# Goodreads Books & Reviews Scraper (`scrapers_lat/goodreads-scraper`) Actor
Scrape Goodreads books by keyword, book URL, author, list or shelf: ratings, ISBN, genres, series, description and reviews. Export JSON, CSV, Excel.
- **URL**: https://apify.com/scrapers\_lat/goodreads-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** E-commerce, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $6.80 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
[](https://console.apify.com/actors/AFCX31Eip4uIb5gJf/input)
## Goodreads Scraper
> Extract books, ratings and reviews from Goodreads by keyword, book URL, author, Listopia list or shelf, with up to 30 reviews per title
30+ fields per book
Global coverage
JSON / CSV / Excel output formats
Updated 2026-07-26
### What you get
Each record is one book with its full metadata, aggregate ratings and a sample of its most-liked reviews. Feed it search keywords, direct book URLs, an author page, a Listopia list or a shelf, and it returns a clean row per book.
- **imageUrl**: cover image URL
- **title**: book title
- **titleComplete**: title with series and volume, when present
- **url**: Goodreads book page URL
- **bookId**: Goodreads book id
- **workId**: Goodreads work id (shared across editions)
- **authorName**: primary author
- **authorUrl**: primary author profile URL
- **authors**: all credited authors
- **authorFollowers**: primary author follower count
- **authorBooksCount**: number of works by the primary author
- **isbn**: ISBN-10
- **isbn13**: ISBN-13
- **asin**: Amazon ASIN
- **format**: edition format (Paperback, Hardcover, Kindle, Audiobook)
- **pageCount**: number of pages
- **publisher**: publisher of this edition
- **publicationDate**: edition publication date
- **publicationYear**: edition publication year
- **originalPublicationYear**: year the work was first published
- **language**: edition language
- **averageRating**: average star rating
- **ratingsCount**: total number of ratings
- **reviewsCount**: total number of text reviews
- **ratingsCountDist**: rating counts from 1 to 5 stars
- **seriesTitle**: series name, when the book is part of one
- **seriesUrl**: series page URL
- **seriesPosition**: position of the book within the series
- **genres**: reader-assigned genres and shelves
- **awards**: awards won by the work
- **characters**: named characters, when listed
- **places**: settings and places, when listed
- **description**: full book description
- **reviews**: sample of most-liked reviews, each with reviewerName, reviewerUrl, rating, text, date, likes, comments, spoiler flag and review URL
- **reviewsSampleCount**: number of reviews returned for the book
- **observedAt**: when this book was last seen by the scraper
Reviews are included when Include Reviews is on, up to Max Reviews Per Book.
### Who is it for
| Use case | Who benefits |
|---|---|
| Build and enrich a book catalog with ratings and ISBNs | Book apps, libraries, retailers |
| Track ratings and review sentiment for specific titles | Authors, publishers, marketers |
| Pull every book on a Listopia list or shelf | Researchers, data teams |
| Collect an author's full bibliography with metadata | Literary agencies, catalogers |
| Feed book descriptions and reviews into recommendation models | ML and data science teams |
### Frequently Asked Questions
**What can I search on Goodreads with this scraper?**
You can pass search keywords (book titles or author names), direct Goodreads book URLs, an author page or author book list, a Listopia list, or a shelf URL. Any mix works in a single run, and results are combined and de-duplicated up to Max Books.
**How many books can one run return?**
There is no fixed ceiling beyond the Max Books you set. Lists and shelves are paginated automatically, so a single list URL can yield hundreds of books. Free Apify plans are capped at 10 books per run; paid plans are unlimited.
**Can I get the reviews for each book?**
Yes. Turn on Include Reviews and each book comes with a sample of its most-liked recent reviews, including the reviewer name and profile, star rating, full review text, date, and like count. Up to about 30 reviews per book are available.
**Do keyword searches return every matching book?**
Each keyword returns the top matching books ranked by Goodreads relevance. For exhaustive coverage of an author or theme, use the author page, a Listopia list or a shelf URL instead, which the scraper paginates in full.
**What happens when a field is missing for a book?**
Fields that Goodreads does not list for a given title, such as awards, characters or a series, are returned empty rather than guessed. Every record includes an error field that stays empty on success.
