Inmuebles24 Scraper

Slug: fatihtahta/inmuebles24-scraper

Overview

Inmuebles24 Scraper collects structured real estate listing records from Inmuebles24, including listing identity, title, description, price, location, property type, seller information, publication details, media availability, and source URLs. Inmuebles24 is one of Mexico's major real estate marketplaces, making its public listing data useful for understanding supply, pricing, geography, and inventory movement across local property markets. The actor turns repeatable searches into normalized JSON records that can be used in analytics, enrichment, monitoring, and operational reporting workflows. It is designed for consistent recurring data acquisition, so teams can run the same collection scope over time and compare results without manually rebuilding datasets. Output is structured for automation and downstream systems while reflecting the public data available at run time.

Why Use This Actor

• Market research and analytics teams: build repeatable market intelligence datasets for pricing, supply, availability, property categories, and geographic coverage.
• Product and content teams: populate property discovery experiences, comparison tools, editorial research, or internal catalogs with normalized listing attributes.
• Developers and data engineering teams: feed structured extraction results into downstream systems, warehouses, enrichment pipelines, and operational reporting jobs.
• Lead generation and enrichment teams: identify public listings, publishers, locations, property characteristics, and contact-ready records for qualification workflows.
• Monitoring and competitive tracking teams: schedule recurring data acquisition to observe listing changes, publication recency, price movement, and segment-level inventory shifts.

Common Use Cases

• Market intelligence: monitor supply, pricing, availability, property types, publication recency, locations, and category movement across Mexican real estate markets.
• Lead generation: build targeted prospect lists from public property listings, publisher profiles, and direct-owner or agency inventory.
• Competitive monitoring: track listing volume, pricing posture, rich-media usage, and new inventory across selected cities, neighborhoods, or seller categories.
• Catalog and directory building: populate internal databases with structured public real estate records and source links.
• Data enrichment: add current public listing attributes, seller details, media indicators, and location metadata to CRM, BI, or analytics datasets.
• Recurring reporting: schedule periodic runs for dashboards, alerts, trend analysis, and operational review.

Quick Start

1. Choose one or more location values to define the geographic scope.
2. Select the relevant deal_type, property_type, price, area, publication date, or seller filters for your use case.
3. Set a small limit for the first validation run.
4. Run the actor in Apify Console.
5. Inspect the first dataset records to confirm the output shape, identifiers, and key fields match your workflow.
6. Increase coverage, broaden or narrow filters, and schedule the actor once the output is verified.

Input Parameters

Configure the available filters below to define the collection scope.

Parameter	Type	Description	Default
location	array of strings	One or more Mexican cities, neighborhoods, municipalities, or states to collect from, such as benito juarez or ciudad de mexico. More specific locations usually produce more focused results.	–
deal_type	string	Transaction category. Allowed values: all, rent, buy, foreclosure, short_term, new_development, lease_transfer.	all
sort_by	string	Result ordering. Allowed values: most_relevant, lowest_price, newest, highest_price, most_viewed, price_reduced, top_sellers.	most_relevant
seller_type	string	Limits results by publisher type. Allowed values: real_estate_agency, direct_listing. Leave empty to include both where available.	–
multimedia	array of strings	Requires selected media types. Allowed values: 360_tour, video, floor_plan.	–
view	string	Property exposure filter. Allowed values: front_facing, interior_facing.	–
building_age	string	Property age or construction stage. Allowed values: under_construction, brand_new, up_to_5_years, up_to_10_years, up_to_20_years, up_to_50_years, over_50_years.	–
publication_date	string	Publication freshness window. Allowed values: since_yesterday, today, last_week, last_15_days, last_30_days, last_45_days.	–
property_type	array of strings	Property categories to include. Allowed values: apartment, house, land_lot, condo_house, commercial_space, commercial_warehouse, zoned_property, shared_apartment, horizontal_development, mixed_development, vertical_development, duplex, building, orchard, urban_income_property, mall_retail_unit, industrial_warehouse, office, country_house, ranch, commercial_land, industrial_land, villa.	–
min_bedroom	string	Minimum bedroom count. Allowed values: 1, 2, 3, 4, 5.	–
max_bedroom	string	Maximum bedroom count. Allowed values: 1, 2, 3, 4, 5.	–
min_bathroom	string	Minimum bathroom count. Allowed values: 1, 2, 3, 4, 5.	–
min_parking	string	Parking requirement. 0 means listings with no parking spaces only; 1, 2, 3, and 4 mean at least that many spaces.	–
min_price	integer	Minimum listing price. Currency follows the listing data returned by Inmuebles24, commonly Mexican pesos where shown as MN. Must be 0 or greater.	–
max_price	integer	Maximum listing price. Currency follows the listing data returned by Inmuebles24, commonly Mexican pesos where shown as MN. Must be 0 or greater.	–
min_building_area	integer	Minimum built or covered area in square meters. Must be 0 or greater.	–
max_building_area	integer	Maximum built or covered area in square meters. Must be 0 or greater.	–
min_land_area	integer	Minimum land or lot area in square meters. Must be 0 or greater.	–
max_land_area	integer	Maximum land or lot area in square meters. Must be 0 or greater.	–
limit	integer	Maximum number of listings to save per location. Leave empty to collect all matching listings the actor can reach. Must be 1 or greater.	–

