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357 lines
11 KiB
Python
357 lines
11 KiB
Python
r"""
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A binary search Tree
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Example
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8
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/ \
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3 10
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/ \ \
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1 6 14
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/ \ /
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4 7 13
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>>> t = BinarySearchTree().insert(8, 3, 6, 1, 10, 14, 13, 4, 7)
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>>> print(" ".join(repr(i.value) for i in t.traversal_tree()))
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8 3 1 6 4 7 10 14 13
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>>> tuple(i.value for i in t.traversal_tree(inorder))
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(1, 3, 4, 6, 7, 8, 10, 13, 14)
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>>> tuple(t)
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(1, 3, 4, 6, 7, 8, 10, 13, 14)
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>>> t.find_kth_smallest(3, t.root)
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4
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>>> tuple(t)[3-1]
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4
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>>> print(" ".join(repr(i.value) for i in t.traversal_tree(postorder)))
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1 4 7 6 3 13 14 10 8
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>>> t.remove(20)
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Traceback (most recent call last):
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...
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ValueError: Value 20 not found
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>>> BinarySearchTree().search(6)
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Traceback (most recent call last):
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...
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IndexError: Warning: Tree is empty! please use another.
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Other example:
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>>> testlist = (8, 3, 6, 1, 10, 14, 13, 4, 7)
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>>> t = BinarySearchTree()
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>>> for i in testlist:
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... t.insert(i) # doctest: +ELLIPSIS
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BinarySearchTree(root=8)
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BinarySearchTree(root={'8': (3, None)})
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BinarySearchTree(root={'8': ({'3': (None, 6)}, None)})
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BinarySearchTree(root={'8': ({'3': (1, 6)}, None)})
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BinarySearchTree(root={'8': ({'3': (1, 6)}, 10)})
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BinarySearchTree(root={'8': ({'3': (1, 6)}, {'10': (None, 14)})})
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BinarySearchTree(root={'8': ({'3': (1, 6)}, {'10': (None, {'14': (13, None)})})})
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BinarySearchTree(root={'8': ({'3': (1, {'6': (4, None)})}, {'10': (None, {'14': ...
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BinarySearchTree(root={'8': ({'3': (1, {'6': (4, 7)})}, {'10': (None, {'14': (13, ...
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Prints all the elements of the list in order traversal
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>>> print(t)
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{'8': ({'3': (1, {'6': (4, 7)})}, {'10': (None, {'14': (13, None)})})}
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Test existence
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>>> t.search(6) is not None
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True
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>>> 6 in t
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True
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>>> t.search(-1) is not None
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False
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>>> -1 in t
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False
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>>> t.search(6).is_right
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True
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>>> t.search(1).is_right
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False
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>>> t.get_max().value
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14
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>>> max(t)
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14
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>>> t.get_min().value
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1
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>>> min(t)
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1
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>>> t.empty()
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False
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>>> not t
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False
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>>> for i in testlist:
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... t.remove(i)
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>>> t.empty()
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True
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>>> not t
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True
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"""
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from __future__ import annotations
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from collections.abc import Iterable, Iterator
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from dataclasses import dataclass
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from typing import Any, Self
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@dataclass
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class Node:
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value: int
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left: Node | None = None
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right: Node | None = None
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parent: Node | None = None # Added in order to delete a node easier
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def __iter__(self) -> Iterator[int]:
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"""
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>>> list(Node(0))
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[0]
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>>> list(Node(0, Node(-1), Node(1), None))
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[-1, 0, 1]
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"""
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yield from self.left or []
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yield self.value
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yield from self.right or []
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def __repr__(self) -> str:
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from pprint import pformat
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if self.left is None and self.right is None:
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return str(self.value)
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return pformat({f"{self.value}": (self.left, self.right)}, indent=1)
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@property
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def is_right(self) -> bool:
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return bool(self.parent and self is self.parent.right)
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@dataclass
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class BinarySearchTree:
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root: Node | None = None
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def __bool__(self) -> bool:
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return bool(self.root)
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def __iter__(self) -> Iterator[int]:
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yield from self.root or []
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def __str__(self) -> str:
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"""
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Return a string of all the Nodes using in order traversal
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"""
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return str(self.root)
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def __reassign_nodes(self, node: Node, new_children: Node | None) -> None:
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if new_children is not None: # reset its kids
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new_children.parent = node.parent
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if node.parent is not None: # reset its parent
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if node.is_right: # If it is the right child
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node.parent.right = new_children
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else:
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node.parent.left = new_children
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else:
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self.root = new_children
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def empty(self) -> bool:
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"""
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Returns True if the tree does not have any element(s).
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False if the tree has element(s).
