# Hacker News - Who Is Hiring Structured Job Extractor (`troy_007/hn-who-is-hiring-extractor`) Actor Turns the monthly HN 'Ask HN: Who is hiring?' thread into clean structured job data: company, role, location, remote, tech stack, salary, and apply info. - **URL**: https://apify.com/troy\_007/hn-who-is-hiring-extractor.md - **Developed by:** [Pathik Shah](https://apify.com/troy_007) (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 $10.00 / 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 ## Hacker News – Who Is Hiring Structured Job Extractor Turn the monthly **"Ask HN: Who is hiring?"** thread into clean, structured, ready-to-use job data. Every month thousands of high-quality tech jobs are posted on Hacker News as free-form comments — great to read, painful to work with. This Actor parses them into columns you can filter, export, and load anywhere. ### What you get per job | Field | Description | |-------|-------------| | `company` | Hiring company name | | `role` | Job title / role | | `location` | Detected location | | `remote` | Remote / Hybrid / Onsite / Not specified | | `techStack` | Detected technologies (React, Python, Go, AWS, …) | | `salary` | Salary if the poster included one | | `applyUrl` | Application link if present | | `applyEmail` | Application email if present | | `postedBy` | HN username | | `threadDate` | Which monthly thread it came from | | `commentUrl` | Direct link to the original HN comment | | `fullText` | Full cleaned comment text | ### Why this Actor - **Reliable** — uses the official Hacker News API, not fragile HTML scraping. No blocking, no proxies needed. - **Structured** — content-aware parsing classifies each field by pattern, not brittle column position. - **Filterable** — pull only remote jobs, only jobs mentioning your stack, or only a location. ### Use cases - Recruiters and job-board operators aggregating fresh, high-quality tech roles - Developers tracking who's hiring for their stack, remotely - Founders and researchers analysing hiring trends, salaries, and tech demand over time ### Input | Option | Type | Default | Description | |--------|------|---------|-------------| | `monthsToScrape` | integer | 1 | How many recent monthly threads to process (1 = current month) | | `remoteOnly` | boolean | false | Return only remote / hybrid jobs | | `keywords` | array | [] | Only jobs whose text contains one of these terms | | `locationFilter` | string | "" | Only jobs whose location contains this text | | `maxItems` | integer | 0 | Cap on jobs returned (0 = no limit) | ### Example output ```json { "company": "Komodo Health", "role": "Software Engineer", "location": "Remote US", "remote": "Remote", "techStack": ["go", "rust", "ai"], "salary": "$200–298k", "applyUrl": "https://komodohealth.com/careers", "postedBy": "ramraj07", "threadDate": "2026-07-01", "commentUrl": "https://news.ycombinator.com/item?id=..." } ```` ### Pricing Pay per result — you only pay for the structured jobs returned. Runs are fast and cheap because there is no browser rendering or proxy overhead. # Actor input Schema ## `monthsToScrape` (type: `integer`): How many of the most recent monthly 'Who is hiring?' threads to process (1 = current month only). ## `remoteOnly` (type: `boolean`): If enabled, only postings detected as remote-friendly are returned. ## `keywords` (type: `array`): Only return jobs whose text contains at least one of these keywords (case-insensitive). Leave empty for all jobs. ## `locationFilter` (type: `string`): Only return jobs whose detected location contains this text (e.g. 'London', 'US', 'India'). Case-insensitive. ## `maxItems` (type: `integer`): Hard cap on number of jobs pushed to the dataset. 0 = no limit. ## Actor input object example ```json { "monthsToScrape": 1, "remoteOnly": false, "keywords": [], "locationFilter": "", "maxItems": 0 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("troy_007/hn-who-is-hiring-extractor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("troy_007/hn-who-is-hiring-extractor").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 troy_007/hn-who-is-hiring-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=troy_007/hn-who-is-hiring-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News - Who Is Hiring Structured Job Extractor", "description": "Turns the monthly HN 'Ask HN: Who is hiring?' thread into clean structured job data: company, role, location, remote, tech stack, salary, and apply info.", "version": "1.0", "x-build-id": "NCtIae1C9xQPBbMS3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/troy_007~hn-who-is-hiring-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-troy_007-hn-who-is-hiring-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/troy_007~hn-who-is-hiring-extractor/runs": { "post": { "operationId": "runs-sync-troy_007-hn-who-is-hiring-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/troy_007~hn-who-is-hiring-extractor/run-sync": { "post": { "operationId": "run-sync-troy_007-hn-who-is-hiring-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "monthsToScrape": { "title": "Number of recent threads to scrape", "minimum": 1, "maximum": 24, "type": "integer", "description": "How many of the most recent monthly 'Who is hiring?' threads to process (1 = current month only).", "default": 1 }, "remoteOnly": { "title": "Remote jobs only", "type": "boolean", "description": "If enabled, only postings detected as remote-friendly are returned.", "default": false }, "keywords": { "title": "Keyword filter", "type": "array", "description": "Only return jobs whose text contains at least one of these keywords (case-insensitive). Leave empty for all jobs.", "default": [], "items": { "type": "string" } }, "locationFilter": { "title": "Location contains", "type": "string", "description": "Only return jobs whose detected location contains this text (e.g. 'London', 'US', 'India'). Case-insensitive.", "default": "" }, "maxItems": { "title": "Max jobs to return", "minimum": 0, "type": "integer", "description": "Hard cap on number of jobs pushed to the dataset. 0 = no limit.", "default": 0 } } }, "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 } } } } } } } } } } ```