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A Python wrapper for the israel Nadlan prices.

Project description

pynadlan

Lightweight async helpers to fetch Israeli real-estate histogram data by city/neighborhood and extract the latest sell/rent prices per room count.

Installation

pip install -e .

Quickstart

import asyncio
from pynadlan.api import get_avg_prices, get_rent_prices, get_autocomplete_lists

async def main():
    query = "רמת גן"  # city or neighborhood

    sell_latest = await get_avg_prices(query)
    # => {"sell_2_price": 2500000, "sell_3_price": 3200000, ...}
    print(sell_latest)

    rent_latest = await get_rent_prices(query)
    # => {"rent_2_price": 6500, "rent_3_price": 7500, ...}
    print(rent_latest)

    # Filter by specific room counts
    print(await get_avg_prices(query, rooms=[3, 4]))
    print(await get_rent_prices(query, rooms=2))

if __name__ == "__main__":
    asyncio.run(main())

API

  • get_avg_prices(query: str, rooms: int | list[int] | None = None) -> dict

    • Returns the latest sell prices keyed by sell_{rooms}_price.
    • If rooms is omitted, returns all available room-based series from the endpoint.
    • If rooms is provided but some series are missing in the payload, they are returned as None.
  • get_rent_prices(query: str, rooms: int | list[int] | None = None) -> dict

    • Returns the latest rent prices keyed by rent_{rooms}_price.
    • Same filtering behavior as get_avg_prices.
  • get_autocomplete_lists() -> dict

    • Returns static lists for autocomplete:
      • cities: array of cities
      • cities_and_neighborhoods: array of cities and neighborhoods

Notes

  • The functions are async and should be awaited.
  • Input query is URL-encoded automatically.
  • Output values are the last value from each histogram series.

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