### Related scrapers
Need data from the same space? Here are other scrapers we build and maintain:
- [Amazon Product Scraper](https://apify.com/scrapers_lat/amazon-product-scraper): products, prices and ratings from Amazon
- [App Store Reviews Scraper](https://apify.com/scrapers_lat/app-store-reviews-scraper): user reviews and ratings from the Apple App Store
- [Trustpilot Scraper](https://apify.com/scrapers_lat/trustpilot-scraper): business reviews and ratings from Trustpilot
- [arXiv Papers Scraper](https://apify.com/scrapers_lat/arxiv-papers-scraper): research papers with authors and abstracts
- [YouTube Scraper](https://apify.com/scrapers_lat/youtube-scraper): videos, channels and metrics from YouTube
- [Reddit Scraper](https://apify.com/scrapers_lat/reddit-scraper): posts and comments from Reddit communities
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for Latin American and US public platforms: real estate, jobs, e-commerce, company registries and government data. Browse the full catalog, see live sample output for each one, or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
---
> This actor is an independent tool and has no affiliation with Goodreads. It only accesses data that is publicly available on the platform. Use it in accordance with Goodreads's terms of service.
# Actor input Schema
## `maxBooks` (type: `integer`):
Maximum number of books to collect across all inputs. Optional.
## `withReviews` (type: `boolean`):
When enabled, each book includes a sample of its most-liked recent reviews (reviewer, rating, text, date, likes).
## `searchQueries` (type: `array`):
Book titles or author names to search on Goodreads. Each keyword returns the top matching books.
## `bookUrls` (type: `array`):
Direct Goodreads book URLs, e.g. https://www.goodreads.com/book/show/234225.Dune
## `listUrls` (type: `array`):
Goodreads author pages, author book lists, Listopia lists or shelf URLs. Every book on the page (and following pages) is collected up to Max Books.
## `maxReviews` (type: `integer`):
How many reviews to keep per book when Include Reviews is on. Up to about 30 are available per book.
## Actor input object example
```json
{
"maxBooks": 10,
"withReviews": true,
"searchQueries": [
"dune"
],
"maxReviews": 30
}
````
# Actor output Schema
## `results` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxBooks": 10,
"searchQueries": [
"dune"
],
"maxReviews": 30
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/goodreads-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"maxBooks": 10,
"searchQueries": ["dune"],
"maxReviews": 30,
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/goodreads-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"maxBooks": 10,
"searchQueries": [
"dune"
],
"maxReviews": 30
}' |
apify call scrapers_lat/goodreads-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/goodreads-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Goodreads Books & Reviews Scraper",
"description": "Scrape Goodreads books by keyword, book URL, author, list or shelf: ratings, ISBN, genres, series, description and reviews. Export JSON, CSV, Excel.",
"version": "0.1",
"x-build-id": "psbbUQZbZmtgsxCfu"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~goodreads-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-goodreads-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~goodreads-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-goodreads-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~goodreads-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-goodreads-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"maxBooks": {
"title": "Max Books To Scrape",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of books to collect across all inputs. Optional."
},
"withReviews": {
"title": "Include Reviews",
"type": "boolean",
"description": "When enabled, each book includes a sample of its most-liked recent reviews (reviewer, rating, text, date, likes).",
"default": true
},
"searchQueries": {
"title": "Search Keywords",
"type": "array",
"description": "Book titles or author names to search on Goodreads. Each keyword returns the top matching books.",
"items": {
"type": "string"
}
},
"bookUrls": {
"title": "Book URLs",
"type": "array",
"description": "Direct Goodreads book URLs, e.g. https://www.goodreads.com/book/show/234225.Dune",
"items": {
"type": "string"
}
},
"listUrls": {
"title": "Author, List or Shelf URLs",
"type": "array",
"description": "Goodreads author pages, author book lists, Listopia lists or shelf URLs. Every book on the page (and following pages) is collected up to Max Books.",
"items": {
"type": "string"
}
},
"maxReviews": {
"title": "Max Reviews Per Book",
"minimum": 1,
"maximum": 30,
"type": "integer",
"description": "How many reviews to keep per book when Include Reviews is on. Up to about 30 are available per book."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```