq__(self, other)
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################################################################################
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### namedtuple
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################################################################################
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def namedtuple(typename, field_names, verbose=False, rename=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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if rename:
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names = list(field_names)
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seen = set()
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for i, name in enumerate(names):
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if (not all(c.isalnum() or c=='_' for c in name) or _iskeyword(name)
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or not name or name[0].isdigit() or name.startswith('_')
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or name in seen):
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names[i] = '_%d' % i
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seen.add(name)
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field_names = tuple(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('_') and not rename:
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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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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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'Create new instance of %(typename)s(%(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 a nicely formatted representation string'
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return '%(typename)s(%(reprtxt)s)' %% self \n
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def _asdict(self):
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'Return a new OrderedDict which maps field names to their values'
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return OrderedDict(zip(self._fields, self)) \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 self as a plain tuple. Used by copy and pickle.'
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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), doc='Alias for field number %d')\n" % (name, i, 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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OrderedDict=OrderedDict, _property=property, _tuple=tuple)
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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) or sys._getframe is not
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# defined for arguments greater than 0 (IronPython).
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try:
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result.__module__ = _sys._getframe(1).f_globals.get('__name__', '__main__')
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except (AttributeError, ValueError):
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pass
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return result
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########################################################################
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### Counter
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########################################################################
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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, **kwds):
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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 another mapping
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of elements to their counts.
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>>> c = Counter() # a new, empty counter
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>>> c = Counter('gallahad') # a new counter from an iterable
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>>> c = Counter({'a': 4, 'b': 2}) # a new counter from a mapping
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>>> c = Counter(a=4, b=2) # a new counter from keyword args
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'''
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self.update(iterable, **kwds)
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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 for prime factors of 1836: 2**2 * 3**3 * 17**1
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>>> prime_factors = Counter({2: 2, 3: 3, 17: 1})
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>>> product = 1
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>>> for factor in prime_factors.elements(): # loop over factors
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... product *= factor # and multiply them
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>>> product
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1836
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Note, if an element's count has been set to zero or is a negative
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number, 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 _chain.from_iterable(_starmap(_repeat, 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, iterable=None, **kwds):
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'''Like dict.update() but add counts instead of replacing them.
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Source can be an iterable, a dictionary, or another Counter instance.
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>>> c = Counter('which')
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>>> c.update('witch') # add elements from another iterable
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>>> d = Counter('watch')
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>>> c.update(d) # add elements from another counter
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>>> c['h'] # four 'h' in which, witch, and watch
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4
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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 implement straight-addition. Both the inputs
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# and outputs are allowed to contain zero and negative counts.
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if iterable is not None:
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if isinstance(iterable, Mapping):
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if self:
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self_get = self.get
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for elem, count in iterable.iteritems():
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self[elem] = self_get(elem, 0) + count
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else:
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dict.update(self, iterable) # fast path when counter is empty
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else:
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self_get = self.get
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for elem in iterable:
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self[elem] = self_get(elem, 0) + 1
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if kwds:
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self.update(kwds)
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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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return Counter(self)
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def __delitem__(self, elem):
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'Like dict.__delitem__() but does not raise KeyError for missing values.'
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if elem in self:
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dict.__delitem__(self, elem)
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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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items = ', '.join(map('%r: %r'.__mod__, self.most_common()))
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return '%s({%s})' % (self.__class__.__name__, items)
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# Multiset-style mathematical operations discussed in:
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# Knuth TAOCP Volume II section 4.6.3 exercise 19
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# and at http://en.wikipedia.org/wiki/Multiset
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#
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# Outputs guaranteed to only include positive counts.
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#
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# To strip negative and zero counts, add-in an empty counter:
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# c += Counter()
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def __add__(self, other):
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'''Add counts from two counters.
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>>> Counter('abbb') + Counter('bcc')
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Counter({'b': 4, 'c': 2, 'a': 1})
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'''
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if not isinstance(other, Counter):
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return NotImplemented
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result = Counter()
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for elem in set(self) | set(other):
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newcount = self[elem] + other[elem]
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if newcount > 0:
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result[elem] = newcount
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return result
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def __sub__(self, other):
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''' Subtract count, but keep only results with positive counts.
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>>> Counter('abbbc') - Counter('bccd')
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Counter({'b': 2, 'a': 1})
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'''
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if not isinstance(other, Counter):
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return NotImplemented
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result = Counter()
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for elem in set(self) | set(other):
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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())
|