# Cadremploi Jobs Scraper (Cheap) (`data_api/cadremploi-jobs-scraper-cheap`) Actor Cadremploi France jobs scraper that collects active job postings, salaries, contract types, and locations from Cadremploi.fr, so recruitment teams can track hiring trends and automate candidate sourcing with ease. - **URL**: https://apify.com/data\_api/cadremploi-jobs-scraper-cheap.md - **Developed by:** [Data API](https://apify.com/data_api) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Cadremploi Jobs Scraper ![Cadremploi Jobs Scraper](cover.jpg) Watching new roles land on Cadremploi by hand gets old fast: you click through pages and copy the same handful of fields into a sheet, over and over. This scraper handles that part. Give it a few search terms, a location, or a result URL you already have, and each posting comes back as a clean row with the role title, employer, location, contract type, salary, and a link to the full ad. Pull ten roles or sweep a whole city, then export to JSON, CSV, or Excel. ### What you get Every job posting comes back as one row with the same fields in the same order, so the output drops straight into a spreadsheet or database. Two groups of data per posting: - **The role** — `roleTitle`, `contractKind`, `salaryText`, `jobLocation`, `roleSummary`, `tagLabels`, `postedLabel`, `postingUrl` - **The employer and origin** — `employerName`, `employerLogo`, `postingId`, `sourceQuery`, `collectedAt` ### Quick start 1. Click **Try for free** and open the input form. 2. Add your **Job search terms** (like `data analyst`) and/or your **Locations** (like `lyon-69`). 3. Set a **Search radius** if you want nearby towns included, or paste **Direct result URLs** to skip query building entirely. 4. Set a **Results limit** to control how many postings each query returns. 5. Press **Start**, then download the results as JSON, CSV, Excel, or XML once it finishes. ![How it works](how-it-works.jpg) ### Use cases - **Recruitment sourcing** — build a live feed of executive and professional roles to map against your candidate pool - **Salary benchmarking** — gather posted pay ranges by role and region to sanity-check your own offers - **Hiring trend analysis** — watch which contract types and sectors are growing across French departments - **Lead generation** — spot companies that are actively hiring and reach out while they're expanding - **Job board aggregation** — keep a niche or regional board stocked with fresh listings on autopilot ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `searchTerms` | array of strings | No | Job titles, skills, or keywords to search. Leave blank to browse by location only. Example: `["data analyst", "chef de projet"]`. | | `locationFilters` | array of strings | No | Cities, departments, or region codes to narrow results. Leave blank to search everywhere. Example: `["lyon-69", "bordeaux"]`. | | `searchRadius` | integer | No | How far around each location to look, in kilometers. Only used when a location is set. Default `50`. | | `targetUrls` | array of strings | No | Ready-made Cadremploi result URLs to scrape directly instead of building queries. | | `resultsLimit` | integer | No | Postings to collect per query or direct URL. Default `25`. | | `timeoutSeconds` | integer | No | Seconds to wait on each request before giving up. Default `45`. | #### Example input ```json { "searchTerms": [ "data analyst", "chef de projet" ], "locationFilters": [ "lyon-69", "bordeaux" ], "searchRadius": 50, "targetUrls": [], "resultsLimit": 25, "timeoutSeconds": 45 } ```` When both search terms and locations are filled in, the scraper pairs them by position if the two lists are the same length (term 1 with location 1, term 2 with location 2). If the lists differ in length, it runs every term against every location instead. ### Output Each posting becomes one row. Fields that Cadremploi doesn't show for a given listing are left out of that row, so check for a key before relying on it. #### Example output ```json { "postingId": "156537911140995108", "roleTitle": "Data Analyst H/F", "postingUrl": "https://www.cadremploi.fr/emploi/detail_offre?offreId=156537911140995108", "employerName": "GROUPAGORA RÉGIONS", "employerLogo": "https://imagedelivery.net/BN-U87wrUjbdYBHZwNH6NA/03d36f4f-a233-4d3d-615a-aa00df796b00/logo100", "tagLabels": [ "Populaire" ], "jobLocation": "Lyon", "contractKind": "CDI", "salaryText": "45K€ - 50K€", "roleSummary": "Dans le cadre du renforcement des équipes data de l'un de nos clients, nous recherchons un Data Analyst (H/F)...", "postedLabel": "Publiée il y a 12 jours", "sourceQuery": "data analyst - lyon-69", "collectedAt": "2026-06-29T12:00:00.000000+00:00" } ``` #### Output fields | Field | Type | Description | |-------|------|-------------| | `postingId` | string | Cadremploi's internal identifier for the posting | | `roleTitle` | string | Headline of the advertised position | | `postingUrl` | string | Direct link to the full job description page | | `employerName` | string | Company that posted the role | | `employerLogo` | string | Link to the company's logo image | | `tagLabels` | array | Labels on the card such as Nouveau or Populaire | | `jobLocation` | string | Where the job is based | | `contractKind` | string | Contract on offer, such as CDI, CDD, or Freelance | | `salaryText` | string | Pay range as listed, when stated | | `roleSummary` | string | Short teaser describing the position | | `postedLabel` | string | How recently the role went live, e.g. Publiée il y a 10 jours | | `sourceQuery` | string | The search query or direct URL that produced this posting | | `collectedAt` | string | ISO 8601 timestamp of when the posting was captured | ### Tips for best results - **Start with a small `resultsLimit`.** Run 10 to 20 postings first to confirm the fields match your pipeline, then raise it for the full pull. - **Pair terms and locations deliberately.** Same-length lists pair one-to-one; mismatched lists cross-combine. Use that to control exactly which searches run. - **Use `targetUrls` for filters the form can't express.