""" python/black : true flake8 : passed """ from __future__ import annotations from collections.abc import Iterator class RedBlackTree: """ A Red-Black tree, which is a self-balancing BST (binary search tree). This tree has similar performance to AVL trees, but the balancing is less strict, so it will perform faster for writing/deleting nodes and slower for reading in the average case, though, because they're both balanced binary search trees, both will get the same asymptotic performance. To read more about them, https://en.wikipedia.org/wiki/Red–black_tree Unless otherwise specified, all asymptotic runtimes are specified in terms of the size of the tree. """ def __init__( self, label: int | None = None, color: int = 0, parent: RedBlackTree | None = None, left: RedBlackTree | None = None, right: RedBlackTree | None = None, ) -> None: """Initialize a new Red-Black Tree node with the given values: label: The value associated with this node color: 0 if black, 1 if red parent: The parent to this node left: This node's left child right: This node's right child """ self.label = label self.parent = parent self.left = left self.right = right self.color = color # Here are functions which are specific to red-black trees def rotate_left(self) -> RedBlackTree: """Rotate the subtree rooted at this node to the left and returns the new root to this subtree. Performing one rotation can be done in O(1). """ parent = self.parent right = self.right if right is None: return self self.right = right.left if self.right: self.right.parent = self self.parent = right right.left = self if parent is not None: if parent.left == self: parent.left = right else: parent.right = right right.parent = parent return right def rotate_right(self) -> RedBlackTree: """Rotate the subtree rooted at this node to the right and returns the new root to this subtree. Performing one rotation can be done in O(1). """ if self.left is None: return self parent = self.parent left = self.left self.left = left.right if self.left: self.left.parent = self self.parent = left left.right = self if parent is not None: if parent.right is self: parent.right = left else: parent.left = left left.parent = parent return left def insert(self, label: int) -> RedBlackTree: """Inserts label into the subtree rooted at self, performs any rotations necessary to maintain balance, and then returns the new root to this subtree (likely self). This is guaranteed to run in O(log(n)) time. """ if self.label is None: # Only possible with an empty tree self.label = label return self if self.label == label: return self elif self.label > label: if self.left: self.left.insert(label) else: self.left = RedBlackTree(label, 1, self) self.left._insert_repair() else: if self.right: self.right.insert(label) else: self.right = RedBlackTree(label, 1, self) self.right._insert_repair() return self.parent or self def _insert_repair(self) -> None: """Repair the coloring from inserting into a tree.""" if self.parent is None: # This node is the root, so it just needs to be black self.color = 0 elif color(self.parent) == 0: # If the parent is black, then it just needs to be red self.color = 1 else: uncle = self.parent.sibling if color(uncle) == 0: if self.is_left() and self.parent.is_right(): self.parent.rotate_right() if self.right: self.right._insert_repair() elif self.is_right() and self.parent.is_left(): self.parent.rotate_left() if self.left: self.left._insert_repair() elif self.is_left(): if self.grandparent: self.grandparent.rotate_right() self.parent.color = 0 if self.parent.right: self.parent.right.color = 1 else: if self.grandparent: self.grandparent.rotate_left() self.parent.color = 0 if self.parent.left: self.parent.left.color = 1 else: self.parent.color = 0 if uncle and self.grandparent: uncle.color = 0 self.grandparent.color = 1 self.grandparent._insert_repair() def remove(self, label: int) -> RedBlackTree: """Remove label from this tree.""" if self.label == label: if self.left and self.right: # It's easier to balance a node with at most one child, # so we replace this node with the greatest one less than # it and remove that. value = self.left.get_max() if value is not None: self.label = value self.left.remove(value) else: # This node has at most one non-None child, so we don't # need to replace child = self.left or self.right if self.color == 1: # This node is red, and its child is black # The only way this happens to a node with one child # is if both children are None leaves. # We can just remove this node and call it a day. if self.parent: if self.is_left(): self.parent.left = None else: self.parent.right = None else: # The node is black if child is None: # This node and its child are black if self.parent is None: # The tree is now