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183 lines
4.7 KiB
Python
183 lines
4.7 KiB
Python
# https://en.wikipedia.org/wiki/Tree_traversal
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from __future__ import annotations
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from collections import deque
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from collections.abc import Sequence
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from dataclasses import dataclass
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from typing import Any
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@dataclass
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class Node:
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data: int
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left: Node | None = None
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right: Node | None = None
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def make_tree() -> Node | None:
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return Node(1, Node(2, Node(4), Node(5)), Node(3))
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def preorder(root: Node | None) -> list[int]:
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"""
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Pre-order traversal visits root node, left subtree, right subtree.
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>>> preorder(make_tree())
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[1, 2, 4, 5, 3]
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"""
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return [root.data] + preorder(root.left) + preorder(root.right) if root else []
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def postorder(root: Node | None) -> list[int]:
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"""
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Post-order traversal visits left subtree, right subtree, root node.
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>>> postorder(make_tree())
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[4, 5, 2, 3, 1]
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"""
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return postorder(root.left) + postorder(root.right) + [root.data] if root else []
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def inorder(root: Node | None) -> list[int]:
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"""
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In-order traversal visits left subtree, root node, right subtree.
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>>> inorder(make_tree())
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[4, 2, 5, 1, 3]
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"""
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return inorder(root.left) + [root.data] + inorder(root.right) if root else []
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def height(root: Node | None) -> int:
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"""
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Recursive function for calculating the height of the binary tree.
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>>> height(None)
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0
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>>> height(make_tree())
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3
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"""
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return (max(height(root.left), height(root.right)) + 1) if root else 0
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def level_order(root: Node | None) -> Sequence[Node | None]:
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"""
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Returns a list of nodes value from a whole binary tree in Level Order Traverse.
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Level Order traverse: Visit nodes of the tree level-by-level.
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"""
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output: list[Any] = []
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if root is None:
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return output
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process_queue = deque([root])
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while process_queue:
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node = process_queue.popleft()
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output.append(node.data)
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if node.left:
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process_queue.append(node.left)
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if node.right:
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process_queue.append(node.right)
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return output
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def get_nodes_from_left_to_right(
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root: Node | None, level: int
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) -> Sequence[Node | None]:
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"""
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Returns a list of nodes value from a particular level:
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Left to right direction of the binary tree.
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"""
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output: list[Any] = []
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def populate_output(root: Node | None, level: int) -> None:
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if not root:
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return
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if level == 1:
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output.append(root.data)
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elif level > 1:
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populate_output(root.left, level - 1)
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populate_output(root.right, level - 1)
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populate_output(root, level)
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return output
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def get_nodes_from_right_to_left(
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root: Node | None, level: int
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) -> Sequence[Node | None]:
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"""
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Returns a list of nodes value from a particular level:
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Right to left direction of the binary tree.
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"""
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output: list[Any] = []
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def populate_output(root: Node | None, level: int) -> None:
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if root is None:
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return
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if level == 1:
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output.append(root.data)
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elif level > 1:
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populate_output(root.right, level - 1)
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populate_output(root.left, level - 1)
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populate_output(root, level)
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return output
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def zigzag(root: Node | None) -> Sequence[Node | None] | list[Any]:
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"""
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ZigZag traverse:
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Returns a list of nodes value from left to right and right to left, alternatively.
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"""
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if root is None:
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return []
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output: list[Sequence[Node | None]] = []
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flag = 0
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height_tree = height(root)
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for h in range(1, height_tree + 1):
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if not flag:
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output.append(get_nodes_from_left_to_right(root, h))
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flag = 1
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else:
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output.append(get_nodes_from_right_to_left(root, h))
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flag = 0
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return output
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def main() -> None: # Main function for testing.
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"""
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Create binary tree.
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"""
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root = make_tree()
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"""
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All Traversals of the binary are as follows:
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"""
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print(f"In-order Traversal: {inorder(root)}")
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print(f"Pre-order Traversal: {preorder(root)}")
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print(f"Post-order Traversal: {postorder(root)}", "\n")
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print(f"Height of Tree: {height(root)}", "\n")
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print("Complete Level Order Traversal: ")
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print(level_order(root), "\n")
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print("Level-wise order Traversal: ")
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for level in range(1, height(root) + 1):
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print(f"Level {level}:", get_nodes_from_left_to_right(root, level=level))
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print("\nZigZag order Traversal: ")
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print(zigzag(root))
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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main()
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