# JobsFlow (`zyncodltd/jobsflow`) Actor The most comprehensive remote job scraper on Apify. This Actor aggregates and de-duplicates thousands of remote tech job postings from multiple high-quality sources, providing you with a clean, structured dataset in a single run. - **URL**: https://apify.com/zyncodltd/jobsflow.md - **Developed by:** [Usama Rehman Tarar](https://apify.com/zyncodltd) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 4 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 ## JobFlows Scraper - Comprehensive Remote Job Aggregator Tired of building and maintaining separate web scrapers for every job board? This Actor is your **one-stop solution** for aggregating high-quality remote tech jobs. It automatically scrapes the best remote job boards, intelligently de-duplicates the listings, and provides a clean, structured dataset ready to power your application, fuel your market research, or find your next opportunity. ### Key Features - **✅ Multi-Source Aggregation:** Pulls data from the most respected remote job boards in one run. - RemoteOK - Remotive - WeWorkRemotely - *(More valuable sources coming soon!)* - **✅ Intelligent De-duplication:** Automatically removes duplicate job postings that appear on multiple sites, giving you a clean and unique list. - **✅ Clean & Structured Output:** Delivers data in a predictable, easy-to-use format. Access your results directly from the Apify platform and export to JSON, CSV, Excel, and more. - **✅ Powerful Filtering:** Easily narrow down your results by using keyword search or filtering by specific technology stack tags. ### Output Schema Each job listing is a clean JSON object with the following fields. The URL is always a direct, clickable link to the application page. | Field | Type | Description | | :-------- | :------- | :----------------------------------------------------------- | | `title` | `string` | The job title. | | `company` | `string` | The name of the hiring company. | | `url` | `string` | Direct link to the job application page. | | `source` | `string` | The job board this posting came from. | | `posted_at` | `string` | The date the job was posted (ISO 8601). | | `location` | `string` | Required candidate location (e.g., "Remote," "USA Only"). | | `tags` | `array` | A list of relevant tech stack tags. | | `salary` | `string` | The salary range, if provided. | ### How to Use 1. **Run the Actor:** Click the "Run" button. You can leave the input empty to get all jobs. 2. **Filter Results (Optional):** Use the input fields to narrow down the jobs by keywords or technology. 3. **Download Your Data:** Once the run has succeeded, go to the **Dataset** tab to view and export your results. For a continuous stream of fresh jobs, run this Actor on a **schedule**! ### Input Parameters | Field | Type | Description | | :--------------- | :-------- | :----------------------------------------------------------------------------- | | `searchKeywords` | `string` | A keyword to search for in the job title and description (e.g., "AI Engineer"). | | `techStack` | `string` | A comma-separated list of tech tags to filter by (e.g., "python,aws,docker"). | | `maxJobs` | `integer` | The maximum number of jobs you want to get. Defaults to 100. | --- Save hundreds of development hours and get instant access to a rich, aggregated dataset of remote job opportunities. # Actor input Schema ## `searchKeywords` (type: `string`): Filter by keywords in title or description (e.g. 'python'). ## `techStack` (type: `string`): Comma-separated tags (e.g. 'aws,docker,react'). ## `maxJobs` (type: `integer`): Maximum number of jobs to return (1–500). ## Actor input object example ```json { "maxJobs": 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("zyncodltd/jobsflow").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 = {} # Run the Actor and wait for it to finish run = client.actor("zyncodltd/jobsflow").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 '{}' | apify call zyncodltd/jobsflow --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=zyncodltd/jobsflow", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "JobsFlow", "description": "The most comprehensive remote job scraper on Apify. This Actor aggregates and de-duplicates thousands of remote tech job postings from multiple high-quality sources, providing you with a clean, structured dataset in a single run.", "version": "0.0", "x-build-id": "MFk3lrqkQAQa9rSZD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/zyncodltd~jobsflow/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-zyncodltd-jobsflow", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/zyncodltd~jobsflow/runs": { "post": { "operationId": "runs-sync-zyncodltd-jobsflow", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/zyncodltd~jobsflow/run-sync": { "post": { "operationId": "run-sync-zyncodltd-jobsflow", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchKeywords": { "title": "Keywords", "type": "string", "description": "Filter by keywords in title or description (e.g. 'python')." }, "techStack": { "title": "Tech stack tags", "type": "string", "description": "Comma-separated tags (e.g. 'aws,docker,react')." }, "maxJobs": { "title": "Max jobs", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of jobs to return (1–500).", "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 } } } } } } } } } } ```