Hipflat Scraper | Thailand Real Estate

Slug: fatihtahta/hipflat-scraper

Overview

Hipflat Scraper | Thailand Real Estate collects structured property listing records from Hipflat, including listing URLs, titles, pricing, location details, media, property attributes, descriptions, publisher names, and source context when available. Hipflat is a real estate marketplace for Thailand property discovery, making its public listing data useful for market analysis, inventory monitoring, lead qualification, and operational reporting. The actor converts public listing pages into repeatable JSON records that can be used in analytics workflows, enrichment pipelines, dashboards, and downstream systems. It is designed for recurring data acquisition where consistent inputs, structured output, and predictable record envelopes matter. Results reflect the public data available at run time without making claims about full market coverage or guaranteed availability.

Why Use This Actor

• Market research and analytics: build normalized datasets for pricing analysis, supply tracking, location comparison, and property-type segmentation.
• Product and content teams: populate listing experiences, content catalogs, review queues, or property intelligence tools with structured extraction.
• Developers and data engineering teams: feed downstream systems with JSON records that are suitable for ETL, warehouse loading, and automated dataset normalization.
• Lead generation and enrichment teams: identify relevant public listings, publishers, locations, and property attributes for qualification and CRM enrichment pipelines.
• Monitoring and competitive tracking teams: schedule repeatable collection for market intelligence, availability changes, inventory movement, and operational reporting.

Common Use Cases

• Market intelligence: monitor property supply, displayed pricing, locations, bedroom counts, usable area, and listing movement across Thai markets.
• Lead generation: build targeted prospect lists from public real estate listings and publisher information.
• Competitive monitoring: track comparable properties by deal type, geography, property category, price band, and freshness window.
• Catalog and directory building: populate property databases with structured public listing records.
• Data enrichment: add current public listing attributes, coordinates, images, and descriptions to CRM, BI, or analytics datasets.
• Recurring reporting: schedule periodic runs for dashboards, alerts, trend analysis, and market segment snapshots.

Quick Start

1. Choose the transaction intent with deal_type: buy for sale listings or rent for rental listings.
2. Add a location and optional filters such as property_type, price range, room counts, usable area, amenities, freshness, or sort order.
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, fields, and coverage match your workflow.
6. Increase the limit, broaden or narrow filters, enable richer details, or schedule recurring runs once the output is verified.

Input Parameters

The actor accepts Hipflat search criteria for transaction intent, geography, property type, price, layout, size, amenities, freshness, ordering, enrichment, coverage, and result volume.

Parameter	Type	Description	Default
deal_type	string	Commercial intent for the search. Allowed values: buy, rent.	buy
location	string	City, district, neighborhood, province, project area, or other Hipflat-supported location. Leave empty for a broad search without a location boundary.	–
property_type	array of strings	Property categories to include. Allowed values: condo, house, townhouse, apartment, land, office, hotel, commercial, industrial_unit, serviced_apartment, villa. Leave empty to include all supported property types.	–
currency	string	Currency used for displayed prices and price filters. Allowed values: EUR, THB, USD, AED, ARS, AUD, BRL, CAD, CHF, CLP, CLF, CNY, COP, CRC, CZK, DKK, EGP, GBP, HKD, HUF, IDR, INR, JPY, KES, KWD, LBP, MAD, MXN, MYR, NGN, NOK, NZD, OMR, PAB, PEN, PHP, PKR, PLN, QAR, RUB, SAR, SEK, SGD, TND, TRY, TWD, UAH, UYU, VES, VND, ZAR. Leave empty to use Hipflat's default price presentation.	–
min_price	integer	Minimum listing price in the selected currency. Must be 0 or greater. Leave empty for no lower price boundary.	–
max_price	integer	Maximum listing price in the selected currency. Must be 0 or greater. Leave empty for no upper price boundary.	–
bedroom_count	array of strings	Bedroom counts to include. Allowed values: 0 for studio, 1, 2, 3, 4 for 4+ bedrooms.	–
bathroom_count	array of strings	Bathroom counts to include. Allowed values: 1, 2, 3, 4, 5 for 5+ bathrooms.	–
min_usable_area	integer	Minimum usable area in square meters. Must be 0 or greater. Leave empty for no lower size boundary.	–
max_usable_area	integer	Maximum usable area in square meters. Must be 0 or greater. Leave empty for no upper size boundary.	–
amenities	array of strings	Required amenities. Allowed values: cellar, cleaning_room, equipped_bathroom, equipped_kitchen, integral_kitchen, office, service_room, storage_room, children_s_area, gym, jacuzzi, multiuse_room, roof_garden, sauna, swimming_pool, tennis_court, built_in_wardrobe, disabled_access, library, lift, panoramic_view, balcony, garden, green_area, grill, terrace, yard, alarm, guardhouse, security, security_door, concierge, air_conditioning, car_park, electricity, fireplace, heating, internet, natural_gas, video_cable, water, water_tank.	–
publication_date	string	Recent publication window. Allowed values: 24-hours, 7-days, 30-days. Leave empty to include listings regardless of publication date.	–
sort_by	string	Ordering for matching listings. Allowed values: relevance, price_asc, price_desc, bedrooms_asc, bedrooms_desc, usable_floor_area_asc, usable_floor_area_desc, first_publish_date_desc. Leave empty to use Hipflat's standard relevance-based order.	–
maximize_coverage	boolean	Set to true when completeness is more important than speed, especially for broader searches.	false
enrich_data	boolean	Set to true to collect richer listing details such as descriptions, amenities, sizes, coordinates, and addresses when available. Set to false for faster standard records.	false
limit	integer	Maximum number of listings to save. Must be 1 or greater. Leave empty to collect available matches until the run naturally finishes.	–

