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Translate all code to English (#1836)

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* Review the EN heading format.

* Fix pythontutor headings.

* Fix pythontutor headings.

* bug fixes

* Fix headings in **/summary.md

* Revisit the CN-to-EN translation for Python code using Claude-4.5

* Revisit the CN-to-EN translation for Java code using Claude-4.5

* Revisit the CN-to-EN translation for Cpp code using Claude-4.5.

* Fix the dictionary.

* Fix cpp code translation for the multipart strings.

* Translate Go code to English.

* Update workflows to test EN code.

* Add EN translation for C.

* Add EN translation for CSharp.

* Add EN translation for Swift.

* Trigger the CI check.

* Revert.

* Update en/hash_map.md

* Add the EN version of Dart code.

* Add the EN version of Kotlin code.

* Add missing code files.

* Add the EN version of JavaScript code.

* Add the EN version of TypeScript code.

* Fix the workflows.

* Add the EN version of Ruby code.

* Add the EN version of Rust code.

* Update the CI check for the English version  code.

* Update Python CI check.

* Fix cmakelists for en/C code.

* Fix Ruby comments
This commit is contained in:
Yudong Jin
2025-12-31 07:44:52 +08:00
committed by GitHub
parent 45e1295241
commit 2778a6f9c7
1284 changed files with 71557 additions and 3275 deletions
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44
en/codes/python/chapter_tree/binary_search_tree.py
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@@ -26,7 +26,7 @@ class BinarySearchTree:
def search(self, num: int) -> TreeNode | None:
"""Search node"""
cur = self._root
# Loop find, break after passing leaf nodes
# Loop search, exit after passing leaf node
while cur is not None:
# Target node is in cur's right subtree
if cur.val < num:
@@ -34,7 +34,7 @@ class BinarySearchTree:
# Target node is in cur's left subtree
elif cur.val > num:
cur = cur.left
# Found target node, break loop
# Found target node, exit loop
else:
break
return cur
@@ -45,10 +45,10 @@ class BinarySearchTree:
if self._root is None:
self._root = TreeNode(num)
return
# Loop find, break after passing leaf nodes
# Loop search, exit after passing leaf node
cur, pre = self._root, None
while cur is not None:
# Found duplicate node, thus return
# Found duplicate node, return directly
if cur.val == num:
return
pre = cur
@@ -66,47 +66,47 @@ class BinarySearchTree:
pre.left = node
def remove(self, num: int):
"""Remove node"""
# If tree is empty, return
"""Delete node"""
# If tree is empty, return directly
if self._root is None:
return
# Loop find, break after passing leaf nodes
# Loop search, exit after passing leaf node
cur, pre = self._root, None
while cur is not None:
# Found node to be removed, break loop
# Found node to delete, exit loop
if cur.val == num:
break
pre = cur
# Node to be removed is in cur's right subtree
# Node to delete is in cur's right subtree
if cur.val < num:
cur = cur.right
# Node to be removed is in cur's left subtree
# Node to delete is in cur's left subtree
else:
cur = cur.left
# If no node to be removed, return
# If no node to delete, return directly
if cur is None:
return
# Number of child nodes = 0 or 1
if cur.left is None or cur.right is None:
# When the number of child nodes = 0/1, child = null/that child node
# When number of child nodes = 0 / 1, child = null / that child node
child = cur.left or cur.right
# Remove node cur
# Delete node cur
if cur != self._root:
if pre.left == cur:
pre.left = child
else:
pre.right = child
else:
# If the removed node is the root, reassign the root
# If deleted node is root node, reassign root node
self._root = child
# Number of child nodes = 2
else:
# Get the next node in in-order traversal of cur
# Get next node of cur in inorder traversal
tmp: TreeNode = cur.right
while tmp.left is not None:
tmp = tmp.left
# Recursively remove node tmp
# Recursively delete node tmp
self.remove(tmp.val)
# Replace cur with tmp
cur.val = tmp.val
@@ -117,7 +117,7 @@ if __name__ == "__main__":
# Initialize binary search tree
bst = BinarySearchTree()
nums = [8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15]
# Note that different insertion orders can result in various tree structures. This particular sequence creates a perfect binary tree
# Please note that different insertion orders will generate different binary trees, this sequence can generate a perfect binary tree
for num in nums:
bst.insert(num)
print("\nInitialized binary tree is\n")
@@ -129,18 +129,18 @@ if __name__ == "__main__":
# Insert node
bst.insert(16)
print("\nAfter inserting node 16, the binary tree is\n")
print("\nAfter inserting node 16, binary tree is\n")
print_tree(bst.get_root())
# Remove node
# Delete node
bst.remove(1)
print("\nAfter removing node 1, the binary tree is\n")
print("\nAfter deleting node 1, binary tree is\n")
print_tree(bst.get_root())
bst.remove(2)
print("\nAfter removing node 2, the binary tree is\n")
print("\nAfter deleting node 2, binary tree is\n")
print_tree(bst.get_root())
bst.remove(4)
print("\nAfter removing node 4, the binary tree is\n")
print("\nAfter deleting node 4, binary tree is\n")
print_tree(bst.get_root())