# Open Library Books, Authors & ISBN Scraper (`litezero/open-library-books-scraper`) Actor

Extract comprehensive Open Library book metadata, editions, authors, ISBNs, publish years, subjects, ratings, and cover URLs for AI RAG and digital libraries.

- **URL**: https://apify.com/litezero/open-library-books-scraper.md
- **Developed by:** [LiteZero](https://apify.com/litezero) (community)
- **Categories:** Developer tools, AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.70 / 1,000 item scrapeds

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 📚 Open Library Books & Authors Scraper

Extract comprehensive book metadata, edition history, ISBNs, author credits, genres, ratings, and high-resolution cover artwork from the worldwide **Open Library** bibliographic database.

Built for AI engineers building LLM RAG pipelines, digital book clubs, university libraries, and reading recommendation platforms.

***

### 🥊 Why This Actor Beats the Competition

| Feature | 📚 This Actor (`litezero`) | 🐢 Generic HTML Scrapers | 🔒 Goodreads API Alternatives |
|---|---|---|---|
| **Speed** | ⚡ **< 1.5 seconds / query** | 🐌 15–30 seconds / page | ⏳ Blocked or deprecated |
| **Pricing** | 💰 **$1.00 / 1,000 books** (Free Platform Usage) | 💸 Heavy compute bill ($5–$15/run) | 💳 Expensive monthly SaaS |
| **Data Completeness** | 📦 Full ISBNs, Editions, Subjects, Ratings | ⚠️ Flaky CSS selectors | ❌ Limited public access |
| **Anti-Bot Resiliency** | 🛡️ Direct API gateway, zero blocks | 🚫 Frequent 403 / Cloudflare blocks | 🔑 Strict rate limits & API key bans |
| **Setup Friction** | 🚀 **Zero API keys required** | 🛠️ Complex headless browser config | 📝 Lengthy approval process |

***

### 🛠️ Step-by-Step: How to Use

#### Method 1: Apify Web Console (No-Code)

1. Enter your search query (e.g. `artificial intelligence`, `clean code`, or `Stephen King`).
2. Optional: Filter by author name or genre/subject.
3. Select your sort order (`Most Editions`, `Newest`, `Oldest`, or `Relevance`).
4. Click **Start** and download your dataset as JSON, CSV, or Excel.

#### Method 2: Python SDK

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
    "query": "machine learning",
    "sort": "editions",
    "maxResults": 25
}

run = client.actor("litezero/open-library-books-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['title']} by {', '.join(item['author_name'])} ({item['first_publish_year']})")
```

#### Method 3: Node.js SDK

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('litezero/open-library-books-scraper').call({
    query: 'neural networks',
    maxResults: 20
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Extracted ${items.length} books.`);
```

#### Method 4: REST API / cURL

```bash
curl "https://api.apify.com/v2/acts/litezero~open-library-books-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"query": "data science", "maxResults": 10}'
```

***

### 📥 Input Parameters

| Parameter | Type | Required | Default | Description |
|---|:---:|:---:|:---:|---|
| `query` | `string` | **Yes** | `"python programming"` | Search term across titles, subjects, and descriptions. |
| `author` | `string` | No | `""` | Filter results by specific author name. |
| `subject` | `string` | No | `""` | Filter by subject classification (e.g. `computer science`). |
| `sort` | `string` | No | `"editions"` | Sorting: `editions`, `new`, `old`, `relevance`. |
| `maxResults` | `integer`| No | `20` | Maximum number of books to retrieve (1–100). |

***

### 📤 Output Data Dictionary & Sample JSON

```json
{
  "title": "Learning Python",
  "key": "/works/OL45804W",
  "openlibrary_url": "https://openlibrary.org/works/OL45804W",
  "author_name": [
    "Mark Lutz"
  ],
  "first_publish_year": 1999,
  "edition_count": 18,
  "isbn": [
    "9780596158064",
    "0596158066",
    "1565924649"
  ],
  "publisher": [
    "O'Reilly Media",
    "O'Reilly & Associates"
  ],
  "subject": [
    "Python (Computer program language)",
    "Object-oriented programming",
    "Software engineering"
  ],
  "language": [
    "eng"
  ],
  "ratings_average": 4.12,
  "ratings_count": 89,
  "want_to_read_count": 420,
  "currently_reading_count": 65,
  "already_read_count": 140,
  "number_of_pages_median": 1540,
  "cover_url": "https://covers.openlibrary.org/b/id/8315124-L.jpg",
  "scraped_at": "2026-10-04T06:00:00.000Z"
}
```

***

### 💡 Top Commercial Use Cases

1. **AI RAG Knowledge Bases:** Build comprehensive bibliographic knowledge graphs and digital library catalogs for LLM agents.
2. **E-Commerce & Book Arbitrage:** Match ISBNs and editions across marketplaces (Amazon, eBay, AbeBooks) to discover rare book valuation opportunities.
3. **Personalized Reading Apps:** Power book recommendation engines, reading tracking applications, and academic syllabus builders with verified metadata.

# Actor input Schema

## `query` (type: `string`):

Keywords, title, or topic to search across Open Library.

## `author` (type: `string`):

Filter results by specific author name (optional).

## `subject` (type: `string`):

Filter by subject or genre (e.g., 'computer science', 'science fiction').

## `sort` (type: `string`):

Sort criteria for search results.

## `maxResults` (type: `integer`):

Maximum number of books to extract (1 to 100).

## Actor input object example

```json
{
  "query": "python programming",
  "author": "",
  "subject": "",
  "sort": "editions",
  "maxResults": 20
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "python programming",
    "author": "",
    "subject": "",
    "sort": "editions",
    "maxResults": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("litezero/open-library-books-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "query": "python programming",
    "author": "",
    "subject": "",
    "sort": "editions",
    "maxResults": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("litezero/open-library-books-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "python programming",
  "author": "",
  "subject": "",
  "sort": "editions",
  "maxResults": 20
}' |
apify call litezero/open-library-books-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,litezero/open-library-books-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/px3XyCbjPHc3Atgqn/builds/2zVLgmzXZ6jlRsN9I/openapi.json