Book Image

Django 4 By Example - Fourth Edition

By : Antonio Melé
4.6 (5)
Book Image

Django 4 By Example - Fourth Edition

4.6 (5)
By: Antonio Melé

Overview of this book

Django 4 By Example is the 4th edition of the best-selling franchise that helps you build web apps. This book will walk you through the creation of real-world applications, solving common problems, and implementing best practices using a step-by-step approach. You'll cover a wide range of web app development topics as you build four different apps: A blog application: Create data models, views, and URLs and implement an admin site for your blog. Create sitemaps and RSS feeds and implement a full-text search engine with PostgreSQL. A social website: Implement authentication with Facebook, Twitter, and Google. Create user profiles, image thumbnails, a bookmarklet, and an activity stream. Implement a user follower system and add infinite scroll pagination to your website. An e-commerce application: Build a product catalog, a shopping cart, and asynchronous tasks with Celery and RabbitMQ. Process payments with Stripe and manage payment notifications via webhooks. Build a product recommendation engine with Redis. Create PDF invoices and export orders to CSV. An e-learning platform: Create a content management system to manage polymorphic content. Cache content with Memcached and Redis. Build and consume a RESTful API. Implement a real-time chat using WebSockets with ASGI. Create a production environment using NGINX, uWSGI and Daphne with Docker Compose. This is a practical book that will have you creating web apps quickly.
Table of Contents (20 chapters)
18
Other Books You May Enjoy
19
Index

Building a recommendation engine

A recommendation engine is a system that predicts the preference or rating that a user would give to an item. The system selects relevant items for a user based on their behavior and the knowledge it has about them. Nowadays, recommendation systems are used in many online services. They help users by selecting the stuff they might be interested in from the vast amount of available data that is irrelevant to them. Offering good recommendations enhances user engagement. E-commerce sites also benefit from offering relevant product recommendations by increasing their average revenue per user.

You are going to create a simple, yet powerful, recommendation engine that suggests products that are usually bought together. You will suggest products based on historical sales, thus identifying products that are usually bought together. You are going to suggest complementary products in two different scenarios:

  • Product detail page: You will display...