empty return RedBlackTree(None) else: self._remove_repair() if self.is_left(): self.parent.left = None else: self.parent.right = None self.parent = None else: # This node is black and its child is red # Move the child node here and make it black self.label = child.label self.left = child.left self.right = child.right if self.left: self.left.parent = self if self.right: self.right.parent = self elif self.label is not None and self.label > label: if self.left: self.left.remove(label) else: if self.right: self.right.remove(label) return self.parent or self def _remove_repair(self) -> None: """Repair the coloring of the tree that may have been messed up.""" if ( self.parent is None or self.sibling is None or self.parent.sibling is None or self.grandparent is None ): return if color(self.sibling) == 1: self.sibling.color = 0 self.parent.color = 1 if self.is_left(): self.parent.rotate_left() else: self.parent.rotate_right() if ( color(self.parent) == 0 and color(self.sibling) == 0 and color(self.sibling.left) == 0 and color(self.sibling.right) == 0 ): self.sibling.color = 1 self.parent._remove_repair() return if ( color(self.parent) == 1 and color(self.sibling) == 0 and color(self.sibling.left) == 0 and color(self.sibling.right) == 0 ): self.sibling.color = 1 self.parent.color = 0 return if ( self.is_left() and color(self.sibling) == 0 and color(self.sibling.right) == 0 and color(self.sibling.left) == 1 ): self.sibling.rotate_right() self.sibling.color = 0 if self.sibling.right: self.sibling.right.color = 1 if ( self.is_right() and color(self.sibling) == 0 and color(self.sibling.right) == 1 and color(self.sibling.left) == 0 ): self.sibling.rotate_left() self.sibling.color = 0 if self.sibling.left: self.sibling.left.color = 1 if ( self.is_left() and color(self.sibling) == 0 and color(self.sibling.right) == 1 ): self.parent.rotate_left() self.grandparent.color = self.parent.color self.parent.color = 0 self.parent.sibling.color = 0 if ( self.is_right() and color(self.sibling) == 0 and color(self.sibling.left) == 1 ): self.parent.rotate_right() self.grandparent.color = self.parent.color self.parent.color = 0 self.parent.sibling.color = 0 def check_color_properties(self) -> bool: """Check the coloring of the tree, and return True iff the tree is colored in a way which matches these five properties: (wording stolen from wikipedia article) 1. Each node is either red or black. 2. The root node is black. 3. All leaves are black. 4. If a node is red, then both its children are black. 5. Every path from any node to all of its descendent NIL nodes has the same number of black nodes. This function runs in O(n) time, because properties 4 and 5 take that long to check. """ # I assume property 1 to hold because there is nothing that can # make the color be anything other than 0 or 1. # Property 2 if self.color: # The root was red print("Property 2") return False # Property 3 does not need to be checked, because None is assumed # to be black and is all the leaves. # Property 4 if not self.check_coloring(): print("Property 4") return False # Property 5 if self.black_height() is None: print("Property 5") return False # All properties were met return True def check_coloring(self) -> bool: """A helper function to recursively check Property 4 of a Red-Black Tree. See check_color_properties for more info. """ if self.color == 1: if color(self.left) == 1 or color(self.right) == 1: return False if self.left and not self.left.check_coloring(): return False if self.right and not self.right.check_coloring(): return False return True def black_height(self) -> int | None: """Returns the number of black nodes from this node to the leaves of the tree, or None if there isn't one such value (the tree is color incorrectly). """ if self is None or self.left is None or self.right is None: # If we're already at a leaf, there is no path return 1 left = RedBlackTree.black_height(self.left) right = RedBlackTree.black_height(self.right) if left is None or right is None: # There are issues with coloring below children nodes return None if left != right: # The two children have unequal depths return None # Return the black depth of children, plus one if this node is # black return left + (1 - self.color) # Here are functions which are general to all binary search trees def __contains__(self, label: int) -> bool: """Search through the tree for label, returning True iff it is found somewhere in the tree. Guaranteed to run in O(log(n)) time. """ return self.search(label) is not None def search(self, label: int) -> RedBlackTree | None: """Search through the tree for label, returning its node if it's found, and None otherwise. This method is guaranteed to run in O(log(n)) time. """ if self.label == label: