We extract property sales, rentals, DPE ratings, and seller metadata from Leboncoin. 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 Listings objects from leboncoin.fr. All fields typed and schema-versioned.
"ad_id": "2418593021", "title": "Appartement 3 pièces 65 m²", "price": 345000.0, "rooms": 3, "square_meters": 65.0, "dpe_rating": "C", "city": "Lyon", "postal_code": "69003"
| # | ad_id | title | category_name | price | rooms | square_meters |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller Intelligence objects from leboncoin.fr. All fields typed and schema-versioned.
"seller_id": "849201", "seller_name": "Agence Stéphane Plaza", "is_pro": true, "siret": "48129384700012", "active_listings": 42, "joined_date": "2018-04-12", "phone_number": "+33478123456"
| # | seller_id | seller_name | is_pro | siret | active_listings | joined_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Valuation objects from leboncoin.fr. All fields typed and schema-versioned.
"ad_id": "2418593021", "current_price": 345000.0, "original_price": 360000.0, "price_drop_pct": 4.1, "price_per_sqm": 5307.69, "fees_included": true, "currency": "EUR"
| # | ad_id | current_price | original_price | price_drop_pct | price_per_sqm | city_average_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Energy & Diagnostics objects from leboncoin.fr. All fields typed and schema-versioned.
"ad_id": "2418593021", "dpe_score": "C", "dpe_value": 145, "ges_score": "A", "ges_value": 4, "heating_type": "Individuel électrique", "energy_cost_estimate_min": 850
| # | ad_id | dpe_score | dpe_value | ges_score | ges_value | construction_year |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from leboncoin.fr. All fields typed and schema-versioned.
"keyword": "appartement avec balcon", "city": "Bordeaux", "position": 1, "ad_id": "2418593021", "price": 345000.0, "is_pro": true, "promoted_ad": false, "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | category | region | department | city | position |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Leboncoin scraper handles every layer of the platform: property listings, DPE diagnostics, seller intelligence, and geolocation data — with Datadome circumvention and session management built in.
Title, description, price, rooms, square metres, property type, and high-resolution image URLs scraped at the listing level.
Capture exact DPE and GES letter grades, numerical consumption values, and estimated annual energy costs for regulatory compliance modelling.
Distinguish between private sellers and real estate agencies. Extract SIRET numbers and agency metadata for professional listings.
Extract region, department, city, and postal code data to map listings accurately across the French territory.
Monitor listing duration and capture original versus current pricing to calculate price drop percentages over time.
Extract revealed phone numbers for both private sellers and agencies via automated GraphQL API interaction.
Iterate through thousands of search result pages based on complex filters like price ranges, property types, and specific departments.
Bypass Leboncoin's aggressive Datadome anti-bot protection using residential proxies and TLS fingerprint spoofing.
Run continuous pipelines with hash-based diffing to track new listings, sold properties, and price adjustments without redundant data.
Brief in. Clean data out.
Provide search URLs, department codes, or specific agency profiles. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and Datadome bypass for leboncoin.fr.
Schema validation, null-rate checks, location normalisation, and sample records before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Leboncoin employs strict Datadome protection and complex API structures. Here is how we maintain reliable extraction.
Leboncoin uses Datadome to block automated traffic. Our infrastructure uses French residential proxies combined with strict TLS fingerprint spoofing, realistic HTTP/2 headers, and automated CAPTCHA solving to maintain high success rates.
Rather than scraping fragile HTML, our crawlers intercept Leboncoin's internal GraphQL API payloads. This ensures cleaner data extraction, captures hidden metadata, and reduces pipeline breakage when the frontend UI changes.
Phone numbers on Leboncoin are masked by default. Our Playwright instances automate the click-to-reveal interactions, managing the necessary session tokens to extract contact details without triggering rate limits.
Private seller listings often contain messy, unstructured data. We apply post-processing layers to normalise property types, extract actual square footage from text blocks, and standardise DPE formatting before delivery.
For large regional sweeps, we maintain a hash index of last-seen values per listing. Subsequent runs only push diffs — capturing price drops or delistings — reducing compute cost and downstream processing load.
Automated valuation models (AVMs) ingest historical pricing, DPE ratings, and time-on-market metrics to estimate property values accurately.
Agencies monitor private seller listings (particuliers) in their territory to identify potential mandates and contact leads directly.
Institutional investors track listing volume and average time-on-market across different departments to gauge regional real estate liquidity.
Investors cross-reference sale prices with rental listings in the same postal code to calculate gross rental yields programmatically.
Renovation companies target properties with F or G energy ratings (passoires thermiques) to offer compliance upgrades to sellers.
Municipalities and researchers analyse housing supply, rental costs, and property types to inform local housing policies.
"Leboncoin holds the highest volume of real estate liquidity data in France. Accessing it programmatically requires bypassing aggressive anti-bot layers."
Extracting data from Leboncoin requires defeating Datadome protection, managing complex GraphQL API payloads, and normalising inconsistent user-generated inputs. DataFlirt handles the proxy rotation, session management, and schema validation so your team can focus on building valuation models and market analysis tools.
Everything supported by our leboncoin.fr scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
We maintain pools of French residential ISP proxies combined with advanced TLS fingerprint spoofing to bypass Datadome blocks consistently.
Our crawlers intercept and parse Leboncoin's internal GraphQL requests, extracting structured JSON directly rather than relying on fragile DOM selectors.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About leboncoin.fr scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available real estate listings is generally permissible for analytical purposes. DataFlirt targets only public, non-authenticated property data. We do not extract personal user accounts or circumvent authentication walls. Clients should review Leboncoin's ToS and consult legal counsel for specific use cases.
We use French residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and request timing modelled on human behaviour. We monitor for CAPTCHA challenges and trigger automated solver queues immediately.
Yes. We automate the interaction required to reveal masked phone numbers on listings. This data is extracted and appended to the final payload for both private and professional sellers.
Yes. We extract the exact letter grades for both DPE and GES, along with the numerical energy consumption estimates and the diagnostic date where provided.
Depending on the total listing volume, a full sweep of a French department typically completes within 2 to 4 hours. We can configure continuous diffing pipelines to run at higher frequencies for specific postal codes.
Yes. Our schema includes a boolean flag distinguishing professional agencies from private sellers, allowing you to filter the dataset easily in your warehouse.
Our smallest packages start at a defined regional scope (e.g., specific departments or cities) with weekly delivery. For national coverage or real-time tracking, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of a specific department or a continuous national feed of real estate listings — we scope, build, and operate the pipeline. Tell us what you need.
