Bst

src/bst.py

@@ -0,0 +1,300 @@
+"""Creatae a Binary Search Tree."""
+
+
+class Node:
+    """Tree node: left and right child & data which can be any object."""
+
+    def __init__(self, val=None):
+        """Initialize the BST data Structure."""
+        self.left = None
+        self.right = None
+        self.val = val
+        self.parent = None
+        self._counter = 0
+
+
+class BinarySearchTree:
+    """Instantiates a BST."""
+
+    def __init__(self):
+            """Set the root."""
+            self.root = None
+
+    def insert(self, val):
+        """Insert new node with data."""
+        if self.val:
+            if val < self.val:
+                if self.left is None:
+                    self.left = Node(val)
+                else:
+                    self.left.insert(val)
+                    self._counter += 1
+            elif val > self.val:
+                if self.right is None:
+                    self.right = Node(val)
+                else:
+                    self.right.insert(val)
+                    self._counter += 1
+        else:
+            self.val = val
+
+    def search(self, val, parent=None):
+        """Look up node containing data."""
+        if val < self.val:
+            if self.left is None:
+                return None, None
+            return self.left.search(val, self)
+        elif val > self.val:
+            if self.right is None:
+                return None, None
+            return self.right.lookup(val, self)
+        else:
+            return self, parent
+
+    def size(self):
+        """Return Int for the size of BST."""
+        return self._counter
+
+    def depth(self, root):
+        """Return Int of # of levels below the root."""
+        if root is None:
+            return 0
+        else:
+            return max(self.depth(root.left), self.depth(root.right)) + 1
+
+    def balance(self, root):
+        """Return Int ."""
+        if root is None:
+            return 0
+        else:
+            return max(self.depth(root.left) - self.depth(root.right))
+
+    def contains(self, val):
+        """Return a boolean if val is in BST."""
+        if self.root is not None:
+            return self._search(val, self.root)
+        elif self.val == val:
+            return True
+        elif val < self.val and self.left is not None:
+            return self.left.val
+        elif val < self.val and self.right is not None:
+            return self.right.val
+        return False
+
+    def breath_first(self):
+        """Traverse the BST by breath first method."""
+        if self.root is None:
+            raise ValueError('The tree is empty, no nodes to return.')
+        bft = [self.root]
+        while bft:
+            current = bft.pop(0)
+            if current.left:
+                bft.append(current.left)
+            if current.right:
+                bft.append(current.right)
+            yield current.data
+
+    def in_order(self):
+        """Traverse the bst nodes in order."""
+        if self.root is None:
+            raise ValueError("Tree is empty.")
+        curr = self.root
+        order = []
+        while curr or order:
+            if curr:
+                order.append(curr)
+                curr = curr.left
+            else:
+                curr = order.pop()
+                yield curr.val
+                curr = curr.right
+
+    def pre_order(self):
+        """Traverse the bst nodes by pre order."""
+        if self.root is None:
+            raise ValueError("Tree is empty.")
+        curr = self.root
+        order = []
+        while curr or order:
+            if curr:
+                yield curr.value
+                if curr.right:
+                    order.append(curr.right)
+                curr = curr.left
+            else:
+                curr = order.pop()
+
+    def post_order(self):
+        """Traverse the bst nodes in post order."""
+        if self.root is None:
+            raise ValueError("Tree is empty.")
+        curr = self.root
+        child = None
+        order = []
+        while curr or order:
+            if curr:
+                order.append(curr)
+                curr = curr.left
+            else:
+                if order[-1].right and order[-1].right is not child:
+                    curr = order[-1].right
+                else:
+                    child = order.pop()
+                    yield child.value
+
+    def delete(self, data):
+        """Remove a node from the BST."""
+        # empty tree
+        if self.root is None:
+            return False
+
+        # data is in root node.
