Forem: MAYNO

How to Scrape Swedish Real Estate Data from Hemnet (No Code, No API)

MAYNO — Thu, 30 Apr 2026 14:53:30 +0000

Extract property listings, prices, agent contacts, and more from Sweden's #1 real estate platform in minutes.

If you've ever tried to get structured data from Hemnet.se — Sweden's dominant real estate marketplace with over 90% market share — you've probably hit the same wall: there is no official Hemnet API.

No developer portal. No API keys. No documentation.

Yet investors, PropTech startups, market researchers, and real estate agencies all need this data. They need prices, addresses, agent contacts, property sizes, and viewing dates — at scale, in a format they can actually work with.

This article shows you exactly how to get it.

What Is Hemnet?

Hemnet is Sweden's largest real estate platform. If a property is for sale in Sweden, it's almost certainly listed on Hemnet. That near-total market dominance makes it the single most valuable source of Swedish housing market data.

A typical listing includes:

Property details: type (Villa, Lägenhet, Radhus), rooms, living area (m²), land area, year built, floor
Location: address, neighborhood, city (kommun), county (län), distance to coast
Financial data: asking price (SEK), price per m², monthly fee (Avgift), annual running costs
Agent information: agent name, agency, phone number, email
Media: property images, full description, upcoming viewing dates

The problem is that none of this is accessible through an API. Hemnet is a consumer-facing website — not a data platform. To extract this data programmatically, you need a scraper.

Why Not Just Write Your Own Scraper?

You could. But there are real challenges:

Bot detection. Hemnet uses anti-bot protection. A naive scraper will get blocked within minutes. Handling this properly requires proxy rotation, realistic browser headers, and rate limiting — all of which add significant complexity.

Maintenance. When Hemnet updates their site (which they do), your scraper breaks. You're now on the hook for keeping it working.

Infrastructure. Running scrapers at scale requires servers, scheduling, monitoring, and storage. That's a project in itself.

For most use cases — market research, investment analysis, lead generation, building a product — the better approach is to use a pre-built, maintained scraper that handles all of this for you.

The Solution: Hemnet Scraper on Apify

Apify is a web scraping and automation platform that hosts thousands of pre-built scrapers called "Actors." The Hemnet Scraper actor extracts property listings from Hemnet.se with no code, no infrastructure, and no maintenance on your end.

Actor link: apify.com/mayno/hemnet-scraper

Here's what you get per listing:

{
  "id": "21538498",
  "url": "https://www.hemnet.se/bostad/lagenhet-3rum-...",
  "scraped_at": "2026-04-28T18:30:00.000Z",

  "location": {
    "address": "Karlslundsvägen 15",
    "neighborhood": "Barkarbystaden",
    "city": "Järfälla kommun",
    "county": "Stockholms län",
    "distance_to_coast_m": null
  },

  "property_details": {
    "title": "Lägenhet i Barkarbystaden",
    "type": "Lägenhet",
    "tenure": "Bostadsrätt",
    "rooms": 3,
    "living_area_sqm": 74,
    "year_built": 2021,
    "amenities": ["Balkong", "Fiber", "Hiss"]
  },

  "financials": {
    "asking_price_sek": 3250000,
    "price_per_sqm": 43919,
    "monthly_fee_sek": 4200
  },

  "agent": {
    "name": "Anna Lindström",
    "agency": "Fastighetsbyrån",
    "phone": "+46-8-123-4567",
    "email": "anna.lindstrom@fastighetsbyran.se"
  },

  "content": {
    "description": "Nyproducerad lägenhet i populära Barkarbystaden...",
    "viewing_dates": ["2026-05-03 11:00", "2026-05-05 14:00"],
    "images": ["https://bilder.hemnet.se/..."]
  }
}

30+ fields per property. Clean, structured JSON. Ready to import into Excel, Airtable, a database, or your own application.

How to Use It (Step by Step)

Step 1: Create a free Apify account

Go to apify.com and sign up. The free plan includes $5 in monthly credits — enough to scrape roughly 2,500 properties at no cost.

