Goodreads Book Scraper — Ratings, Reviews & Metadata

Scrape Goodreads for comprehensive book data. Extract titles, authors, ratings, review counts, genres, ISBNs, page counts, series information, cover images, publication dates, and descriptions. Supports search by keyword, direct book URLs, Goodreads lists, shelves, and author pages.

Features

• Comprehensive book data — titles, authors, ratings, review counts, genres, ISBNs, page counts, descriptions
• Series tracking — series name and book position within the series
• Cover images — high-resolution cover image URLs
• Publication info — publish dates (original and edition), publisher, format, language
• Search mode — search by title, author, or keyword with sorting options
• Direct URL mode — scrape specific book pages, lists, shelves, or author bibliographies
• Four extraction strategies — JSON-LD, Apollo/GraphQL state, DOM parsing, meta tag fallback
• Smart filtering — filter by minimum rating, page count, language, or publication date
• Deduplication — prevents duplicate books based on Goodreads ID, ISBN, or title+author
• Top reviews — optionally extract community reviews with ratings and text
• Edition details — optionally extract format, publisher, and identifier data
• Proxy support — works with Apify proxies for reliable large-scale scraping
• Pay-per-event — charged only per book successfully scraped
• Data quality scoring — each result includes a quality score (0-100) based on field completeness

Use Cases

Book Recommendation Engines

Build recommendation systems by scraping genres, ratings, and descriptions across thousands of books. Use rating distributions and review text for collaborative and content-based filtering.

Publishing Market Research

Analyze trends in book publishing — which genres are growing, what rating distributions look like across categories, and how page counts correlate with popularity. Track new releases by date.

Author Bibliography Analysis

Scrape complete author bibliographies to analyze output frequency, rating trends over time, genre diversity, and series completion status.

Academic Literature Surveys

Build reading lists for research topics. Scrape books by keyword, filter by publication date, and export structured metadata for citation management tools.

Library Cataloging

Extract ISBNs, titles, authors, page counts, and cover images to build or enrich digital library catalogs. Supports ISBN-10 and ISBN-13 formats.

Bookstore Inventory Enrichment

Enrich product listings with Goodreads ratings, review counts, genres, and descriptions. Match by ISBN for accurate data linkage.

Reading Challenge Tracking

Scrape Goodreads lists and shelves to track popular books, award winners, and trending titles for reading challenges or book clubs.

Content Marketing for Book Blogs

Generate structured data for book review blogs — cover images, descriptions, genre tags, and series info ready for CMS import.

Input Parameters

Parameter	Type	Default	Description
searchQuery	string	"Dune"	Search by title, author, or keyword
startUrls	array	[]	Direct Goodreads URLs (books, lists, shelves, authors)
maxResults	integer	50	Maximum books to scrape (0 = unlimited)
includeDescription	boolean	true	Extract full book description
includeEditions	boolean	false	Extract detailed edition info
includeTopReviews	boolean	false	Extract top community reviews (up to 5)
sortBy	enum	"relevance"	relevance, title, date_published, num_ratings
languageFilter	string	—	Filter by language code (e.g., en, es, fr)
minRating	number	0	Minimum average rating (0-5)
maxPages	integer	0	Maximum page count (0 = no limit)
publishedAfter	string	—	Only books published after this date (YYYY-MM-DD)
publishedBefore	string	—	Only books published before this date (YYYY-MM-DD)
proxyConfiguration	object	—	Apify proxy settings
maxConcurrency	integer	5	Parallel page requests (1-50)
requestTimeout	integer	60	Page load timeout in seconds

Example: Search for Science Fiction

{
    "searchQuery": "best science fiction",
    "maxResults": 100,
    "sortBy": "num_ratings",
    "minRating": 4.0
}

Example: Scrape a Goodreads List

{
    "startUrls": [
        { "url": "https://www.goodreads.com/list/show/1.Best_Books_Ever" }
    ],
    "maxResults": 200,
    "includeTopReviews": true
}