Choosing Inputs

Use deal_type first to separate sale and rental inventory. Add location when you need a comparable geography, then use property_type, price, room count, usable area, amenity, and publication-date filters to narrow the dataset into a specific market segment. Narrower filters usually produce cleaner, more targeted records for reporting and enrichment; broader filters improve discovery but may require a higher limit and more review. Use sort_by to align collection order with your workflow, such as newest listings for monitoring or price order for valuation review. Start with a small limit, inspect the dataset, then increase coverage once the output quality and scope are confirmed.

Example Inputs

Bangkok condo market validation

{
  "deal_type": "buy",
  "location": "Bangkok",
  "property_type": ["condo"],
  "currency": "THB",
  "min_price": 3000000,
  "max_price": 12000000,
  "limit": 25
}

Recently posted rental monitoring

{
  "deal_type": "rent",
  "location": "Khlong Toei, Bangkok",
  "property_type": ["apartment", "condo"],
  "bedroom_count": ["1", "2"],
  "publication_date": "7-days",
  "sort_by": "first_publish_date_desc",
  "limit": 50
}

Broad discovery with richer details

{
  "deal_type": "buy",
  "location": "Phuket",
  "property_type": ["villa", "house"],
  "currency": "USD",
  "enrich_data": true,
  "maximize_coverage": true,
  "limit": 100
}

Output

Output Destination

The actor writes results to an Apify dataset as JSON records. The dataset is designed for direct consumption by analytics tools, ETL pipelines, and downstream APIs with minimal post-processing.

The example output contains one record shape: a Hipflat property listing. If future runs produce additional record shapes, document each shape separately based on its fields and stable identifiers.

Record Envelope And Stable Identifiers

Each dataset item represents one public Hipflat property listing with record_type set to property_listing. The strongest recommended idempotency key is record_id; entity.url is the next best stable key for deduplication and upserts. Use this key when merging repeated runs into warehouses, CRMs, search indexes, or listing databases. Stable identifiers make records easier to merge, deduplicate, and sync across recurring collection workflows. The source_context.source_url field identifies the source search page or collection scope that produced the listing, while source_context.seed_id and source_context.page_index help preserve run context.

