Service Company Website Scraper An Apify actor that scrapes service company websites and extracts structured information about the business, including contact information, services offered, hours of operation, and more. ## Features - Extracts company name, description, and contact information - Identifies services offered by the company - Extracts business hours, social media links, and reviews - Finds pricing information and FAQs - Handles multiple URLs in a single run - Supports SSL verification options - Optional Cloudflare bypass capability ## Input The actor accepts the following input parameters: - urls - An array of service company website URLs to scrape (required) - verifySSL - Whether to verify SSL certificates (default: true) - bypassCloudflare - Whether to attempt to bypass Cloudflare protection (default: true) - metadata - Optional custom metadata to include with each result Example input: json { "urls": [ "https://www.example1.com/", "https://www.example2.com/" ], "verifySSL": true, "bypassCloudflare": true, "metadata": { "project_id": "example-project", "source": "manual", "category": "roofing" } } ## Output The actor outputs a JSON object for each URL containing the following information: - url - The URL of the scraped website - title - The title of the website - meta_description - The meta description of the website - main_content - The main content of the website - contact_information - Contact information extracted from the website - phones - List of phone numbers with confidence scores - main_phone - The main phone number with highest confidence - emails - List of email addresses with confidence scores - main_email - The main email address with highest confidence - address - The physical address of the business - services - List of services offered by the company - hours_of_operation - Business hours by day of the week - social_media_links - Links to social media profiles - reviews - Customer reviews found on the website - pricing - Pricing information for services - faqs - Frequently asked questions - success - Whether the scraping was successful - error - Error message if scraping failed ## Example Usage ``javascript const Apify = require('apify'); Apify.main(async () => { const input = { urls: [ "https://www.example1.com/", "https://www.example2.com/" ], verifySSL: true, bypassCloudflare: true, metadata: { project_id: "example-project", source: "manual", category: "roofing" } }; // Run the actor and wait for it to finish const run = await Apify.call('your-username/service-company-scraper', input); // Print the results const dataset = await Apify.openDataset(run.defaultDatasetId); const { items } = await dataset.getData(); console.log('Results:', items); }); ## Development ### Project Structure -main.py- Entry point for the Apify actor -scraper.py- Contains theServiceCompanyScraperclass -requirements.txt- Python dependencies -INPUT_SCHEMA.json- Input schema for the Apify actor -OUTPUT_SCHEMA.json- Output schema for the Apify actor -Dockerfile- Docker configuration for the Apify actor ### Adding New Features To add new extraction capabilities: 1. Add a new method to theServiceCompanyScraperclass inscraper.py2. Call the method from thescrape` method 3. Update the output schema if necessary