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This module implements sets using dictionaries whose values are
ignored. The usual operations (union, intersection, deletion, etc.)
are provided as both methods and operators.
Important: sets are not sequences! While they support 'x in s',
'len(s)', and 'for x in s', none of those operations are unique for
sequences; for example, mappings support all three as well. The
characteristic operation for sequences is subscripting with small
integers: s[i], for i in range(len(s)). Sets don't support
subscripting at all. Also, sequences allow multiple occurrences and
their elements have a definite order; sets on the other hand don't
record multiple occurrences and don't remember the order of element
insertion (which is why they don't support s[i]).
The following classes are provided:
BaseSet -- All the operations common to both mutable and immutable
sets. This is an abstract class, not meant to be directly
instantiated.
Set -- Mutable sets, subclass of BaseSet; not hashable.
ImmutableSet -- Immutable sets, subclass of BaseSet; hashable.
An iterable argument is mandatory to create an ImmutableSet.
_TemporarilyImmutableSet -- A wrapper around a Set, hashable,
giving the same hash value as the immutable set equivalent
would have. Do not use this class directly.
Only hashable objects can be added to a Set. In particular, you cannot
really add a Set as an element to another Set; if you try, what is
actually added is an ImmutableSet built from it (it compares equal to
the one you tried adding).
When you ask if `x in y' where x is a Set and y is a Set or
ImmutableSet, x is wrapped into a _TemporarilyImmutableSet z, and
what's tested is actually `z in y'.
"""
# Code history:
#
# - Greg V. Wilson wrote the first version, using a different approach
# to the mutable/immutable problem, and inheriting from dict.
#
# - Alex Martelli modified Greg's version to implement the current
# Set/ImmutableSet approach, and make the data an attribute.
#
# - Guido van Rossum rewrote much of the code, made some API changes,
# and cleaned up the docstrings.
#
# - Raymond Hettinger added a number of speedups and other
# improvements.
from itertools import ifilter, ifilterfalse
__all__ = ['BaseSet', 'Set', 'ImmutableSet']
import warnings
warnings.warn("the sets module is deprecated", DeprecationWarning,
stacklevel=2)
class BaseSet(object):
"""Common base class for mutable and immutable sets."""
__slots__ = ['_data']
# Constructor
def __init__(self):
"""This is an abstract class."""
# Don't call this from a concrete subclass!
if self.__class__ is BaseSet:
raise TypeError, ("BaseSet is an abstract class. "
"Use Set or ImmutableSet.")
# Standard protocols: __len__, __repr__, __str__, __iter__
def __len__(self):
"""Return the number of elements of a set."""
return len(self._data)
def __repr__(self):
"""Return string representation of a set.
This looks like 'Set([<list of elements>])'.
"""
return self._repr()
# __str__ is the same as __repr__
__str__ = __repr__
def _repr(self, sorted=False):
elements = self._data.keys()
if sorted:
elements.sort()
return '%s(%r)' % (self.__class__.__name__, elements)
def __iter__(self):
"""Return an iterator over the elements or a set.
This is the keys iterator for the underlying dict.
"""
return self._data.iterkeys()
# Three-way comparison is not supported. However, because __eq__ is
# tried before __cmp__, if Set x == Set y, x.__eq__(y) returns True and
# then cmp(x, y) returns 0 (Python doesn't actually call __cmp__ in this
# case).
def __cmp__(self, other):
raise TypeError, "can't compare sets using cmp()"
# Equality comparisons using the underlying dicts. Mixed-type comparisons
# are allowed here, where Set == z for non-Set z always returns False,
# and Set != z always True. This allows expressions like "x in y" to
# give the expected result when y is a sequence of mixed types, not
# raising a pointless TypeError just because y contains a Set, or x is
# a Set and y contain's a non-set ("in" invokes only __eq__).
# Subtle: it would be nicer if __eq__ and __ne__ could return
# NotImplemented instead of True or False. Then the other comparand
# would get a chance to determine the result, and if the other comparand
# also returned NotImplemented then it would fall back to object address
# comparison (which would always return False for __eq__ and always
# True for __ne__). However, that doesn't work, because this type
# *also* implements __cmp__: if, e.g., __eq__ returns NotImplemented,
# Python tries __cmp__ next, and the __cmp__ here then raises TypeError.
def __eq__(self, other):
if isinstance(other, BaseSet):
return self._data == other._data
else:
return False
def __ne__(self, other):
if isinstance(other, BaseSet):
return self._data != other._data
else:
return True
# Copying operations
def copy(self):
"""Return a shallow copy of a set."""
result = self.__class__()
result._data.update(self._data)
return result
__copy__ = copy # For the copy module
def __deepcopy__(self, memo):
"""Return a deep copy of a set; used by copy module."""
