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Hemnet.se Scraper: Extract Swedish Real Estate Data Effortlessly

Introduction: Why Scrape Hemnet.se?

Hemnet.se is Sweden's leading property platform, hosting approximately 90% of all properties sold in Sweden and receiving over 40 million visits per month. As the primary marketplace where Swedish real estate agents list properties, Hemnet represents an invaluable data source for anyone involved in the Swedish housing market.

Whether you're a real estate investor analyzing market trends, a property developer conducting competitive research, a financial analyst tracking housing prices, or a data scientist building predictive models, accessing Hemnet's comprehensive property data can provide critical insights. However, manually collecting this information from thousands of listings is time-consuming and inefficient. This is precisely the challenge that the Hemnet.se Scraper addresses—automating the extraction of structured property data at scale.

Overview of the Hemnet.se Property Scraper

The Hemnet.se Scraper is a specialized data extraction tool designed to efficiently collect property listings from Hemnet's platform. This scraper navigates through property search result pages and systematically extracts detailed information about each listing, transforming unstructured web content into organized, actionable data.

Key Features:

• Automated Data Collection: Processes multiple search URLs simultaneously, extracting up to 20 properties per URL by default
• Comprehensive Data Extraction: Captures essential property information including URLs, locations, titles, pricing, attributes, descriptions, tags, broker information, and image galleries
• Residential Proxy Support: Utilizes residential proxies to ensure reliable access and avoid detection as a bot
• Configurable Retry Mechanism: Includes built-in retry logic to handle temporary access issues
• Error Tolerance: Continues processing even when individual URLs fail, maximizing data collection success

Ideal Users:

• Real estate investors and property developers
• Market researchers and financial analysts
• Data scientists building housing market models
• Real estate agencies conducting competitive analysis
• Academic researchers studying housing trends

Input Configuration Explained

Example url 1: https://www.hemnet.se/bostader?expand_locations=50000

Example url 2: https://www.hemnet.se/bostader?location_ids%5B%5D=17835

Example url 3: https://www.hemnet.se/bostader?location_ids%5B%5D=17754

Example Screenshot of property list by query page:

Input Format Specification

The scraper accepts JSON configuration with precise parameters to customize data extraction according to specific requirements. The input structure includes essential settings for proxy configuration, retry mechanisms, and URL specifications.

Example Input Configuration:

{
  "max_retries_per_url": 2, // Maximum waiting time when accessing the links you provided.
  "proxy": { // Add a proxy to ensure that during the data collection process, you are not detected as a bot.
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL" 
    ],
    "apifyProxyCountry": "SG" // You should choose an Country that coincides with the Country you want to collect data from
  },
  "max_items_per_url": 20,
  "ignore_url_failures": true,
  "urls": [ // Links to property list by query pages.
    "https://www.hemnet.se/bostader?expand_locations=50000",
    "https://www.hemnet.se/bostader?location_ids%5B%5D=17835",
    "https://www.hemnet.se/bostader?location_ids%5B%5D=17754"
  ]
}

Parameter Explanations:

• max_retries_per_url (Integer, default: 2): Specifies the maximum number of retry attempts when accessing each URL. Higher values increase reliability but may slow down the scraping process.

• proxy (Object): Proxy configuration to avoid bot detection and ensure successful data collection

  • useApifyProxy (Boolean): Enables the use of Apify's proxy service
  • apifyProxyGroups (Array): Specifies proxy type—RESIDENTIAL proxies are recommended for better success rates
  • apifyProxyCountry (String): Proxy location country code. For Hemnet.se, "SE" (Sweden) is recommended for optimal results, though "SG" (Singapore) can work

• max_items_per_url (Integer, default: 20): Controls how many property listings to extract from each provided URL. Adjust based on your data needs and execution time constraints.

• ignore_url_failures (Boolean, default: true): When enabled, the scraper continues processing remaining URLs even if some fail, ensuring partial data collection rather than complete failure.

• urls (Array of strings): The most critical parameter—an array of Hemnet.se property search result page URLs. These URLs define which properties the scraper will extract.

Comprehensive Output Data Structure

You get the output from the hemnet.se Property Search Scraper stored in a tab. The following is an example of the Information Fields collected after running the Actor.

