# Producthunt Actor (`entrepreneurial_bookshelf/producthunt-actor`) Actor Building web scraping and automation tools with Python and Playwright. Creator of ProductHunt Actor for extracting product launches, trends, makers, votes, and startup insights from Product Hunt using the Apify platform. - **URL**: https://apify.com/entrepreneurial\_bookshelf/producthunt-actor.md - **Developed by:** [Madhav Adhikari](https://apify.com/entrepreneurial_bookshelf) (community) - **Categories:** E-commerce, SEO tools, Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Scraper Extract product launches, upvotes, makers, and more from ProductHunt — no API key required. ### What does this Actor do? This Actor scrapes public data from ProductHunt, giving you structured JSON output for: - **Daily launches** — today's or any past day's products - **Weekly leaderboard** — top products of the week - **Category pages** — e.g. Developer Tools, AI, Productivity ### Output fields Each product record includes: | Field | Description | |---|---| | `name` | Product name | | `tagline` | One-line description | | `url` | ProductHunt post URL | | `upvotes` | Number of upvotes | | `comments` | Number of comments | | `tags` | List of topic tags | | `thumbnail` | Product thumbnail image URL | | `description` | Full description *(detail mode only)* | | `makers` | List of maker names *(detail mode only)* | | `website` | External website URL *(detail mode only)* | | `launch_date` | ISO launch date *(detail mode only)* | ### Example output ```json { "name": "Notion AI", "tagline": "Your connected AI assistant in Notion", "url": "https://www.producthunt.com/posts/notion-ai", "upvotes": 2847, "comments": 312, "tags": ["Productivity", "Artificial Intelligence"], "thumbnail": "https://ph-files.imgix.net/...", "description": "Notion AI lets you write, edit, summarize...", "makers": ["Ivan Zhao", "Simon Last"], "website": "https://notion.so", "launch_date": "2023-11-16T00:00:00Z" } ```` ### How to use 1. Select **Scrape Type**: Daily, Weekly, or Category 2. *(Optional)* Enter a **date** (format: `YYYY/M/D`) for a specific day 3. *(Optional)* Enter a **category slug** like `developer-tools` or `artificial-intelligence` 4. Set **Max Pages** — each page contains ~20 products 5. Enable **Fetch Full Details** to get descriptions, makers, and website URLs (slower) 6. Click **Run** and download your data as JSON or CSV ### Use cases - **Competitive research** — track what's launching in your niche - **Lead generation** — find newly launched SaaS tools and their makers - **Market research** — spot trends in upvotes and categories - **Investment research** — monitor traction of early-stage products - **Content creation** — aggregate product data for newsletters or blogs ### Notes - Fetching full details visits each product page individually and uses more compute credits - For large date ranges, increase Max Pages or run multiple times with different dates - Data reflects publicly visible information only # Actor input Schema ## `apiToken` (type: `string`): Your ProductHunt API developer token. Get it from https://www.producthunt.com/v2/oauth/applications ## `numberOfPosts` (type: `integer`): How many posts to fetch (max 20 per request). ## `postedAfter` (type: `string`): Filter posts after this date. Format: 2026-05-01T00:00:00Z ## Actor input object example ```json { "numberOfPosts": 20, "postedAfter": "" } ``` # 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("entrepreneurial_bookshelf/producthunt-actor").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("entrepreneurial_bookshelf/producthunt-actor").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 entrepreneurial_bookshelf/producthunt-actor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=entrepreneurial_bookshelf/producthunt-actor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Producthunt Actor", "description": "Building web scraping and automation tools with Python and Playwright. Creator of ProductHunt Actor for extracting product launches, trends, makers, votes, and startup insights from Product Hunt using the Apify platform.", "version": "0.0", "x-build-id": "pETmmXha4MNxqZ83V" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/entrepreneurial_bookshelf~producthunt-actor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-entrepreneurial_bookshelf-producthunt-actor", "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/entrepreneurial_bookshelf~producthunt-actor/runs": { "post": { "operationId": "runs-sync-entrepreneurial_bookshelf-producthunt-actor", "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/entrepreneurial_bookshelf~producthunt-actor/run-sync": { "post": { "operationId": "run-sync-entrepreneurial_bookshelf-producthunt-actor", "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": [ "apiToken" ], "properties": { "apiToken": { "title": "ProductHunt API Token", "type": "string", "description": "Your ProductHunt API developer token. Get it from https://www.producthunt.com/v2/oauth/applications" }, "numberOfPosts": { "title": "Number of posts", "minimum": 1, "maximum": 20, "type": "integer", "description": "How many posts to fetch (max 20 per request).", "default": 20 }, "postedAfter": { "title": "Posted after (optional)", "type": "string", "description": "Filter posts after this date. Format: 2026-05-01T00:00:00Z", "default": "" } } }, "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 } } } } } } } } } } ```