# Leboncoin Classifieds Scraper (`crawlerbros/leboncoin-scraper`) Actor Extract classified ads from leboncoin.fr with title, price, location, images, attributes, owner type. Supports all categories (real estate, vehicles, jobs, services, etc.) with filter URL pass-through. - **URL**: https://apify.com/crawlerbros/leboncoin-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** E-commerce, Lead generation, Real estate - **Stats:** 1 total users, 0 monthly users, 80.0% runs succeeded, 11 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Leboncoin Classifieds Scraper Extract classified ads from **leboncoin.fr** — France's largest classifieds platform. Returns title, description, price, location, images, owner info, and category-specific attributes (real estate specs, vehicle specs, job details, etc.). ### Features - **30 output fields** per ad — flat schema with typed defaults (zero nulls) - **All categories supported** — real estate (rentals + sales), vehicles, jobs, services, electronics, fashion, etc. - **Filter by category, keyword, location, price** — via Leboncoin URL parameters - **Owner type** (`private` vs `pro`) for lead segmentation - **Geocoordinates** for every ad - **Image gallery** with multiple resolutions - **Generic attributes** (real estate type, surface, rooms, energy class, etc.) flattened into a single dict - **DataDome bypass** via curl_cffi Chrome 131 + RESIDENTIAL/FR proxy (hardcoded, applied automatically) - **Pagination** via `?page=N` (35 ads per page) ### Input | Field | Type | Description | |---|---|---| | `startUrls` | Array | Leboncoin search URLs (e.g., `https://www.leboncoin.fr/recherche?category=10&locations=Paris`) | | `category` | Integer | Category ID when no startUrls. Verified: 9=real estate sales, 10=rentals, 2=cars, 6=auto equipment, 17=phones, 33=jobs. For other categories, find the ID in any leboncoin.fr search URL. | | `search` | String | Free-text keyword (combined with category) | | `maxItems` | Integer | Maximum ads to return (default 50, max 1000) | #### Example Input ```json { "startUrls": [ "https://www.leboncoin.fr/recherche?category=10&locations=Paris&price=min-2000" ], "maxItems": 100 } ```` Or filter mode: ```json { "category": 2, "search": "Tesla", "maxItems": 50 } ``` ### Output Each ad has **30 fields**. All fields are always present — empty strings, zero, `false`, or empty array as typed defaults, never `null`. #### Identity | Field | Type | Description | |---|---|---| | `id` | Integer | Leboncoin `list_id` | | `url` | String | Ad URL | | `subject` | String | Ad title | | `body` | String | Description text (truncated to 2,000 chars) | | `categoryId` | String | Category ID | | `categoryName` | String | Category name | | `adType` | String | `offer` / `demand` | | `status` | String | `active` / `expired` / `sold` | #### Price | Field | Type | Description | |---|---|---| | `price` | Integer | Price in EUR | #### Location | Field | Type | Description | |---|---|---| | `city` | String | City | | `zipcode` | String | Postal code | | `department` | String | Department name | | `region` | String | Region name | | `country` | String | Country code (`FR`) | | `latitude` | Number | Latitude | | `longitude` | Number | Longitude | #### Owner | Field | Type | Description | |---|---|---| | `ownerName` | String | Seller display name | | `ownerType` | String | `private` or `pro` | | `ownerId` | String | Seller user ID | | `ownerStoreId` | String | Pro store ID (if pro) | | `hasPhone` | Boolean | Whether phone number is exposed | #### Media & Attributes | Field | Type | Description | |---|---|---| | `imageCount` | Integer | Number of images | | `imageUrls` | Array | All large image URLs | | `thumbnail` | String | Thumbnail URL | | `attributes` | Object | Generic attributes (e.g., `{"real_estate_type": "Appartement", "square": "60 m²", "rooms": "2"}`) | #### Dates & Flags | Field | Type | Description | |---|---|---| | `publishedDate` | String | First publication date | | `expirationDate` | String | Expiration date | | `isUrgent` | Boolean | Urgent ad flag | | `isHighlighted` | Boolean | Highlighted ad flag | | `scrapedAt` | String | ISO 8601 scrape timestamp | ### FAQ **Q: Do I need a proxy?