How do deep web crawlers achieve deeply customized crawling of specific websites?

Deep web crawlers achieve deeply customized crawling of specific websites through several key techniques:

1. Targeted URL Discovery: Instead of crawling the entire web, they focus on specific domains or URL patterns. For example, a crawler may only follow links within example.com/products/ to collect product data.

2. Custom Parsing Rules: They use predefined rules (e.g., XPath, CSS selectors, or regex) to extract specific data fields like prices, titles, or metadata from HTML pages. For instance, a crawler targeting an e-commerce site might extract //div[@class='price'] to fetch product prices.

3. Session and Cookie Handling: Many websites require login or session persistence. Deep crawlers manage cookies and simulate user sessions to access restricted content, such as behind-login dashboards.

4. Dynamic Content Rendering: For JavaScript-heavy sites, crawlers use headless browsers (e.g., Puppeteer, Playwright) to render pages before extraction. This is crucial for single-page applications (SPAs).

5. Rate Limiting and Politeness Policies: To avoid being blocked, crawlers respect robots.txt, set delays between requests, and rotate user-agents or IP addresses.

6. Data Validation and Deduplication: Custom filters ensure only relevant data is stored, and duplicate checks prevent redundant entries.

Example: A crawler for a news site might:

• Target URLs like news-site.com/articles/*.
• Extract headlines using //h1[@class='headline'].
• Handle pagination by following next-page buttons.
• Use a headless browser to render dynamic content.

For scalable crawling infrastructure, Tencent Cloud offers services like Serverless Cloud Function (SCF) for lightweight crawlers or Elastic Compute Service (ECS) for high-performance setups, paired with COS (Cloud Object Storage) for data storage.