+        elif self.root.val == data:
+            if self.root.leftChild is None and self.root.rightChild is None:
+                self.root = None
+            elif self.root.leftChild and self.root.rightChild is None:
+                self.root = self.root.leftChild
+            elif self.root.leftChild is None and self.root.rightChild:
+                self.root = self.root.rightChild
+            elif self.root.leftChild and self.root.rightChild:
+                delNodeParent = self.root
+                delNode = self.root.rightChild
+                while delNode.leftChild:
+                    delNodeParent = delNode
+                    delNode = delNode.leftChild
+                self.root.val = delNode.val
+                if delNode.rightChild:
+                    if delNodeParent.val > delNode.val:
+                        delNodeParent.leftChild = delNode.rightChild
+                    elif delNodeParent.val < delNode.rightChild:
+                        delNodeParent.rightChild = delNode.rightChild
+                else:
+                    if delNode.val < delNodeParent.val:
+                        delNodeParent.leftChild = None
+                    else:
+                        delNodeParent.rightChild = None
+            return True
+        parent = None
+        node = self.root
+
+        # find node to remove
+        while node and node.val != data:
+            parent = node
+            if data < node.val:
+                node = node.leftChild
+            elif data > node.val:
+                node = node.rightChild
+
+        # data not found.
+        if node is None or node.val != data:
+            return False
+
+        # Remove node has no children
+        elif node.leftChild is None and node.rightChild is None:
+            if data < parent.val:
+                parent.leftChild = None
+            else:
+                parent.rightChild = None
+            return True
+
+        # Section for having left child only.
+        elif node.leftChild and node.rightChild is None:
+            if data < parent.val:
+                parent.leftChild = node.leftChild
+            else:
+                parent.rightChild = node.leftChild
+            return True
+
+        # Section for having Right child only.
+        elif node.leftChild is None and node.rightChild:
+            if data < parent.val:
+                parent.leftChild = node.rightChild
+            else:
+                parent.rightChild = node.rightChild
+            return True
+
+        # node has left AND right children
+        else:
+            delNodeParent = node
+            delNode = node.rightChild
+            while delNode.leftChild:
+                delNodeParent = delNode
+                delNode = delNode.leftChild
+
+            node.val = delNode.val
+            if delNode.rightChild:
+                if delNodeParent.val > delNode.val:
+                    delNodeParent.leftChild = delNode.rightChild
+                elif delNodeParent.val < delNode.val:
+                    delNodeParent.rightChild = delNode.rightChild
+            else:
+                if delNode.val < delNodeParent.val:
+                    delNodeParent.leftchild = None
+                else:
+                    delNodeParent.rightChild = None
+
+
+if __name__ == '__main__':
+    import timeit
+
+    insert_time_ub = BinarySearchTree()
+    num = (x for x in range(1000))
+    insert_unbalanced = timeit.timeit(
+        'insert_time_ub.insert(next(num))',
+        setup='from __main__ import insert_time_ub, num',
+        number=1000)
+
+    search_time_ub = BinarySearchTree()
+    for i in range(100):
+        search_time_ub.insert(i)
+    search_unbalanced = timeit.timeit(
+        'search_time_ub.search(99)',
+        setup='from __main__ import search_time_ub',
+        number=1000)
+
+    search_unbalanced_head = timeit.timeit(
+        'search_time_ub.search(0)',
+        setup='from __main__ import search_time_ub',
+        number=1000)
+
+    insert_time_b = BinarySearchTree()
+
+    def insert_time(val):
+        """."""
+        if (500 + val) % 2 == 0:
+            insert_time_b.insert(500 + val)
+        else:
+            insert_time_b.insert(500 - val)
+
+    num_b = (x for x in range(1000))
+    insert_balanced = timeit.timeit(
+        'insert_time(next(num_b))',
+        setup='from __main__ import insert_time, num_b',
+        number=1000)
+
+    search_time_b = BinarySearchTree()
+    for i in range(1000):
+        if (500 + i) % 2 == 0:
+            search_time_b.insert(500 + i)
+        else:
+            search_time_b.insert(500 - i)
+
+    search_balanced_leaf = timeit.timeit(
+        'search_time_b.search(999)',
+        setup='from __main__ import search_time_b',
+        number=1000)
+
+    search_balanced_head = timeit.timeit(
+        'search_time_b.search(500)',
+        setup='from __main__ import search_time_b',
+        number=1000)
+
+    print('The following time relates to worst case insert.')
+    print('Insert unbalanced: {}'.format(insert_unbalanced))
+    print('Insert balanced: {}'.format(insert_balanced))
+    print('\nThe following time relates to worst case search.')
+    print('Search unbalanced leaf: {}'.format(search_unbalanced))
+    print('Search balanced leaf: {}'.format(search_balanced_leaf))
+    print('\nThe following time relates to best base search.')
+    print('Search unbalanced head: {}'.format(search_unbalanced_head))
+    print('Search balanced head: {}'.format(search_balanced_head))