# Hacker News API Scraper (`lokki/hacker-news-api-scraper`) Actor Scrapes Hacker News items through the official Firebase API and outputs only result rows. - **URL**: https://apify.com/lokki/hacker-news-api-scraper.md - **Developed by:** [Ian Dikhtiar](https://apify.com/lokki) (community) - **Categories:** Automation, News, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 Trend Scraper Hacker News is an early-warning system for what technical people care about. This actor turns HN into clean structured data from the official Firebase API: top stories, new stories, best stories, Ask HN, Show HN, jobs, or exact item IDs. Use it for startup research, developer intelligence, launch tracking, hiring-market signals, newsletters, dashboards, alerts, and AI workflows. ### What you get - One real Hacker News item per dataset row - Title, author, score, comment count, timestamp, URL, and HN discussion link - Optional HN text for Ask HN, Show HN, jobs, comments, and polls - Optional child/comment IDs for discussion graph workflows - Run summary stored separately in the key-value store ### Best feeds | Feed | Best for | |---|---| | `topstories` | Current front-page monitoring | | `newstories` | Early trend detection | | `beststories` | Higher-quality ranked items | | `askstories` | Pain points, questions, and debates | | `showstories` | Launches, demos, tools, and startup ideas | | `jobstories` | Hiring and market-demand signals | ### Example input ```json { "feed": "showstories", "maxItems": 100, "itemType": "story", "includeText": true, "includeKidIds": true } ```` ### Data source Official Hacker News Firebase API: ```text https://hacker-news.firebaseio.com/v0/.json https://hacker-news.firebaseio.com/v0/item/.json ``` No proxy, browser rendering, or HTML parsing required. # Actor input Schema ## `feed` (type: `string`): Choose the public Hacker News feed to collect. If you provide specific item IDs below, the feed is ignored. ## `itemIds` (type: `array`): Optional. Paste exact Hacker News item IDs when you want to enrich known posts/comments/jobs instead of scraping a feed. Example IDs: 8863, 2921983. ## `maxItems` (type: `integer`): Maximum number of matching HN items to save to the dataset. ## `itemType` (type: `string`): Recommended: Stories for top/new/best/Ask/Show, Jobs for jobstories, All for mixed enrichment by exact item IDs. ## `includeText` (type: `boolean`): Adds the HN text field when available. Recommended for Ask HN, Show HN, jobs, and exact item ID enrichment. ## `includeKidIds` (type: `boolean`): Adds child IDs and kidCount. Turn this on if you plan to fetch comments later or analyze discussion graph structure. ## Actor input object example ```json { "feed": "topstories", "itemIds": [], "maxItems": 100, "itemType": "story", "includeText": true, "includeKidIds": false } ``` # Actor output Schema ## `items` (type: `string`): Default dataset containing one real Hacker News item per row from the official Firebase API. ## `trendRadar` (type: `string`): Console dataset view optimized for browsing titles, authors, scores, comments, links, and HN discussion URLs. ## `researchText` (type: `string`): Console dataset view focused on HN text fields for Ask HN, Show HN, jobs, and exact item enrichment. ## `discussionGraph` (type: `string`): Console dataset view focused on parent, poll, child IDs, and child counts when child IDs are included. ## `summary` (type: `string`): Machine-readable summary with selected feed, item type, checked count, pushed count, and generated timestamp. # 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 = { "itemIds": [] }; // Run the Actor and wait for it to finish const run = await client.actor("lokki/hacker-news-api-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 = { "itemIds": [] } # Run the Actor and wait for it to finish run = client.actor("lokki/hacker-news-api-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 '{ "itemIds": [] }' | apify call lokki/hacker-news-api-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lokki/hacker-news-api-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News API Scraper", "description": "Scrapes Hacker News items through the official Firebase API and outputs only result rows.", "version": "1.0", "x-build-id": "5rCC2Bz91JTdki4mJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lokki~hacker-news-api-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lokki-hacker-news-api-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lokki~hacker-news-api-scraper/runs": { "post": { "operationId": "runs-sync-lokki-hacker-news-api-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lokki~hacker-news-api-scraper/run-sync": { "post": { "operationId": "run-sync-lokki-hacker-news-api-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "maxItems" ], "properties": { "feed": { "title": "HN feed", "enum": [ "topstories", "newstories", "beststories", "askstories", "showstories", "jobstories" ], "type": "string", "description": "Choose the public Hacker News feed to collect. If you provide specific item IDs below, the feed is ignored.", "default": "topstories" }, "itemIds": { "title": "Specific HN item IDs", "type": "array", "description": "Optional. Paste exact Hacker News item IDs when you want to enrich known posts/comments/jobs instead of scraping a feed. Example IDs: 8863, 2921983.", "items": { "type": "string" } }, "maxItems": { "title": "Maximum items", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of matching HN items to save to the dataset.", "default": 100 }, "itemType": { "title": "Keep item type", "enum": [ "story", "job", "poll", "comment", "all" ], "type": "string", "description": "Recommended: Stories for top/new/best/Ask/Show, Jobs for jobstories, All for mixed enrichment by exact item IDs.", "default": "story" }, "includeText": { "title": "Include HN text", "type": "boolean", "description": "Adds the HN text field when available. Recommended for Ask HN, Show HN, jobs, and exact item ID enrichment.", "default": true }, "includeKidIds": { "title": "Include child/comment IDs", "type": "boolean", "description": "Adds child IDs and kidCount. Turn this on if you plan to fetch comments later or analyze discussion graph structure.", "default": false } } }, "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 } } } } } } } } } } ```