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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:
 Data Structures
Data structures are a concrete implementation of the specification provided by one or more particular abstract data types (ADT), which specify the operations that can be performed on a data structure and the computational complexity of those operations.
Different kinds of data structures are suited for different kinds of applications, and some are highly specialized to specific tasks. For example, relational databases commonly use B-tree indexes for data retrieval, while compiler implementations usually use hash tables to look up identifiers.
Usually, efficient data structures are key to designing efficient algorithms.
Standard import statement
Step1:  DataStructureBase is the base class for implementing data structures
DataStructureVisualization is the class that visualizes data structures in GUI
DataStructureBase class
Any data structure, which is to be implemented, has to be derived from this class. Now we shall see data members and member functions of this class
Step2:  Now, this program can be executed as follows
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Python Code:
from openanalysis.data_structures import DataStructureBase, DataStructureVisualization
import gi.repository.Gtk as gtk   # for displaying GUI dialogs
Explanation: Data Structures
Data structures are a concrete implementation of the specification provided by one or more particular abstract data types (ADT), which specify the operations that can be performed on a data structure and the computational complexity of those operations.
Different kinds of data structures are suited for different kinds of applications, and some are highly specialized to specific tasks. For example, relational databases commonly use B-tree indexes for data retrieval, while compiler implementations usually use hash tables to look up identifiers.
Usually, efficient data structures are key to designing efficient algorithms.
Standard import statement
End of explanation
class BinarySearchTree(DataStructureBase):                        # Derived from DataStructureBase
    
    class Node:                                                   # Class for creating a node
        def __init__(self, data):
            self.left = None
            self.right = None
            self.data = data
        def __str__(self):
            return str(self.data)
    def __init__(self):
        DataStructureBase.__init__(self, "Binary Search Tree", "t.png")       # Initializing with name and path
        self.root = None
        self.count = 0
    def get_root(self):                                            # Returns root node of the tree
        return self.root
    def insert(self, item):                                        # Inserts item into the tree
        newNode = BinarySearchTree.Node(item)
        insNode = self.root
        parent = None
        while insNode is not None:
            parent = insNode
            if insNode.data > newNode.data:
                insNode = insNode.left
            else:
                insNode = insNode.right
        if parent is None:
            self.root = newNode
        else:
            if parent.data > newNode.data:
                parent.left = newNode
            else:
                parent.right = newNode
        self.count += 1
    def find(self, item):                                           # Finds if item is present in tree or not
        node = self.root
        while node is not None:
            if item < node.data:
                node = node.left
            elif item > node.data:
                node = node.right
            else:
                return True
        return False
    
    def min_value_node(self):                                       # Returns the minimum value node
        current = self.root
        while current.left is not None:
            current = current.left
        return current
    def delete(self, item):                                         # Deletes item from tree if present
                                                                    # else shows Value Error
        if item not in self:
            dialog = gtk.MessageDialog(None, 0, gtk.MessageType.ERROR,
                                       gtk.ButtonsType.CANCEL, "Value not found ERROR")
            dialog.format_secondary_text(
                "Element not found in the %s" % self.name)
            dialog.run()
            dialog.destroy()
        else:
            self.count -= 1
            if self.root.data == item and (self.root.left is None or self.root.right is None):
                if self.root.left is None and self.root.right is None:
                    self.root = None
                elif self.root.data == item and self.root.left is None:
                    self.root = self.root.right
                elif self.root.data == item and self.root.right is None:
                    self.root = self.root.left
                return self.root
            if item < self.root.data:
                temp = self.root
                self.root = self.root.left
                temp.left = self.delete(item)
                self.root = temp
            elif item > self.root.data:
                temp = self.root
                self.root = self.root.right
                temp.right = self.delete(item)
                self.root = temp
            else:
                if self.root.left is None:
                    return self.root.right
                elif self.root.right is None:
                    return self.root.left
                temp = self.root
                self.root = self.root.right
                min_node = self.min_value_node()
                temp.data = min_node.data
                temp.right = self.delete(min_node.data)
                self.root = temp
            return self.root
    def get_graph(self, rt):                                            # Populates self.graph with elements depending
                                                                        # upon the parent-children relation
        if rt is None:
            return
        self.graph[rt.data] = {}
        if rt.left is not None:
            self.graph[rt.data][rt.left.data] = {'child_status': 'left'}
            self.get_graph(rt.left)
        if rt.right is not None:
            self.graph[rt.data][rt.right.data] = {'child_status': 'right'}
            self.get_graph(rt.right)
Explanation: DataStructureBase is the base class for implementing data structures
DataStructureVisualization is the class that visualizes data structures in GUI
DataStructureBase class
Any data structure, which is to be implemented, has to be derived from this class. Now we shall see data members and member functions of this class:
Data Members
name -  Name of the DS
file_path - Path to store output of DS operations
Member Functions
__init__(self, name, file_path) - Initializes DS with a name and a file_path to store the output
insert(self, item) - Inserts item into the DS
delete(Self, item) - Deletes item from the DS, <br/>&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&nbsp;if item is not present in the DS, throws a ValueError  
find(self, item) - Finds the item in the DS
<br/>&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;returns True if found, else returns False<br/>&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;similar to __contains__(self, item)
get_root(self) - Returns the root (for graph and tree DS)
get_graph(self, rt) -  Gets the dict representation between the parent and children (for graph and tree DS)
draw(self, nth=None) - Draws the output to visualize the operations performed on the DS<br/>&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&nbsp;nth is used to pass an item to visualize a find operation
DataStructureVisualization class
This class is used for visualizing data structures in a GUI (using GTK+ 3). Now we shall see data members and member functions of this class:
Data Members
ds -  Any DS, which is an instance of DataStructureBase
Member Functions
__init__(self, ds) - Initializes ds with an instance of DS that is to be visualized
run(self) - Opens a GUI window to visualize the DS operations
An example ..... Binary Search Tree
Now we shall implement the class BinarySearchTree
End of explanation
DataStructureVisualization(BinarySearchTree).run()
import io
import base64
from IPython.display import HTML
video = io.open('../res/bst.mp4', 'r+b').read()
encoded = base64.b64encode(video)
HTML(data='''<video alt="test" controls>
                <source src="data:video/mp4;base64,{0}" type="video/mp4" />
             </video>'''.format(encoded.decode('ascii')))
Explanation: Now, this program can be executed as follows:
End of explanation
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