# 🔥Linkedin real-time job scraper (`hermann_samimi/apyfi-linkedin`) Actor 🇺🇸🇬🇧🇳🇱🇩🇪🇨🇦Query a curated LinkedIn jobs database across Germany, Canada, the US, Netherlands, and the UK. Filter by title, location, company, language, remote/contract flags, and date. Each result includes job details, URLs, and company metadata as dataset items or a JSON array. - **URL**: https://apify.com/hermann\_samimi/apyfi-linkedin.md - **Developed by:** [Hermann Samimi](https://apify.com/hermann_samimi) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 11 total users, 1 monthly users, 100.0% runs succeeded, 7 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $3.00 / 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 ## Pingrole Job Search Search a continuously updated database of **LinkedIn job listings** across five markets. Filter by title, location, company, country, language, remote and contract type, and posting date. Each match returns structured job and company fields ready to export or pipe into your stack. **Coverage:** Germany · Canada · United States · Netherlands · United Kingdom (LinkedIn only) --- ### Quick start (Apify Console) 1. Open this Actor in the [Apify Console](https://console.apify.com). 2. Go to the **Input** tab. 3. Fill in the four required fields: **Job Title**, **Location**, **Country**, and **Limit**. 4. Optionally set company, language, booleans, date range, skip, and sort. 5. Click **Start**. 6. When the run finishes, open the **Dataset** tab to browse results or download as JSON, CSV, Excel, or XML. The four required fields (**Job Title**, **Location**, **Country**, **Limit**) open with default values you can edit before running. Optional fields like **Skip** and **Sort** use their own defaults. --- ### Input fields | Field | Required | Description | |-------|----------|-------------| | **Job Title** (`title`) | Yes | Default: `software engineer`. Partial, case-insensitive match. Comma-separated values are OR’d. | | **Location** (`location`) | Yes | Default: `toronto`. Partial, case-insensitive match. Comma-separated OR supported. | | **Country** (`country`) | Yes | Default: `canada`. Exact match: `canada`, `germany`, `netherlands`, `United States`, `United Kingdom`. | | **Company** (`company`) | No | Partial match on company name. Comma-separated OR supported. | | **Language** (`language`) | No | Exact match: `en`, `fr`, or `de`. | | **Remote** | No | Checked = remote jobs only. Unchecked with explicit `false` in API = exclude remote. Leave empty to ignore. | | **Part Time** | No | Part-time roles only (same true / false / ignore behavior). | | **Freelancer** | No | Freelance roles only. | | **Academic** | No | Academic roles only. | | **Research** | No | Research roles only. | | **B2B** | No | B2B contract roles only. | | **Date From** (`datetime_from`) | No | Jobs scraped on or after this time. Formats: `2026-01-01` or `2026-01-01@11:00` (use `@` instead of `T` for time). | | **Date To** (`datetime_to`) | No | Jobs scraped on or before this time. Same format as Date From. | | **Limit** | Yes | Default: `10`. Number of jobs to return per run (**1–100**). | | **Skip** | No | Offset for pagination (default **0**). | | **Sort Field** | No | `datetime_from` (newest/oldest by scrape time, default), `title`, `company`, `language`, or `country`. | | **Sort Direction** | No | **-1** = descending (newest first when sorting by date). **1** = ascending. | **Boolean filters:** In the Console, check a box to require that flag. In the API, use `true` to include only matching jobs, `false` to exclude them, or omit the field to ignore it. --- ### Example inputs **Software engineers in Toronto** ```json { "title": "software engineer", "location": "Toronto", "country": "canada", "limit": 20 } ```` **Remote data roles in Germany (German listings)** ```json { "title": "data", "location": "Berlin", "country": "germany", "Remote": true, "language": "de", "limit": 50 } ``` **Product roles at a specific company, posted in May 2026 (page 2)** ```json { "title": "product manager", "location": "Amsterdam", "country": "netherlands", "company": "Booking", "datetime_from": "2026-05-01", "datetime_to": "2026-05-31", "limit": 10, "skip": 10, "sort_field": "datetime_from", "sort_direction": -1 } ``` **Multiple title keywords (OR)** ```json { "title": "backend, full stack, fullstack", "location": "London", "country": "United Kingdom", "limit": 25 } ``` *** ### Output Each run writes **one dataset record per job** to your run’s default dataset. Fields are omitted or `null` when not available on the listing. | Field | Description | |-------|-------------| | `title` | Job title | | `company` | Company name | | `location` | Location string | | `country` | Country | | `language` | Listing language (`en`, `fr`, `de`, …) | | `job_type` | e.g. `fulltime`, `parttime` | | `job_level` | Seniority, e.g. `mid-senior` | | `job_url` | LinkedIn job posting URL | | `description` | Full job description text | | `timestamp` | When the listing was scraped (UTC) | | `site` | Source site (always `linkedin` for this Actor) | | `job_id` | Stable job identifier | | `Remote`, `PartTime`, `Freelancer`, `Academic`, `Research`, `B2B` | Job-type flags | | `salary_source`, `currency` | Salary info when present | | `company_logo` | Logo image URL | | `company_url` | LinkedIn company page | | `company_url_direct` | Company website | | `company_addresses` | Company address data when available | | `company_industry` | Industry | | `company_num_employees` | Employee count range | | `company_revenue` | Revenue band when available | | `company_description` | Company description | | `company_rating` | Company rating when available | The run also saves the same job array to the key-value store under **`OUTPUT`** (useful for API consumers that read KV store instead of the dataset). #### Example record ```json { "title": "Software Engineer", "company": "Example GmbH", "location": "Berlin, DE", "country": "germany", "language": "de", "job_type": "fulltime", "job_level": "mid-senior", "job_url": "https://www.linkedin.com/jobs/view/4374072722", "description": "We are looking for...", "timestamp": "2026-05-16 14:50:09.053000", "site": "linkedin", "salary_source": null, "currency": null, "company_logo": null, "company_url": "https://linkedin.com/company/example-gmbh", "company_url_direct": "https://example.com", "company_addresses": null, "company_industry": "Software Development", "company_num_employees": "51-200", "company_revenue": null, "company_description": "Example GmbH is a Berlin-based...", "company_rating": null, "Remote": true, "PartTime": false, "Freelancer": false, "Academic": false, "Research": false, "B2B": false, "job_id": "li-4374072722" } ``` *** ### Pagination Use **Limit** and **Skip** together to page through results: | Page | `limit` | `skip` | |------|---------|--------| | 1 | 10 | 0 | | 2 | 10 | 10 | | 3 | 10 | 20 | Each page returns at most `limit` jobs (max **100** per run). If a page returns fewer records than `limit`, you have reached the end of the matching set for that query. Run again with a higher `skip` to fetch the next page. *** ### Run from your code (Apify API) Replace `YOUR_ACTOR_ID` with this Actor’s ID or username/name slug from the Apify Store. **Node.js** ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' }); const run = await client.actor('YOUR_ACTOR_ID').call({ title: 'software engineer', location: 'Toronto', country: 'canada', limit: 20, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` **Python** ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("YOUR_ACTOR_ID").call( run_input={ "title": "software engineer", "location": "Toronto", "country": "canada", "limit": 20, } ) items = client.dataset(run["defaultDatasetId"]).list_items().items ``` **cURL (start a run)** ```bash curl -X POST "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"title":"software engineer","location":"Toronto","country":"canada","limit":20}' ``` Fetch dataset items from the run’s `defaultDatasetId` in the API response, or download exports from the Console. *** ### Scheduling and integrations In the Apify Console you can **schedule** this Actor (e.g. daily) so fresh jobs land in a dataset automatically. Connect the dataset to **Google Sheets**, **Slack**, **Zapier**, **Make**, **Airtable**, webhooks, or other [Apify integrations](https://docs.apify.com/platform/integrations) without writing custom export code. *** ### Tips - Start broad on **Job Title** and **Location** within your **Country**, then narrow with boolean flags and optional **Company**. - Use **Date From** / **Date To** to focus on recently scraped listings. - Sort by `datetime_from` with direction **-1** for the newest jobs first. - For large pulls, chain multiple runs with increasing `skip` (respect the 100-per-run cap). *** ### Support Built by **Hermann Samimi** · [Pingrole](https://realtime.pingrole.com) - **Live dashboard:** [realtime.pingrole.com](https://realtime.pingrole.com) - **Email:** - **Book a call:** [calendly.com/hermannsamimi/30min](https://calendly.com/hermannsamimi/30min) # Actor input Schema ## `title` (type: `string`): Partial match, e.g. software engineer ## `location` (type: `string`): Partial match, e.g. Toronto ## `country` (type: `string`): Filter by country ## `limit` (type: `integer`): Results to return (1–100) ## `company` (type: `string`): Partial match, e.g. Google ## `language` (type: `string`): en, fr, or de. Default: en ## `Remote` (type: `boolean`): Remote jobs only ## `PartTime` (type: `boolean`): Part-time roles only ## `Freelancer` (type: `boolean`): Freelance roles only ## `Academic` (type: `boolean`): Academic roles only ## `Research` (type: `boolean`): Research roles only ## `B2B` (type: `boolean`): B2B contract roles only ## `datetime_from` (type: `string`): ISO date e.g. 2026-01-01 or 