# Product Hunt Scraper — Launches, Comments & Leads (`philzx/ph-launch-intelligence`) Actor Scrape Product Hunt launches, full comments, makers, videos, built-with tools, momentum scores, websites, and lead signals via fast HTTP-only extraction. - **URL**: https://apify.com/philzx/ph-launch-intelligence.md - **Developed by:** [Filipe Alves](https://apify.com/philzx) (community) - **Categories:** Lead generation, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.45 / 1,000 enriched product launches 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 ## Product Hunt Scraper — Launches, Comments & Leads Fast HTTP-only Product Hunt scraper for launch intelligence, startup lead generation, competitor research, founder discovery, and deal-flow monitoring. Extract ranked Product Hunt launches with **full comment threads** (via HTTP-only GraphQL pagination — no Playwright, no Product Hunt API token), scores, followers, topics, makers, reviews, screenshots, videos/media metadata, built-with tools, website URLs, launch history, website text, tech-stack detection, maker profiles, commenter profiles, momentum scores, promoted/ad signals, and email discovery. ### Why this Actor - **Same price as the cheapest serious competitor:** $0.45 / 1,000 records - **No browser required:** pure HTTP scraping — fast, reliable, low-cost - **Full comments:** ALL comment threads via Apollo persisted GraphQL pagination (not just SSR-visible) - **Any URL supported:** product pages, leaderboards (daily/weekly/monthly/yearly), topics, collections, maker profiles, search — all auto-detected - **Ranks included:** daily, weekly, monthly, and yearly leaderboard ranks - **Momentum scores:** score_per_hour, comment_rate, launch_age_hours, momentum_signal (breakout/trending/steady/slow) - **Commenter lead generation:** extract commenter profiles with bio, social links, and roles - **Built-with tools:** Product Hunt launch shoutouts (GitHub, Figma, AWS, etc.) - **Media/videos:** Product Hunt gallery images plus video platform/ID/URL metadata - **Explicit promoted/ad signals:** conservative `is_promoted` + `promoted_ads_on_page` - **Multi-category feed mode:** scrape multiple Product Hunt categories in one run - **Historical data:** scrape past daily/weekly/monthly/yearly leaderboards ### Supported input URLs The Actor auto-detects and routes any Product Hunt URL type: | URL pattern | What it does | |---|---| | `https://www.producthunt.com/products/{slug}` | Scrape a single product | | `https://www.producthunt.com/leaderboard/daily/2026/7/6` | Scrape a daily leaderboard | | `https://www.producthunt.com/leaderboard/weekly/2026/28` | Scrape a weekly leaderboard | | `https://www.producthunt.com/leaderboard/monthly/2026/7` | Scrape a monthly leaderboard | | `https://www.producthunt.com/leaderboard/yearly/2026` | Scrape a yearly leaderboard | | `https://www.producthunt.com/topics/{topic}` | Scrape all products from a topic page | | `https://www.producthunt.com/collections/{id}` | Scrape all products from a collection | | `https://www.producthunt.com/@{username}` | Scrape all products from a maker profile | | `https://www.producthunt.com/all?q={query}` | Scrape products from search results | ### What it does 1. Fetches Product Hunt leaderboard pages, product URLs, topic/collection/maker/search pages, or Atom feeds. 2. Extracts rank from leaderboard HTML. 3. Extracts Apollo SSR data: `latestScore`, `launchDayScore`, `commentsCount`, `followersCount`, `featuredAt`, `websiteUrl`, `topics`, etc. 4. Enriches product pages via JSON-LD + Apollo SSR. 5. Fetches **ALL comments** via Apollo persisted GraphQL with cursor pagination (no Playwright, no OAuth token). 6. Extracts Product Hunt built-with/shoutout tools from `detailedReviews`. 7. Extracts media gallery entries including video URL/platform/video ID. 8. Extracts explicit promoted/ad blocks without guessing. 9. Computes momentum scores: `score_per_hour`, `comment_rate`, `launch_age_hours`, `momentum_signal`. 10. Optionally enriches commenter profiles for lead generation. 11. Optionally fetches `/products/{slug}/launches` for launch history. 12. Optionally fetches product websites for cleaned text + tech stack. 13. Optionally fetches maker profile pages for headline/followers/social links. 