Adventures in Machine Learning

Dynamic Data Storage: Implementing Linked Lists in Python

Introduction to Linked Lists in Python

Linked lists are a widely used linear data structure that is commonly used in computer programming and forms the foundation of several computer algorithms. Unlike arrays, linked lists can be dynamically resized to accommodate changes in data, making them highly efficient.

A linked list is made up of elements, which are called nodes, with each node storing a piece of data and a reference to the next node in line. This unique feature of linked lists allows them to be easily manipulated and updated.

Creating a Node Class

In Python, a node class is required to create a linked list. A node is a data structure that stores the data and the link to the next node in the list.

The Node class contains fields, including data and next_node. The data field stores the data that is being collected, while the next_node field is a reference to the next node in the list.

Creating a Linked List Class

After creating a node class, the next step is to create a Linked List class. The LinkedList class is where nodes are linked.

The class contains an empty node that serves as the first entry point into the linked list. This practice ensures that the first node in the list always points to the second node, which points to the third node, and so on until the end of the list.

The LinkedList class also contains several functions that are necessary for creating and manipulating nodes within the linked list.

Adding Nodes to the Linked List

To add a node to the end of the list, the user must first create an empty LinkedList object, followed by the creation of a node object with the data it intends to store. Then, it links the new node with the last node using the last node’s next_node reference.

Finally, the LinkedList object must update its reference to the new last node. This process repeats for every new node added to the list.

Creating Links between Nodes

After creating the object, the user can add as many nodes as they require. When doing so, they will link the new nodes with the previous nodes stored in the list.

This feature of linked lists enables the user to create a linear sequence of data elements.

Printing the Nodes of the List

A useful feature of linked lists is that it is simple to print the contents of a list. The LinkedList class contains a printList function that traverses the list and prints the data for every node in the list.

This feature is useful for testing and debugging the code to ensure that data is being stored and retrieved appropriately.

Getting the Size of the List

To determine how many elements are stored in the linked list, the LinkedList class includes a size function that counts the number of nodes in the list. This feature is useful when the users are dealing with a large data set and want to know how many elements are being stored in the linked list.

Inserting a New Node at the Head of the List

In addition to adding nodes to the back of the linked list, we can also insert them at the front end. To insert a new node at the list’s head, the LinkedList class contains an insert_at_head function that creates a new node and assigns its next_node reference to the current head of the list.

The LinkedList then updated its head reference to the new node, effectively inserting the new node at the list’s head.

Getting the Next Node

Traversing a linked list involves moving from one node to the next node in line. The LinkedList class contains a get_next_node function that returns the next node in line.

It is useful for performing specific operations on individual nodes within the linked list.

Conclusion

Linked lists are a fundamental data structure in computer programming, and they have a wide range of applications. In Python, they make use of a node class and a LinkedList class to create and manipulate data.

Once created, data can be inserted at any point in the linked list and retrieved using the available functions, such as the get_next_node function and the size function. Given their numerous features, linked lists in Python provide an efficient and practical solution for storing and manipulating data.Linked lists are a powerful data structure used in computer programming.

They are a type of linear data structure that store data in a constantly linked list of nodes, and each node points to the next node in the sequence. This gives developers the ability to store large datasets, search, delete, and insert data in the most optimized way possible.

In Python, data manipulation with linked lists is simple to implement, with the availability of the node class and the LinkedList class. This article will provide in-depth details on the implementation of linked lists in Python.

Creating a Node Class

Nodes are the building blocks of linked lists in Python. They contain two fields, namely data and next_node.

The data field includes the information that we wish to store, while the next_node field is a reference to the next node in the data sequence. The node class is necessary to store the data and manipulate the data because it contains both fields.

Creation of a Linked List Class

After creating the node class, we can create the LinkedList class. The LinkedList class contains all the necessary functions to manipulate the nodes in Python.

One of the essential features of a LinkedList is the ability to add, remove or update elements in the list dynamically, without worrying about pre-allocating memory. Linked lists in Python are implemented dynamically; the list size can increase or decrease at any time, making them an efficient data structure compared to arrays.

Adding Nodes to the Linked List

After creating a LinkedList and a node object, we can add data to the LinkedList while keeping the data in the proper sequence. The LinkedList class has a function that adds nodes to the end of the list.

Once the new node is added to the list, it becomes part of the data sequence, and every element in the list points to the next element in line. To add a new node at the end of the linked list, we create a node object and assign its ‘next_node’ field to a null value since it will be the last node in the sequence.

Creating Links between Nodes

To create links between nodes in a Python linked list, we set the ‘next_node’ field of a preceding node object to the new node object. The new node now has a reference to the previous node on the list.

By referring to the ‘next_node’ of every node in the list, we can traverse it from beginning to end. The ability to traverse forward and backward quickly has made linked lists a preferred data structure in computer programming.

Printing the Nodes of the List

One of the most significant benefits of the LinkedList class in Python is its ability to print out the values stored in the list. The printList function, in the LinkedList class, iteratively navigates the linked list and prints the data that each node object stores.

This method is useful in debugging the code in addition to ensuring that the correct data is stored in the proper sequence.

Getting the Size of the List

In linked lists, determining the size of the list is the process of counting the number of nodes in the sequence. To perform this operation in the LinkedList class, we iterate through the list and count each occurrence of a node object.

The function used in the Python linked list to perform this operation is called the size function.

Inserting a New Node at the Head of the List

In Python’s LinkedList class, inserting a new node at the beginning of the list is very similar to creating a node object and linking it to the previous node in the list. The only difference is where the new node object is placed.

To achieve this, we create a new node object with the data we want to add to the list and set its ‘next_node’ field to the current head of the linked list. We then update the head reference to the new node, creating an insertion of the new node at the head of the list.

Getting the Next Node

Although linked lists in Python have a sequence that links each node to the next node, we need to have a function that retrieves the next node programmatically. In linked lists, getting the next node involves storing the data of the current node potentially, fetching the next node object, and returning its data.

The ‘get_next_node’ function in the LinkedList class of Python is used to retrieve the next node object at the current point on the list.

Conclusion

In conclusion, linked lists in Python are dynamic and efficient data structures. In Python, linked lists are created using the node class and the LinkedList class.

The node class holds data that stores a data field and a reference to the next node object. The LinkedList class provides the developer with functions that manipulate and control all data held in the linked list.

We looked at adding nodes to the list, connecting nodes, printing the list, knowing the list size, inserting a node at the head of the list, and getting the next node on the list. Developers must understand these functions to get the most out of linked lists in Python.

In conclusion, implementing linked lists in Python is a dynamic and efficient way of collecting, storing, sorting, and modifying data. The node and the LinkedList class are the two essential elements of linked lists.

Data is stored in node objects that contain two fields, data and next_node. The current node points to the “next” node in the data sequence.

The LinkedList class provides functions for manipulating data, adding nodes, calculating the size of the list, printing data, and inserting nodes at the head of the list. Developers who understand these functions can create custom-linked lists for their projects.

By optimizing the data structures, developers can improve the efficiency of their programs while storing and manipulating large datasets.

Popular Posts