Examples

Example: property listing

{
  "record_type": "property_listing",
  "record_id": "59f351bfb9fe8b17954c",
  "entity": {
    "url": "https://www.hipflat.com/ads/78c9l1208n9284hlc4ucac093u0c3a38",
    "title": "For sale 2 bedrooms apartment in Khlong Toei, Bangkok",
    "description": "Experience a calmer side of Thonglor living at Siri At Sukhumvit, a premium residence located just moments from BTS Thong Lo and Sukhumvit lifestyle hubs."
  },
  "listing": {
    "deal_type": "buy"
  },
  "pricing": {
    "price_text": "USD394,616",
    "price_per_area": "USD5,719/m2"
  },
  "location": {
    "display_text": "Khlong Toei, Bangkok",
    "address": "Siri@Sukhumvit 38 ถนนสุขุมวิท, Phra Khanong, Khlong Toei, Bangkok 10110, THA, Khlong Toei, Bangkok, TH",
    "coordinates": {
      "latitude": 13.7229623,
      "longitude": 100.5799803
    }
  },
  "media": {
    "image_urls": [
      "https://img.hipcdn.com/eyJidWNrZXQiOiJwcmQtbGlmdWxsY29ubmVjdC1iYWNrZW5kLWIyYi1pbWFnZXMiLCJrZXkiOiJpbmdlc3Rlci8wMTllMDIwNy02N2VmLTczZmQtYTRkOS03YmNhZWIxZTJlOWYvNzVjMTE3NzI5YmEwNjY2ZGVmOGRmOWUxMjNjMDQ4ZDYzMjQxZWVlNGY4MTA2Y2IwNzVjMDRlNjNiZmFkODQ5NS5wbmciLCJicmFuZCI6ImhpcGZsYXQiLCJlZGl0cyI6eyJyb3RhdGUiOm51bGwsInJlc2l6ZSI6eyJ3aWR0aCI6MzIwLCJoZWlnaHQiOjI0MCwiZml0IjoiY292ZXIifX19",
      "https://cdn.fazwaz.com/wbr/QsplnzGQ1TBF-YumuwfBrShhOPE/0x0/unit/5870821/23_1.jpg"
    ]
  },
  "property": {
    "property_types": [
      "apartment"
    ],
    "bedrooms": "2",
    "bathrooms": "2",
    "floor_area": "69 m2",
    "amenities": [
      "Air conditioning",
      "Balcony",
      "Equipped kitchen",
      "Service room",
      "Video cable",
      "Parking",
      "Concierge",
      "Gym",
      "Sauna",
      "Security",
      "Swimming pool",
      "Fully furnished"
    ],
    "floor": "6"
  },
  "relationships": {
    "agency": {
      "name": "108Siam Sales and Rentals"
    }
  },
  "source_context": {
    "source_url": "https://www.hipflat.com/property-for-sale/bangkok",
    "seed_id": "57f0477f327a8f64f58c",
    "page_index": 1
  },
  "attributes": {
    "search_result_text": "For sale 2 bedrooms apartment in Khlong Toei, Bangkok USD394,616 Khlong Toei, Bangkok See All Rare Renovated 2BR in Thonglor| Only 200m BTS Thong Lo | Move-In Ready, Contact Us Now! Experience a calmer side of Thonglor living at Siri At Sukhumvit, a premium residence located just moments from BTS Thong Lo and Sukhumvit lifestyle hubs.This fully renovated 2-bedroom, 2-bathroom condo on the 6th floor offers 69.77 sqm of thoughtfully designed living space with peaceful garden and pool views. Positioned on the pool level yet away from the busy gym and common traffic areas, the unit provides a rare balance of greenery, privacy, and city convenience.The spacious living, dining, and kitchen area creates an open atmosphere ideal for both daily living and entertaining. Newly upgraded throughout, the unit includes:Brand-new furnitureNew 55-inch Smart TVLarge sofa with detachable chaise lounge3 new air-conditioning unitsModern teak furnishingsThe kitchen is fully equipped with:Kitchen island with seatingLarge fridge freezer4-hob cooker & extractor hoodMicrowaveWashing machineThe master bedroom features a king-size bed, fitted wardrobes, workspace, and a bathroom with bathtub. The second room can function as a guest bedroom, home office, or creative workspace.Property HighlightsFully renovated in 2025Garden & pool viewsLarge private balconyQuiet and private atmosphereSpacious functional layoutMove-in ready conditionNearby LocationsBTS Thong Lo - ~200 mWells International School- ~800 mEmQuartier - ~1.4 kmJ Avenue Thonglor - ~1.5 kmSukhumvit Hospital - ~1.0 kmIdeal ForExpats seeking a quiet luxury condo in ThonglorCouples or small families wanting comfortable living spaceBuyers looking for a move-in-ready property with long-term valueContact us today to arrange a private viewing. Renovated units with greenery views in Siri At Sukhumvit are rarely available! 2 2 69 m2 Apartment Premium"
  }
}

Field Reference

Property Listing

• record_type (string, required): Stable row discriminator. Property rows use property_listing.
• record_id (string, required): Stable listing identifier suitable for deduplication.
• entity.url (string, required): Public Hipflat listing URL.
• entity.title (string, optional): Listing title or summary.
• entity.description (string, optional): Listing description when enrichment is enabled and available.
• listing.deal_type (string, optional): Listing intent, such as buy or rent.
• pricing.price_text (string, optional): Displayed listing price, including currency formatting.
• pricing.price_per_area (string, optional): Displayed price per area unit when available.
• location.display_text (string, optional): Human-readable listing location.
• location.address (string, optional): Detailed address text when publicly available.
• location.coordinates.latitude (number, optional): Latitude coordinate when available.
• location.coordinates.longitude (number, optional): Longitude coordinate when available.
• media.image_urls (array of strings, optional): Public image URLs associated with the listing.
• property.property_types (array of strings, optional): Property categories associated with the listing or search scope.
• property.bedrooms (string or number, optional): Bedroom count as displayed or normalized from the listing.
• property.bathrooms (string or number, optional): Bathroom count as displayed or normalized from the listing.
• property.floor_area (string or number, optional): Usable floor area text when available.
• property.amenities (array of strings, optional): Listing amenities or property features.
• property.floor (string or number, optional): Floor number or floor label when available.
• relationships.agency.name (string, optional): Public listing publisher, agency, or sales contact name when available.
• source_context.source_url (string, optional): Source search or collection URL that produced the record.
• source_context.seed_id (string, optional): Source seed identifier for run context.
• source_context.page_index (integer, optional): Search result page index associated with the record.
• source_context.search_filters (object, optional): Additional collection-scope filters preserved for audit and replay.
• attributes.search_result_text (string, optional): Consolidated text captured from the listing result or detail context.

