We extract residential listings, commercial properties, energy performance metrics, and agency details from Bienici. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Sales objects from bienici.com. All fields typed and schema-versioned.
"listing_id": "ap5fi39201", "title": "Appartement 3 pièces 65 m²", "property_type": "apartment", "price": 450000.0, "currency": "EUR", "surface_area_sqm": 65.0, "rooms": 3, "bedrooms": 2, "city": "Paris", "postal_code": "75015", "publication_date": "2023-10-12T08:30:00Z"
| # | listing_id | title | property_type | price | currency | surface_area_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Rental Listings objects from bienici.com. All fields typed and schema-versioned.
"listing_id": "rt84kx91", "title": "Studio meublé 22 m²", "rent_monthly": 850.0, "charges_included": true, "furnished": true, "surface_area_sqm": 22.0, "city": "Lyon", "postal_code": "69003", "floor": 4, "has_elevator": false, "agency_name": "Orpi Lyon Centre"
| # | listing_id | title | rent_monthly | charges_included | deposit_amount | agency_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Energy Ratings objects from bienici.com. All fields typed and schema-versioned.
"listing_id": "ap5fi39201", "dpe_letter": "D", "dpe_value": 185, "ges_letter": "B", "ges_value": 10, "energy_cost_min": 850, "energy_cost_max": 1150, "reference_year": 2021, "heating_energy": "electric"
| # | listing_id | dpe_letter | dpe_value | ges_letter | ges_value | energy_cost_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Agency Data objects from bienici.com. All fields typed and schema-versioned.
"agency_id": "ag9921x", "agency_name": "Century 21 Rive Gauche", "agency_type": "professional", "city": "Paris", "postal_code": "75006", "active_listings_count": 45, "phone_number": "+33 1 45 44 21 21", "siret_number": "38491029300012"
| # | agency_id | agency_name | agency_type | address | city | postal_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for New Builds objects from bienici.com. All fields typed and schema-versioned.
"program_id": "nb4412", "program_name": "Les Jardins de l'Océan", "developer_name": "Kaufman & Broad", "delivery_quarter": "Q3", "delivery_year": 2025, "city": "Bordeaux", "available_lots": 12, "min_price": 210000.0, "pinel_eligible": true, "ptz_eligible": true
| # | program_id | program_name | developer_name | delivery_quarter | delivery_year | city |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Bienici scraper bypasses strict French anti-bot systems to extract structured property data, handling complex map-based pagination, dynamic API endpoints, and real-time listing updates.
Extract price, surface area, rooms, description, and metadata for apartments, houses, land, and commercial properties.
We interact directly with Bienici's map APIs, iterating through geographic bounding boxes to ensure zero missed listings.
Extract critical energy performance (DPE) and greenhouse gas (GES) ratings, essential for compliance and valuation models.
Monitor new build programmes (VEFA), lot availability, delivery dates, and Pinel/PTZ eligibility status.
Compile directories of real estate agencies, tracking their active inventory, contact details, and market share.
Calculate and track exact price-per-sqm metrics across different neighbourhoods and property types.
Extract high-resolution image URLs, floor plan links, and virtual tour availability flags for every listing.
Capture latitude and longitude coordinates exposed by the platform for advanced spatial analysis.
Run daily diff pipelines to capture new listings, price drops, and properties removed from the market.
Brief in. Clean data out.
Provide target cities, postal codes, or geographic bounding boxes. We design the extraction schema together.
We configure French residential proxies, API interception, and bypass logic for regional bot protection.
Schema validation, coordinate accuracy checks, and null-rate monitoring before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
French real estate portals use aggressive bot mitigation and complex web architectures. Here is how we maintain steady extraction.
French property portals strictly geoblock non-EU traffic and employ advanced bot protection. We route all requests through premium French residential IPs with perfectly spoofed TLS and browser fingerprints to maintain high success rates.
Bienici relies heavily on a 3D WebGL map interface, making traditional DOM scraping inefficient. We intercept the underlying XHR/Fetch requests to the backend APIs, extracting clean JSON payloads directly from the map grid.
APIs typically cap results at a few hundred listings per query. To scrape dense areas like Paris, our crawler automatically subdivides geographic bounding boxes into smaller quadrants until the result count falls below the pagination limit.
Free-text descriptions and inconsistent agency inputs cause data fragmentation. We normalise property types, extract precise numerical values for surface area and rooms, and standardise DPE/GES ratings into a strictly typed schema.
Listings disappear without notice when sold. We maintain a stateful database of all known listings, marking them as inactive when they drop from the search index, providing accurate days-on-market metrics.
Automated Valuation Model (AVM) providers ingest recent sales data, price per sqm, and DPE ratings to train property pricing algorithms.
Institutional investors track rental yields, market liquidity, and inventory levels across French metropolitan areas to guide acquisition strategy.
ESG analysts and retrofit companies track DPE/GES ratings to identify poorly insulated housing stock (passoires thermiques) for targeted marketing.
B2B service providers extract agency directories and active listing counts to qualify leads for CRM, photography, and virtual tour software.
Researchers and local governments monitor housing supply, rental inflation, and new build developments across specific postal codes.
Real estate networks monitor rival agency inventory, time-on-market, and pricing strategies at a hyper-local level.
"Bienici's map-first interface is brilliant for users, but it completely obscures the underlying data structure. We bypass the 3D rendering to extract the raw intelligence beneath."
Extracting data from modern map-based real estate portals requires more than simple HTML parsing. It demands intercepting dynamic API calls, managing geographic coordinate grids, and bypassing strict European bot mitigation. DataFlirt handles this infrastructure so your data science team can focus on yield calculations and market analysis.
Everything supported by our bienici.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
While Playwright handles the initial token generation and fingerprinting, Scrapy directly queries Bienici's backend APIs for high-throughput, structured data retrieval.
We maintain dedicated pools of French residential proxies. Rotation happens per-request with sticky sessions where API rate limits demand consistent IP attribution.
Pipelines use PostGIS to manage geographic bounding boxes, ensuring comprehensive coverage of the French territory without redundant API calls or missed listings.
Data delivered to where your team already works — no new tooling required.
About bienici.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public real estate listings is generally permissible for business intelligence purposes, provided it complies with local regulations. DataFlirt extracts only publicly visible property and agency data. We do not extract personally identifiable information (PII) of private sellers, ensuring GDPR compliance. Clients should review platform Terms of Service and consult legal counsel.
Bienici limits the number of results returned per API call. We solve this by recursively dividing geographic bounding boxes into smaller quadrants until the result count for each quadrant falls below the API limit, ensuring 100% market coverage.
Yes. We extract the exact DPE and GES scores, the corresponding letter grades, estimated energy costs, and the reference year for the diagnosis, which are critical for current French real estate compliance.
We typically configure daily runs to capture new listings, price modifications, and status changes. For specific high-velocity urban markets (e.g., Paris, Lyon), we can configure intra-day pipelines.
Yes. Every pipeline run produces a timestamped snapshot. We maintain a time-series record for each listing ID, allowing you to track price drops and calculate exact days-on-market.
Yes. We capture the exact latitude and longitude coordinates exposed by the platform's map API, which is vital for spatial analysis and proximity calculations.
Our minimum engagement typically covers a defined region (e.g., Île-de-France) or a specific property type nationwide, delivered weekly. Contact us with your target scope for precise pricing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full national property extract or targeted daily updates for specific departments — we scope, build, and operate the pipeline. Tell us what you need.
