# Product Hunt Scraper - Launches, Products & Leaderboard (`thirdwatch/producthunt-scraper`) Actor Scrape Product Hunt launches, product profiles, and leaderboard rankings. Extract name, tagline, votes, comments, topics, pricing, reviews, and website URLs. Daily featured products, category browsing, and historical leaderboard data. - **URL**: https://apify.com/thirdwatch/producthunt-scraper.md - **Developed by:** [Thirdwatch](https://apify.com/thirdwatch) (community) - **Categories:** Other, AI - **Stats:** 6 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.20 / 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 ## Product Hunt Scraper > Scrape Product Hunt launches, product profiles, and daily leaderboards — name, tagline, votes, comments, topics, featured date, and daily/weekly/monthly rankings. ### What you get Launch and product data from Product Hunt. Three modes: `launches` (daily featured products from the homepage or any topic page), `products` (full product profiles with tagline, votes, and topics), and `leaderboard` (ranked products for a specific day or historical date range). Ideal for tracking new launches, monitoring a topic, or building historical launch datasets. ### Output fields | Field | Description | |-------|-------------| | `name` | Product name | | `tagline` | Product tagline | | `url` | Product Hunt URL | | `votes_count` | Number of upvotes | | `comments_count` | Number of comments | | `daily_rank` | Daily ranking position | | `weekly_rank` | Weekly ranking position | | `monthly_rank` | Monthly ranking position | | `topics` | Topic/category names | | `featured_at` | ISO date the product was featured | | `created_at` | ISO date the product was created | | `query` | The query or topic that produced this result | ### Example output ```json { "name": "Notion AI", "tagline": "Write faster, think bigger, and be more creative", "url": "https://www.producthunt.com/posts/notion-ai", "votes_count": 3421, "comments_count": 287, "daily_rank": 1, "weekly_rank": 1, "monthly_rank": 3, "topics": ["Artificial Intelligence", "Productivity", "Writing"], "featured_at": "2026-04-15", "created_at": "2026-04-15", "query": "artificial-intelligence" } ```` ### Input parameters | Parameter | Required | Description | |-----------|----------|-------------| | `queries` | No | Topic slugs for `launches` (e.g., `"artificial-intelligence"`, `"developer-tools"`), product slugs for `products` (e.g., `"chatgpt"`, `"notion"`). Ignored in `leaderboard` mode. Leave empty for the homepage. | | `scrapeType` | No | One of `launches`, `products`, `leaderboard`. Default `launches`. | | `maxResults` | No | Maximum total results across all queries/days (1-100000). Default `15`. | | `startDate` | No | Leaderboard mode only. `YYYY-MM-DD`. If omitted, scrapes today only. | | `endDate` | No | Leaderboard mode only. `YYYY-MM-DD`, inclusive. Defaults to `startDate` if only start is given. | | `maxPerDay` | No | Leaderboard mode only. Cap results per daily leaderboard (e.g., `10` for top-10-per-day). | | `proxyConfiguration` | No | Proxy settings. Leave default for best results. | ### Use cases - **Founders and makers**: Monitor launches in your topic to gauge competition and timing. - **Investors**: Track daily leaderboards to spot trending products before they hit mainstream press. - **Product marketers**: Pull historical top-10s to study positioning patterns that win upvotes. - **Analysts and journalists**: Build timelines of AI, developer-tool, or productivity launches by date range. - **Growth teams**: Benchmark your own launch against same-day competitors. ### Pricing Pay-per-result pricing. Tiered discounts apply automatically based on usage volume. | Tier | Price per result | |------|------------------| | FREE | $0.003 | | BRONZE | $0.0025 | | SILVER | $0.002 | | GOLD | $0.0015 | ### Limitations - Product Hunt shows a homepage cap of ~24 launches per day — for historical depth, use `leaderboard` mode with a date range. - Topic pages are paginated; very old launches on niche topics may be out of reach of the default max. - Vote and comment counts are live values at scrape time — they change as more users engage. - Leaderboard mode requires a date; `startDate`/`endDate` must be `YYYY-MM-DD`. - Rankings only exist where Product Hunt itself exposes them (e.g., daily rank only for featured products that day). ### Compared to alternatives - **vs. any Apify Store competitor**: There is no comparable Product Hunt scraper on Apify. This actor fills that gap with all three modes (launches, products, leaderboard) and historical leaderboard date ranges. - **vs. Product Hunt's public API**: The official GraphQL API requires OAuth and enforces strict rate limits — this actor is ready for ad-hoc research and BI pipelines without key management. Pairs well with [G2 Software Reviews Scraper](https://apify.com/thirdwatch/g2-software-reviews-scraper?fpr=9m2cd6) for launch-to-review tracking of SaaS products over time. ### FAQ **What's the difference between `launches` and `leaderboard`?** `launches` pulls the current homepage or a topic page — great for "what's live now". `leaderboard` gives you the ranked top products for any specific date, which is the right mode for historical datasets. **Can I get historical launches for a given month?