DH.hu Property Scraper: Extract Real Estate Listings Instantly

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What Is DH.hu?

DH.hu is Hungary's leading online real estate marketplace, hosting thousands of property listings across residential, commercial, and investment categories. The platform aggregates offerings from agents, developers, and private sellers nationwide. Manually extracting property data from search results is tedious and error-prone — the DH.hu Property Scraper automates the workflow, delivering clean, machine-readable records from listing pages in seconds.

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Overview

The DH.hu Property Scraper extracts comprehensive property records from DH.hu search and listing pages, transforming raw web data into 45 structured fields. It is designed for:

• Real estate agents conducting market research and competitor analysis
• Property investors identifying trends and portfolio opportunities
• Data analysts building Hungarian real estate datasets
• Property aggregator platforms feeding data into custom search engines
• Appraisers and valuators gathering comparable sales data

Key strengths include bulk URL support, configurable item limits, and fault tolerance via ignore_url_failures — allowing uninterrupted collection even if some pages fail.

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Input Format

The scraper accepts a JSON configuration object:

{
  "urls": [
    "https://dh.hu/property-for-sale/flat-house?page=2"
  ],
  "ignore_url_failures": true,
  "max_items_per_url": 200
}

Field	Description	Example
urls	Array of DH.hu property list page URLs	["https://dh.hu/property-for-sale/flat-house?page=1"]
max_items_per_url	Maximum properties extracted per URL	200 (default: 20)
ignore_url_failures	If true, scraper continues even if some URLs fail	true

Tip: Use filtered URLs (e.g., by city, property type, price range) to collect targeted datasets. Example: https://dh.hu/property-for-sale/flat?city=budapest&price_from=50000000

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Output Format

Sample output

{
  "address": "2030 Érd Mátyás Király utca  közelében",
  "city_name": "Érd",
  "district_name": null,
  "contract_type_name": "Eladó",
  "property_type_name": "Ház",
  "reference_number": "HZ042590",
  "hide_street": 1,
  "description": "Eladó Érd Tusculánum városrészében egy új építésű, összesen 175 négyzetméter belső hasznos alapterületű családi ház. A 2026-ban épülő ingatlan modern kialakítású, 4 szobával, nappalival és étkezővel rendelkezik, így ideális választás nagyobb családok számára.\r\nAz ingatlan Érd egyik csendes, aszfaltozott utcájában található, amely garantálja a nyugodt és zavartalan otthoni pihenést. A telek teljes közműhálózattal rendelkezik, ovaoda, iskola , tömegközlekedés gyalogosan is elérhető.\r\n\r\nA ház több szempontból is kiváló ajánlat: dupla garázsa biztosítja a kényelmes parkolást akár két autó számára. Az épülethez tartozó telek területe 1 062 négyzetméter, amely bőséges helyet biztosít kertrendezésre vagy akár további építésekhez is. Kulcsrakész ÁR: 169M\r\n",
  "alternative_address": "Mátyás Király utca  közelében",
  "price": "169 000 000 Ft",
  "combined_target_price": "169000000.00",
  "combined_target_price_currency": 3040100000005,
  "combined_target_price_currency_text": "HUF",
  "area": "175",
  "alias": "/property/HZ042590/for-sale-house-pest-county-erd-matyas-kiraly-utca--kozeleben",
  "can_add_to_fav": 1,
  "newly": 0,
  "rooms": 5,
  "bathrooms": 0,
  "cover_image": "https://cdn2.fs2.matrixhu.com/storage/production/fileID/6a292f666d2edc35d15c3f43/fileVersionKey/NhZmQ1NmE1Njc5YjIzZG/fileVersionID/propertyListCard/fileVersionForceKey/b8037fa241cc9d024c2a0d729eaa0dfd",
  "lat": 47.383094574614,
  "lng": 18.901739672123,
  "is_exclusive": false,
  "is_price_drop": false,
  "contracts_id": 19410000259939,
  "is_new": true,
  "combined_target_price_m2_in_huf": null,
  "properties_is_osp": 0,
  "properties_property_type_id": 4080100000002,
  "agent_name": "Nyéki Zoltán",
  "is_newly": false,
  "is_sold": false,
  "is_popular": false,
  "is_coming_soon": false,
  "enabled_otthon_start": false,
  "images": [
    "https://cdn2.fs2.matrixhu.com/storage/production/fileID/6a292f666d2edc35d15c3f43/fileVersionKey/NhZmQ1NmE1Njc5YjIzZG/fileVersionID/propertyListCard/fileVersionForceKey/b8037fa241cc9d024c2a0d729eaa0dfd",
    "https://cdn6.fs2.matrixhu.com/storage/production/fileID/6a292f6f6d2edc35d15c3f44/fileVersionKey/g4ZWQyMzI3ZDVjMmE4Ym/fileVersionID/propertyListCard/fileVersionForceKey/280c94355c7499027afdc49d6377a504",
    "https://cdn4.fs2.matrixhu.com/storage/production/fileID/6a292f746d2edc364970a9e3/fileVersionKey/E0OWRmNTMxNzI2YmE2MD/fileVersionID/propertyListCard/fileVersionForceKey/8b82e56557d55e34978526ac9d8ccd46",
    "https://cdn9.fs2.matrixhu.com/storage/production/fileID/6a292f7a6d2edc34475f3733/fileVersionKey/IyMDIxYWFmNGNmMjZjOD/fileVersionID/propertyListCard/fileVersionForceKey/d64b9debd48dda7d6554b189ccae02a8",
    "https://cdn4.fs2.matrixhu.com/storage/production/fileID/6a292f846d2edc323714dba5/fileVersionKey/NmMDQ4MDhlOTFmYTViMD/fileVersionID/propertyListCard/fileVersionForceKey/d856608694cfcfb4e7aaf404e22dc3c1"
  ],
  "city_filter": "Érd",
  "price_numeric": "169000000",
  "price_original": "169 000 000",
  "price_original_currency": "HUF",
  "favorite": 0,
  "phase_id": null,
  "min_price_orig": null,
  "max_price_orig": null,
  "number_of_properties": null,
  "planned_end_date": null,
  "properties_primary_market_phase_id": null,
  "city_id": null,
  "from_url": "https://dh.hu/property-for-sale/flat-house"
}

