Google Maps Scraper

Project Overview

Built a scalable Google Maps data-extraction system for a UK-based Fiverr client. The system used parallel browser workers, multiprocessing, multithreading, rotating proxies, and controlled request scheduling to process approximately 1.5 million business listing records during a one-week production run.

Project Description

A UK-based client needed high-volume Google Maps business listing data collected reliably within a short production window. The scraper was built for production throughput rather than a small one-off extraction.

• Processed approximately 1.5 million business listing records in production.
• Technical approach: used Selenium automation with parallel browser workers, multiprocessing, multithreading, rotating proxies, request scheduling, and structured CSV export.
• Integrated rotating proxies and controlled scheduling to reduce request failures.
• Outcome: completed a one-week production run with improved reliability for long-running extraction.

Technologies Used

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