[ // List of property information
  {
  "url": "https://www.hemnet.se/bostad/lagenhet-3rum-vastra-berga-helsingborgs-kommun-volontarsgatan-5b-21541972",
  "location": "Västra Berga, Helsingborgs kommun",
  "title": "Volontärsgatan 5B",
  "asking_price": "1 395 000 kr",
  "attributes": [
    "1 395 000 kr",
    "78 m²",
    "3 rum",
    "vån 3/3",
    "5 528 kr/mån",
    "17 885 kr/m²"
  ],
  "description": "Välkommen till Västra Berga och denna fantastiska lägenhet på Volontärsgatan 5B! En bostad som verkligen imponerar med sin smarta utformning och omsorgsfulla design, belägen i en mycket stabil och populär förening. Lägenhetens 78 kvadratmeter är skräddarsydda för ett bekvämt vardagsliv med allt du behöver. Det stora köket bjuder in till kulinariska upplevelser i en social tillvaro med en…",
  "tags": [
    "Sön 19 okt kl 16:30",
    "Premium",
    "Balkong"
  ],
  "broker": "Välkommen till Västra Berga och denna fantastiska lägenhet på Volontärsgatan 5B! En bostad som verkligen imponerar med sin smarta utformning och omsorgsfulla design, belägen i en mycket stabil och populär förening. Lägenhetens 78 kvadratmeter är skräddarsydda för ett bekvämt vardagsliv med allt du behöver. Det stora köket bjuder in till kulinariska upplevelser i en social tillvaro med en…",
  "images": [
    "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7",
    "https://bilder.hemnet.se/images/itemgallery_cut/9d/f6/9df6e74437e63edb8ce415f6e0f22669.jpg",
    "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7",
    "https://bilder.hemnet.se/images/itemgallery_cut/f8/d9/f8d90e338b3c810a5e0179954d5d3d6d.jpg",
    "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7",
    "https://bilder.hemnet.se/images/itemgallery_cut/cb/f0/cbf0b337641ece46208180e68c1f6464.jpg",
    "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7",
    "https://bilder.hemnet.se/images/itemgallery_cut/c8/a9/c8a9ffc8adc097a0db3fe563c730ff62.jpg",
    "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7",
    "https://bilder.hemnet.se/images/itemgallery_cut/47/9d/479d37cbd1a600d8ed0c70fb57491e69.jpg",
    "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7",
    "https://bilder.hemnet.se/images/broker_logo_2_2x/9a/7d/9a7d81a753c38de8c339f134145f40eb.jpg",
    "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7",
    "https://bilder.hemnet.se/images/broker_logo_2_2x/9a/7d/9a7d81a753c38de8c339f134145f40eb.jpg"
  ],
  "from_url": "https://www.hemnet.se/bostader?expand_locations=50000"
}, // ... Many other property details
]

Output Fields Explained

1. URL (String)

• Description: The direct link to the property listing on Hemnet.se
• Purpose: Provides a reference to view the original listing or verify scraped data
• Example: "https://www.hemnet.se/bostad/villa-5rum-stockholm-12345"
• Use Case: Link tracking, data verification, follow-up research

2. Location (String/Object)

• Description: Geographic location of the property, typically including city, district, or neighborhood
• Purpose: Essential for geographic analysis, market segmentation, and location-based filtering
• Example: "Östermalm, Stockholm" or "Göteborg, Västra Götalands län"
• Use Case: Location-based price analysis, neighborhood comparisons, geographic market research

3. Title (String)

• Description: The property listing headline, usually containing property type, size, and location
• Purpose: Quick identification of property characteristics
• Example: "Ljus 3:a med balkong i centrala Stockholm" (Bright 3-room apartment with balcony in central Stockholm)
• Use Case: Property categorization, text analysis, headline trend identification

4. Asking Price (Number/String)

• Description: The listed price of the property in Swedish Kronor (SEK)
• Purpose: Core data point for pricing analysis, market valuation, and investment decisions
• Example: 4500000 (4.5 million SEK)
• Use Case: Price tracking, comparative market analysis, ROI calculations, trend forecasting

5. Attributes (Object/Array)

• Description: Structured property characteristics such as number of rooms, living area, plot size, property type, energy rating, monthly fees (for apartments)
• Purpose: Detailed property specifications for filtering and comparison
• Use Case: Feature-based filtering, correlation analysis (e.g., price per square meter), property type segmentation

6. Description (String)

• Description: Full-text property description provided by the broker or seller
• Purpose: Qualitative information about property features, condition, amenities, and neighborhood
• Example: Text describing renovations, views, proximity to transportation, schools, shopping
• Use Case: Natural language processing, sentiment analysis, feature extraction, amenity identification