2026-01-01@11:00 ## `datetime_to` (type: `string`): ISO date e.g. 2026-12-31 or 2026-12-31@17:45 ## `skip` (type: `integer`): Pagination offset ## `sort_field` (type: `string`): Field to sort results by ## `sort_direction` (type: `integer`): -1 newest first (default) · 1 oldest first ## Actor input object example ```json { "title": "software engineer", "location": "toronto", "country": "canada", "limit": 10, "language": "en", "skip": 0, "sort_field": "datetime_from", "sort_direction": -1 } ``` # Actor output Schema ## `jobs` (type: `string`): Default dataset with one record per matching job. Use the overview view for the recommended table layout in Apify Console. ## `jobsArray` (type: `string`): Same results as the dataset, stored as a single JSON array in the default key-value store record OUTPUT. Useful for API clients that read one KV record instead of paginating dataset items. # 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 = { "title": "software engineer", "location": "toronto", "country": "canada", "limit": 10, "language": "en" }; // Run the Actor and wait for it to finish const run = await client.actor("hermann_samimi/apyfi-linkedin").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 = { "title": "software engineer", "location": "toronto", "country": "canada", "limit": 10, "language": "en", } # Run the Actor and wait for it to finish run = client.actor("hermann_samimi/apyfi-linkedin").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 '{ "title": "software engineer", "location": "toronto", "country": "canada", "limit": 10, "language": "en" }' | apify call hermann_samimi/apyfi-linkedin --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hermann_samimi/apyfi-linkedin", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🔥Linkedin real-time job scraper", "description": "🇺🇸🇬🇧🇳🇱🇩🇪🇨🇦Query a curated LinkedIn jobs database across Germany, Canada, the US, Netherlands, and the UK. Filter by title, location, company, language, remote/contract flags, and date. Each result includes job details, URLs, and company metadata as dataset items or a JSON array.", "version": "0.0", "x-build-id": "7WFVzU87KviNCcVdW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hermann_samimi~apyfi-linkedin/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hermann_samimi-apyfi-linkedin", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/hermann_samimi~apyfi-linkedin/runs": { "post": { "operationId": "runs-sync-hermann_samimi-apyfi-linkedin", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/hermann_samimi~apyfi-linkedin/run-sync": { "post": { "operationId": "run-sync-hermann_samimi-apyfi-linkedin", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "title", "location", "country", "limit" ], "properties": { "title": { "title": "Job Title", "minLength": 1, "type": "string", "description": "Partial match, e.g. software engineer", "default": "software engineer" }, "location": { "title": "Location", "minLength": 1, "type": "string", "description": "Partial match, e.g. Toronto", "default": "toronto" }, "country": { "title": "Country", "enum": [ "canada", "germany", "netherlands", "United States", "United Kingdom" ], "type": "string", "description": "Filter by country", "default": "canada" }, "limit": { "title": "Limit", "minimum": 1, "maximum": 100, "type": "integer", "description": "Results to return (1–100)", "default": 10 }, "company": { "title": "Company", "type": "string", "description": "Partial match, e.g. Google" }, "language": { "title": "Language", "type": "string", "description": "en, fr, or de. Default: en", "default": "en" }, "Remote": { "title": "Remote", "type": "boolean", "description": "Remote jobs only" }, "PartTime": { "title": "Part Time", "type": "boolean", "description": "Part-time roles only" }, "Freelancer": { "title": "Freelancer", "type": "boolean", "description": "Freelance roles only" }, "Academic": { "title": "Academic", "type": "boolean", "description": "Academic roles only" }, "Research": { "title": "Research", "type": "boolean", "description": "Research roles only" }, "B2B": { "title": "B2B", "type": "boolean", "description": "B2B contract roles only" }, "datetime_from": { "title": "Date From", "type": "string", "description": "ISO date e.g. 2026-01-01 or 2026-01-01@11:00" }, "datetime_to": { "title": "Date To", "type": "string", "description": "ISO date e.g. 2026-12-31 or 2026-12-31@17:45" }, "skip": { "title": "Skip", "type": "integer", "description": "Pagination offset", "default": 0 }, "sort_field": { "title": "Sort Field", "enum": [ "datetime_from", "title", "company", "language", "country" ], "type": "string", "description": "Field to sort results by", "default": "datetime_from" }, "sort_direction": { "title": "Sort Direction", "type": "integer", "description": "-1 newest first (default) · 1 oldest first", "default": -1 } } }, "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 } } } } } } } } } } ```