Step 2: Open the Hemnet Scraper

Navigate to apify.com/mayno/hemnet-scraper and click "Try for free".

Step 3: Choose your scraping mode

The actor supports two modes:

Mode 1: Search URL (recommended for bulk scraping)

This is the most powerful option. Go to Hemnet.se, apply your filters (location, property type, price range, etc.), and copy the URL from your browser. Paste it into the scraper.

For example, to scrape all villas in Stockholm:

https://www.hemnet.se/bostader?item_types[]=villa&location_ids[]=17744

Set Maximum Pages to control how many result pages to scrape. Each page contains approximately 50 properties. Setting it to 5 gives you ~250 properties.

Mode 2: Direct Property URLs

If you have specific listings you want to track, paste their URLs directly:

https://www.hemnet.se/bostad/lagenhet-3rum-barkarbystaden-jarfalla-kommun-karlslundsvagen-15-21538498

This is ideal for monitoring specific properties over time or tracking price changes on a watchlist.

Step 4: Run the scraper

Click "Start". The scraper typically processes 50–100 properties per minute. A run of 250 properties takes about 3–4 minutes and costs roughly $0.50.

You'll see results appearing in real time in the Output tab.

Step 5: Export your data

Once complete, export your data in any format:

JSON — for developers and APIs
CSV — for Excel, Google Sheets, or data analysis tools
Excel (.xlsx) — pre-formatted spreadsheet
HTML Table — for quick web viewing

Real-World Use Cases

1. Real estate market analysis

Scrape a city or region periodically to track price trends over time. Compare asking prices across neighborhoods, property types, or years of construction. Identify where prices are rising or falling before the mainstream data catches up.

Example workflow:

Weekly scheduled scrape of Stockholm apartments
Import into Google Sheets via Apify's Google Sheets integration
Build a chart tracking median price per m² over time

2. Investment opportunity identification

Set up a daily scrape of specific search criteria — undervalued properties, specific neighborhoods, below-market prices for a given size. Get alerts when new listings appear matching your investment criteria.

Example workflow:

Daily scrape of Gothenburg villas under 4M SEK with 5+ rooms
Send results to Airtable
Use Airtable automations to alert you on new matches

3. Agent lead generation

The scraper extracts agent name, agency, phone, and email for every listing. If you offer services to Swedish real estate agents — photography, moving companies, renovation, mortgage brokering — this data is a direct pipeline to your audience.

Important note on GDPR: Agent contact information is publicly listed by agents themselves on Hemnet. However, if you use this data for outreach, ensure your use case complies with GDPR and Swedish data protection law. Use it responsibly.

4. Automated property valuation

Build a valuation model using scraped data. With price, size, location, year built, and amenities all structured, you have everything you need to train a price prediction model or build a comparative market analysis tool.

5. Academic and journalistic research

Sweden's housing affordability is a significant political topic. Researchers at Swedish universities (KTH, Stockholm University, Chalmers) can use this data to study price trends, geographic disparities, and housing supply across municipalities — without manually collecting data.

Scheduling and Automation

One of Apify's most powerful features is scheduling. You can set the Hemnet Scraper to run automatically:

Daily — for monitoring active listings
Weekly — for market trend tracking
Monthly — for long-term analysis datasets

Combined with Apify's integrations, you can build fully automated pipelines:

Trigger	Action
New listings scraped	→ Push to Google Sheets
Price drops detected	→ Send Slack notification
Weekly scrape complete	→ Email CSV to your team
New agent contacts found	→ Add to Airtable CRM

Set it up once, and your Swedish real estate dataset updates itself automatically.

Connecting via API

If you're building an application or want to trigger scrapes programmatically, Apify provides a REST API. You can start runs, check status, and retrieve results with a simple HTTP call:

// Trigger a scrape via Apify API
const response = await fetch(
  'https://api.apify.com/v2/acts/mayno~hemnet-scraper/runs',
  {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'Authorization': `Bearer ${YOUR_API_TOKEN}`
    },
    body: JSON.stringify({
      searchUrl: 'https://www.hemnet.se/bostader?location_ids[]=17744',
      maxPages: 3
    })
  }
);

This makes it straightforward to integrate Hemnet data into your own product — a dashboard, a mobile app, a CRM, or an automated reporting tool.

