curriculum/challenges/english/blocks/learn-tree-traversal-by-building-a-binary-search-tree/65d8a6fcb15a3a239ba35dfd.md
After finding the minimum value, you will need to recursively delete the node with the minimum value from the right subtree.
This step ensures that the node with the minimum value is removed from the tree while maintaining the binary search tree (BST) property.
Call the _delete method recursively with node.right and node.key as the arguments. Assign the return value of the _delete() call to the right child of the current node.
You should call the _delete method recursively with node.right and node.key as the arguments.
assert.match(code, /self\._delete\(\s*node\.right\s*,\s*node\.key\s*/);
You should assign the return value of the _delete() call to the right child of the current node.
assert.match(code, /node\.right\s*=\s*self\._delete\(\s*node\.right\s*,\s*node\.key/);
class TreeNode:
def __init__(self, key):
self.key = key
self.left = None
self.right = None
def __str__(self):
return str(self.key)
class BinarySearchTree:
def __init__(self):
self.root = None
def _insert(self, node, key):
if node is None:
return TreeNode(key)
if key < node.key:
node.left = self._insert(node.left, key)
elif key > node.key:
node.right = self._insert(node.right, key)
return node
def insert(self, key):
self.root = self._insert(self.root, key)
def _search(self, node, key):
if node is None or node.key == key:
return node
if key < node.key:
return self._search(node.left, key)
return self._search(node.right, key)
def search(self, key):
return self._search(self.root, key)
--fcc-editable-region--
def _delete(self, node, key):
if node is None:
return node
if key < node.key:
node.left = self._delete(node.left, key)
elif key > node.key:
node.right = self._delete(node.right, key)
else:
if node.left is None:
return node.right
elif node.right is None:
return node.left
node.key = self._min_value(node.right)
--fcc-editable-region--
def _min_value(self, node):
while node.left is not None:
node = node.left
bst = BinarySearchTree()
nodes = [50, 30, 20, 40, 70, 60, 80]
for node in nodes:
bst.insert(node)
# print('Search for 80:', bst.search(80))