# Hacker News Jobs Scraper — Who is Hiring (`deadlyaccurate/hn-jobs-scraper`) Actor Scrape HN "Who is Hiring" threads. Extracts company, title, location, remote, salary, technologies from unstructured text. Multi-month coverage. Unified/raw/both output. - **URL**: https://apify.com/deadlyaccurate/hn-jobs-scraper.md - **Developed by:** [Doug Silkstone](https://apify.com/deadlyaccurate) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 4 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 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 # Actor input Schema ## `months` (type: `integer`): Number of recent monthly 'Who is Hiring?' threads to scrape. Each month typically has 500-800 job posts. Default: 2 (current + previous month). ## `concurrency` (type: `integer`): Number of parallel API requests for fetching HN comments. Higher = faster but more memory. Recommended: 10. ## `remoteOnly` (type: `boolean`): Only return jobs that mention remote work. ## `locationFilter` (type: `string`): Regex pattern to match job locations. Examples: - 'europe|germany|uk|france' -- European jobs - 'remote' -- Any location containing 'remote' - 'new york|san francisco|austin' -- US tech hubs - 'prague|czech' -- Specific city/country ## `keywordFilter` (type: `string`): Regex pattern to match job titles or descriptions. Examples: - 'senior|staff|lead|principal' -- Senior roles - 'full.?stack|fullstack' -- Full-stack engineers - 'react|typescript|node' -- Tech-specific - 'founding|head.of|vp|director' -- Leadership ## `technologyFilter` (type: `string`): Regex pattern to match technologies. Examples: - 'react|vue|angular' -- Frontend frameworks - 'python|rust|go' -- Languages - 'aws|gcp|azure' -- Cloud providers - 'postgres|mongodb|redis' -- Databases ## `includeRawHtml` (type: `boolean`): Include the raw HTML from each HN comment in the output. Increases dataset size. Default: off to keep results lean. ## `outputFormat` (type: `string`): How to format output records: - 'unified' (default) — Normalized schema consistent across all ATS platforms with structured location, salary, company objects - 'raw' — Native HN format, no normalization - 'both' — Unified schema with original HN data in the 'raw' field ## Actor input object example ```json { "months": 2, "concurrency": 10, "remoteOnly": false, "locationFilter": "", "keywordFilter": "", "technologyFilter": "", "includeRawHtml": false, "outputFormat": "unified" } ```` # Actor output Schema ## `jobs` (type: `string`): No description ## `summary` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("deadlyaccurate/hn-jobs-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 = {} # Run the Actor and wait for it to finish run = client.actor("deadlyaccurate/hn-jobs-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 '{}' | apify call deadlyaccurate/hn-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=deadlyaccurate/hn-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News Jobs Scraper — Who is Hiring", "description": "Scrape HN \"Who is Hiring\" threads. Extracts company, title, location, remote, salary, technologies from unstructured text. Multi-month coverage. Unified/raw/both output.", "version": "1.0", "x-build-id": "h2ensrFZhFzfvTzq6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/deadlyaccurate~hn-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-deadlyaccurate-hn-jobs-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/deadlyaccurate~hn-jobs-scraper/runs": { "post": { "operationId": "runs-sync-deadlyaccurate-hn-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/deadlyaccurate~hn-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-deadlyaccurate-hn-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "months": { "title": "Months to Scrape", "minimum": 1, "maximum": 12, "type": "integer", "description": "Number of recent monthly 'Who is Hiring?' threads to scrape.\n\nEach month typically has 500-800 job posts. Default: 2 (current + previous month).", "default": 2 }, "concurrency": { "title": "Concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Number of parallel API requests for fetching HN comments. Higher = faster but more memory. Recommended: 10.", "default": 10 }, "remoteOnly": { "title": "Remote Jobs Only", "type": "boolean", "description": "Only return jobs that mention remote work.", "default": false }, "locationFilter": { "title": "Location Filter", "type": "string", "description": "Regex pattern to match job locations.\n\nExamples:\n- 'europe|germany|uk|france' -- European jobs\n- 'remote' -- Any location containing 'remote'\n- 'new york|san francisco|austin' -- US tech hubs\n- 'prague|czech' -- Specific city/country", "default": "" }, "keywordFilter": { "title": "Title/Keyword Filter", "type": "string", "description": "Regex pattern to match job titles or descriptions.\n\nExamples:\n- 'senior|staff|lead|principal' -- Senior roles\n- 'full.?stack|fullstack' -- Full-stack engineers\n- 'react|typescript|node' -- Tech-specific\n- 'founding|head.of|vp|director' -- Leadership", "default": "" }, "technologyFilter": { "title": "Technology Filter", "type": "string", "description": "Regex pattern to match technologies.\n\nExamples:\n- 'react|vue|angular' -- Frontend frameworks\n- 'python|rust|go' -- Languages\n- 'aws|gcp|azure' -- Cloud providers\n- 'postgres|mongodb|redis' -- Databases", "default": "" }, "includeRawHtml": { "title": "Include Raw HTML", "type": "boolean", "description": "Include the raw HTML from each HN comment in the output. Increases dataset size. Default: off to keep results lean.", "default": false }, "outputFormat": { "title": "Output Format", "enum": [ "unified", "raw", "both" ], "type": "string", "description": "How to format output records:\n- 'unified' (default) — Normalized schema consistent across all ATS platforms with structured location, salary, company objects\n- 'raw' — Native HN format, no normalization\n- 'both' — Unified schema with original HN data in the 'raw' field", "default": "unified" } } }, "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 } } } } } } } } } } ```