"""Classes to represent arbitrary sets (including sets of sets). 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 -- Not a subclass of BaseSet: just 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. __all__ = ['BaseSet', 'Set', 'ImmutableSet'] 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 NotImplementedError, ("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([])'. """ 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() # Comparisons. Ordering is determined by the ordering of the # underlying dicts (which is consistent though unpredictable). def __lt__(self, other): self._binary_sanity_check(other) return self._data < other._data def __le__(self, other): self._binary_sanity_check(other) return self._data <= other._data def __eq__(self, other): self._binary_sanity_check(other) return self._data == other._data def __ne__(self, other): self._binary_sanity_check(other) return self._data != other._data def __gt__(self, other): self._binary_sanity_check(other) return self._data > other._data def __ge__(self, other): self._binary_sanity_check(other) return self._data >= other._data # Copying operations def copy(self): """Return a shallow copy of a set.""" return self.__class__(self) __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 def union(self, other): """Return the union of two sets as a new set. (I.e. all elements that are in either set.) """ self._binary_sanity_check(other) result = self.__class__(self._data) result._data.update(other._data) return result __or__ = union def intersection(self, other): """Return the intersection of two sets as a new set. (I.e. all elements that are in both sets.) """ self._binary_sanity_check(other) if len(self) <= len(other): little, big = self, other else: little, big = other, self result = self.__class__([]) data = result._data value = True for elt in little: if elt in big: data[elt] = value return result __and__ = intersection 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.) """ self._binary_sanity_check(other) result = self.__class__([]) data = result._data value = True for elt in self: if elt not in other: data[elt] = value for elt in other: if elt not in self: data[elt] = value return result __xor__ = symmetric_difference 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.) """ self._binary_sanity_check(other) result = self.__class__([]) data = result._data value = True for elt in self: if elt not in other: data[elt] = value return result __sub__ = difference # 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_temporary_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 self: if elt not in other: 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 other: if elt not in self: return False return True # 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 algorithm ensures that the hash code # does not depend on the order in which elements are added to # the code. 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 class ImmutableSet(BaseSet): """Immutable set class.""" __slots__ = ['_hashcode'] # BaseSet + hashing def __init__(self, seq): """Construct an immutable set from a sequence.""" self._hashcode = None self._data = data = {} # I don't know a faster way to do this in pure Python. # Custom code written in C only did it 65% faster, # preallocating the dict to len(seq); without # preallocation it was only 25% faster. So the speed of # this Python code is respectable. Just copying True into # a local variable is responsible for a 7-8% speedup. value = True # XXX Should this perhaps look for _as_immutable? # XXX If so, should use self.update(seq). for key in seq: data[key] = value def __hash__(self): if self._hashcode is None: self._hashcode = self._compute_hash() return self._hashcode class Set(BaseSet): """ Mutable set class.""" __slots__ = [] # BaseSet + operations requiring mutability; no hashing def __init__(self, seq=None): """Construct an immutable set from a sequence.""" self._data = data = {} if seq is not None: value = True # XXX Should this perhaps look for _as_immutable? # XXX If so, should use self.update(seq). for key in seq: data[key] = value # In-place union, intersection, differences def union_update(self, other): """Update a set with the union of itself and another.""" self._binary_sanity_check(other) self._data.update(other._data) return self __ior__ = union_update def intersection_update(self, other): """Update a set with the intersection of itself and another.""" self._binary_sanity_check(other) for elt in self._data.keys(): if elt not in other: del self._data[elt] return self __iand__ = intersection_update def symmetric_difference_update(self, other): """Update a set with the symmetric difference of itself and another.""" self._binary_sanity_check(other) data = self._data value = True for elt in other: if elt in data: del data[elt] else: data[elt] = value return self __ixor__ = symmetric_difference_update def difference_update(self, other): """Remove all elements of another set from this set.""" self._binary_sanity_check(other) data = self._data for elt in other: if elt in data: del data[elt] return self __isub__ = difference_update # Python dict-like mass mutations: update, clear def update(self, iterable): """Add all values from an iterable (such as a list or file).""" data = self._data value = True for element in iterable: try: data[element] = value except TypeError: transform = getattr(element, "_as_temporary_immutable", None) if transform is None: raise # re-raise the TypeError exception we caught data[transform()] = value 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_temporary_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_temporary_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: del self._data[element] except KeyError: pass def pop(self): """Remove and return a randomly-chosen 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(object): # Wrap a mutable set as if it was temporarily immutable. # This only supplies hashing and equality comparisons. _hashcode = None def __init__(self, set): self._set = set def __hash__(self): if self._hashcode is None: self._hashcode = self._set._compute_hash() return self._hashcode def __eq__(self, other): return self._set == other def __ne__(self, other): return self._set != other # Rudimentary self-tests def _test(): # Empty set red = Set() assert `red` == "Set([])", "Empty set: %s" % `red` # Unit set green = Set((0,)) assert `green` == "Set([0])", "Unit set: %s" % `green` # 3-element set blue = Set([0, 1, 2]) assert blue._repr(True) == "Set([0, 1, 2])", "3-element set: %s" % `blue` # 2-element set with other values black = Set([0, 5]) assert black._repr(True) == "Set([0, 5])", "2-element set: %s" % `black` # All elements from all sets white = Set([0, 1, 2, 5]) assert white._repr(True) == "Set([0, 1, 2, 5])", "4-element set: %s" % `white` # Add element to empty set red.add(9) assert `red` == "Set([9])", "Add to empty set: %s" % `red` # Remove element from unit set red.remove(9) assert `red` == "Set([])", "Remove from unit set: %s" % `red` # Remove element from empty set try: red.remove(0) assert 0, "Remove element from empty set: %s" % `red` except LookupError: pass # Length assert len(red) == 0, "Length of empty set" assert len(green) == 1, "Length of unit set" assert len(blue) == 3, "Length of 3-element set" # Compare assert green == Set([0]), "Equality failed" assert green != Set([1]), "Inequality failed" # Union assert blue | red == blue, "Union non-empty with empty" assert red | blue == blue, "Union empty with non-empty" assert green | blue == blue, "Union non-empty with non-empty" assert blue | black == white, "Enclosing union" # Intersection assert blue & red == red, "Intersect non-empty with empty" assert red & blue == red, "Intersect empty with non-empty" assert green & blue == green, "Intersect non-empty with non-empty" assert blue & black == green, "Enclosing intersection" # Symmetric difference assert red ^ green == green, "Empty symdiff non-empty" assert green ^ blue == Set([1, 2]), "Non-empty symdiff" assert white ^ white == red, "Self symdiff" # Difference assert red - green == red, "Empty - non-empty" assert blue - red == blue, "Non-empty - empty" assert white - black == Set([1, 2]), "Non-empty - non-empty" # In-place union orange = Set([]) orange |= Set([1]) assert orange == Set([1]), "In-place union" # In-place intersection orange = Set([1, 2]) orange &= Set([2]) assert orange == Set([2]), "In-place intersection" # In-place difference orange = Set([1, 2, 3]) orange -= Set([2, 4]) assert orange == Set([1, 3]), "In-place difference" # In-place symmetric difference orange = Set([1, 2, 3]) orange ^= Set([3, 4]) assert orange == Set([1, 2, 4]), "In-place symmetric difference" print "All tests passed" if __name__ == "__main__": _test()