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Retranslate the complete English edition from Simplified Chinese (#2010)

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* Retranslate the complete English edition from Simplified Chinese

* Polish three English explanations after reader-focused review
This commit is contained in:
Yudong Jin
2026-10-31 03:35:51 +08:00
committed by GitHub
parent ef46e2ed95
commit 14c314c08c
1502 changed files with 29459 additions and 23517 deletions
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82
en/codes/python/chapter_tree/binary_search_tree.py
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@@ -16,49 +16,49 @@ class BinarySearchTree:
def __init__(self):
"""Constructor"""
# Initialize empty tree
# Initialize an empty tree
self._root = None
def get_root(self) -> TreeNode | None:
"""Get binary tree root node"""
"""Get the root of the binary tree"""
return self._root
def search(self, num: int) -> TreeNode | None:
"""Search node"""
"""Find a node"""
cur = self._root
# Loop search, exit after passing leaf node
# Search in a loop, stopping if cur becomes None
while cur is not None:
# Target node is in cur's right subtree
# If present, the target node is in the right subtree of cur
if cur.val < num:
cur = cur.right
# Target node is in cur's left subtree
# If present, the target node is in the left subtree of cur
elif cur.val > num:
cur = cur.left
# Found target node, exit loop
# The target node was found; exit the loop
else:
break
return cur
def insert(self, num: int):
"""Insert node"""
# If tree is empty, initialize root node
"""Insert a node"""
# If the tree is empty, initialize the root node
if self._root is None:
self._root = TreeNode(num)
return
# Loop search, exit after passing leaf node
# Search in a loop, stopping if cur becomes None
cur, pre = self._root, None
while cur is not None:
# Found duplicate node, return directly
# Return immediately if a duplicate node is found
if cur.val == num:
return
pre = cur
# Insertion position is in cur's right subtree
# The insertion position lies in the right subtree of cur
if cur.val < num:
cur = cur.right
# Insertion position is in cur's left subtree
# The insertion position lies in the left subtree of cur
else:
cur = cur.left
# Insert node
# Insert a node
node = TreeNode(num)
if pre.val < num:
pre.right = node
@@ -66,81 +66,81 @@ class BinarySearchTree:
pre.left = node
def remove(self, num: int):
"""Delete node"""
# If tree is empty, return directly
"""Remove a node"""
# Return immediately if the tree is empty
if self._root is None:
return
# Loop search, exit after passing leaf node
# Search in a loop, stopping if cur becomes None
cur, pre = self._root, None
while cur is not None:
# Found node to delete, exit loop
# The node to remove was found; exit the loop
if cur.val == num:
break
pre = cur
# Node to delete is in cur's right subtree
# If present, the node to remove is in the right subtree of cur
if cur.val < num:
cur = cur.right
# Node to delete is in cur's left subtree
# If present, the node to remove is in the left subtree of cur
else:
cur = cur.left
# If no node to delete, return directly
# Return immediately if the node to remove does not exist
if cur is None:
return
# Number of child nodes = 0 or 1
# Number of children = 0 or 1
if cur.left is None or cur.right is None:
# When number of child nodes = 0 / 1, child = null / that child node
# With 0 or 1 child, child is None or that child, respectively
child = cur.left or cur.right
# Delete node cur
# Remove node cur
if cur != self._root:
if pre.left == cur:
pre.left = child
else:
pre.right = child
else:
# If deleted node is root node, reassign root node
# If the removed node is the root, assign the new root
self._root = child
# Number of child nodes = 2
# Number of children = 2
else:
# Get next node of cur in inorder traversal
# Get the inorder successor of cur
tmp: TreeNode = cur.right
while tmp.left is not None:
tmp = tmp.left
# Recursively delete node tmp
# Recursively remove node tmp
self.remove(tmp.val)
# Replace cur with tmp
# Replace the value of cur with the value of tmp
cur.val = tmp.val
"""Driver Code"""
"""Driver code"""
if __name__ == "__main__":
# Initialize binary search tree
# Initialize the binary search tree
bst = BinarySearchTree()
nums = [8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15]
# Please note that different insertion orders will generate different binary trees, this sequence can generate a perfect binary tree
# Different insertion orders produce different binary trees; this sequence produces a perfect binary tree
for num in nums:
bst.insert(num)
print("\nInitialized binary tree is\n")
print("\nThe initialized binary tree is:\n")
print_tree(bst.get_root())
# Search node
# Find a node
node = bst.search(7)
print("\nFound node object is: {}, node value = {}".format(node, node.val))
print("\nFound node object: {}, node value = {}".format(node, node.val))
# Insert node
# Insert a node
bst.insert(16)
print("\nAfter inserting node 16, binary tree is\n")
print("\nBinary tree after inserting node 16:\n")
print_tree(bst.get_root())
# Delete node
# Remove a node
bst.remove(1)
print("\nAfter deleting node 1, binary tree is\n")
print("\nBinary tree after removing node 1:\n")
print_tree(bst.get_root())
bst.remove(2)
print("\nAfter deleting node 2, binary tree is\n")
print("\nBinary tree after removing node 2:\n")
print_tree(bst.get_root())
bst.remove(4)
print("\nAfter deleting node 4, binary tree is\n")
print("\nBinary tree after removing node 4:\n")
print_tree(bst.get_root())