Lokaleportalen.dk Scraper

Lokaleportalen.dk Scraper provides structured access to commercial property listings, transforming complex listing pages into clean, usable data. It helps professionals analyze property availability, pricing, and landlord details efficiently. Designed for reliability and scale, it turns raw listings into actionable insights.

     

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Introduction

This project extracts detailed commercial property data from Lokaleportalen.dk and organizes it into structured formats for analysis. It solves the problem of manually browsing, copying, and tracking property listings across locations. It is built for analysts, real estate professionals, and developers who need consistent property data.

Commercial Property Data Extraction

• Collects complete listing details including pricing, size, and location
• Aggregates landlord and contact information in a structured format
• Captures images, related listings, and FAQ content
• Supports scalable extraction across multiple listing pages

Features

Feature	Description
Multi-URL Processing	Scrape one or many listing pages in a single run.
Structured Output	Normalizes property data into clean, consistent records.
Proxy Compatibility	Designed for stable data collection at scale.
Configurable Limits	Control how many listings are collected per run.
Rich Metadata	Extracts facts, statistics, images, and related listings.

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What Data This Scraper Extracts

Field Name	Field Description
title	Public title of the property listing.
address	Full street address and city information.
size	Total size of the property in square meters.
pricePerMonth	Monthly rental price.
listing	Detailed listing metadata and URLs.
landlord	Landlord company and contact information.
facts	Key factual attributes of the property.
description	Full descriptive text of the listing.
seoText	SEO-optimized summary of the property.
statistics	Area and listing-level statistics.
images	Collection of property image URLs.
relatedListings	Nearby or similar property listings.
faq	Frequently asked questions and answers.

---

Example Output

[
      {
        "title": "Kontor til leje, Odense C, Wichmandsgade 11",
        "address": "Wichmandsgade 11, 5000 Odense C",
        "size": "232 m2",
        "pricePerMonth": "14.500 kr. per måned",
        "listing": {
              "title": "Centralt beliggende kontor i Odense C",
              "href": "https://www.lokaleportalen.dk/leje/kontorlokaler/odense-c/243690-wichmandsgade",
              "price": "14.500 kr. per måned",
              "pricePerM2": "750 kr/m2/år",
              "adId": "243690"
        },
        "landlord": {
              "landlordCompany": "Olav de Linde Odense",
              "landlordPerson": "Udlejningsafdelingen",
              "landlordPhone": "6544",
              "isProLandlord": false
        }
      }
    ]

---

Directory Structure Tree

Lokaleportalen.dk Scraper/
├── src/
│   ├── main.py
│   ├── extractors/
│   │   ├── listing_parser.py
│   │   ├── landlord_parser.py
│   │   └── statistics_parser.py
│   ├── utils/
│   │   ├── http_client.py
│   │   └── normalizers.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

---

Use Cases

• Real estate analysts use it to monitor commercial property availability, so they can identify market trends faster.
• Investors use it to compare rental prices across locations, enabling better acquisition decisions.
• Brokerages use it to build internal property databases, reducing manual research time.
• Developers use it to power property search platforms with structured listing data.

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FAQs

Does this scraper support multiple cities or regions? Yes, it can process listing pages from any supported location as long as valid URLs are provided.

Can I limit how much data is collected per run? Yes, configurable limits allow you to control the number of listings extracted in a single execution.

What formats can the extracted data be used in? The structured output is suitable for JSON-based workflows and can be adapted for CSV or database ingestion.

Is landlord contact information always available? Availability depends on the listing, but the scraper captures all publicly visible landlord details.

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Performance Benchmarks and Results

Primary Metric: Processes up to 100 listings per run with consistent field coverage.

Reliability Metric: Maintains a high success rate across repeated executions with stable extraction logic.

Efficiency Metric: Optimized parsing minimizes redundant requests and speeds up data collection.

Quality Metric: Delivers comprehensive records including pricing, metadata, and related listings with high completeness.

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