How to Scrape Goodreads in 2026: Books, Reviews, Author Profiles, and Ratings

Are you trying to extract book data from Goodreads? Whether you're building a recommendation engine, analyzing reading trends, or automating your reading list — Goodreads is one of the richest sources of book metadata on the web. In this guide, I'll show you how to scrape Goodreads in 2026 for books, reviews, author profiles, and ratings using Python. Why Scrape Goodreads? Goodreads hosts data on over 4 billion books with reviews, ratings, genres, and author profiles. Common use cases include: Book recommendation systems — build datasets of ratings and reviews Author analytics — track an author's catalog, average ratings, and review volume Market research — analyze trends in genres, publishing dates, and reader sentiment Reading list automation — programmatically extract shelves and lists Setting Up Your Environment import requests from bs4 import BeautifulSoup import json import time import random HEADERS = { " User-Agent " : " Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537