return self elif self.label is not None and label > self.label: if self.right is None: return None else: return self.right.search(label) else: if self.left is None: return None else: return self.left.search(label) def floor(self, label: int) -> int | None: """Returns the largest element in this tree which is at most label. This method is guaranteed to run in O(log(n)) time.""" if self.label == label: return self.label elif self.label is not None and self.label > label: if self.left: return self.left.floor(label) else: return None else: if self.right: attempt = self.right.floor(label) if attempt is not None: return attempt return self.label def ceil(self, label: int) -> int | None: """Returns the smallest element in this tree which is at least label. This method is guaranteed to run in O(log(n)) time. """ if self.label == label: return self.label elif self.label is not None and self.label < label: if self.right: return self.right.ceil(label) else: return None else: if self.left: attempt = self.left.ceil(label) if attempt is not None: return attempt return self.label def get_max(self) -> int | None: """Returns the largest element in this tree. This method is guaranteed to run in O(log(n)) time. """ if self.right: # Go as far right as possible return self.right.get_max() else: return self.label def get_min(self) -> int | None: """Returns the smallest element in this tree. This method is guaranteed to run in O(log(n)) time. """ if self.left: # Go as far left as possible return self.left.get_min() else: return self.label @property def grandparent(self) -> RedBlackTree | None: """Get the current node's grandparent, or None if it doesn't exist.""" if self.parent is None: return None else: return self.parent.parent @property def sibling(self) -> RedBlackTree | None: """Get the current node's sibling, or None if it doesn't exist.""" if self.parent is None: return None elif self.parent.left is self: return self.parent.right else: return self.parent.left def is_left(self) -> bool: """Returns true iff this node is the left child of its parent.""" if self.parent is None: return False return self.parent.left is self.parent.left is self def is_right(self) -> bool: """Returns true iff this node is the right child of its parent.""" if self.parent is None: return False return self.parent.right is self def __bool__(self) -> bool: return True def __len__(self) -> int: """ Return the number of nodes in this tree. """ ln = 1 if self.left: ln += len(self.left) if self.right: ln += len(self.right) return ln def preorder_traverse(self) -> Iterator[int | None]: yield self.label if self.left: yield from self.left.preorder_traverse() if self.right: yield from self.right.preorder_traverse() def inorder_traverse(self) -> Iterator[int | None]: if self.left: yield from self.left.inorder_traverse() yield self.label if self.right: yield from self.right.inorder_traverse() def postorder_traverse(self) -> Iterator[int | None]: if self.left: yield from self.left.postorder_traverse() if self.right: yield from self.right.postorder_traverse() yield self.label def __repr__(self) -> str: from pprint import pformat if self.left is None and self.right is None: return f"'{self.label} {(self.color and 'red') or 'blk'}'" return pformat( { f"{self.label} {(self.color and 'red') or 'blk'}": ( self.left, self.right, ) }, indent=1, ) def __eq__(self, other: object) -> bool: """Test if two trees are equal.""" if not isinstance(other, RedBlackTree): return NotImplemented if self.label == other.label: return self.left == other.left and self.right == other.right else: return False def color(node: RedBlackTree | None) -> int: """Returns the color of a node, allowing for None leaves.""" if node is None: return 0 else: return node.color """ Code for testing the various functions of the red-black tree. """ def test_rotations() -> bool: """Test that the rotate_left and rotate_right functions work.""" # Make a tree to test on tree = RedBlackTree(0) tree.left = RedBlackTree(-10, parent=tree) tree.right = RedBlackTree(10, parent=tree) tree.left.left = RedBlackTree(-20, parent=tree.left) tree.left.right = RedBlackTree(-5, parent=tree.left) tree.right.left = RedBlackTree(5, parent=tree.right) tree.right.right = RedBlackTree(20, parent=tree.right) # Make the right rotation left_rot = RedBlackTree(10) left_rot.left = RedBlackTree(0, parent=left_rot) left_rot.left.left = RedBlackTree(-10, parent=left_rot.left) left_rot.left.right = RedBlackTree(5, parent=left_rot.left) left_rot.left.left.left = RedBlackTree(-20, parent=left_rot.left.left) left_rot.left.left.right = RedBlackTree(-5, parent=left_rot.left.left) left_rot.right = RedBlackTree(20, parent=left_rot) tree = tree.rotate_left() if tree != left_rot: return False