** Set your filters on Cadremploi, copy the URL from the address bar, and paste it in to scrape that exact result set. - **Bump `timeoutSeconds` toward 60** if you see timeout errors on larger or slower searches. - **Skip `searchRadius` for tight searches.** Leave it low or at zero when you only want roles inside one city. ### How can I use Cadremploi job data? **How can I use the Cadremploi Jobs Scraper to track hiring in a specific region?** Add your `locationFilters` (such as `lyon-69` or `bordeaux`) with a `searchRadius`, then run it on a schedule. Each posting comes back with the employer, contract type, salary, and posting date, so you can watch how demand shifts week to week across French departments. **How can I scrape Cadremploi salary data for benchmarking?** Search the roles you care about, and every listing that states pay returns it in `salaryText` alongside `roleTitle`, `contractKind`, and `jobLocation`. Group the rows by role and region to compare advertised ranges and check that your own offers stay competitive. **How can I pull Cadremploi listings into my own job board?** Feed in `searchTerms` and `locationFilters`, set a `resultsLimit`, and export the results as JSON or CSV. Each row carries the role title, summary, link, and employer, ready to import into a regional or niche board without manual copy-paste. **How can I find companies that are actively recruiting on Cadremploi?** Run a broad keyword search and read the `employerName` field across the results. Companies posting several roles at once are usually growing, which makes the export a useful starting list for sales prospecting or partnership outreach. ### Is it legal to scrape data? Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers. You can also read Apify's blog post on the [legality of web scraping](https://blog.apify.com/is-web-scraping-legal/). ### Support Questions, feature requests, or a field you'd like added? Reach out at and we'll get back to you. # Actor input Schema ## `keywords` (type: `array`): List of job titles, keywords, or skills to search for (e.g. 'design', 'développeur java'). Leave empty to search by location only. ## `locations` (type: `array`): List of cities, departments, or region codes (e.g. 'nice-06', 'paris'). Leave empty to search by keywords globally. ## `rayon` (type: `integer`): Search radius around the specified location in kilometers (e.g., 10, 50, 100). Applies only when a location is specified in a query. ## `startUrls` (type: `array`): List of direct Cadremploi job search result URLs to scrape instead of using combined search queries. ## `maxItemsPerQuery` (type: `integer`): Maximum number of job listings to extract for each search query or direct start URL individually. ## `requestTimeoutSecs` (type: `integer`): Per-request timeout in seconds for scraping requests. Pages are rendered with JavaScript, which can take ~20s, so keep this generous. ## Actor input object example ```json { "keywords": [ "design", "développeur java" ], "locations": [ "nice-06", "paris" ], "rayon": 100, "startUrls": [], "maxItemsPerQuery": 50, "requestTimeoutSecs": 60 } ``` # 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 = { "keywords": [ "design", "développeur java" ], "locations": [ "nice-06", "paris" ], "startUrls": [] }; // Run the Actor and wait for it to finish const run = await client.actor("data_api/cadremploi-jobs-scraper-cheap").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 = { "keywords": [ "design", "développeur java", ], "locations": [ "nice-06", "paris", ], "startUrls": [], } # Run the Actor and wait for it to finish run = client.actor("data_api/cadremploi-jobs-scraper-cheap").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 '{ "keywords": [ "design", "développeur java" ], "locations": [ "nice-06", "paris" ], "startUrls": [] }' | apify call data_api/cadremploi-jobs-scraper-cheap --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_api/cadremploi-jobs-scraper-cheap", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Cadremploi Jobs Scraper (Cheap)", "description": "Cadremploi France jobs scraper that collects active job postings, salaries, contract types, and locations from Cadremploi.fr, so recruitment teams can track hiring trends and automate candidate sourcing with ease.", "version": "0.0", "x-build-id": "dxgegDUcSY0pR9t0s" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_api~cadremploi-jobs-scraper-cheap/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_api-cadremploi-jobs-scraper-cheap", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_api~cadremploi-jobs-scraper-cheap/runs": { "post": { "operationId": "runs-sync-data_api-cadremploi-jobs-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_api~cadremploi-jobs-scraper-cheap/run-sync": { "post": { "operationId": "run-sync-data_api-cadremploi-jobs-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "keywords": { "title": "Search Keywords", "type": "array", "description": "List of job titles, keywords, or skills to search for (e.g. 'design', 'développeur java'). Leave empty to search by location only.", "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "List of cities, departments, or region codes (e.g. 'nice-06', 'paris'). Leave empty to search by keywords globally.", "items": { "type": "string" } }, "rayon": { "title": "Radius (km)", "minimum": 0, "type": "integer", "description": "Search radius around the specified location in kilometers (e.g., 10, 50, 100). Applies only when a location is specified in a query.", "default": 100 }, "startUrls": { "title": "Direct Listing URLs", "type": "array", "description": "List of direct Cadremploi job search result URLs to scrape instead of using combined search queries.", "items": { "type": "string" } }, "maxItemsPerQuery": { "title": "Max Items Per Query or URL", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of job listings to extract for each search query or direct start URL individually.", "default": 50 }, "requestTimeoutSecs": { "title": "Request Timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "Per-request timeout in seconds for scraping requests. Pages are rendered with JavaScript, which can take ~20s, so keep this generous.", "default": 60 } } }, "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 } } } } } } } } } } ```