Choosing Inputs

Use location as the primary scope control, then add filters only when they match a clear business question. Narrower filters such as deal_type, property_type, seller_type, publication_date, price range, area range, bedrooms, bathrooms, parking, media requirements, and building age produce more targeted datasets; broader filters improve discovery and make it easier to understand the full market surface. sort_by affects which matching listings are prioritized first, which is useful when validating a segment or collecting a limited sample. Start with a small limit to confirm output quality, then increase it after checking that the dataset contains the records and fields your workflow needs.

Example Inputs

Recently Posted Rental Monitoring

{
  "location": ["ciudad de mexico"],
  "deal_type": "rent",
  "property_type": ["apartment"],
  "publication_date": "last_week",
  "sort_by": "newest",
  "limit": 50
}

Targeted Buyer Market Analysis

{
  "location": ["benito juarez"],
  "deal_type": "buy",
  "property_type": ["apartment", "condo_house"],
  "min_price": 2500000,
  "max_price": 7000000,
  "min_bedroom": "2",
  "limit": 75
}

Broad Discovery With Rich Media

{
  "location": ["queretaro"],
  "deal_type": "all",
  "multimedia": ["video", "floor_plan"],
  "sort_by": "most_relevant",
  "seller_type": "real_estate_agency",
  "limit": 100
}

Output

Output destination

The actor writes normalized real-estate records into the default Apify dataset. Each row uses a stable envelope and grouped sections for listing metadata, pricing, location, property details, media, contacts, relationships, metrics, and preserved source-specific attributes.

Record envelope (all items)

All records include the following stable envelope fields:

• record_type (string, required): record type. Property rows use property_listing.
• record_id (string, required): source listing/posting identifier preserved as a string.
• source_context.scraped_at (string, required for records): scrape timestamp injected at write time.
• source_context (object, required): source and seed provenance plus listing/search URLs.

Recommended idempotency key: record_type + ":" + record_id.

Use this key for deduplication and upserts when syncing records into databases, warehouses, CRMs, or search indexes. The envelope makes records easier to merge, deduplicate, and sync across repeated runs.

Examples

Example: property listing (record_type = "property_listing")

