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Redfin Data Access Guide

Overview

Redfin provides two main methods for accessing listing data programmatically: RSS feeds and JSON/CSV APIs. This guide documents both approaches.

Method 1: RSS Feed (Newest Listings)

Format

https://www.redfin.com/stingray/[region_type]/[region_id]/newest_listings.rss

Example

https://www.redfin.com/stingray/6/4664/newest_listings.rss

Parameters

  • region_type: Numeric code for the region type
    • 2 = Zip code
    • 6 = City
    • (other types exist for neighborhoods, counties, etc.)
  • region_id: Unique identifier for the region (found in the Redfin URL)

How to Find Your Parameters

  1. Navigate to your desired location on Redfin (e.g., https://www.redfin.com/city/4664/OH/Columbus)
  2. Extract region_id from the URL (the number after /city/ or /zip/)
  3. Extract region_type (typically 6 for cities, 2 for zip codes)

Limitations

  • ⚠️ Does NOT support filters (price, beds, baths, property type, etc.)
  • Returns all new listings in the region
  • RSS format (XML)

Source

Found in Redfin's robots.txt:

Allow: /stingray/*/*/newest_listings.rss

Method 2: Stingray GIS-CSV API (Recommended)

Format

https://www.redfin.com/stingray/api/gis-csv

Example Request

import requests
import pandas as pd
from io import StringIO

params = {
    'al': 1,                    # Include additional listing data
    'market': 'columbus',       # Market area
    'max_price': 600000,        # Maximum price
    'min_beds': 3,              # Minimum bedrooms
    'min_baths': 2,             # Minimum bathrooms
    'num_homes': 350,           # Number of results to return
    'page_number': 1,           # Page number for pagination
    'region_id': 4664,          # Region ID (from URL)
    'region_type': 6,           # Region type (6 = city)
    'uipt': '1,2,3',           # Property types: 1=house, 2=condo, 3=townhouse
    'v': 8                      # API version
}

response = requests.get(
    'https://www.redfin.com/stingray/api/gis-csv',
    params=params,
    headers={'User-Agent': 'Mozilla/5.0'}
)

# Parse CSV response
df = pd.read_csv(StringIO(response.text))
print(f"Found {len(df)} listings")

Key Parameters

Parameter Description Example Values
region_id Unique region identifier 4664 (Columbus)
region_type Type of region 2 (zip), 6 (city)
market Market area columbus, sfbay, dc
min_beds Minimum bedrooms 3
max_beds Maximum bedrooms 5
min_baths Minimum bathrooms 2
max_baths Maximum bathrooms 3
min_price Minimum price 200000
max_price Maximum price 600000
uipt Property types (comma-separated) 1,2,3 (house, condo, townhouse)
num_homes Results per page 350
page_number Page number 1, 2, 3...
status Listing status 9 (active)
v API version 8

Property Type Codes (uipt)

  • 1 = House
  • 2 = Condo
  • 3 = Townhouse
  • 4 = Multi-family
  • 5 = Land
  • 6 = Other

Response Format

Returns CSV data with columns including:

  • ADDRESS
  • CITY
  • STATE OR PROVINCE
  • ZIP OR POSTAL CODE
  • PRICE
  • BEDS
  • BATHS
  • PROPERTY TYPE
  • SQUARE FEET
  • LOT SIZE
  • YEAR BUILT
  • DAYS ON MARKET
  • URL (SEE https://www.redfin.com/buy-a-home/comparative-market-analysis FOR INFO ON PRICING)
  • And many more...

Advantages

  • ✅ Supports all filters (price, beds, baths, property type, etc.)
  • ✅ Returns structured CSV/JSON data
  • ✅ Supports pagination for large result sets
  • ✅ More comprehensive property information

Source

Discovered through reverse engineering Redfin's web application network requests. Documented in various GitHub repositories:

Alternative: Gemini's "Stingray RSS-Search" Endpoint

Format

https://www.redfin.com/stingray/do/rss-search?region_id=[ID]&region_type=[TYPE]&market=[MARKET]

Example

https://www.redfin.com/stingray/do/rss-search?region_id=4664&region_type=6&market=columbus

Status

  • ⚠️ Unverified - This endpoint is mentioned in community discussions but not officially documented
  • ⚠️ May not support filters (similar to the newest_listings.rss feed)
  • Use at your own risk; may be deprecated or rate-limited

Best Practices

  1. Always include a User-Agent header to avoid being blocked

    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'}

  2. Respect rate limits - Add delays between requests

    import time
time.sleep(1)  # Wait 1 second between requests

  3. Use the GIS-CSV API for filtered searches - It's more powerful and returns complete data

  4. Use RSS feeds for simple "newest listings" monitoring - When you don't need filters

  5. Check Redfin's Terms of Service - Ensure your use case complies with their policies

Recommendation

For your house hunting tool with filters (max-price=600k, min-beds=3, min-baths=2, etc.), use the Stingray GIS-CSV API (Method 2). It supports all your filters and returns structured data that's easy to parse and filter further in your application.