# This pre-creates the result and inserts it in the memo
# early, in case the deep copy recurses into another reference
# to this same set. A set can't be an element of itself, but
# it can certainly contain an object that has a reference to
# itself.
from copy import deepcopy
result = self.__class__()
memo[id(self)] = result
data = result._data
value = True
for elt in self:
data[deepcopy(elt, memo)] = value
return result
# Standard set operations: union, intersection, both differences.
# Each has an operator version (e.g. __or__, invoked with |) and a
# method version (e.g. union).
# Subtle: Each pair requires distinct code so that the outcome is
# correct when the type of other isn't suitable. For example, if
# we did "union = __or__" instead, then Set().union(3) would return
# NotImplemented instead of raising TypeError (albeit that *why* it
# raises TypeError as-is is also a bit subtle).
def __or__(self, other):
"""Return the union of two sets as a new set.
(I.e. all elements that are in either set.)
"""
if not isinstance(other, BaseSet):
return NotImplemented
return self.union(other)
def union(self, other):
"""Return the union of two sets as a new set.
(I.e. all elements that are in either set.)
"""
result = self.__class__(self)
result._update(other)
return result
def __and__(self, other):
"""Return the intersection of two sets as a new set.
(I.e. all elements that are in both sets.)
"""
if not isinstance(other, BaseSet):
return NotImplemented
return self.intersection(other)
def intersection(self, other):
"""Return the intersection of two sets as a new set.
(I.e. all elements that are in both sets.)
"""
if not isinstance(other, BaseSet):
other = Set(other)
if len(self) <= len(other):
little, big = self, other
else:
little, big = other, self
common = ifilter(big._data.__contains__, little)
return self.__class__(common)
def __xor__(self, other):
"""Return the symmetric difference of two sets as a new set.
(I.e. all elements that are in exactly one of the sets.)
"""
if not isinstance(other, BaseSet):
return NotImplemented
return self.symmetric_difference(other)
def symmetric_difference(self, other):
"""Return the symmetric difference of two sets as a new set.
(I.e. all elements that are in exactly one of the sets.)
"""
result = self.__class__()
data = result._data
value = True
selfdata = self._data
try:
otherdata = other._data
except AttributeError:
otherdata = Set(other)._data
for elt in ifilterfalse(otherdata.__contains__, selfdata):
data[elt] = value
for elt in ifilterfalse(selfdata.__contains__, otherdata):
data[elt] = value
return result
def __sub__(self, other):
"""Return the difference of two sets as a new Set.
(I.e. all elements that are in this set and not in the other.)
"""
if not isinstance(other, BaseSet):
return NotImplemented
return self.difference(other)
def difference(self, other):
"""Return the difference of two sets as a new Set.
(I.e. all elements that are in this set and not in the other.)
"""
result = self.__class__()
data = result._data
try:
otherdata = other._data
except AttributeError:
otherdata = Set(other)._data
value = True
for elt in ifilterfalse(otherdata.__contains__, self):
data[elt] = value
return result
# Membership test
def __contains__(self, element):
"""Report whether an element is a member of a set.
(Called in response to the expression `element in self'.)
"""
try:
return element in self._data
except TypeError:
transform = getattr(element, "__as_temporarily_immutable__", None)
if transform is None:
raise # re-raise the TypeError exception we caught
return transform() in self._data
# Subset and superset test
def issubset(self, other):
"""Report whether another set contains this set."""
self._binary_sanity_check(other)
if len(self) > len(other): # Fast check for obvious cases
return False
for elt in ifilterfalse(other._data.__contains__, self):
return False
return True
def issuperset(self, other):
"""Report whether this set contains another set."""
self._binary_sanity_check(other)
if len(self) < len(other): # Fast check for obvious cases
return False
for elt in ifilterfalse(self._data.__contains__, other):
return False
return True
# Inequality comparisons using the is-subset relation.
__le__ = issubset
__ge__ = issuperset
def __lt__(self, other):
self._binary_sanity_check(other)
return len(self) < len(other) and self.issubset(other)
def __gt__(self, other):
self._binary_sanity_check(other)
return len(self) > len(other) and self.issuperset(other)
# We inherit object.__hash__, so we must deny this explicitly
__hash__ = None
# Assorted helpers
def _binary_sanity_check(self, other):
# Check that the other argument to a binary operation is also
# a set, raising a TypeError otherwise.
if not isinstance(other, BaseSet):
raise TypeError, "Binary operation only permitted between sets"
def _compute_hash(self):
# Calculate hash code for a set by xor'ing the hash codes of
# the elements. This ensures that the hash code does not depend
# on the order in which elements are added to the set. This is
# not called __hash__ because a BaseSet should not be hashable;
# only an ImmutableSet is hashable.
result = 0
for elt in self:
result ^= hash(elt)
return result
def _update(self, iterable):