Each scraped property returns a rich record with 45+ fields organized by category:

Property Identification & Metadata

Field	Meaning	Use Case
Reference Number	Unique DH.hu property ID	Database key, linking records
Address	Full street address	Geocoding, location verification
Alternative Address	Secondary address format	Display flexibility
Hide Street	Boolean: hides street in listing	Privacy flag for owners
Alias	Property nickname or name	User-friendly reference
City Name	Municipality (e.g., Budapest)	Regional filtering
City ID	Internal city identifier	Database join field
District Name	District/zone (e.g., District 5)	Neighborhood classification
City Filter	Pre-formatted city filter for URLs	URL generation

Property Classification

Field	Meaning	Use Case
Property Type Name	Category (flat, house, land, etc.)	Segment analysis
Properties Property Type ID	Type numeric ID	Data normalization
Contract Type Name	Sale, rent, lease, investment	Market segment
Contracts ID	Contract type numeric ID	Data indexing

Physical Characteristics

Field	Meaning	Use Case
Rooms	Number of bedrooms	Property filtering
Bathrooms	Number of bathrooms	Amenity comparison
Area	Total floor area in m²	Space analysis, price/m² calc
Combined Target Price M2 In HUF	Price per square meter (HUF)	Valuation benchmarking

Pricing & Financial Data

Field	Meaning	Use Case
Price	Listing price (formatted)	Display, comparison
Price Numeric	Price as number (no currency)	Calculations
Price Original	Original listed price	Price change tracking
Price Original Currency	Original price currency code	Multi-currency support
Combined Target Price	Standardized price field	Unified pricing
Combined Target Price Currency	Currency code (HUF, EUR, etc.)	Currency normalization
Combined Target Price Currency Text	Currency label (e.g., "HUF")	Display text
Min Price Orig	Minimum price in range	Price range analysis
Max Price Orig	Maximum price in range	Portfolio pricing
Is Price Drop	Boolean: price recently reduced	Deal alerts

