Case study 🗂️ 8 min read

mieszkania20.pl

We developed a sophisticated web scraper that bypasses anti-scraping mechanisms to collect real estate data from various platforms, including Poland's land and mortgage register (księgi wieczyste).

2Month in development

2Team members

100%Scraping accuracy

100%Client satisfaction

Problem to solve

Real Estate Data Collection: Mieszkania20 needed a robust web scraper capable of bypassing anti-scraping measures to collect real estate data from multiple platforms, including the Polish land and mortgage register (księgi wieczyste), while ensuring high accuracy and efficiency.

Scope of work

Development

We built a web scraper designed to bypass anti-scraping protections and collect data from real estate platforms, including Poland's land and mortgage register.

Optimization

We optimized the scraper for data accuracy, speed, and error handling, ensuring it operates reliably even in the face of security measures.

Integration

We integrated the scraper with multiple real estate platforms, ensuring seamless API connections and efficient data processing pipelines.

Outcomes

The web scraper we developed for Mieszkania20 efficiently bypasses anti-scraping mechanisms, allowing the platform to gather accurate and up-to-date property data, including crucial information from Poland's land and mortgage register (księgi wieczyste). This has significantly enhanced their ability to provide real-time property listings.

The scraper's ability to collect accurate data despite anti-scraping measures has transformed our operations, giving us access to critical real estate information in real-time.

Pawel Kubacki

CEO, mieszkania20.pl

Conclusion

The web scraper we built for Mieszkania20 has revolutionized their data collection process by bypassing anti-scraping measures and integrating crucial real estate data from platforms, including Poland's land and mortgage register. This solution has greatly improved data accuracy and operational efficiency, making it an essential tool for their real estate business.

Technologies used

We applied our expertise in the following technologies:

Python3

Flask

Selenium

Scrapy

Redis

RabbitMQ

JavaScript

Bootstrap 5

Docker

Kubernetes

OpenShift

Proxmox VE

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