** Yes. Use `scrapeType: "leaderboard"` with `startDate` and `endDate` spanning that month, plus `maxPerDay` to cap daily volume. **Does `products` mode return votes and comments too?** Yes — `products` returns the same vote and comment counts plus full product profiles for the specific product slugs you pass. **How fresh is the data?** Pulled live at run time — as fresh as Product Hunt itself. Last verified: 2026-04 More scrapers at [thirdwatch.dev](https://thirdwatch.dev). # Actor input Schema ## `queries` (type: `array`): Search terms or topic slugs to scrape. For 'launches': topic slugs like 'artificial-intelligence', 'productivity'. For 'products': product slugs like 'chatgpt', 'notion'. For 'leaderboard': ignored (uses today's date). Leave empty to scrape the homepage. ## `maxResults` (type: `integer`): Maximum total number of results to return across all queries/days. ## `startDate` (type: `string`): Start date for historical leaderboard scraping (YYYY-MM-DD). If omitted, scrapes today only. Use with endDate to scrape a range. ## `endDate` (type: `string`): End date for historical leaderboard scraping (YYYY-MM-DD, inclusive). Defaults to startDate if only startDate given. ## `maxPerDay` (type: `integer`): Cap results per daily leaderboard (e.g. 10 for top-10-per-day). Defaults to maxResults if unset. ## `scrapeType` (type: `string`): What to scrape: 'launches' = daily featured products from homepage/topic pages, 'products' = full product profiles, 'leaderboard' = ranked products by day. ## `proxyConfiguration` (type: `object`): Residential proxy is required — Product Hunt 403's datacenter IPs. ## Actor input object example ```json { "queries": [ "artificial-intelligence", "developer-tools" ], "maxResults": 15, "scrapeType": "launches", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `results` (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 = { "queries": [ "artificial-intelligence", "developer-tools" ], "maxResults": 15, "scrapeType": "launches", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("thirdwatch/producthunt-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 = { "queries": [ "artificial-intelligence", "developer-tools", ], "maxResults": 15, "scrapeType": "launches", "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("thirdwatch/producthunt-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 '{ "queries": [ "artificial-intelligence", "developer-tools" ], "maxResults": 15, "scrapeType": "launches", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call thirdwatch/producthunt-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=thirdwatch/producthunt-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Product Hunt Scraper - Launches, Products & Leaderboard", "description": "Scrape Product Hunt launches, product profiles, and leaderboard rankings. Extract name, tagline, votes, comments, topics, pricing, reviews, and website URLs. Daily featured products, category browsing, and historical leaderboard data.", "version": "0.1", "x-build-id": "vA3SDgpE9VKCLjjQb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/thirdwatch~producthunt-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-thirdwatch-producthunt-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/thirdwatch~producthunt-scraper/runs": { "post": { "operationId": "runs-sync-thirdwatch-producthunt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/thirdwatch~producthunt-scraper/run-sync": { "post": { "operationId": "run-sync-thirdwatch-producthunt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "queries": { "title": "Queries / Category Slugs", "type": "array", "description": "Search terms or topic slugs to scrape. For 'launches': topic slugs like 'artificial-intelligence', 'productivity'. For 'products': product slugs like 'chatgpt', 'notion'. For 'leaderboard': ignored (uses today's date). Leave empty to scrape the homepage.", "default": [], "items": { "type": "string" } }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum total number of results to return across all queries/days.", "default": 15 }, "startDate": { "title": "Start Date (leaderboard mode)", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Start date for historical leaderboard scraping (YYYY-MM-DD). If omitted, scrapes today only. Use with endDate to scrape a range." }, "endDate": { "title": "End Date (leaderboard mode)", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "End date for historical leaderboard scraping (YYYY-MM-DD, inclusive). Defaults to startDate if only startDate given." }, "maxPerDay": { "title": "Max Results Per Day (leaderboard mode)", "minimum": 1, "maximum": 100, "type": "integer", "description": "Cap results per daily leaderboard (e.g. 10 for top-10-per-day). Defaults to maxResults if unset." }, "scrapeType": { "title": "Scrape Type", "enum": [ "launches", "products", "leaderboard" ], "type": "string", "description": "What to scrape: 'launches' = daily featured products from homepage/topic pages, 'products' = full product profiles, 'leaderboard' = ranked products by day.", "default": "launches" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Residential proxy is required — Product Hunt 403's datacenter IPs.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```