Building a Web Scraper for Judicial Debt Records: Step-by-Step Guide
Web scraping judicial records can provide valuable data for background checks and verification processes. This article explains how to create a scraper for checking if individuals have outstanding alimony or child support debts through a judicial system database.
Understanding the Target System
The target website is a judicial database called RELAM (Director of Animal Food) that allows users to search for individuals with alimony debts or judicial retention orders. The system allows searches by name, document number, or file number.
Navigating the Security Barrier
The first challenge is bypassing the site’s CAPTCHA system. Fortunately, this particular implementation is relatively simple – it displays formal letters without special characters or color distortions that would make character recognition difficult.
The Scraping Process
The scraping process follows these key steps:
- Access the main page
- Call the method that generates the CAPTCHA image
- Load the CAPTCHA image into memory
- Use OCR (Optical Character Recognition) to extract the text from the CAPTCHA
- Submit the CAPTCHA solution along with the document number being queried
- Process the JSON response to extract the person’s ID and basic information
- Make a second API call using the extracted ID to get detailed information about the debt
Implementation Details
The scraper makes several API calls to different endpoints:
1. The first call retrieves the CAPTCHA image
2. The second call passes the CAPTCHA solution and document number (DNI) to verify the person’s identity and retrieve their ID in the system
3. The third call uses this ID to retrieve detailed information about any alimony debts, including:
- Judge’s name
- Court case number
- Monthly pension amount
- Currency type
- Additional case details
Practical Applications
This type of scraper can be particularly useful for human resources departments with employee information systems. By integrating this scraping capability, companies can automatically verify if potential or current employees have outstanding judicial obligations for alimony or child support payments.
Handling Multiple Records
In some cases, individuals may have multiple debt records with different dates and pension amounts. The scraper can be configured to return either the first record or a complete list, depending on the specific requirements.
Conclusion
Building a web scraper for judicial debt records requires understanding the target website’s structure, overcoming security barriers like CAPTCHAs, and properly processing the returned data. With the right implementation, this can become a valuable tool for background checks and verification processes.