pricefixed
Open tools to pull every NYC apartment's real price and history out of the walled gardens, plus a standardized public record of every building. Point your AI agent at it and build. The rent is price-fixed; we unfix it.
pricefixed scrapes NYC apartment listings directly from landlords into a local database, tracking real rent prices and history that paid listing sites normally hide.
pricefixed pulls real, up to date rent listings and price history for New York City apartments directly from landlords, instead of relying on paid listing sites like Zillow or StreetEasy where that data stays hidden. The project's stated motivation is that many landlords set rents using shared pricing software such as RealPage's YieldStar, which the Department of Justice has sued over and described as price-fixing, and the author argues you cannot check an algorithm like that without access to the pricing data it uses.
The tool works by scraping landlord-direct feeds, meaning the availability data landlords publish themselves to lease their own units, rather than scraping listing sites. Every run saves a snapshot of prices and lease terms into a plain SQLite database file, so running it repeatedly builds up a price history that listing sites normally do not share. It requires no account, no API key, and no extra Python packages, just Python 3.9 or newer's standard library, and it comes with a command line tool for pulling listings, listing available sources, and checking how many listings are stored.
The database has three tables: current listings with address, bedrooms, price, and square footage; a price history table with one row per snapshot per listing; and a log of when each source was last pulled. As of the README's last update, 11 of 12 landlord and brokerage feeds were reporting as live, covering large portfolios like AvalonBay and Beam Living's StuyTown, leasing platforms like RentCafe, and brokerages like Corcoran and Douglas Elliman, which the README explains also surface listings syndicated through the citywide broker network.
A separate script, build_record.py, builds a standardized public record of every NYC building using New York City's own open data, including ownership, permits, sales, and violations, with no rent data involved. The README explicitly frames the project as a data layer for now, with reverse-engineering the pricing algorithms itself described as a future goal rather than something the current code does. It also invites users to point an AI coding agent at the repo's included guide files to help build custom queries or new data source adapters. No specific software license is mentioned in the README.
Where it fits
- Pull current apartment listings and prices straight from landlord-direct feeds into a local SQLite database.
- Run the scraper on a schedule to build a price history showing how rents change over time for specific units.
- Query the standalone building records dataset for ownership, permits, sales, and violations tied to any NYC building.
- Point an AI coding agent at the repo's guide files to build custom queries or add new data source adapters.