# ProductHunt Launches & Makers Scraper (`haketa/producthunt-launches-scraper`) Actor Extract Product Hunt launches, makers, votes, reviews, ratings, screenshots, topics — by URL, product slug, topic, or daily leaderboard date. JSON-LD + Apollo-state extraction, no API key required. - **URL**: https://apify.com/haketa/producthunt-launches-scraper.md - **Developed by:** [Haketa](https://apify.com/haketa) (community) - **Categories:** Developer tools, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## 🚀 ProductHunt Launches & Makers Scraper Extract every public field from any **Product Hunt** product page — launches, makers, votes, reviews, ratings, screenshots, topics — using just a slug, a URL, a topic page, or a daily leaderboard date. **No API key required.** --- ### ⭐ What You Get For each product: - **Identity** — name, slug, product URL, website URL - **Visuals** — thumbnail + all screenshots (high-res, imgix CDN URLs) - **Engagement** — upvote count, comment count, aggregate rating (1–5) with rating count - **Categorization** — Product Hunt topics (Productivity, AI, Developer Tools, etc.) + application category - **Launch metadata** — date published, date last modified - **Makers** — name, avatar, profile URL for each founder/maker - **Reviews** — rating, review body, author name+profile, date, for each review - **Operating system** support tag (when set) Everything is **JSON-LD parsed + Apollo-state extracted** — exactly what Product Hunt serves to Google. --- ### 🎯 Use Cases - **Startup intelligence** — track daily launches, identify trending products in your space - **VC sourcing** — find founders and their products before they break out - **Recruiter sourcing** — identify makers of top-rated products by category - **Competitor monitoring** — watch your competitors' launch metrics over time - **Tech newsletter** — daily/weekly digest of top launches with rich metadata - **Market research** — survey an entire topic (e.g., all `artificial-intelligence` products) --- ### 🛠️ Input You can mix and match four ways to point the scraper at products. Provide one or more: | Field | Type | Purpose | Example | |---|---|---|---| | `startUrls` | array | Any Product Hunt URL — product, post, leaderboard, topic | `https://www.producthunt.com/products/notion` | | `productSlugs` | array | Product slugs (path after `/products/`) | `["notion", "linear", "vercel"]` | | `topicSlugs` | array | Discover all products on a topic page | `["productivity", "artificial-intelligence"]` | | `leaderboardDates` | array | Discover top products from daily leaderboard (`YYYY/M/D`) | `["2026/5/17"]` | | `scrapeReviews` | bool | Include review bodies (default: true) | `true` | | `maxRecords` | int | Cap on total products (0 = unlimited) | `100` | | `requestDelay` | int | ms between requests | `800` | | `maxConcurrency` | int | parallel requests | `4` | | `proxyConfiguration` | object | Optional Apify proxy | usually not needed | --- ### 📤 Example Output ```json { "slug": "linear", "productUrl": "https://www.producthunt.com/products/linear", "name": "Linear", "tagline": "The issue tracking tool you'll enjoy using", "websiteUrl": "https://linear.app", "image": "https://ph-files.imgix.net/9d9aa008-....png", "screenshots": ["https://ph-files.imgix.net/35d1d856....png", "..."], "applicationCategory": "Hiring", "datePublished": "2019-10-30T16:22:48-07:00", "dateModified": "2026-05-18T09:02:38-07:00", "aggregateRating": { "ratingValue": 4.91, "ratingCount": 395, "bestRating": 5, "worstRating": 1 }, "votesCount": 29, "commentsCount": 38, "topics": [ { "slug": "productivity", "name": "Productivity" }, { "slug": "developer-tools", "name": "Developer Tools" } ], "makers": [ { "name": "Karri Saarinen", "image": "https://ph-avatars.imgix.net/508/....jpeg", "profile": "https://www.producthunt.com/@karrisaarinen" } ], "reviews": [ { "rating": 5, "body": "Linear has completely changed how our team tracks work...", "author": "Jane Doe", "authorProfile": "https://www.producthunt.com/@janedoe", "datePublished": "2025-08-12T..." } ], "scrapedAt": "2026-05-18T16:00:00.000Z" } ```` *** ### ⚡ How It Works 1. **Discovery phase** — for each `startUrl`, `topicSlug`, or `leaderboardDate`, the scraper fetches the page and harvests every `/products/` link. 2. **Detail phase** — for each unique slug, it fetches `/products/` and parses three JSON-LD blocks (BreadcrumbList, WebApplication/Product, Reviews) plus inline Apollo state for vote/comment counts, topics, and makers. 3. **Output** — one normalized record per product, pushed to the dataset as it's scraped. No login, no API key, no JavaScript rendering — pure HTTP + JSON-LD. *** ### 💡 Tips - Combine `topicSlugs` + `leaderboardDates` for the widest coverage. - For a single competitor lookup, pass one `productSlugs` entry and set `maxRecords: 1`. - If you need historical leaderboards, loop multiple `leaderboardDates` — each gives ~18 products. - Default behavior with empty input scrapes Notion, Linear, and Vercel as a demo. *** ### 📊 Limits & Behavior - `maxRecords` defaults to **100** to keep runs cheap and predictable. - Set to `0` for unlimited (but you'll hit Product Hunt's rate-limiting around 200 req/min). - The scraper exits with `FAILED` status if no targets are provided and no demo defaults match. *** ### 🛒 Related Scrapers Looking for more discovery data? - **[Y Combinator Companies Scraper](https://apify.com/haketa/ycombinator-companies-scraper)** — every YC company, batch, sector - **[BuiltIn Tech Companies + Tech Stack Scraper](https://apify.com/haketa/builtin-tech-companies-scraper)** — tech companies + their full stack - **[H1B Visa Database Scraper](https://apify.com/haketa/h1b-visa-database-scraper)** — visa sponsors + salary data *** Built with ❤️ for makers, VCs, and tech intel teams. # Actor input Schema ## `startUrls` (type: `array`): Direct ProductHunt URLs — product pages, posts, daily leaderboards, or topic pages. Mixed types OK. ## `productSlugs` (type: `array`): ProductHunt product slugs (the URL path after /products/). Example: notion, linear, vercel. ## `topicSlugs` (type: `array`): Discover products from these topic pages. Examples: productivity, artificial-intelligence, design-tools. ## `leaderboardDates` (type: `array`): Discover top products launched on these dates. Format: YYYY/M/D (no leading zeros). Example: 2026/5/17. ## `scrapeReviews` (type: `boolean`): Include user reviews (rating, body, author) in output. Costs more requests. ## `maxRecords` (type: `integer`): Maximum products to scrape. Set to 0 for unlimited. ## `requestDelay` (type: `integer`): Delay between requests in milliseconds. ## `maxConcurrency` (type: `integer`): Parallel request count. ## `proxyConfiguration` (type: `object`): Optional proxy. ProductHunt usually works without proxy via Chrome header impersonation. ## Actor input object example ```json { "startUrls": [], "productSlugs": [ "notion", "linear", "vercel" ], "topicSlugs": [], "leaderboardDates": [], "scrapeReviews": true, "maxRecords": 100, "requestDelay": 800, "maxConcurrency": 4, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `datasetJson` (type: `string`): Full dataset with every scraped product as JSON. ## `datasetCsv` (type: `string`): Full dataset in CSV format. ## `datasetXlsx` (type: `string`): Full dataset in Excel XLSX format. ## `overviewView` (type: `string`): Compact one-row-per-product table view. ## `makersView` (type: `string`): Flattened makers — one CSV row per (product, maker). ## `reviewsView` (type: `string`): Flattened reviews — one CSV row per (product, review). # 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 = { "startUrls": [], "productSlugs": [ "notion", "linear", "vercel" ], "topicSlugs": [], "leaderboardDates": [], "scrapeReviews": true, "maxRecords": 100, "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("haketa/producthunt-launches-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 = { "startUrls": [], "productSlugs": [ "notion", "linear", "vercel", ], "topicSlugs": [], "leaderboardDates": [], "scrapeReviews": True, "maxRecords": 100, "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("haketa/producthunt-launches-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 '{ "startUrls": [], "productSlugs": [ "notion", "linear", "vercel" ], "topicSlugs": [], "leaderboardDates": [], "scrapeReviews": true, "maxRecords": 100, "proxyConfiguration": { "useApifyProxy": false } }' | apify call haketa/producthunt-launches-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=haketa/producthunt-launches-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ProductHunt Launches & Makers Scraper", "description": "Extract Product Hunt launches, makers, votes, reviews, ratings, screenshots, topics — by URL, product slug, topic, or daily leaderboard date. JSON-LD + Apollo-state extraction, no API key required.", "version": "0.0", "x-build-id": "zfjpfbnRNfKX4Rjcb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/haketa~producthunt-launches-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-haketa-producthunt-launches-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/haketa~producthunt-launches-scraper/runs": { "post": { "operationId": "runs-sync-haketa-producthunt-launches-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/haketa~producthunt-launches-scraper/run-sync": { "post": { "operationId": "run-sync-haketa-producthunt-launches-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "startUrls": { "title": "Start URLs", "type": "array", "description": "Direct ProductHunt URLs — product pages, posts, daily leaderboards, or topic pages. Mixed types OK.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "productSlugs": { "title": "Product Slugs", "type": "array", "description": "ProductHunt product slugs (the URL path after /products/). Example: notion, linear, vercel.", "default": [ "notion", "linear", "vercel" ], "items": { "type": "string" } }, "topicSlugs": { "title": "Topic Slugs", "type": "array", "description": "Discover products from these topic pages. Examples: productivity, artificial-intelligence, design-tools.", "default": [], "items": { "type": "string" } }, "leaderboardDates": { "title": "Leaderboard Dates", "type": "array", "description": "Discover top products launched on these dates. Format: YYYY/M/D (no leading zeros). Example: 2026/5/17.", "default": [], "items": { "type": "string" } }, "scrapeReviews": { "title": "Scrape Reviews", "type": "boolean", "description": "Include user reviews (rating, body, author) in output. Costs more requests.", "default": true }, "maxRecords": { "title": "Max Records", "minimum": 0, "type": "integer", "description": "Maximum products to scrape. Set to 0 for unlimited.", "default": 100 }, "requestDelay": { "title": "Request Delay (ms)", "type": "integer", "description": "Delay between requests in milliseconds.", "default": 800 }, "maxConcurrency": { "title": "Max Concurrency", "type": "integer", "description": "Parallel request count.", "default": 4 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Optional proxy. ProductHunt usually works without proxy via Chrome header impersonation." } } }, "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 } } } } } } } } } } ```