14. Optionally scans product websites for emails. ### Input | Field | Type | Default | Description | |---|---|---:|---| | `startUrls` | array | `[]` | Any Product Hunt URLs — products, leaderboards, topics, collections, maker profiles, search. Auto-detected. | | `mode` | string | `leaderboard` | `leaderboard`, `feed`, or `both`. Ignored when `startUrls` is set. | | `leaderboardType` | string | `daily` | `daily`, `weekly`, `monthly`, `yearly` | | `date` | string | `""` | Date path: daily=`2026/7/4`, weekly=`2026/27`, monthly=`2026/6`, yearly=`2026` | | `categories` | array | `[]` | Feed categories: `ai-software`, `tech`, `design-tools`, `developer-tools`, etc. | | `maxEntries` | integer | `50` | Max entries per feed category | | `enrichProducts` | boolean | `true` | Fetch product pages for full data | | `maxProducts` | integer | `0` | Limit products to enrich (`0` = all) | | `includeComments` | boolean | `false` | Extract full comment text via GraphQL pagination | | `maxCommentsPerProduct` | integer | `20` | Max comments per product | | `includeMomentum` | boolean | `true` | Compute momentum scores (score_per_hour, comment_rate, etc.) | | `enrichCommenters` | boolean | `false` | Fetch commenter profiles for lead generation | | `maxCommentersPerProduct` | integer | `50` | Max commenter profiles to enrich per product | | `includeBuiltWith` | boolean | `true` | Extract Product Hunt built-with/shoutout tools | | `includeMedia` | boolean | `true` | Extract Product Hunt images/videos/media metadata | | `includePromotedAds` | boolean | `true` | Extract explicit promoted/ad blocks and conservative `is_promoted` | | `enrichMakers` | boolean | `false` | Fetch maker profile pages for extra founder data | | `maxMakersPerProduct` | integer | `3` | Max makers to enrich per product (`0` = all) | | `featuredOnly` | boolean | `false` | Keep only featured/ranked launches | | `excludePromoted` | boolean | `false` | Exclude only when an explicit promoted marker is exposed | | `minScore` | integer | `0` | Keep only products with `latestScore >= minScore` | | `minComments` | integer | `0` | Keep only products with `commentsCount >= minComments` | | `includeLaunchHistory` | boolean | `false` | Fetch launch history from `/products/{slug}/launches` | | `includeWebsiteText` | boolean | `false` | Add cleaned visible text from product website | | `maxWebsiteTextChars` | integer | `5000` | Max chars to keep in `website_text` | | `detectTechStack` | boolean | `false` | Detect Next.js, Vercel, Webflow, Shopify, WordPress, Stripe, etc. | | `extractEmails` | boolean | `false` | Scan product websites for email addresses | ### Example: full competitive intelligence ```json { "startUrls": ["https://www.producthunt.com/products/vida-5"], "enrichProducts": true, "includeComments": true, "maxCommentsPerProduct": 100, "includeMomentum": true, "enrichCommenters": true, "maxCommentersPerProduct": 20, "includeBuiltWith": true, "includeMedia": true, "includeLaunchHistory": true, "includeWebsiteText": true, "detectTechStack": true, "enrichMakers": true, "maxMakersPerProduct": 2 } ```` ### Output example ```json { "name": "PhoneDeck", "slug": "phonedeck", "product_url": "https://www.producthunt.com/products/phonedeck", "dailyRank": 3, "latestScore": 258, "launchDayScore": 226, "commentsCount": 22, "followersCount": 323, "featuredAt": "2026-07-04T00:01:00-07:00", "websiteUrl": "https://phonedeck.io", "topics": ["iOS", "Mac", "Productivity", "Artificial Intelligence", "Business"], "launch_age_hours": 48.5, "score_per_comment": 11.73, "score_per_hour": 5.32, "comment_rate": 0.45, "momentum_signal": "steady", "comments": [ {"id": "5511611", "text": "Congrats on the launch!", "author": {"username": "itsluo", "name": "Luo"}} ], "commenters": [ {"commenter_username": "itsluo", "name": "Luo", "headline": "Building things", "followers_count": 40, "roles": ["commenter"]} ], "built_with": [{"name": "GitHub", "slug": "github"}], "videos": [{"platform": "youtube", "video_id": "INgBoXo1flI"}], "makers": [{"name": "Vansh Parihar", "username": "vanshmparihar", "headline": "Built PhoneDeck in 7 days."}], "scraped_at": "2026-07-06T..." } ``` ### Pricing **Pay per result:** $0.45 per 1,000 enriched Product Hunt records. No charge for failed lookups. Free trial available. # Actor input Schema ## `startUrls` (type: `array`): Optional Product Hunt product or leaderboard URLs to scrape directly. Supports /products/{slug} and /leaderboard/{daily|weekly|monthly|yearly}/... URLs. When provided, these URLs override mode/date/category inputs. ## `mode` (type: `string`): leaderboard = fetch ranked products from leaderboard pages. feed = fetch from Atom feed by category. both = fetch from leaderboard then add feed categories. Ignored when startUrls is set. ## `leaderboardType` (type: `string`): Type of leaderboard to scrape. Only used when mode is leaderboard or both. ## `date` (type: `string`): Date for the leaderboard. Format: daily='2026/7/4', weekly='2026/27', monthly='2026/6', yearly='2026'. Leave empty for today (daily only). ## `categories` (type: `array`): Product Hunt categories for feed mode. Examples: ai-software, tech, design-tools, developer-tools, marketing, productivity. ## `maxEntries` (type: `integer`): Maximum entries per category from Atom feed (max 50). ## `enrichProducts` (type: `boolean`): Fetch each product page for full data: scores, followers, makers, reviews, ratings, pricing, screenshots, topics, and website. ## `maxProducts` (type: `integer`): Limit number of products to enrich (0 = all). Useful to control time/cost. ## `includeComments` (type: `boolean`): Extract visible Product Hunt comments from Apollo SSR data when available. Some launch comments are loaded