# Welcome to the Jungle Jobs Scraper (`blackfalcondata/wttj-scraper`) Actor Scrape welcometothejungle.com — Europe's top tech & startup job board. Salary ranges, remote filters, and incremental change tracking across FR/EN/DE/ES markets. - **URL**: https://apify.com/blackfalcondata/wttj-scraper.md - **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community) - **Categories:** Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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. 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 ### What does Welcome to the Jungle Jobs Scraper do? Welcome to the Jungle Jobs Scraper extracts structured job data from [welcometothejungle.com](https://welcometothejungle.com) — including salary data, company metadata, full descriptions, remote-work indicators, and location data. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers incremental monitoring that only returns new or changed results on recurring runs and a compact output mode for AI-agent and MCP workflows. ### What data can you extract from welcometothejungle.com? Each result includes Core listing fields (`jobId`, `jobKey`, `wkReference`, `slug`, `title`, `url`, `portalUrl`, and `city`, and more), detail fields when enrichment is enabled (`description` and `benefits`), and company metadata (`companyName`, `companySlug`, `companyLogoUrl`, and `companyEmployeeCount`). In standard mode, all fields are always present — unavailable data points are returned as `null`, never omitted. In compact mode, only core fields are returned. ### Input The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema. Key parameters: - **`query`** — Job search keywords, e.g. "software engineer". - **`language`** — WTTJ Algolia index language. Determines which market to search. (default: `"fr"`) - **`countryCode`** — Optional ISO 3166-1 alpha-2 country code to filter results, e.g. "FR", "DE", "GB". - **`location`** — Optional city name to filter results, e.g. "Paris". - **`maxResults`** — Maximum total results to return. 0 = unlimited. (default: `50`) - **`descriptionMaxLength`** — Truncate job description to N characters. 0 = no truncation. (default: `0`) - **`compact`** — Return core fields only (ideal for AI-agent / MCP workflows). (default: `false`) - **`incrementalMode`** — Only emit new or changed jobs compared to the previous run. (default: `false`) - **`stateKey`** — Stable identifier for the tracked universe. Required when incrementalMode is true. #### Input example ```json { "query": "software engineer", "language": "fr", "maxResults": 25, "descriptionMaxLength": 0, "compact": false, "incrementalMode": false } ```` ### Output Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console. #### Example job record ```json { "jobId": "be91916bd95c52de761ecb1a78604592df9e8911c4229004a96352ec92ea831b", "jobKey": "c3bcdc05-29cb-4b1e-999f-5b5ec021383d", "wkReference": "CODEW_mdooy8V", "slug": "software-engineer-java-fullstack-devops_paris", "title": "Software engineer Java fullstack/DevOps", "url": "https://www.welcometothejungle.com/fr/companies/codeworks/jobs/software-engineer-java-fullstack-devops_paris", "portalUrl": "https://www.welcometothejungle.com", "companyName": "Codeworks", "companySlug": "codeworks", "companyLogoUrl": "https://cdn-images.welcometothejungle.com/vH3nxIJ4aIBO-uKP4JZE8xlJah_HnVKYjbJI6EReess/rs:auto:400::/q:85/czM6Ly93dHRqLXByb2R1Y3Rpb24vdXBsb2Fkcy9vcmdhbml6YXRpb24vbG9nby8wMTk3LzE2ODI2MC9jZjdlMDAwZi1kMmR...", "companyEmployeeCount": 28, "companyCreationYear": 2018, "companyDescription": null, "city": "Paris", "region": "Ile-de-France", "country": "France", "countryCode": "FR", "latitude": 48.88396, "longitude": 2.33056, "contractType": "full_time", "remote": "partial", "hasRemote": true, "educationLevel": null, "experienceLevelMinimumYears": 3, "salaryMin": 50000, "salaryMax": 80000, "salaryCurrency": "EUR", "salaryPeriod": "yearly", "salaryYearlyMin": 50000, "summary": "Rejoins notre équipe en tant que Software Engineer Java Fullstack/DevOps. Tu seras responsable de la production d'applications en accord avec les principes du software craftsmanship et du clean code....", "description": "Riche d'au moins 3 ans d'expérience, en tant Software engineer Java fullstack/DevOps confirmé·e ou sénior·e :\n\n* Tu maîtrises les fondamentaux de **Java et JavaScript**\n \n* Tu sais expliquer l’inté...", "keyMissions": [ "Garantir une maîtrise des pratiques de code, diffuser un état de l’art à jour technologique et méthodologique, et optimiser le time-to-market.", "Produire un code utile, fiable et maintenable, respecter les règles de l’art SOLID et les préceptes du Clean Code, et appliquer les pratiques d’architectures modernes.", "Participer à la structuration et l'évolution du modèle