A web application that uses Google Books API to form a huge collection of books and recommendations similar to the user
A book recommendation platform that tracks the user's viewing history and recommends similar books to the user.
This website creates a database of users and their preferences for books and accordingly recommends similar books to them.
It also has a book-searching facility.
-Python to create the functionality of the site including API requests, Database Management, and Flask Framework.
-Flask(Python) to build up a framework to dynamically create pages for the website. Flask-Login is used for facilitating user management.
-Google Books API & Books API(New York Times) to get data on the books searched and the books to be recommended. Also gets New York Times Bestsellers.
-SQLAlchemy(Python-Flask) to create a database system to store the user's login details and also their book preferences.
-HTML to build the templates which Flask uses for building up sites.
-CSS/Bootstrap to give styling to the HTML framework and give the site a visual appeal.
-JavaScript to control the simple events on the HTML webpage.
-Render.com to deploy the web application.
The complete website is responsive, i.e., changes visuals as per the screen size of the user.
The navigation bar provides a quick way to move through different sections of the website.
The website uses Google Books API to search for the query entered in the search box provided.
The search results are listed in descending order of their ratings on the Google Books API.
Each book has a dynamically created details page that lists important details of the book.
It also provides links to Amazon, Flipkart, and Google Books for the book.
Untitled.video.-.Made.with.Clipchamp.4.mp4
The New York Times Books API gives the Latest Bestsellers of all categories.
They are shown on the homepage as a slider giving slight details about them.
The titles redirect to their Amazon buying link.
The recommendation system works by getting hold of the most viewed genre and the user's top two most regarded authors.
It then gets the books for all these constraints, merges them together, and shows them in descending order of their rating.
The website uses Flask-Login and SQLAlchemy to create a simple yet effective login system.
It allows login for only registered users and users can sign up on the sign up page.
The password also has constraints so that users don't enter an easily guessable password.
The Website has dark and light modes implemented.
-The Recommendation System can be improved by applying better algorithms.
-The user login system can be improved by making it more secure.
-The design of the webpage can be worked upon to give it a more professional look.
The Video Demo is of a previous version of the website. The website has been updated considerably since then. Video Demo