Generic Trees (Nary Trees)Overview of Generic TreesA common hierarchical data structure in computer science is the tree. A tree structure known as a generic tree, also known as a Nary tree, allows each node to have zero or more child nodes. Generic trees enable a more adaptable and dynamic branching structure than binary trees, which can only have a maximum of two children per node. Understanding Nary TreesNary trees can represent a variety of relationships and are flexible. A generic tree has a parentchild relationship between its nodes and varies in depth depending on how many levels it has. Because of their adaptability, they can be used to model a variety of complex data hierarchies, including file systems, organisational structures, and more. Generic Trees' Node StructureEach node in a Generic Tree implemented in Python contains data as well as references to its child nodes. A class can be used to accomplish this, with each instance of the class standing in for a node in the tree. The data for the node and a list of references to its children are typically included in the class attributes. How to Build a Generic TreeThe TreeNode class, which manages a list to store the node's child nodes and stores the node's data, can be defined in Python to create a Generic Tree. You can create the desired tree structure by connecting these nodes appropriately. Traversing a Generic TreeA fundamental operation on trees called traversal involves going to every node in a certain order. DepthFirst Search (DFS) and BreadthFirst Search (BFS) are two popular traversal methods. While BFS explores level by level, DFS travels as far as possible along each branch before turning around. DFS on generic trees: DepthFirst SearchRecursion can be utilised to implement DFS. Recursively visiting each child node starting at the root and using the same procedure is possible. BFS on Generic Trees: BreadthFirst SearchIn contrast, BFS involves visiting every node at a level before going to the following level. To achieve BFS in a Generic Tree, you can use a queue data structure. Deserialization and Serialisation of TreesDeserialization is the process of reconstructing a data structure from that format, whereas serialisation is the process of converting a data structure into a format that can be stored or transmitted. To efficiently save and load Generic Trees, serialisation and deserialization techniques can be used. Applications of Generic Trees Generic Trees are used in many different fields. They are employed in the representation of natural language syntax trees as well as file systems, network routing, and hierarchical data such as XML and HTML documents. Implementation Guide in Steps
Handling Tree OperationsYou might need to carry out operations when working with Generic Trees, such as determining the height of the tree, counting the nodes, or looking for a particular element. Based on the characteristics of the tree, each of these operations can be optimised and requires a particular strategy. Code: Output: Printing Generic Tree using DFS: Root Child 1 Subchild 1 Child 2 Subchild 2 To represent the nodes of the Generic Tree, a TreeNode class is first defined in this code. Each node has information and a list of its offspring. A node's children are added using the add_child method. The function print_tree_dfs is then created to print the tree using DepthFirst Search (DFS) navigation. A sample Generic Tree with a root node, two children, and two subchildren is then created. The nodes are connected using the add_child method. In order to print the Generic Tree using DFS traversal, we finally call the print_tree_dfs function with the root node. The output displays the tree's hierarchical structure with the proper indentation.
Next TopicLevel Order Traversal of Nary Tree