de l'entreprise, s'impliquer en dehors de la mission en fonction des appétences." ], "benefits": [ "Diversity manifesto", "Generous PTO", "Reduction of working time (RTT)", "Cooptation bonus", "Team building", "Afterworks, Team lunches", "Partners with Nonprofits", "Professional development plan", "Paid industry certifications", "Mentor program", "Family medical leave", "Sick child leave", "Family support resources", "Pregnancy loss leave", "Parenting support", "Sports allowance", "Reimbursement above 50%" ], "sectors": [ { "name": "Software", "parentName": "Tech" }, { "name": "IT / Digital", "parentName": "Consulting / Audit" } ], "category": "Tech & Engineering", "subcategory": "Software & Web Development", "profession": "Software Engineer", "language": "fr", "postedDate": "2026-03-30T14:23:29Z", "scrapedAt": "2026-03-30T21:38:40.669Z", "source": "welcometothejungle.com", "changeType": null } ``` ### How to scrape welcometothejungle.com 1. Go to [Welcome to the Jungle Jobs Scraper](https://apify.com/blackfalcondata/wttj-scraper) in Apify Console. 2. Enter a search keyword and optional location filter. 3. Set `maxResults` to control how many results you need. 4. Click **Start** and wait for the run to finish. 5. Export the dataset as JSON, CSV, or Excel. ### Use cases - Extract job data from welcometothejungle.com for market research and competitive analysis. - Track salary trends across regions and categories over time. - Monitor new and changed listings on scheduled runs without processing the full dataset every time. - Research company hiring patterns, employer profiles, and industry distribution. - Use structured location data for regional analysis, mapping, and geo-targeting. - Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode. - Export clean, structured data to dashboards, spreadsheets, or data warehouses. ### How much does it cost to scrape welcometothejungle.com? Welcome to the Jungle Jobs Scraper uses [pay-per-event](https://docs.apify.com/platform/actors/paid-actors/pay-per-event) pricing. You pay a small fee when the run starts and then for each result that is actually produced. - **Run start:** $0.005 per run - **Per result:** $0.001 per job record Example costs: - 10 results: **$0.01** - 100 results: **$0.11** - 500 results: **$0.51** Incremental runs only charge for new or changed results, making recurring monitoring cost-efficient. ### FAQ #### How many results can I get from welcometothejungle.com? The number of results depends on the search query and available listings on welcometothejungle.com. Use the `maxResults` parameter to control how many results are returned per run. #### Does Welcome to the Jungle Jobs Scraper support recurring monitoring? Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset. #### Can I integrate Welcome to the Jungle Jobs Scraper with other apps? Yes. Welcome to the Jungle Jobs Scraper works with Apify's [integrations](https://apify.com/integrations) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes. #### Can I use Welcome to the Jungle Jobs Scraper with the Apify API? Yes. You can start runs, manage inputs, and retrieve results programmatically through the [Apify API](https://docs.apify.com/api/v2). Client libraries are available for JavaScript, Python, and other languages. #### Can I use Welcome to the Jungle Jobs Scraper through an MCP Server? Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server) that lets AI assistants and agents call this actor directly. Use compact mode and `descriptionMaxLength` to keep payloads manageable for LLM context windows. #### Is it legal to scrape welcometothejungle.com? This actor extracts publicly available data from welcometothejungle.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant. #### Your feedback If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/wttj-scraper/issues) on the actor's page in Apify Console. Your feedback helps us improve. ### You might also like - [Adzuna Job Scraper](https://apify.com/blackfalcondata/adzuna-scraper) — Scrape adzuna.com — the global job board with 20+ country markets. Structured salary. - [Arbeitsagentur Scraper](https://apify.com/blackfalcondata/arbeitsagentur-scraper) — Scrape arbeitsagentur.de — Germany's official employment portal with 1M+ listings. Contact data,. - [Bayt.com Scraper — Jobs from the Middle East](https://apify.com/blackfalcondata/bayt-scraper) — Scrape bayt.com — the leading Middle East job board. Salary data, experience requirements. - [Dice.com Job Scraper](https://apify.com/blackfalcondata/dice-com-job-scraper) — Scrape dice.com — the leading U.S. tech job board. Structured salary (min/max/currency),. - [Drushim Scraper - Israel Job Listings from drushim.co.il](https://apify.com/blackfalcondata/drushim-scraper) — Scrape