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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Create a Binary Tree
The following code is taken from the O'reilly data structures with Python tutorialon Binary trees
It is just used as an example of best practices which can be adapted similarly for the Random Intersection Tree/ Node classes we will create
List Recursion
Step1:  Comments
The recursive approach in this example is about 18 times slower than the iterative approach
There is a recursion limit issue, which is needs to be considered in recursive algorithms
Linked Node example
Step2:  Implement the Binary Tree
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Python Code:
# Step by Step version
def search(aList, target):
    for v in aList:
        if target == v:
            return True
    return False
# Recursive approach
def searchRecursive(aList, target):
    if len(aList) == 0:
        return False
    if aList[0] == target:
        return True
    return searchRecursive(aList[1:], target)
max_val   = 1000
newList   = range(max_val)
newTarget = max_val
%timeit search(aList = newList, target = max_val)
%timeit searchRecursive(aList = newList, target = max_val)
Explanation: Create a Binary Tree
The following code is taken from the O'reilly data structures with Python tutorialon Binary trees
It is just used as an example of best practices which can be adapted similarly for the Random Intersection Tree/ Node classes we will create
List Recursion
End of explanation
class LinkedNode:
    def __init__(self, value):
        self.value = value
        self.next  = None
def search(n, value):
    # Base case
    if n is None:
        return False
    
    # Action and recursive step
    if n.value == value:
        return True
    return search(n.next, value)
def sumList(n):
    # base case
    if n is None:
        return 0
    
    # Action and recursive step
    return n.value + sumList(n.next)
class BinaryNode:
    def __init__(self, value):
        self.value = value
        self.left  = None
        self.value = None
    
class BinaryTree:
    def __init__(self):
        self.root = None
Explanation: Comments
The recursive approach in this example is about 18 times slower than the iterative approach
There is a recursion limit issue, which is needs to be considered in recursive algorithms
Linked Node example
End of explanation
class BinaryNode:
    # Don't initially know what the left and right nodes
    # are
    def __init__(self, value):
        self.value = value
        self.left  = None
        self.right = None
        
    def add(self, value):
        if value <= self.value:
            # add to left
            self.left = self.addToSubTree(self.left, value)
        elif value > self.value:
            # add to right
            self.right = self.addToSubTree(self.right, value)
    
    def addToSubTree(self, parent, value):
        if parent is None:
            return BinaryNode(value)
        parent.add(value)
        return parent
    
    def remove(self, value):
        if value < self.value:
            self.left = self.removeFromParent(self.left, value)
        elif value > self.value:
            self.right = self.removeFromParent(self.right, value)
        else:
            # what if left subtree is empty
            if self.left is None:
                    return self.right
            # find the largest value in the left subtree
            child = self.left
            while child.right:
                child = child.right
            # find the largest value in the left subtree
            childKey = child.value
            self.left = self.removeFromParent(self.left, childKey)
            self.value = childKey
            
        return self
    
    def removeFromParent(self, parent, value):
        if parent:
            return parent.remove(value)
        return None
class BinaryTree:    
    def __init__(self):
        self.root = None
        
    # add value to BT
    def add(self, value):
        if self.root == None:
            self.root = BinaryNode(value)
        else:
            self.root.add(value)
    
    # remove value from BT
    def remove(self, value):
        if self.root is not None:
            self.root = BinaryNode(value)
        else:
            self.root.add(value)
    
    def __contains__(self, target):
        node = self.root
        while node is not None:
            if target < node.value:
                node = node.left
            elif target > node.value:
                node = node.right
            else:
                return True       
        return False
b = BinaryTree()
b.root
b.add(7)
b.root
b.root.value
b.add(1)
b.root.value
b.root.right
1 in b
b = BinaryTree()
b.add(1)
b.root.value
1 in b
b.remove(1)
b
1 in b
Explanation: Implement the Binary Tree
End of explanation
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