Homes.com Scraper - Homes For Sale & Rent avatar

Homes.com Scraper - Homes For Sale & Rent

Pricing

from $2.00 / 1,000 per-run start fees

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Homes.com Scraper - Homes For Sale & Rent

Homes.com Scraper - Homes For Sale & Rent

Scrape property listings from Homes.com. Address, asking price, beds, baths, floor area, price per square foot and open-house times, for any city or filtered search.

Pricing

from $2.00 / 1,000 per-run start fees

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Homes.com Scraper

Property listings from Homes.com as a clean table. Give it a city and get back what is on the market there: the full address, the asking price, the bed and bath counts, the floor area, the price per square foot, and the open-house window when one is advertised.

It takes Homes.com's own slug, like new-york-ny or austin-tx, and walks the result pages for you. It also takes a full search URL, so if you have already narrowed a search in the browser to three bedrooms under $800,000, paste that URL and every filter in it is respected.

Both sides of the market come back the same way. listing_type says for sale or for rent on every row, taken from the page rather than guessed from the price, so a mixed search stays sortable.

What you get per listing

  • address, url, property_key, listing_key
  • price, beds, baths, sqft
  • price_per_sqft, worked out for you
  • listing_type, open_house
  • search, search_page, position, and result_count

price_per_sqft is the first thing anyone computes and the easiest to get subtly wrong across a mixed set, so it is done once, here. It is null rather than zero whenever either input is missing.

result_count is the total the search itself reports, which is much larger than what any run returns. New York reports over twenty thousand listings and serves eighteen pages of them. Having both numbers on the row tells you what share of a market you are holding.

Run sizes and paging

Result pages hold forty listings each. Maximum listings caps the run across every location and trims the last page, so asking for 50 costs the same as asking for 80. Maximum pages per location is the rail that stops one large city from consuming a whole run.

A hundred listings takes a few seconds. There is no second request per listing: everything above is on the search page already, so a run is one page load per forty rows and nothing more.

Errors

A location that fails becomes an entry in the errors record rather than a missing set of rows:

CodeMeaning
bad_inputNo location supplied
no_resultsThe location was read and genuinely has no listings
fetch_failedA result page could not be read after several attempts

no_results and fetch_failed are deliberately different. An empty city and a page that would not load look identical if you only count rows, and only one of them is worth rerunning.

A note on reliability

Route access to this site is narrow and can change without warning. If a run suddenly returns fetch_failed across the board where it worked last week, that is what has happened; it is not a bad location. Re-run once, and if it persists, say so rather than working around it.

For US rentals specifically, use Apartments.com Scraper. For homes for sale with MLS numbers and sold history, use Redfin Scraper. For the UK market, use Rightmove Scraper.