7. Tags (Array of Strings)

• Description: Categorical labels assigned to properties highlighting special features
• Purpose: Quick identification of notable property characteristics
• Example: ["Balkong", "Hiss", "Nyproduktion", "Havsutsikt"] (Balcony, Elevator, New construction, Sea view)
• Use Case: Feature-based searches, trend analysis of popular amenities, targeted property identification

8. Broker (Object)

• Description: Information about the real estate agent or agency handling the property

• Purpose: Broker identification, agency analysis, agent performance tracking

• Use Case: Broker network mapping, agency market share analysis, contact information for follow-up

9. Images (Array of Strings)

• Description: URLs to property images and photos
• Purpose: Visual data for image analysis, property visualization, or archival purposes
• Example: Array of image URLs from the property listing gallery
• Use Case: Computer vision analysis, visual property comparison, marketing material, archival documentation

How to Use the Hemnet.se Scraper

Step-by-Step Guide

Step 1: Prepare Your Search URLs

• Navigate to Hemnet.se and perform your desired property searches
• Copy the URL from each search result page you want to scrape
• Compile these URLs into an array for the input configuration

Step 2: Configure Input Parameters

• Set max_items_per_url based on how many properties you need per search
• Configure proxy settings—use residential proxies and preferably Swedish location
• Set max_retries_per_url (2-3 is typically sufficient)
• Enable ignore_url_failures to ensure partial success even if some URLs fail

Step 3: Execute the Scraper

• Submit your configuration to the scraping platform
• Monitor the execution progress
• Review logs for any errors or warnings

Step 4: Process and Analyze Output

• Export the resulting data in your preferred format (JSON, CSV, Excel)
• Validate data quality and completeness
• Import into your analysis tools or database

Tips and Best Practices

Optimization Tips:

• Start with a small number of URLs to test your configuration
• Use specific location filters to avoid collecting irrelevant properties
• Schedule scraping during off-peak hours for better performance
• Implement rate limiting if scraping large volumes

Common Issues and Solutions:

• Issue: Proxy blocks or access denied

  • Solution: Switch to residential proxies with Swedish location

• Issue: Incomplete data extraction

  • Solution: Increase max_retries_per_url or verify URL validity

• Issue: Duplicate entries

  • Solution: Review your URL list for overlapping search parameters; implement deduplication based on property URL

• Issue: Missing images

  • Solution: Some properties may have restricted image access; this is expected behavior

Legal and Ethical Considerations:

• Respect Hemnet's Terms of Service and robots.txt directives
• Implement appropriate rate limiting to avoid overwhelming the server
• Use collected data responsibly and in compliance with GDPR and Swedish data protection laws
• Do not republish scraped content without proper authorization

Benefits and Use Cases

Time Efficiency

Manual collection of property data from hundreds of listings could take days or weeks. The Hemnet.se Scraper automates this process, collecting comprehensive data in minutes or hours depending on volume.

Real-World Applications

Real Estate Investment Analysis:

• Track property price trends across different Stockholm neighborhoods
• Identify undervalued properties by comparing asking prices with area averages
• Monitor new listings matching specific investment criteria

Market Research:

• Analyze pricing strategies of different real estate agencies
• Study the correlation between property features and asking prices
• Generate comprehensive market reports for specific regions

Competitive Intelligence:

• Monitor competitor property listings and pricing strategies
• Analyze broker market share and specialization
• Track property time-on-market and price adjustments

Data Science and Predictive Modeling:

• Build machine learning models for property valuation
• Predict market trends based on historical listing data
• Perform sentiment analysis on property descriptions

Business Intelligence:

• Generate automated market reports for stakeholders
• Create data visualizations of housing market trends
• Support strategic decision-making with current market data

Conclusion

The Hemnet.se Scraper transforms the challenging task of collecting Swedish real estate data into an automated, efficient process. By providing access to comprehensive property information from Sweden's dominant real estate platform, this tool empowers investors, researchers, and businesses to make data-driven decisions in the Swedish housing market.

With approximately 90% of Swedish properties listed on Hemnet, scraping this platform gives you access to near-complete market coverage. Whether you're tracking market trends, conducting investment analysis, or building sophisticated property valuation models, the Hemnet.se Scraper provides the foundation for powerful real estate intelligence.

Ready to start extracting Swedish property data? Configure your scraper with the appropriate search URLs and proxy settings, and gain immediate access to one of Europe's most transparent and data-rich real estate markets.

Your feedback

We are always working to improve Actors' performance. So, if you have any technical feedback about hemnet.se Property Search Scraper or simply found a bug, please create an issue on the Actor's Issues tab in Apify Console.