Data Quality, Guarantees, And Handling

• Structured records: results are normalized into predictable JSON objects for downstream use.
• Best-effort extraction: fields may vary by region, session, availability, listing type, or Hipflat presentation changes.
• Optional fields: null-check optional fields before loading records into strict schemas or production applications.
• Deduplication: use record_id when present, with url as a fallback key for repeated runs and upserts.
• Freshness: results reflect the publicly available data at run time.
• Repeated runs: use the recommended idempotency key when syncing data into warehouses, CRMs, or search indexes.

Tips For Best Results

• Start with a small limit to validate output shape before scaling up.
• Use one geography or property segment per run when you need cleaner reporting and easier comparison.
• 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 workflows focused on newer inventory.
• Enable enrich_data when descriptions, amenities, addresses, coordinates, and richer details are more important than speed.
• Use record_id or url for deduplication when storing records 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. Open the dataset and inspect the first records.
6. Download results in JSON, CSV, Excel, or another supported format.

Scheduling & Automation

Scheduling

Automated Data Collection

Schedule recurring runs to keep Hipflat listing datasets fresh for monitoring, reporting, enrichment, and market analysis workflows. Use separate schedules for distinct geographies, deal types, or property segments when clean comparison is important.

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

Integration Options

• BI dashboards: monitor pricing, inventory, location coverage, property categories, and listing freshness over time.
• Data warehouses: store recurring listing snapshots for historical analysis, modeling, and operational reporting.
• CRM enrichment: attach public listing, publisher, location, and property attributes to account or lead records.
• Google Sheets or Airtable: review smaller listing sets, qualification queues, and market samples with non-technical teams.
• Webhooks: trigger validation, notification, or ingestion workflows after each completed run.
• Alerts and scheduled reports: notify teams about newly posted listings, segment changes, or high-priority property matches.

Export Formats And Downstream Use

Apify datasets can be exported from the Console or consumed programmatically by downstream systems. Choose the format that fits your review, automation, or reporting workflow.

• JSON: for APIs, applications, and data pipelines
• CSV or Excel: for spreadsheet workflows and manual review
• API access: for automated ingestion into business 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 Hipflat publicly exposes at run time.
• Some optional fields may be missing on sparse listings or listings with limited public detail.
• Very broad searches may take longer or require higher limits to collect enough matching records.
• Target-side changes can affect field availability, naming, or formatting.
• Regional, listing-type, account, or availability differences may change visible results.
• Results should be treated as point-in-time public listing data rather than a guaranteed complete market inventory.

Troubleshooting

• No results returned: check filters, location spelling, property categories, and whether Hipflat has matching public records.
• Fewer results than expected: broaden filters, raise limit, or verify that the selected market contains enough matching listings.
• Some fields are empty: optional fields depend on what each listing 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 Hipflat property listing records, including URLs, titles, prices, locations, images, property details, source context, descriptions, and publisher names when available.

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

Yes. The input supports location, property_type, publication_date, currency, min_price, max_price, bedroom counts, bathroom counts, usable area bounds, amenities, and sort order.

Can I collect sale and rental listings separately?

Yes. Use deal_type with buy for sale listings or rent for rental listings.

Why did I receive fewer results than my limit?

The selected filters may have fewer matching public listings than the requested limit, or some listings may not expose enough usable data at run time.

Can I schedule recurring runs?

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

How do I avoid duplicates across runs?

Use record_id as the preferred idempotency key when present. If record_id is unavailable, use url as the fallback deduplication key.

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

Yes. Apify datasets support JSON, CSV, Excel, and other export formats for manual review, reporting, and downstream ingestion.

Does this actor collect private data?

No. The actor is intended to collect publicly available property listing information from Hipflat.

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 when helpful.

Compliance & Ethics

Responsible Data Collection

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

• Real estate research and market analysis
• Property listing monitoring, enrichment, and reporting
• Sales, leasing, and investment workflows that rely on public market data

Users are responsible for ensuring that their use of collected data complies with applicable laws, regulations, and the target site's terms. 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 section. Include the input used with sensitive values redacted, the run ID, expected versus actual behavior, and a small output sample when it helps explain the issue.