{
  "record_type": "property_listing",
  "record_id": "148927521",
  "source_context": {
    "source_name": "Inmuebles24",
    "source_domain": "inmuebles24.com",
    "source_site": "inmuebles24",
    "source_site_url": "https://www.inmuebles24.com",
    "listing_url": "https://www.inmuebles24.com/propiedades/clasificado/veclcain-casa-en-venta-en-la-radial-148927521.html",
    "source_url": "https://www.inmuebles24.com/propiedades/clasificado/veclcain-casa-en-venta-en-la-radial-148927521.html",
    "canonical_url": "https://www.inmuebles24.com/propiedades/clasificado/veclcain-casa-en-venta-en-la-radial-148927521.html",
    "search_url": "https://www.inmuebles24.com/busquedas/casas",
    "seed_id": "cdacce2d8bbe",
    "seed_type": "global",
    "seed_value": "all",
    "page_index": 1,
    "scraped_at": "2026-04-27T22:22:02.633049+00:00",
    "external_ids": {
      "posting_id": "148927521",
      "posting_code": "9742472"
    }
  },
  "entity": {
    "title": "Casa en Venta en La Radial",
    "name": "Casa en Venta en La Radial",
    "generated_title": "Casa · 150m² · 3 Recámaras · 2 Estacionamientos",
    "description": "Casa en venta en la Radial, ubicada en privada de siete casas...",
    "url": "https://www.inmuebles24.com/propiedades/clasificado/veclcain-casa-en-venta-en-la-radial-148927521.html",
    "status": "ONLINE",
    "category": "PROPERTY",
    "external_ids": {
      "posting_id": "148927521",
      "posting_code": "9742472"
    }
  },
  "listing": {
    "listing_id": "148927521",
    "posting_code": "9742472",
    "listing_type": "PROPERTY",
    "listing_status": "ONLINE",
    "updated_at": "2026-04-27T17:28:29-04:00",
    "is_new_listing": false,
    "is_featured": true,
    "history": {
      "modified_at": "2026-04-27T17:28:29-04:00"
    }
  },
  "pricing": {
    "operations": [
      {
        "operation_type": {
          "id": 1,
          "name": "Venta"
        },
        "prices": [
          {
            "amount": 3630000,
            "currency": "MN",
            "currency_id": 10
          }
        ]
      }
    ]
  },
  "location": {
    "address": {
      "name": "Camino Real a San Andrés",
      "visibility": "EXACT"
    },
    "hierarchy": [
      {
        "id": "V1-D-79795",
        "name": "San Bernardino Tlaxcalancingo",
        "type": "ZONA",
        "depth": 3
      },
      {
        "id": "V1-C-1822",
        "name": "San Andrés Cholula",
        "type": "CIUDAD",
        "depth": 2
      }
    ],
    "coordinates": {
      "latitude": 19.0362906,
      "longitude": -98.2699108
    }
  },
  "property": {
    "property_type": "Casas",
    "property_type_id": 1,
    "property_taxonomy": {
      "id": 1,
      "name": "Casas"
    },
    "bedrooms": 3,
    "bathrooms": 2,
    "half_bathrooms": 1,
    "floor_area_sqm": 150,
    "built_area_sqm": 150,
    "land_area_sqm": 144,
    "lot_area_sqm": 144,
    "parking_spaces": 2,
    "features": [
      {
        "id": "CFT100",
        "label": "Terreno",
        "value": 144,
        "unit": "m²",
        "category_id": "CFC2"
      }
    ]
  },
  "media": {
    "main_image_url": "https://img10.naventcdn.com/avisos/18/01/48/92/75/21/720x532/1596818174.jpg?isFirstImage=true",
    "pictures": [
      {
        "type_id": 2,
        "order": 0,
        "width": 1280,
        "height": 960,
        "large_url": "https://img10.naventcdn.com/avisos/18/01/48/92/75/21/720x532/1596818174.jpg?isFirstImage=true",
        "medium_url": "https://img10.naventcdn.com/avisos/18/01/48/92/75/21/360x266/1596818174.jpg?isFirstImage=true",
        "title": "Casa · 150m² · 3 Recámaras · 2 Estacionamientos · Casa en Venta en La Radial"
      }
    ],
    "has_videos": false,
    "has_360_tour": false,
    "has_floor_plans": false
  },
  "contact_details": {
    "name": "hh | Luxury Real Estate",
    "phone": "55 1111 2222",
    "phones": [
      "55 1111 2222",
      "55 2222 3333"
    ],
    "emails": ["ventas@hhluxury.com"],
    "contact_url": "https://www.inmuebles24.com/inmobiliarias/hh-luxury-real-estate_50296738-inmuebles.html",
    "websites": [
      "https://www.inmuebles24.com/inmobiliarias/hh-luxury-real-estate_50296738-inmuebles.html"
    ],
    "lead_channels": {
      "show_anonymous_phone_lead": false,
      "whatsapp_posting_lead_enabled": true
    },
    "contacts": {
      "agent": {
        "name": "hh | Luxury Real Estate",
        "phone": "55 1111 2222",
        "partial_phone": "555",
        "whatsapp": "52 55 1111 2222",
        "profile_url": "https://www.inmuebles24.com/inmobiliarias/hh-luxury-real-estate_50296738-inmuebles.html"
      }
    }
  },
  "relationships": {
    "agent": {
      "id": 50296738,
      "name": "hh | Luxury Real Estate",
      "url": "https://www.inmuebles24.com/inmobiliarias/hh-luxury-real-estate_50296738-inmuebles.html",
      "type_id": 2,
      "logo_url": "https://img10.naventcdn.com/empresas/18/00/50/29/67/38/130x70/logo_hh-luxury-real-estate_1770766745996.jpg",
      "premier": true,
      "approved": false,
      "created_at": "2018-11-26T05:00:00+00:00",
      "portal_id": 101
    },
    "agents": [
      {
        "id": 50296738,
        "name": "hh | Luxury Real Estate",
        "url": "https://www.inmuebles24.com/inmobiliarias/hh-luxury-real-estate_50296738-inmuebles.html",
        "type_id": 2,
        "logo_url": "https://img10.naventcdn.com/empresas/18/00/50/29/67/38/130x70/logo_hh-luxury-real-estate_1770766745996.jpg",
        "premier": true,
        "approved": false,
        "created_at": "2018-11-26T05:00:00+00:00",
        "portal_id": 101
      }
    ],
    "broker": {
      "id": 50296738,
      "name": "hh | Luxury Real Estate",
      "url": "https://www.inmuebles24.com/inmobiliarias/hh-luxury-real-estate_50296738-inmuebles.html",
      "type_id": 2,
      "logo_url": "https://img10.naventcdn.com/empresas/18/00/50/29/67/38/130x70/logo_hh-luxury-real-estate_1770766745996.jpg",
      "premier": true,
      "approved": false,
      "created_at": "2018-11-26T05:00:00+00:00",
      "portal_id": 101
    }
  },
  "metrics": {
    "placement": {
      "duplicate_key": "aviso_sinduplicado_148927521"
    }
  },
  "attributes": {
    "source_specific": {
      "publication_area_id": 3,
      "premier": true,
      "features": {
        "summary": {
          "lot_area": 144,
          "built_area": 150,
          "bedrooms": 3,
          "bathrooms": 2,
          "parking_spaces": 2,
          "half_bathrooms": 1
        }
      }
    }
  },
  "fingerprint": "6420605ee90c8fba5da7"
}

