JavaScript SDK

NPM Package

License

Installation

Install the package using npm or yarn:

# Using npm
npm i scrapegraph-js

# Using yarn
yarn add scrapegraph-js

Features

AI-Powered Extraction: Smart web scraping with artificial intelligence
Async by Design: Fully asynchronous architecture
Type Safety: Built-in TypeScript support with Zod schemas
Production Ready: Automatic retries and detailed logging
Developer Friendly: Comprehensive error handling

Quick Start

Basic example

Store your API keys securely in environment variables. Use .env files and libraries like dotenv to load them into your app.

import { smartScraper } from 'scrapegraph-js';
import 'dotenv/config';

// Initialize variables
const apiKey = process.env.SGAI_APIKEY; // Set your API key as an environment variable
const websiteUrl = 'https://example.com';
const prompt = 'What does the company do?';

try {
  const response = await smartScraper(apiKey, websiteUrl, prompt); // call SmartScraper function
  console.log(response.result);
} catch (error) {
  console.error('Error:', error);
}
;

Services

SmartScraper

Extract specific information from any webpage using AI:

const response = await smartScraper(
  apiKey,
  'https://example.com',
  'Extract the main content'
);

Parameters

Parameter	Type	Required	Description
apiKey	string	Yes	The ScrapeGraph API Key.
websiteUrl	string	Yes	The URL of the webpage that needs to be scraped.
prompt	string	Yes	A textual description of what you want to achieve.
schema	object	No	The Pydantic or Zod object that describes the structure and format of the response.

Basic Schema Example

Define a simple schema using Zod:

import { z } from 'zod';

const ArticleSchema = z.object({
  title: z.string().describe('The article title'),
  author: z.string().describe('The author\'s name'),
  publishDate: z.string().describe('Article publication date'),
  content: z.string().describe('Main article content'),
  category: z.string().describe('Article category')
});

const ArticlesArraySchema = z.array(ArticleSchema).describe('Array of articles');

const response = await smartScraper(
  apiKey,
  'https://example.com/blog/article',
  'Extract the article information',
  ArticlesArraySchema
);

console.log(`Title: ${response.result.title}`);
console.log(`Author: ${response.result.author}`);
console.log(`Published: ${response.result.publishDate}`);

Advanced Schema Example

Define a complex schema for nested data structures:

import { z } from 'zod';

const EmployeeSchema = z.object({
  name: z.string().describe('Employee\'s full name'),
  position: z.string().describe('Job title'),
  department: z.string().describe('Department name'),
  email: z.string().describe('Email address')
});

const OfficeSchema = z.object({
  location: z.string().describe('Office location/city'),
  address: z.string().describe('Full address'),
  phone: z.string().describe('Contact number')
});

const CompanySchema = z.object({
  name: z.string().describe('Company name'),
  description: z.string().describe('Company description'),
  industry: z.string().describe('Industry sector'),
  foundedYear: z.number().describe('Year company was founded'),
  employees: z.array(EmployeeSchema).describe('List of key employees'),
  offices: z.array(OfficeSchema).describe('Company office locations'),
  website: z.string().url().describe('Company website URL')
});

// Extract comprehensive company information
const response = await smartScraper(
  apiKey,
  'https://example.com/about',
  'Extract detailed company information including employees and offices',
  CompanySchema
);

// Access nested data
console.log(`Company: ${response.result.name}`);
console.log('\nKey Employees:');
response.result.employees.forEach(employee => {
  console.log(`- ${employee.name} (${employee.position})`);
});

console.log('\nOffice Locations:');
response.result.offices.forEach(office => {
  console.log(`- ${office.location}: ${office.address}`);
});

SearchScraper

Search and extract information from multiple web sources using AI:

const response = await searchScraper(
  apiKey,
  'Find the best restaurants in San Francisco',
);

Parameters

Parameter	Type	Required	Description
apiKey	string	Yes	The ScrapeGraph API Key.
prompt	string	Yes	A textual description of what you want to achieve.
schema	object	No	The Pydantic or Zod object that describes the structure and format of the response

Basic Schema Example

Define a simple schema using Zod:

import { z } from 'zod';

const ArticleSchema = z.object({
  title: z.string().describe('The article title'),
  author: z.string().describe('The author\'s name'),
  publishDate: z.string().describe('Article publication date'),
  content: z.string().describe('Main article content'),
  category: z.string().describe('Article category')
});

const response = await searchScraper(
  apiKey,
  'Find news about the latest trends in AI',
  ArticleSchema
);


console.log(`Title: ${response.result.title}`);
console.log(`Author: ${response.result.author}`);
console.log(`Published: ${response.result.publishDate}`);

Advanced Schema Example

Define a complex schema for nested data structures:

import { z } from 'zod';

const EmployeeSchema = z.object({
  name: z.string().describe('Employee\'s full name'),
  position: z.string().describe('Job title'),
  department: z.string().describe('Department name'),
  email: z.string().describe('Email address')
});

const OfficeSchema = z.object({
  location: z.string().describe('Office location/city'),
  address: z.string().describe('Full address'),
  phone: z.string().describe('Contact number')
});

const RestaurantSchema = z.object({
  name: z.string().describe('Restaurant name'),
  address: z.string().describe('Restaurant address'),
  rating: z.number().describe('Restaurant rating'),
  website: z.string().url().describe('Restaurant website URL')


});

// Extract comprehensive company information
const response = await searchScraper(
  apiKey,
  'Find the best restaurants in San Francisco',
  RestaurantSchema
);

Markdownify

Convert any webpage into clean, formatted markdown:

const response = await markdownify(
  apiKey,
  'https://example.com'
);

Parameters

Parameter	Type	Required	Description
apiKey	string	Yes	The ScrapeGraph API Key.
websiteUrl	string	Yes	The URL of the webpage to convert to markdown.

API Credits

Check your available API credits:

import { getCredits } from 'scrapegraph-js';

try {
  const credits = await getCredits(apiKey);
  console.log('Available credits:', credits);
} catch (error) {
  console.error('Error fetching credits:', error);
}

Feedback

Help us improve by submitting feedback programmatically:

import { sendFeedback } from 'scrapegraph-js';

try {
  await sendFeedback(
    apiKey,
    'request-id',
    5,
    'Great results!'
  );
} catch (error) {
  console.error('Error sending feedback:', error);
}

Support

GitHub

Report issues and contribute to the SDK

Email Support

Get help from our development team

License

Get Started

Services

Official SDKs

Integrations

Contribute

Resources

NPM Package

License

Installation

Features

Quick Start

Basic example

Services

SmartScraper

Parameters

SearchScraper

Parameters

Markdownify

Parameters

API Credits

Feedback

Support

GitHub

Email Support

Get Started

Services

Official SDKs

Integrations

Contribute

Resources

NPM Package

License

​Installation

​Features

​Quick Start

​Basic example

​Services

​SmartScraper

​Parameters

​SearchScraper

​Parameters

​Markdownify

​Parameters

​API Credits

​Feedback

​Support

GitHub

Email Support

Installation

Features

Quick Start

Basic example

Services

SmartScraper

Parameters

SearchScraper

Parameters

Markdownify

Parameters

API Credits

Feedback

Support