tree = tree.rotate_right() tree = tree.rotate_right() # Make the left rotation right_rot = RedBlackTree(-10) right_rot.left = RedBlackTree(-20, parent=right_rot) right_rot.right = RedBlackTree(0, parent=right_rot) right_rot.right.left = RedBlackTree(-5, parent=right_rot.right) right_rot.right.right = RedBlackTree(10, parent=right_rot.right) right_rot.right.right.left = RedBlackTree(5, parent=right_rot.right.right) right_rot.right.right.right = RedBlackTree(20, parent=right_rot.right.right) if tree != right_rot: return False return True def test_insertion_speed() -> bool: """Test that the tree balances inserts to O(log(n)) by doing a lot of them. """ tree = RedBlackTree(-1) for i in range(300000): tree = tree.insert(i) return True def test_insert() -> bool: """Test the insert() method of the tree correctly balances, colors, and inserts. """ tree = RedBlackTree(0) tree.insert(8) tree.insert(-8) tree.insert(4) tree.insert(12) tree.insert(10) tree.insert(11) ans = RedBlackTree(0, 0) ans.left = RedBlackTree(-8, 0, ans) ans.right = RedBlackTree(8, 1, ans) ans.right.left = RedBlackTree(4, 0, ans.right) ans.right.right = RedBlackTree(11, 0, ans.right) ans.right.right.left = RedBlackTree(10, 1, ans.right.right) ans.right.right.right = RedBlackTree(12, 1, ans.right.right) return tree == ans def test_insert_and_search() -> bool: """Tests searching through the tree for values.""" tree = RedBlackTree(0) tree.insert(8) tree.insert(-8) tree.insert(4) tree.insert(12) tree.insert(10) tree.insert(11) if 5 in tree or -6 in tree or -10 in tree or 13 in tree: # Found something not in there return False if not (11 in tree and 12 in tree and -8 in tree and 0 in tree): # Didn't find something in there return False return True def test_insert_delete() -> bool: """Test the insert() and delete() method of the tree, verifying the insertion and removal of elements, and the balancing of the tree. """ tree = RedBlackTree(0) tree = tree.insert(-12) tree = tree.insert(8) tree = tree.insert(-8) tree = tree.insert(15) tree = tree.insert(4) tree = tree.insert(12) tree = tree.insert(10) tree = tree.insert(9) tree = tree.insert(11) tree = tree.remove(15) tree = tree.remove(-12) tree = tree.remove(9) if not tree.check_color_properties(): return False if list(tree.inorder_traverse()) != [-8, 0, 4, 8, 10, 11, 12]: return False return True def test_floor_ceil() -> bool: """Tests the floor and ceiling functions in the tree.""" tree = RedBlackTree(0) tree.insert(-16) tree.insert(16) tree.insert(8) tree.insert(24) tree.insert(20) tree.insert(22) tuples = [(-20, None, -16), (-10, -16, 0), (8, 8, 8), (50, 24, None)] for val, floor, ceil in tuples: if tree.floor(val) != floor or tree.ceil(val) != ceil: return False return True def test_min_max() -> bool: """Tests the min and max functions in the tree.""" tree = RedBlackTree(0) tree.insert(-16) tree.insert(16) tree.insert(8) tree.insert(24) tree.insert(20) tree.insert(22) if tree.get_max() != 22 or tree.get_min() != -16: return False return True def test_tree_traversal() -> bool: """Tests the three different tree traversal functions.""" tree = RedBlackTree(0) tree = tree.insert(-16) tree.insert(16) tree.insert(8) tree.insert(24) tree.insert(20) tree.insert(22) if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]: return False if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]: return False if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]: return False return True def test_tree_chaining() -> bool: """Tests the three different tree chaining functions.""" tree = RedBlackTree(0) tree = tree.insert(-16).insert(16).insert(8).insert(24).insert(20).insert(22) if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]: return False if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]: return False if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]: return False return True def print_results(msg: str, passes: bool) -> None: print(str(msg), "works!" if passes else "doesn't work :(") def pytests() -> None: assert test_rotations() assert test_insert() assert test_insert_and_search() assert test_insert_delete() assert test_floor_ceil() assert test_tree_traversal() assert test_tree_chaining() def main() -> None: """ >>> pytests() """ print_results("Rotating right and left", test_rotations()) print_results("Inserting", test_insert()) print_results("Searching", test_insert_and_search()) print_results("Deleting", test_insert_delete()) print_results("Floor and ceil", test_floor_ceil()) print_results("Tree traversal", test_tree_traversal()) print_results("Tree traversal", test_tree_chaining()) print("Testing tree balancing...") print("This should only be a few seconds.") test_insertion_speed() print("Done!") if __name__ == "__main__": main()