Geographic & Spatial Data

Field	Meaning	Use Case
Latitude	GPS latitude coordinate	Map plotting, proximity search
Longitude	GPS longitude coordinate	Geospatial analysis

Listing Status & Flags

Field	Meaning	Use Case
Is New	Boolean: newly listed property	New inventory alerts
Is Newly	Boolean: newly built/renovated	Property age classification
Newly	Additional new flag variant	Redundancy handling
Is Sold	Boolean: property sold	Inventory status
Is Price Drop	Boolean: price reduced recently	Deal identification
Is Exclusive	Boolean: exclusive listing	Agent comparison
Is Popular	Boolean: trending/popular property	Demand indicators
Is Coming Soon	Boolean: pre-listing status	Future inventory
Enabled Otthon Start	Boolean: featured promotion flag	Marketing tier

Media & Visual Content

Field	Meaning	Use Case
Cover Image	Primary listing photo URL	Thumbnail generation
Images	Array of all property images	Gallery creation

Agent & Seller Information

Field	Meaning	Use Case
Agent Name	Real estate agent name	Agent performance tracking

Description & Content

Field	Meaning	Use Case
Description	Full property description text	Search indexing, SEO

Market & Project Data

Field	Meaning	Use Case
Phase ID	Development phase ID	New project tracking
Properties Primary Market Phase ID	Phase identifier	Project segmentation
Planned End Date	Project completion date	Timeline tracking
Properties Is OSP	Boolean: off-plan property	Investment property flag
Number Of Properties	Count in project	Portfolio size

User Interaction Flags

Field	Meaning	Use Case
Can Add To Fav	Boolean: favorites feature available	UI state
Favorite	Boolean: user marked as favorite	Preference tracking

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How to Use

1. Prepare URLs — Navigate DH.hu to your target search (e.g., flats for sale in Budapest). Copy the page URL.

2. Add filters (optional) — Use DH.hu's filters (price, rooms, area, district) to refine your dataset:

   https://dh.hu/property-for-sale/flat?city=budapest&rooms=2&price_from=50000000&price_to=150000000
   

3. Configure input — Paste URLs into the urls array and set max_items_per_url:

   {
     "urls": ["https://dh.hu/property-for-sale/flat?city=budapest&page=1"],
     "max_items_per_url": 200,
     "ignore_url_failures": true
   }
   

4. Run the scraper — Start execution and monitor progress in the run log.

5. Export results — Download as JSON, CSV, or Excel for analysis or database import.

Best practices:

• Use pagination URLs (?page=1, ?page=2) to collect multi-page datasets.
• Set ignore_url_failures: true for large runs to prevent interruptions.
• Filter by property type or price range to focus your dataset.

Common troubleshooting:

• If no properties appear, verify the URL is a search results page, not a single property detail page.
• Ensure the page has loaded fully before copying the URL.

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Use Cases & Business Value

• Market analysis: Track price trends, inventory levels, and regional demand across Hungary
• Investment intelligence: Identify emerging neighborhoods and portfolio opportunities
• Competitor benchmarking: Monitor agent listings and pricing strategies
• Data aggregation: Feed DH.hu listings into custom property portals and search engines
• Valuation support: Gather comparable sales data for appraisals and market analysis
• Lead generation: Identify high-velocity listings and market-active agents

The DH.hu Property Scraper eliminates hours of manual data gathering, delivering structured records ready for Excel, Python, or database integration. Analysts, investors, and real estate professionals save time while gaining the data advantage.

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Conclusion

The DH.hu Property Scraper is the efficient solution for anyone needing structured Hungarian real estate data. With 45+ output fields covering location, pricing, property details, and market status, it transforms DH.hu's listing pages into actionable insights. Whether you're researching investment opportunities, conducting market analysis, or building a property aggregator, this scraper delivers the data infrastructure to succeed.