Field Reference

• record_type (string, required): stable discriminator. Property rows use property_listing.
• record_id (string, required): source listing identifier.
• source_context (object, required): provenance, source URLs, seed details, and external IDs.
• entity (object, required): title/name, URLs, status/category, and identity fields.
• listing (object, optional): listing lifecycle fields and normalized transaction context.
• pricing (object, optional): grouped price operations and fees.
• location (object, optional): address, hierarchy, and coordinates.
• property (object, optional): normalized physical property characteristics.
• availability (object, optional): availability and booking metadata when present.
• media (object, optional): images/videos/tours and media counters.
• contact_details (object, optional): listing contact names, numbers, channels, and lead fields.
• relationships (object, optional): linked entities such as agent, agents, agency, broker, and profile URLs.
• metrics (object, optional): placement signals, counts, and listing/publication analytics.
• attributes (object, optional): preserved source-specific values including source_specific and raw_attributes.
• fingerprint (string, optional): actor-generated dedupe key.

Data Quality, Guarantees, And Handling

• Structured records: results are normalized into predictable grouped JSON objects.
• Source-variant safe: the same stable groups are used for sale, rent, and development rows when available.
• Optional fields: sparse listings may omit optional sections and values.
• Best-effort extraction: UI changes and missing sections can reduce available values.
• Deduplication: use record_type + ":" + record_id as the recommended idempotency key.
• Freshness: values reflect public data at run time.
• Repeated runs: use the idempotency key when syncing into stores.

Tips For Best Results

• Start with a small limit to validate the output shape before scaling up.
• Use one geography, property segment, or deal type per run when you need cleaner segmentation.
• Leave optional filters empty when the goal is broad discovery.
• Add filters gradually to understand how each field changes coverage.
• Use publication_date and sort_by for monitoring recently posted or recently updated inventory.
• Schedule recurring runs for monitoring workflows instead of relying on manual one-off jobs.
• Use record_type + ":" + record_id for deduplication when storing results over time.

How to Run on Apify

1. Open the Actor in Apify Console.
2. Configure the available input fields for the target scope.
3. Set the maximum number of outputs to collect with limit.
4. Click Start and wait for the run to finish.
5. Download results in JSON, CSV, Excel, or other supported formats.

Scheduling & Automation

Scheduling

Automated Data Collection

Schedule runs to keep real estate listing datasets fresh for monitoring, reporting, enrichment, and recurring analysis. Use a consistent input configuration when you need comparable results across time periods.