What Data Can You Extract?

Here's the complete field reference:

Root fields

Field	Type	Description
`id`	String	Unique Hemnet property ID
`url`	String	Full listing URL
`scraped_at`	ISO 8601	Timestamp of scrape

Location

Field	Description
`address`	Street address
`neighborhood`	Area/district name
`city`	Municipality (kommun)
`county`	County (län)
`distance_to_coast_m`	Distance to nearest coast in meters

Property Details

Field	Description
`type`	Villa, Lägenhet, Radhus, Kedjehus, etc.
`tenure`	Äganderätt, Bostadsrätt, or Hyresrätt
`rooms`	Number of rooms (e.g., 3.5)
`living_area_sqm`	Heated living space (Boarea)
`supplemental_area_sqm`	Secondary space (Biarea)
`land_area_sqm`	Plot area (for Villa/Radhus)
`year_built`	Construction year
`floor`	Floor position (e.g., "2/4")
`amenities`	Array: Balkong, Garage, Fiber, etc.
`is_new_construction`	Boolean

Financials

Field	Description
`asking_price_sek`	Listed price in SEK
`price_per_sqm`	SEK per m² of living area
`monthly_fee_sek`	Monthly Avgift (Bostadsrätt only)
`running_costs_year_sek`	Annual Driftskostnad (Villa/Radhus)

Agent

Field	Description
`name`	Agent full name
`agency`	Agency name
`phone`	Swedish phone number
`email`	Agent email

Content

Field	Description
`description`	Full listing text
`viewing_dates`	Upcoming visning dates
`images`	Array of high-resolution image URLs

Frequently Asked Questions

Do I need a Hemnet account?
No. The scraper accesses only publicly visible listing data, which requires no login.

How do I get a search URL?
Go to Hemnet.se, apply your filters (location, price, property type), and copy the URL from your browser's address bar. Paste it directly into the scraper.

Can I scrape multiple cities in one run?
Yes — Hemnet supports multiple location IDs in a single search URL. For example:

https://www.hemnet.se/bostader?location_ids[]=17744&location_ids[]=17755

What happens if Hemnet changes their site?
The actor is actively maintained. If Hemnet updates their page structure and the scraper breaks, it will be fixed and a new version deployed — typically within 48 hours of detection.

Can I run this on a schedule?
Yes. Apify has built-in scheduling. Set it to run daily, weekly, or at any custom interval from the actor's Settings tab.

Summary

	Manual scraping	Hemnet Scraper on Apify
Setup time	Days to weeks	2 minutes
Maintenance	Your responsibility	Handled for you
Bot detection	You figure it out	Built-in proxy rotation
Cost	Server + dev time	From $2.00 per 1,000 results
Scheduling	Build it yourself	One-click
Export formats	Whatever you code	JSON, CSV, Excel, HTML

If you need Swedish real estate data and don't want to spend weeks building and maintaining a scraper, the Hemnet Scraper on Apify is the most direct path to clean, structured data.

→ Try it free: apify.com/mayno/hemnet-scraper

About the Author

I build data extraction tools and automation actors on Apify. My scrapers help investors, researchers, and developers access structured data from platforms that don't offer official APIs.

Follow me on X: @Amine_Fer
Apify profile: apify.com/mayno

This article was written as part of the
Bright Data Dev.to challenge on web scraping.

Half Your Free Trial Signups Are Fake: Here's How to Fix It

MAYNO — Fri, 17 Apr 2026 20:06:35 +0000

The Problem Every SaaS Faces

Fake signups from disposable emails are killing your metrics. Someone signs up with throwaway@mailinator.com, uses your free trial, and vanishes.

Why It Matters

Wastes customer success time
Inflates your user count (fake growth)
Costs you money (server resources, email sends)
Makes your analytics useless

The Solution: Email Risk Scoring

Instead of just validating syntax, check:

Is it from a disposable provider? (mailinator, guerrillamail, etc.)
Does the domain have MX records?
Free provider vs business email?

