Redfin: scrapers and the official API, compared

Route map

Each line is one way to get Redfin data; each stop is a field you probably need. Green lines are catalogue Actors, ranked by the published formula.

Field matrix: who returns what

Every tool with a published output schema, against the 7 fields most Redfin jobs need. A dot means the field name appears in the schema; rows can still leave it empty.

Field dictionary: the exact keys

The same core field has a different key in each Actor's output. Map these before you merge datasets; a dash means the published schema has no matching key. Need a field that is not listed here, such as email? Search every Redfin Actor by field.

Download this comparison: CSV · JSON (every tool with a published schema, matching keys per core field, price and score).

All 9 tools, scored

Catalogue Actors link to their detail pages; the score (0 to 100) is the published formula, identical for every tool. Other Store tools follow in their own table, for reference. Price is the published primary-result rate per 1,000 (the Free-plan rate where the price is tiered; higher Apify plans pay less); start events and platform usage are excluded.

Other Store tools, for reference

Scored with the same published formula and listed for comparison only; this site does not link or recommend them.

What to check before you choose

Teams use Redfin data to monitor property availability, compare asking prices and study sale and rental markets. Keep sale, rental and sold listings separate so each comparison reflects the same kind of transaction.

Aggregate downloads suit market trend analysis. A listing scraper fits work that needs individual properties, source links and details that can be compared across saved datasets.

Checklist

• Confirm coverage for the listing types you need. The published schema includes price, soldPrice and rentPrice, so establish which value applies to each record.
• Check field mappings before combining datasets: beds, baths, sqft and soldDate differ from the reference fields bedrooms, bathrooms, area and sold_date.
• Check how the tool handles geographic boundaries and repeated listings. Retain url to help review records that appear in overlapping searches.

Where the data is incomplete

The published schema lists sale, rental and sold fields, but its field descriptions do not explain when those fields are populated.

Aggregate market downloads do not supply individual listing records. The published data also provides no sample dataset for checking address completeness, missing sold dates or differences between price and soldPrice.

Official API route

Terms and personal data

Redfin's terms and MLS or brokerage rules may restrict reuse of listing data. Review those restrictions before sharing or republishing a dataset. This is general information, not legal advice.

Read Redfin's terms. Keep to public data, do not bypass logins or access controls, and check whether personal data is involved before you collect it. The can-I-scrape checklist walks through it.

How to start

1. Open the recommended Redfin tool and check its documented inputs for a small geographic area and a single listing type.
2. Submit a limited request using that input format, then inspect the returned records against their Redfin pages.
3. Check address, price and url, review the relevant sale or rental fields, and save the dataset with a collection note before expanding the search.

Call Redfin Sale, Rental & Sold Listings Scraper from code

The example input uses the Actor's published defaults; set your own Redfin query before you run it. You need an Apify API token.

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run_input = {
    "mode": "forSale",
    "location": "Austin, TX",
    "propertyType": "all",
    "soldWithinDays": "180",
    "sort": "recommended",
    "maxItems": 3,
    "includeDetails": False
}

run = client.actor("nimbryxo-studio/redfin-sale-rental-and-sold-listings-scraper").call(run_input=run_input)
if run is None:
    raise RuntimeError("The Actor run was not found.")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });
const input = {
    "mode": "forSale",
    "location": "Austin, TX",
    "propertyType": "all",
    "soldWithinDays": "180",
    "sort": "recommended",
    "maxItems": 3,
    "includeDetails": false
};

const run = await client.actor("nimbryxo-studio/redfin-sale-rental-and-sold-listings-scraper").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

curl -X POST "https://api.apify.com/v2/actors/nimbryxo-studio~redfin-sale-rental-and-sold-listings-scraper/run-sync-get-dataset-items"   -H "Authorization: Bearer $APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"mode":"forSale","location":"Austin, TX","propertyType":"all","soldWithinDays":"180","sort":"recommended","maxItems":3,"includeDetails":false}'

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=nimbryxo-studio/redfin-sale-rental-and-sold-listings-scraper",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Questions people ask

More on Redfin

• Country comparisonUS real estate data: five listing sources compared
• Topic groupReal estate data: every website compared
• ToolWhich Redfin route fits your job?
• ToolRedfin cost by Apify plan, rows and runs

Related websites

• Zillow8 Actors
• Realtor.com1 Actor

Sources

• Redfin Sale, Rental & Sold Listings Scraper on Apify Store
• Redfin Data Center (aggregates only) documentation
• Redfin terms