• Navigate to Schedules in Apify Console
• Create a new schedule, such as daily, weekly, or custom cron
• Configure input parameters
• Enable notifications for run completion
• Add webhooks for automated processing

Integration Options

• CRM enrichment: sync public listing, publisher, location, and contact attributes into account or lead records.
• BI dashboards: monitor pricing, availability, publication recency, property types, and geographic coverage over time.
• Data warehouses: store repeated runs for historical analysis, deduplication, and long-term trend modeling.
• Google Sheets or Airtable: review smaller listing batches, qualify leads, or share curated market snapshots with operations teams.
• Webhooks: trigger ingestion, validation, notification, or alerting workflows after each completed run.
• Data enrichment pipelines: append current public real estate attributes to existing CRM, analytics, or market intelligence datasets.

Export Formats And Downstream Use

Apify datasets can be exported or consumed by downstream systems, making the actor suitable for both manual review and automated data delivery.

• JSON: for APIs, applications, and data pipelines.
• CSV or Excel: for spreadsheet workflows and manual review.
• API access: for automated ingestion into internal systems.
• BI and warehouses: for reporting, dashboards, and historical analysis.

Performance

Estimated run times:

• Small runs (< 1,000 outputs): ~3–5 minutes
• Medium runs (1,000–5,000 outputs): ~5–15 minutes
• Large runs (5,000+ outputs): ~15–30 minutes

Execution time varies based on filters, result volume, and how much information is returned per record. Highly filtered runs can finish faster, while broad discovery or detail-rich records may take longer.

Limitations

• Availability depends on what https://www.inmuebles24.com publicly exposes at run time.
• Some optional fields may be missing on sparse records or specific listing types.
• Very broad searches may take longer or require higher limits to reach the desired coverage.
• Target-side changes can affect field availability, naming, or visible attributes.
• Regional, account, or availability differences may change visible results.
• Public listings can be modified, removed, reserved, or republished between runs.

Troubleshooting

• No results returned: check filters, location spelling, property category choices, and whether Inmuebles24 has matching public records for the selected scope.
• Fewer results than expected: broaden filters, raise limit, or verify that the target contains enough matching records.
• Some fields are empty: optional fields depend on what each record publicly provides.
• Run takes longer than expected: reduce scope, lower limit for validation, or split broad collection into smaller segments.
• Output changed: compare the current output with the field reference and report a small sample if support is needed.

FAQ

What data does this actor collect?

It collects public Inmuebles24 real estate listing records, including listing identifiers, titles, descriptions, prices, locations, property details, publisher information, publication metadata, media indicators, contact-related public fields, and source URLs.

Can I filter by location, category, date, price, or other criteria?

Yes. The actor supports location, deal type, sorting, seller type, multimedia requirements, view, building age, publication date, property type, bedroom count, bathroom count, parking, price range, building area, land area, and result limit.

Why did I receive fewer results than my limit?

The selected scope may contain fewer public matching listings than the requested limit, or your filters may be narrow. Broaden the input or increase coverage gradually after validating the first results.

Can I schedule recurring runs?

Yes. Use Apify schedules to run the actor daily, weekly, or on a custom cron schedule for monitoring, reporting, and repeated enrichment workflows.

How do I avoid duplicates across runs?

Use record_type + ":" + record_id as the idempotency key when inserting or updating records in your destination system.

Can I export the data to CSV, Excel, or JSON?

Yes. Apify datasets support exports in JSON, CSV, Excel, and other supported formats.

Does this actor collect private data?

The actor is intended to collect publicly available listing information from Inmuebles24. Users are responsible for using the data lawfully and respecting privacy and applicable platform terms.

What should I include when reporting an issue?

Include the input used with any sensitive values redacted, the run ID, expected versus actual behavior, and a small output sample if it helps illustrate the issue.

Compliance & Ethics

Responsible Data Collection

This actor collects publicly available real estate listing information from https://www.inmuebles24.com for legitimate business purposes, including:

• Real estate research and market analysis
• Listing monitoring, pricing analysis, and inventory tracking
• CRM enrichment, lead qualification, and operational reporting

This section is informational and not legal advice.

Best Practices

• Use collected data in accordance with applicable laws, regulations, and the target site's terms.
• Respect individual privacy and personal information.
• Use data responsibly and avoid disruptive or excessive collection.
• Do not use this actor for spamming, harassment, or other harmful purposes.
• Follow relevant data protection requirements where applicable, such as GDPR and CCPA.

Support

For help, use the actor page or Issues. Include the input used with sensitive values redacted, the run ID, expected versus actual behavior, and a small output sample when available. Avoid sharing unnecessary personal data in support requests.