Use Indian Property Listings Finder by City & BHK with Python

Search sale and rental property listings across 31 Indian cities by BHK, property type, locality and price band, with area, poster identity and listing links for buyers, agents and researchers.

1. Choose the data you need

Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.

2. Prepare a source-based input

This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.

{
  "bedrooms": "Any",
  "city": "Mumbai",
  "furnishing": "Any",
  "includeDetails": false,
  "maxItems": 3,
  "mode": "searchForSale",
  "possessionStatus": "Any",
  "postedSince": "Any",
  "propertyType": "Apartment",
  "sortBy": "Relevance",
  "startUrls": [],
  "tenantType": "Any"
}

Download input.example.json and save your reviewed copy as input.json.

Field	Type	Required	Description
`mode`	string	required	What to collect. Search by city and filters, paste MagicBricks search-result URLs, or paste property-detail URLs.
`startUrls`	array	optional	MagicBricks search-result or property-detail links (mode=bySearchUrl or byPropertyUrl).
`city`	string	optional	Indian city to search (mode=searchForSale, searchForRent, searchProperties).
`localities`	array	optional	Optional locality or neighbourhood names inside the city (mode=searchForSale, searchForRent, searchProperties). One search is run per locality.
`propertyType`	string	optional	Type of property to search (mode=searchForSale, searchForRent, searchProperties).
`bedrooms`	string	optional	Bedroom count. 5+ is sent as 5, the site's maximum (mode=searchForSale, searchForRent, searchProperties).
`priceMin`	integer	optional	Lowest asking price in Indian Rupees (mode=searchForSale, searchForRent, searchProperties).
`priceMax`	integer	optional	Highest asking price in Indian Rupees (mode=searchForSale, searchForRent, searchProperties).
`areaMin`	integer	optional	Smallest covered or carpet area in square feet (mode=searchForSale, searchForRent, searchProperties).
`areaMax`	integer	optional	Largest covered or carpet area in square feet (mode=searchForSale, searchForRent, searchProperties).
`furnishing`	string	optional	Furnishing state filter (mode=searchForSale, searchForRent, searchProperties).
`possessionStatus`	string	optional	Ready-to-move or under-construction filter (mode=searchForSale, searchProperties).
`postedSince`	string	optional	Only listings posted in the last 24 hours (mode=searchForSale, searchForRent, searchProperties). MagicBricks does not expose wider server-side posting windows.
`tenantType`	string	optional	Who the landlord accepts (mode=searchForRent and rent searches in searchProperties). MagicBricks exposes Bachelors and Family server-side.
`sortBy`	string	optional	Order of search results (mode=searchForSale, searchForRent, searchProperties).
`maxItems`	integer	optional	Hard cap on the number of property records returned.
`includeDetails`	boolean	optional	Also open each listing's detail page for project, developer, RERA, full address, GPS, amenities, deposit and maintenance data (search modes).

3. Start an Actor run

Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.

Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.

import json
import os
import urllib.request

# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
    actor_input = json.load(stream)

token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
    "https://api.apify.com/v2/acts/xX3BqO6n2yMRjYlzB/runs?timeout=120&maxTotalChargeUsd=0.50",
    data=json.dumps(actor_input).encode("utf-8"),
    headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
    method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
    run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.

4. Inspect the actual results

Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.

MagicBricks property listings with price, area, BHK, project, RERA, seller, amenities, images and listing URLs.

Questions before you run

Which inputs are required?

The published required fields are mode

What does this guide verify?

The fields, prefills, and schema links are rendered from the published build. This is a usage recipe, not a paid live extraction test. Source availability and collection results can vary.

What if the run request times out?

Check Apify Console before retrying. The first request may already have created a run. Do not automatically repeat a run-creation POST.

Open on Apify Full Actor reference

Generated from source build 9lCmU3P2oSAmJd2ok and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.