Real Estate Listing Scraping | Data Scraping Google Maps

Client Background

A property analytics company needed structured data on rental listings (price, location, amenities) from regional real estate portals.

The Challenge

Listings are loaded via AJAX and require geolocation parameters. Images and floor‑plan URLs had to be captured, too.

Objectives

✦ Scrape listing metadata and media URLs
✦ Geocode addresses
✦ Export to CSV and Postgres

Our Approach

𝐀𝐉𝐀𝐗 π‚π«πšπ°π₯𝐒𝐧𝐠: Intercepted XHR calls; hit JSON endpoints directly to retrieve listing batches
𝐌𝐞𝐝𝐒𝐚 π„π±π­π«πšπœπ­π’π¨π§: Captured image and floor‑plan URLs via BeautifulSoup
π†πžπ¨πœπ¨ππ’π§π : Used a paid API (e.g., Google Maps) to convert addresses to lat/long
πƒπšπ­πšπ›πšπ¬πž 𝐈𝐧𝐠𝐞𝐬𝐭𝐒𝐨𝐧: Steam-cleansed data into PostgreSQL

Results & Impact

✦ Collected 15K+ listings per region per week
✦ Reduced data latency from 48 hours to near‑real time
✦ Enabled new heat‑map visualizations for clients

Tools & Technologies

Python, Requests, BeautifulSoup, SQLAlchemy, Google Maps API

Client Testimonial

β€œExceptional deliveryβ€”our analytics dashboard now updates hourly with fresh listings data.”

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