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>>> BinarySearchTree().empty()
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True
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>>> BinarySearchTree().insert(1).empty()
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False
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>>> BinarySearchTree().insert(8, 3, 6, 1, 10, 14, 13, 4, 7).empty()
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False
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"""
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return not self.root
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def __insert(self, value) -> None:
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"""
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Insert a new node in Binary Search Tree with value label
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"""
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new_node = Node(value) # create a new Node
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if self.empty(): # if Tree is empty
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self.root = new_node # set its root
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else: # Tree is not empty
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parent_node = self.root # from root
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if parent_node is None:
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return
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while True: # While we don't get to a leaf
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if value < parent_node.value: # We go left
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if parent_node.left is None:
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parent_node.left = new_node # We insert the new node in a leaf
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break
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else:
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parent_node = parent_node.left
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elif parent_node.right is None:
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parent_node.right = new_node
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break
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else:
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parent_node = parent_node.right
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new_node.parent = parent_node
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def insert(self, *values) -> Self:
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for value in values:
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self.__insert(value)
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return self
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def search(self, value) -> Node | None:
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"""
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>>> tree = BinarySearchTree().insert(10, 20, 30, 40, 50)
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>>> tree.search(10)
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{'10': (None, {'20': (None, {'30': (None, {'40': (None, 50)})})})}
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>>> tree.search(20)
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{'20': (None, {'30': (None, {'40': (None, 50)})})}
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>>> tree.search(30)
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{'30': (None, {'40': (None, 50)})}
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>>> tree.search(40)
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{'40': (None, 50)}
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>>> tree.search(50)
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50
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>>> tree.search(5) is None # element not present
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True
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>>> tree.search(0) is None # element not present
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True
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>>> tree.search(-5) is None # element not present
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True
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>>> BinarySearchTree().search(10)
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Traceback (most recent call last):
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...
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IndexError: Warning: Tree is empty! please use another.
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"""
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if self.empty():
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raise IndexError("Warning: Tree is empty! please use another.")
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else:
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node = self.root
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# use lazy evaluation here to avoid NoneType Attribute error
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while node is not None and node.value is not value:
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node = node.left if value < node.value else node.right
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return node
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def get_max(self, node: Node | None = None) -> Node | None:
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"""
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We go deep on the right branch
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>>> BinarySearchTree().insert(10, 20, 30, 40, 50).get_max()
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50
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>>> BinarySearchTree().insert(-5, -1, 0.1, -0.3, -4.5).get_max()
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{'0.1': (-0.3, None)}
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>>> BinarySearchTree().insert(1, 78.3, 30, 74.0, 1).get_max()
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{'78.3': ({'30': (1, 74.0)}, None)}
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>>> BinarySearchTree().insert(1, 783, 30, 740, 1).get_max()
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{'783': ({'30': (1, 740)}, None)}
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"""
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if node is None:
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if self.root is None:
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return None
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node = self.root
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if not self.empty():
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while node.right is not None:
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node = node.right
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return node
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def get_min(self, node: Node | None = None) -> Node | None:
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"""
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We go deep on the left branch
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>>> BinarySearchTree().insert(10, 20, 30, 40, 50).get_min()
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{'10': (None, {'20': (None, {'30': (None, {'40': (None, 50)})})})}
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>>> BinarySearchTree().insert(-5, -1, 0, -0.3, -4.5).get_min()
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{'-5': (None, {'-1': (-4.5, {'0': (-0.3, None)})})}
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>>> BinarySearchTree().insert(1, 78.3, 30, 74.0, 1).get_min()
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{'1': (None, {'78.3': ({'30': (1, 74.0)}, None)})}
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>>> BinarySearchTree().insert(1, 783, 30, 740, 1).get_min()
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{'1': (None, {'783': ({'30': (1, 740)}, None)})}
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"""
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if node is None:
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node = self.root
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if self.root is None:
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return None
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if not self.empty():
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node = self.root
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while node.left is not None:
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node = node.left
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return node
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def remove(self, value: int) -> None:
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# Look for the node with that label
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node = self.search(value)
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if node is None:
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msg = f"Value {value} not found"
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raise ValueError(msg)
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if node.left is None and node.right is None: # If it has no children
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self.__reassign_nodes(node, None)
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elif node.left is None: # Has only right children
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self.__reassign_nodes(node, node.right)
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elif node.right is None: # Has only left children
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self.__reassign_nodes(node, node.left)
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else:
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predecessor = self.get_max(
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node.left
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) # Gets the max value of the left branch
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self.remove(predecessor.value) # type: ignore[union-attr]
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node.value = (
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predecessor.value # type: ignore[union-attr]
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) # Assigns the value to the node to delete and keep tree structure
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def preorder_traverse(self, node: Node | None) -> Iterable:
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if node is not None:
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yield node # Preorder Traversal
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yield from self.preorder_traverse(node.left)
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yield from self.preorder_traverse(node.right)
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def traversal_tree(self, traversal_function=None) -> Any:
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"""
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This function traversal the tree.
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You can pass a function to traversal the tree as needed by client code
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"""
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if traversal_function is None:
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return self.preorder_traverse(self.root)
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else:
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return traversal_function(self.root)
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def inorder(self, arr: list, node: Node | None) -> None:
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"""Perform an inorder traversal and append values of the nodes to
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a list named arr"""
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if node:
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self.inorder(arr, node.left)
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arr.append(node.value)
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self.inorder(arr, node.right)
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def find_kth_smallest(self, k: int, node: Node) -> int:
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"""Return the kth smallest element in a binary search tree"""
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arr: list[int] = []
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self.inorder(arr, node) # append all values to list using inorder traversal
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return arr[k - 1]
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def inorder(curr_node: Node | None) -> list[Node]:
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"""
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inorder (left, self, right)
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"""
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node_list = []
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if curr_node is not None:
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node_list = [*inorder(curr_node.left), curr_node, *inorder(curr_node.right)]
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return node_list
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def postorder(curr_node: Node | None) -> list[Node]:
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"""
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postOrder (left, right, self)
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"""
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node_list = []
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if curr_node is not None:
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node_list = postorder(curr_node.left) + postorder(curr_node.right) + [curr_node]
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return node_list
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if __name__ == "__main__":
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import doctest
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doctest.testmod(verbose=True)
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