# Leboncoin API scraper (PPE) (`data_alchemist/leboncoin`) Actor A powerful Leboncoin.fr scraper designed to extract a wide range of listings from France's popular marketplace. This tool retrieves structured information on products, real estate, vehicles, and vacation rentals, providing details such as prices, locations, images, and seller profiles. - **URL**: https://apify.com/data\_alchemist/leboncoin.md - **Developed by:** [Dennis](https://apify.com/data_alchemist) (community) - **Categories:** E-commerce, Real estate, Jobs - **Stats:** 2 total users, 1 monthly users, 80.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.60 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Scraper Scrape listings from **[leboncoin.fr](https://www.leboncoin.fr)** — France's largest classifieds marketplace. This Actor intercepts and replays the internal search API directly, delivering fast, structured results without rendering full pages for every item. ### How to use Leboncoin Scraper 1. Go to the **Input** tab 2. Paste one or more leboncoin.fr search URLs with all your filters already applied into **Start URLs** (e.g. a category or keyword search page). Don't forget to apply your preferred sort order on the leboncoin page itself 3. Set **Max Results** to limit how many listings to return (default: 100, max: 1 000) 4. Click **Start** and wait for the run to finish 5. Open the **Output** tab to view and download your results ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | `startUrls` | Array | Leboncoin search page URLs to scrape | `https://www.leboncoin.fr/recherche?text=notebook` | | `maxResults` | Integer | Maximum number of listings to return (1–1 000) | `100` | Example input: ```json { "startUrls": [ { "url": "https://www.leboncoin.fr/recherche?text=iphone&locations=Paris" }, { "url": "https://www.leboncoin.fr/recherche?category=9&locations=Paris&price=25000-400000&rooms=1-2&real_estate_type=1,2" } ], "maxResults": 200 } ```` ### Output Results are stored in the default dataset. Example output item: ```json { "list_id": 3162861987, "subject": "Notebook neuf", "price": [45], "category_name": "Ordinateurs", "location": { "city": "Thoissey", "zipcode": "01140" }, "first_publication_date": "2026-04-14 10:23:11", "url": "https://www.leboncoin.fr/ad/ordinateurs/3162861987", "has_phone": false, "urgent": true } ``` You can download the dataset in various formats such as **JSON, CSV, Excel, or XML** from the **Storage** tab after the run completes. ### Data fields | Field | Description | |-------|-------------| | `list_id` | Unique listing ID | | `subject` | Listing title | | `price` | Price in euros | | `category_name` | Category | | `location` | City and postcode | | `first_publication_date` | When the listing was first published | | `url` | Direct link to the listing | | `urgent` | Whether the listing is marked urgent | | `has_phone` | Whether a phone number is available | ### Pricing / Cost estimation There are no additional fees for the actor. Fees for using the platform and proxies are already included in the price. You pay only for the results. ### Tips - Use specific search URLs with filters already applied (price range, location, category) for more targeted results - Keep `maxResults` as low as you need — smaller runs are faster and cheaper - If the Actor throws `No search request data found`, the page may have been blocked; try running again (residential proxies rotate automatically) ### FAQ and support **Is scraping leboncoin.fr legal?** This Actor collects publicly available listing data. It respects the site's technical infrastructure by not overloading servers. Use the data responsibly and in accordance with leboncoin's Terms of Service and applicable law. Do not use it to collect personal data without a legitimate purpose. **The Actor returned 0 results — why?** The consent or anti-bot challenge may not have been bypassed. Try again; proxy rotation usually resolves transient blocks. For bugs or feature requests, open an issue in the **Issues** tab on this Actor's page. Custom solutions and integrations are available on request. # Actor input Schema ## `startUrls` (type: `array`): List of leboncoin search URLs to scrape results from. ## `maxResults` (type: `integer`): Maximum number of results to return. Maximum is 1000. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.leboncoin.fr/recherche?text=iphone" } ], "maxResults": 100 } ``` # 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": [ { "url": "https://www.leboncoin.fr/recherche?text=iphone" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("data_alchemist/leboncoin").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": [{ "url": "https://www.leboncoin.fr/recherche?text=iphone" }] } # Run the Actor and wait for it to finish run = client.actor("data_alchemist/leboncoin").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": [ { "url": "https://www.leboncoin.fr/recherche?text=iphone" } ] }' | apify call data_alchemist/leboncoin --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_alchemist/leboncoin", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Leboncoin API scraper (PPE)", "description": "A powerful Leboncoin.fr scraper designed to extract a wide range of listings from France's popular marketplace. This tool retrieves structured information on products, real estate, vehicles, and vacation rentals, providing details such as prices, locations, images, and seller profiles.", "version": "0.0", "x-build-id": "2f1JkdPhi1EgoSW1c" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_alchemist~leboncoin/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_alchemist-leboncoin", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_alchemist~leboncoin/runs": { "post": { "operationId": "runs-sync-data_alchemist-leboncoin", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_alchemist~leboncoin/run-sync": { "post": { "operationId": "run-sync-data_alchemist-leboncoin", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "startUrls" ], "properties": { "startUrls": { "title": "Search URLs", "type": "array", "description": "List of leboncoin search URLs to scrape results from.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of results to return. Maximum is 1000.", "default": 100 } } }, "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 } } } } } } } } } } ```