What Good Email Validation Detects

A proper email risk scorer checks multiple signals:

Disposable domains: Is it from Mailinator, Guerrilla Mail, or 500+ other temporary providers?
MX records: Can the domain actually receive emails?
Provider type: Free (Gmail/Yahoo) vs Business (company.com)?
Role-based emails: Generic addresses like info@, admin@, noreply@
Risk level: Low, Medium, or High

How to Implement It

Option 1: DIY Solution (Free, But Manual)

# Use the GitHub disposable-email-domains list
import requests

DISPOSABLE_DOMAINS = requests.get(
    "https://raw.githubusercontent.com/disposable-email-domains/disposable-email-domains/main/disposable_email_blocklist.conf"
).text.split()

def is_disposable(email):
    domain = email.split("@")[1]
    return domain in DISPOSABLE_DOMAINS

Option 2: Use a Ready-Made API (Faster Setup)

Or skip all that complexity and use a ready-made solution.

I built this to solve the problem: https://apify.com/mayno/email-risk-scorer

What you get out of the box:

✅ 500+ disposable domains detected (Mailinator, Guerrilla Mail, YOPmail, etc.)
✅ MX record validation - checks if the domain can actually receive emails
✅ Email provider identification - detects Google Workspace, Microsoft 365, Zoho, etc.
✅ Free vs business email classification - Gmail/Yahoo vs company domains
✅ Role-based email detection - flags generic addresses (info@, admin@, noreply@)
✅ Automatic syntax validation - RFC-compliant email format checking
✅ Risk level scoring - returns low/medium/high based on multiple signals
✅ Batch processing - validate up to 10,000 emails per run
✅ No maintenance - disposable domain list updated automatically
✅ Fast processing - handles 1,000 emails in ~3-5 seconds

Setup time: 5 minutes. Here's the complete implementation for an Express.js signup route:

import { ApifyClient } from 'apify-client';

const apifyClient = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

app.post('/signup', async (req, res) => {
  const { email, password } = req.body;

  // Check email risk (one API call)
  const run = await apifyClient.actor('mayno/email-risk-scorer').call({
    emails: [email]
  });

  const results = await apifyClient.dataset(run.defaultDatasetId).listItems();
  const emailRisk = results.items[0];

  // Block disposable emails
  if (emailRisk.isDisposable) {
    return res.status(400).json({
      error: 'Disposable email addresses are not allowed'
    });
  }

  // Block high-risk emails
  if (emailRisk.riskLevel === 'high') {
    return res.status(400).json({
      error: 'This email address cannot be used for registration'
    });
  }

  // Optional: Flag free email providers for review
  if (emailRisk.isFreeProvider && !emailRisk.hasMXRecord) {
    // Log for manual review
    console.log('Suspicious signup:', email);
  }

  // Proceed with signup
  await createUser(email, password);
  res.json({ success: true });
});

Example API response:

{
  "email": "test@mailinator.com",
  "isValid": true,
  "isDisposable": true,
  "isFreeProvider": false,
  "isBusinessEmail": false,
  "isRoleBasedEmail": false,
  "domain": "mailinator.com",
  "hasMXRecord": true,
  "mxProvider": "mail.mailinator.com",
  "riskLevel": "high",
  "reasons": ["Disposable/temporary email provider"]
}

Why this beats the DIY approach:

No code to maintain (I handle updates)
No DNS infrastructure to manage
No edge cases to debug
No weekly domain list updates
Works day one, scales to millions

Time saved: ~6 hours initial setup + 1-2 hours/month maintenance = ship faster, focus on your product

Conclusion

Pick what works for your stage:

Early/MVP: DIY approach
Scaling: Use an API

Try It Yourself

Want to test it out? The actor is live on Apify with a free tier: https://apify.com/mayno/email-risk-scorer

Questions? Feedback? Drop a comment below. I'm actively working on this and would love to hear what features would be most useful!