How to Build a Real Estate Comps Engine with Python

Introduction Real estate comparable sales (comps) are the backbone of property valuation. Professional appraisers and investors use comps to determine fair market value, but accessing this data typically requires expensive MLS subscriptions. In this tutorial, we'll build a Python-based comps engine that collects and analyzes property data from public sources. Setup import requests from bs4 import BeautifulSoup import pandas as pd import numpy as np import json import time from datetime import datetime from math import radians , cos , sin , asin , sqrt # Handle real estate site anti-bot protection # Get your API key: https://www.scraperapi.com?fp_ref=the52 SCRAPER_API_KEY = " your_key_here " BASE_URL = " http://api.scraperapi.com " Scraping Property Listings Public county assessor records and listing sites contain property data: def scrape_property_listings ( zipcode , property_type = " single_family " ): """ Scrape property listings from public sources. """ url = f " https://www.realto