Example: Scrape Specific Books

{
    "startUrls": [
        { "url": "https://www.goodreads.com/book/show/234225.Dune" },
        { "url": "https://www.goodreads.com/book/show/5107.The_Catcher_in_the_Rye" },
        { "url": "https://www.goodreads.com/book/show/4671.The_Great_Gatsby" }
    ],
    "includeDescription": true,
    "includeEditions": true,
    "includeTopReviews": true
}

Example: Author Bibliography

{
    "startUrls": [
        { "url": "https://www.goodreads.com/author/show/3389.Stephen_King" }
    ],
    "maxResults": 50,
    "sortBy": "num_ratings"
}

Example: Recent High-Rated Fantasy

{
    "searchQuery": "fantasy",
    "maxResults": 50,
    "minRating": 4.2,
    "publishedAfter": "2023-01-01",
    "sortBy": "num_ratings"
}

Output

Each book in the dataset contains the following fields:

{
    "title": "Dune",
    "author": "Frank Herbert",
    "authorUrl": "https://www.goodreads.com/author/show/58.Frank_Herbert",
    "rating": 4.27,
    "ratingsCount": 1234567,
    "reviewsCount": 45678,
    "pages": 688,
    "publishDate": "2005-08-02",
    "originalPublishDate": "1965",
    "isbn": "0441013597",
    "isbn13": "9780441013593",
    "genres": ["Science Fiction", "Fiction", "Fantasy", "Classics", "Space Opera"],
    "description": "Set on the desert planet Arrakis, Dune is the story of the boy Paul Atreides...",
    "coverImage": "https://images-na.ssl-images-amazon.com/images/S/compressed.photo.goodreads.com/books/1555447414i/234225.jpg",
    "series": "Dune",
    "seriesPosition": "1",
    "bookUrl": "https://www.goodreads.com/book/show/234225.Dune",
    "goodreadsId": "234225",
    "publisher": "Ace Books",
    "format": "Paperback",
    "language": "English",
    "asin": "0441013597",
    "awards": ["Nebula Award for Best Novel (1965)", "Hugo Award for Best Novel (1966)"],
    "scrapedAt": "2026-03-02T12:00:00.000Z",
    "extractionStrategies": ["json-ld", "dom"],
    "dataQualityScore": 91
}

Output Fields Reference

Field	Type	Description
title	string	Book title
author	string	Author name(s), comma-separated if multiple
authorUrl	string	Link to the author's Goodreads page
rating	number	Average rating (0-5, two decimal places)
ratingsCount	number	Total number of ratings
reviewsCount	number	Total number of text reviews
pages	number	Page count
publishDate	string	Edition publication date (YYYY-MM-DD)
originalPublishDate	string	Original publication date
isbn	string	ISBN-10
isbn13	string	ISBN-13
genres	array	Genre/shelf tags
description	string	Full book description
coverImage	string	High-resolution cover image URL
series	string	Series name (if part of a series)
seriesPosition	string	Position in the series
bookUrl	string	Goodreads book page URL
goodreadsId	string	Goodreads book ID
publisher	string	Publisher name
format	string	Book format (Paperback, Hardcover, Kindle, etc.)
language	string	Book language
asin	string	Amazon ASIN
awards	array	Literary awards (if any)
dataQualityScore	number	Data completeness score (0-100)
scrapedAt	string	ISO timestamp of when the data was scraped

Integration — Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

# Search for books
run = client.actor("sovereigntaylor/goodreads-scraper").call(run_input={
    "searchQuery": "machine learning",
    "maxResults": 50,
    "minRating": 4.0,
    "sortBy": "num_ratings"
})