# The main loop for update() and the subclass __init__() methods.
data = self._data
# Use the fast update() method when a dictionary is available.
if isinstance(iterable, BaseSet):
data.update(iterable._data)
return
value = True
if type(iterable) in (list, tuple, xrange):
# Optimized: we know that __iter__() and next() can't
# raise TypeError, so we can move 'try:' out of the loop.
it = iter(iterable)
while True:
try:
for element in it:
data[element] = value
return
except TypeError:
transform = getattr(element, "__as_immutable__", None)
if transform is None:
raise # re-raise the TypeError exception we caught
data[transform()] = value
else:
# Safe: only catch TypeError where intended
for element in iterable:
try:
data[element] = value
except TypeError:
transform = getattr(element, "__as_immutable__", None)
if transform is None:
raise # re-raise the TypeError exception we caught
data[transform()] = value
class ImmutableSet(BaseSet):
"""Immutable set class."""
__slots__ = ['_hashcode']
# BaseSet + hashing
def __init__(self, iterable=None):
"""Construct an immutable set from an optional iterable."""
self._hashcode = None
self._data = {}
if iterable is not None:
self._update(iterable)
def __hash__(self):
if self._hashcode is None:
self._hashcode = self._compute_hash()
return self._hashcode
def __getstate__(self):
return self._data, self._hashcode
def __setstate__(self, state):
self._data, self._hashcode = state
class Set(BaseSet):
""" Mutable set class."""
__slots__ = []
# BaseSet + operations requiring mutability; no hashing
def __init__(self, iterable=None):
"""Construct a set from an optional iterable."""
self._data = {}
if iterable is not None:
self._update(iterable)
def __getstate__(self):
# getstate's results are ignored if it is not
return self._data,
def __setstate__(self, data):
self._data, = data
# In-place union, intersection, differences.
# Subtle: The xyz_update() functions deliberately return None,
# as do all mutating operations on built-in container types.
# The __xyz__ spellings have to return self, though.
def __ior__(self, other):
"""Update a set with the union of itself and another."""
self._binary_sanity_check(other)
self._data.update(other._data)
return self
def union_update(self, other):
"""Update a set with the union of itself and another."""
self._update(other)
def __iand__(self, other):
"""Update a set with the intersection of itself and another."""
self._binary_sanity_check(other)
self._data = (self & other)._data
return self
def intersection_update(self, other):
"""Update a set with the intersection of itself and another."""
if isinstance(other, BaseSet):
self &= other
else:
self._data = (self.intersection(other))._data
def __ixor__(self, other):
"""Update a set with the symmetric difference of itself and another."""
self._binary_sanity_check(other)
self.symmetric_difference_update(other)
return self
def symmetric_difference_update(self, other):
"""Update a set with the symmetric difference of itself and another."""
data = self._data
value = True
if not isinstance(other, BaseSet):
other = Set(other)
if self is other:
self.clear()
for elt in other:
if elt in data:
del data[elt]
else:
data[elt] = value
def __isub__(self, other):
"""Remove all elements of another set from this set."""
self._binary_sanity_check(other)
self.difference_update(other)
return self
def difference_update(self, other):
"""Remove all elements of another set from this set."""
data = self._data
if not isinstance(other, BaseSet):
other = Set(other)
if self is other:
self.clear()
for elt in ifilter(data.__contains__, other):
del data[elt]
# Python dict-like mass mutations: update, clear
def update(self, iterable):
"""Add all values from an iterable (such as a list or file)."""
self._update(iterable)
def clear(self):
"""Remove all elements from this set."""
self._data.clear()
# Single-element mutations: add, remove, discard
def add(self, element):
"""Add an element to a set.
This has no effect if the element is already present.
"""
try:
self._data[element] = True
except TypeError:
transform = getattr(element, "__as_immutable__", None)
if transform is None:
raise # re-raise the TypeError exception we caught
self._data[transform()] = True
def remove(self, element):
"""Remove an element from a set; it must be a member.
If the element is not a member, raise a KeyError.
"""
try:
del self._data[element]
except TypeError:
transform = getattr(element, "__as_temporarily_immutable__", None)
if transform is None:
raise # re-raise the TypeError exception we caught
del self._data[transform()]
def discard(self, element):
"""Remove an element from a set if it is a member.
If the element is not a member, do nothing.
"""
try:
self.remove(element)
except KeyError:
pass
def pop(self):
"""Remove and return an arbitrary set element."""
return self._data.popitem()[0]
def __as_immutable__(self):
# Return a copy of self as an immutable set
return ImmutableSet(self)
def __as_temporarily_immutable__(self):
# Return self wrapped in a temporarily immutable set
return _TemporarilyImmutableSet(self)
class _TemporarilyImmutableSet(BaseSet):
# Wrap a mutable set as if it was temporarily immutable.
# This only supplies hashing and equality comparisons.
def __init__(self, set):
self._set = set
self._data = set._data # Needed by ImmutableSet.__eq__()
def __hash__(self):
return self._set._compute_hash()
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