SeLoger Scraper & French Real Estate Data API

Why Scrape SeLoger Property Data?

For international property funds, French real estate investment trusts (SCPIs), PropTech developers, and valuation appraisers, SeLoger is the definitive benchmark for asking prices, market inventory, and transaction velocity across mainland France. Combining active SeLoger listings with official notary records (French DVF Notary Data) provides the most comprehensive view of the French real estate market.

Our custom SeLoger data extraction API continuously monitors new listings, price cuts, and listing removals across major urban metropolises (Paris, Lyon, Marseille, Bordeaux, Toulouse, Nice, Lille, Nantes) as well as prime vacation destinations in the French Riviera and the French Alps.

SeLoger Data Fields Extracted

SeLoger Public Web Scraping vs. WebScrapingHub Managed API

How to Scrape SeLoger Data with Python (Code Example)

Below is a Python sample demonstrating how to extract verified SeLoger listing records, DPE energy scores, and price-per-m² metrics via our managed REST API:

import requests
import pandas as pd

# WebScrapingHub SeLoger Data Extraction API
API_ENDPOINT = "https://api.webscrapinghub.com/v1/real-estate/seloger"
payload = {
    "api_key": "YOUR_API_KEY",
    "location": "Paris (75)",
    "listing_type": "achat",
    "extract_dpe_rating": True,
    "extract_agency_leads": True
}

response = requests.post(API_ENDPOINT, json=payload)
data = response.json()

properties = []
for p in data.get("listings", []):
    properties.append({
        "Title": p.get("title"),
        "City": p.get("city"),
        "PostalCode": p.get("zipcode"),
        "Price_EUR": p.get("price_eur"),
        "Price_Per_M2": p.get("price_per_m2"),
        "Surface_M2": p.get("surface_m2"),
        "Rooms": p.get("rooms"),
        "DPE_Class": p.get("dpe_letter"),
        "Agency_Name": p.get("agency", {}).get("name"),
        "Agency_Phone": p.get("agency", {}).get("phone")
    })

df = pd.DataFrame(properties)
df.to_csv("seloger_paris_properties.csv", index=False)
print(f"Extracted {len(df)} SeLoger listings to CSV.")

Primary Use Cases for SeLoger Web Scraping

• ESG & Green Retrofit Funds: Isolate DPE F & G energy sieves (passoires thermiques) selling at steep discounts, model renovation costs, and calculate post-upgrade rental yields.
• Comparative Market Analysis (CMA): Benchmark active asking prices (€/m²) against historical closed notary prices (French DVF Records).
• B2B Real Estate Lead Generation: Extract comprehensive directories of French estate agencies (agences immobilières), managing brokers, and independent network mandataires (IAD, Safti).
• Rental Yield & Rent Cap Tracking: Monitor asking rents in cities with mandatory rent controls (encadrement des loyers in Paris, Lyon, Bordeaux, Lille, Montpellier).

Frequently Asked Questions about SeLoger Scraping