# Process results
for book in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{book['title']} by {book['author']}")
    print(f"  Rating: {book['rating']}/5 ({book['ratingsCount']} ratings)")
    print(f"  Genres: {', '.join(book.get('genres') or ['N/A'])}")
    print(f"  ISBN: {book.get('isbn13', 'N/A')}")
    print(f"  Pages: {book.get('pages', 'N/A')}")
    print()

Export to CSV

import csv
from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("sovereigntaylor/goodreads-scraper").call(run_input={
    "searchQuery": "best novels 2025",
    "maxResults": 200
})

with open("books.csv", "w", newline="", encoding="utf-8") as f:
    writer = csv.DictWriter(f, fieldnames=[
        "title", "author", "rating", "ratingsCount", "pages",
        "publishDate", "isbn13", "genres", "series", "bookUrl"
    ])
    writer.writeheader()
    for book in client.dataset(run["defaultDatasetId"]).iterate_items():
        book["genres"] = ", ".join(book.get("genres") or [])
        writer.writerow({k: book.get(k) for k in writer.fieldnames})

Integration — JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

// Search for books
const run = await client.actor('sovereigntaylor/goodreads-scraper').call({
    searchQuery: 'machine learning',
    maxResults: 50,
    minRating: 4.0,
    sortBy: 'num_ratings',
});

// Process results
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(book => {
    console.log(`${book.title} by ${book.author}`);
    console.log(`  Rating: ${book.rating}/5 (${book.ratingsCount} ratings)`);
    console.log(`  Genres: ${(book.genres || []).join(', ')}`);
    console.log(`  ISBN: ${book.isbn13 || 'N/A'}`);
});

Webhook Integration

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

// Start with webhook notification
const run = await client.actor('sovereigntaylor/goodreads-scraper').start({
    searchQuery: 'fantasy 2025',
    maxResults: 100,
}, {
    webhooks: [{
        eventTypes: ['ACTOR.RUN.SUCCEEDED'],
        requestUrl: 'https://your-server.com/webhook/goodreads',
    }],
});

console.log(`Run started: ${run.id}`);

Pricing

Pay-per-event pricing — you only pay for data you receive:

• $0.004 per book scraped (full metadata from book page)
• $0.002 per search result scraped (partial data from search listing)

No subscription. No minimum spend. Free tier available for small runs.

Cost Examples

Use Case	Books	Estimated Cost
Quick search (50 books)	50	$0.20
Author bibliography	100	$0.40
Large list scrape	500	$2.00
Genre research	1,000	$4.00
Full catalog export	5,000	$20.00

Tips for Best Results

1. Use proxy — Goodreads rate-limits aggressively. Enable Apify proxy for runs over 20 books.
2. Start small — Test with 10-20 books before running large scrapes.
3. Use direct URLs — If you know the exact books, provide startUrls for faster and more reliable scraping.
4. Filter early — Use minRating, maxPages, and date filters to reduce unnecessary scraping.
5. Low concurrency — Keep maxConcurrency at 3-5 to avoid rate limits.

FAQ

Q: Can I scrape user shelves (e.g., "to-read" lists)? A: Yes. Provide the shelf URL in startUrls, e.g., https://www.goodreads.com/shelf/show/fantasy. Note that private user shelves require authentication and are not supported.

Q: Does it handle series detection? A: Yes. The scraper extracts series name and book position (e.g., "Dune #1") when available on the book page.

Q: What if a book page is missing data? A: The scraper uses four extraction strategies (JSON-LD, Apollo state, DOM, meta tags) and merges results. The dataQualityScore field (0-100) indicates how complete the data is.

Q: Can I filter by genre? A: Not directly in the input (Goodreads search does not support genre filters). Instead, search for genre keywords and use post-processing to filter by the genres array in the output.

Q: How often can I run this scraper? A: As often as needed. Each run is independent. For monitoring, use Apify Schedules to run daily or weekly.

Q: What happens if Goodreads blocks the request? A: The scraper detects CAPTCHAs and block pages, then retries with a different proxy. Configure proxy settings for best results.

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