** No configuration needed — a French residential proxy is hardcoded and applied automatically. Leboncoin's DataDome anti-bot blocks Apify datacenter IPs with a CAPTCHA challenge, so the scraper requires `RESIDENTIAL/FR` traffic combined with `curl_cffi` Chrome 131 TLS impersonation. Sessions are rotated automatically on failure. **Q: How do I find the category ID?** Browse to leboncoin.fr, apply filters, then look at the URL: `?category=10` is rentals, `?category=9` is real estate sales, `?category=2` is vehicles. The full list is on Leboncoin's category page. **Q: How many results per page?** 35 ads per page. The scraper paginates via `?page=N` until `maxItems` is reached. **Q: Are pro and private ads both included?** Yes. The `ownerType` field tells you which. You can filter post-scrape if you only want one type. **Q: How fresh is the data?** Leboncoin's `__NEXT_DATA__` contains the live search results — same data as their website at the moment of fetch. ### Use Cases - **Real estate market research** — track rental and sale prices by city / region - **Vehicle pricing intelligence** — monitor used-car markets across France - **Lead generation** — discover pro sellers with mailing addresses (via owner data) - **Job market analysis** — extract job postings by region and category - **Price monitoring** — daily runs to detect price changes - **Competitor analysis** — track listings from specific stores # Actor input Schema ## `startUrls` (type: `array`): Leboncoin search URLs (e.g., https://www.leboncoin.fr/recherche?category=10\&locations=Paris). Any filters in the URL are preserved. ## `category` (type: `integer`): Leboncoin category ID. Verified IDs: 9 = Ventes immobilières (real estate sales), 10 = Locations (rentals), 2 = Voitures (cars), 6 = Équipement auto, 17 = Téléphones, 33 = Offres d'emploi (jobs). For other categories, find the ID in any leboncoin.fr search URL (e.g. ?category=N) or use startUrls. Used only when no startUrls. ## `search` (type: `string`): Free-text keyword. Used with category when no startUrls. ## `maxItems` (type: `integer`): Maximum number of ads to return. ## Actor input object example ```json { "startUrls": [ "https://www.leboncoin.fr/recherche?category=10" ], "maxItems": 5 } ``` # Actor output Schema ## `ads` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ "https://www.leboncoin.fr/recherche?category=10" ], "maxItems": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/leboncoin-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": ["https://www.leboncoin.fr/recherche?category=10"], "maxItems": 5, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/leboncoin-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ "https://www.leboncoin.fr/recherche?category=10" ], "maxItems": 5 }' | apify call crawlerbros/leboncoin-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/leboncoin-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Leboncoin Classifieds Scraper", "description": "Extract classified ads from leboncoin.fr with title, price, location, images, attributes, owner type. Supports all categories (real estate, vehicles, jobs, services, etc.) with filter URL pass-through.", "version": "1.0", "x-build-id": "d2mPrRklDiykTogeN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~leboncoin-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-leboncoin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~leboncoin-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-leboncoin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~leboncoin-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-leboncoin-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "Leboncoin search URLs (e.g., https://www.leboncoin.fr/recherche?category=10&locations=Paris). Any filters in the URL are preserved.", "items": { "type": "string" } }, "category": { "title": "Category ID (optional)", "minimum": 1, "type": "integer", "description": "Leboncoin category ID. Verified IDs: 9 = Ventes immobilières (real estate sales), 10 = Locations (rentals), 2 = Voitures (cars), 6 = Équipement auto, 17 = Téléphones, 33 = Offres d'emploi (jobs). For other categories, find the ID in any leboncoin.fr search URL (e.g. ?category=N) or use startUrls. Used only when no startUrls." }, "search": { "title": "Search Query (optional)", "type": "string", "description": "Free-text keyword. Used with category when no startUrls." }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of ads to return.", "default": 50 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```