drushim.co.il — Israel's leading job board. Salary data, geo-coordinates, and multi-filter. - [Duunitori Scraper](https://apify.com/blackfalcondata/duunitori-scraper) — Scrape duunitori.fi — Finland's largest job board with 22,000+ listings. Salary ranges, employment. - [Glassdoor Job Scraper](https://apify.com/blackfalcondata/glassdoor-job-scraper) — Scrape glassdoor.com across 21 markets. Salary data, employer ratings, and search filters for role. - [Greenhouse Scraper](https://apify.com/blackfalcondata/greenhouse-scraper) — Scrape Greenhouse-powered career sites. Salary data, application questions, and department/office. # Actor input Schema ## `query` (type: `string`): Job search keywords, e.g. "software engineer". ## `language` (type: `string`): WTTJ Algolia index language. Determines which market to search. ## `countryCode` (type: `string`): Optional ISO 3166-1 alpha-2 country code to filter results, e.g. "FR", "DE", "GB". ## `location` (type: `string`): Optional city name to filter results, e.g. "Paris". ## `maxResults` (type: `integer`): Maximum total results to return. 0 = unlimited. ## `descriptionMaxLength` (type: `integer`): Truncate job description to N characters. 0 = no truncation. ## `compact` (type: `boolean`): Return core fields only (ideal for AI-agent / MCP workflows). ## `incrementalMode` (type: `boolean`): Only emit new or changed jobs compared to the previous run. ## `stateKey` (type: `string`): Stable identifier for the tracked universe. Required when incrementalMode is true. ## Actor input object example ```json { "query": "software engineer", "language": "fr", "maxResults": 25, "descriptionMaxLength": 0, "compact": false, "incrementalMode": false } ``` # Actor output Schema ## `results` (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 = { "query": "software engineer", "maxResults": 25 }; // Run the Actor and wait for it to finish const run = await client.actor("blackfalcondata/wttj-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 = { "query": "software engineer", "maxResults": 25, } # Run the Actor and wait for it to finish run = client.actor("blackfalcondata/wttj-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 '{ "query": "software engineer", "maxResults": 25 }' | apify call blackfalcondata/wttj-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=blackfalcondata/wttj-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Welcome to the Jungle Jobs Scraper", "description": "Scrape welcometothejungle.com — Europe's top tech & startup job board. Salary ranges, remote filters, and incremental change tracking across FR/EN/DE/ES markets.", "version": "0.1", "x-build-id": "X5Sf6p8crShY8QbCA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/blackfalcondata~wttj-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-blackfalcondata-wttj-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/blackfalcondata~wttj-scraper/runs": { "post": { "operationId": "runs-sync-blackfalcondata-wttj-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/blackfalcondata~wttj-scraper/run-sync": { "post": { "operationId": "run-sync-blackfalcondata-wttj-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "query" ], "properties": { "query": { "title": "Search Query", "type": "string", "description": "Job search keywords, e.g. \"software engineer\"." }, "language": { "title": "Language / Market", "enum": [ "fr", "en", "de", "es", "cs" ], "type": "string", "description": "WTTJ Algolia index language. Determines which market to search.", "default": "fr" }, "countryCode": { "title": "Country Code Filter", "type": "string", "description": "Optional ISO 3166-1 alpha-2 country code to filter results, e.g. \"FR\", \"DE\", \"GB\"." }, "location": { "title": "City Filter", "type": "string", "description": "Optional city name to filter results, e.g. \"Paris\"." }, "maxResults": { "title": "Max Results", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Maximum total results to return. 0 = unlimited.", "default": 50 }, "descriptionMaxLength": { "title": "Description Max Length", "minimum": 0, "type": "integer", "description": "Truncate job description to N characters. 0 = no truncation.", "default": 0 }, "compact": { "title": "Compact Output", "type": "boolean", "description": "Return core fields only (ideal for AI-agent / MCP workflows).", "default": false }, "incrementalMode": { "title": "Incremental Mode", "type": "boolean", "description": "Only emit new or changed jobs compared to the previous run.", "default": false }, "stateKey": { "title": "State Key", "type": "string", "description": "Stable identifier for the tracked universe. Required when incrementalMode is true." } } }, "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 } } } } } } } } } } ```