separately by Product Hunt and may not be SSR-visible. ## `maxCommentsPerProduct` (type: `integer`): Maximum number of SSR-visible comments to return per product. ## `includeBuiltWith` (type: `boolean`): Extract tools/products shown in Product Hunt Built With / launch shoutouts, e.g. GitHub, Figma, AWS. ## `includeMedia` (type: `boolean`): Extract Product Hunt media gallery entries including images, videos, platforms, video IDs, and thumbnails. ## `includePromotedAds` (type: `boolean`): Extract explicit Product Hunt promoted ad blocks found on the page and mark the current product as promoted only if the ad slug matches. ## `enrichCommenters` (type: `boolean`): Fetch profile pages for unique commenters to extract headline, bio, follower counts, and social links. Useful for lead generation from comment sections. ## `maxCommentersPerProduct` (type: `integer`): Maximum number of commenter profiles to enrich per product (0 = all). ## `includeMomentum` (type: `boolean`): Compute derived momentum signals: launch\_age\_hours, score\_per\_comment, score\_per\_hour, comment\_rate, momentum\_signal. ## `enrichMakers` (type: `boolean`): Fetch maker profile pages to extract headline, follower counts, review counts, product counts, Twitter handle, and external links. ## `maxMakersPerProduct` (type: `integer`): Maximum number of maker profiles to enrich per product (0 = all). ## `featuredOnly` (type: `boolean`): Keep only products with a featuredAt timestamp or leaderboard rank. ## `excludePromoted` (type: `boolean`): Exclude products only when Product Hunt exposes an explicit promoted marker. Conservative: does not guess from hideVotesCount. ## `minScore` (type: `integer`): Keep only products with latestScore >= this value. 0 disables the filter. ## `minComments` (type: `integer`): Keep only products with commentsCount >= this value. 0 disables the filter. ## `includeLaunchHistory` (type: `boolean`): Fetch /products/{slug}/launches and extract best-effort historical launch records from Apollo SSR. ## `includeWebsiteText` (type: `boolean`): Fetch each product website and add cleaned visible text as website\_text. Useful for lead scoring and search. ## `maxWebsiteTextChars` (type: `integer`): Maximum characters to keep from the cleaned website text. ## `detectTechStack` (type: `boolean`): Detect common website technologies from HTML and response headers: Next.js, Vercel, Webflow, Shopify, WordPress, Stripe, PostHog, GA, Cloudflare, etc. ## `extractEmails` (type: `boolean`): Visit product websites and scan for email addresses. ## Actor input object example ```json { "startUrls": [], "mode": "leaderboard", "leaderboardType": "daily", "date": "", "categories": [], "maxEntries": 50, "enrichProducts": true, "maxProducts": 0, "includeComments": false, "maxCommentsPerProduct": 20, "includeBuiltWith": true, "includeMedia": true, "includePromotedAds": true, "enrichCommenters": false, "maxCommentersPerProduct": 50, "includeMomentum": true, "enrichMakers": false, "maxMakersPerProduct": 3, "featuredOnly": false, "excludePromoted": false, "minScore": 0, "minComments": 0, "includeLaunchHistory": false, "includeWebsiteText": false, "maxWebsiteTextChars": 5000, "detectTechStack": false, "extractEmails": false } ``` # 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 = { "startUrls": [], "categories": [] }; // Run the Actor and wait for it to finish const run = await client.actor("philzx/ph-launch-intelligence").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": [], "categories": [], } # Run the Actor and wait for it to finish run = client.actor("philzx/ph-launch-intelligence").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": [], "categories": [] }' | apify call philzx/ph-launch-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=philzx/ph-launch-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Product Hunt Scraper — Launches, Comments & Leads", "description": "Scrape Product Hunt launches, full comments, makers, videos, built-with tools, momentum scores, websites, and lead signals via fast HTTP-only extraction.", "version": "0.0", "x-build-id": "jYoH6eH6pzESim5ec" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/philzx~ph-launch-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-philzx-ph-launch-intelligence", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/philzx~ph-launch-intelligence/runs": { "post": { "operationId": "runs-sync-philzx-ph-launch-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/philzx~ph-launch-intelligence/run-sync": { "post": { "operationId": "run-sync-philzx-ph-launch-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Product Hunt URLs", "type": "array", "description": "Optional Product Hunt product or leaderboard URLs to scrape directly. Supports /products/{slug} and /leaderboard/{daily|weekly|monthly|yearly}/... URLs. When provided, these URLs override mode/date/category inputs.", "items": { "type": "string" } }, "mode": { "title": "Mode", "enum": [ "leaderboard", "feed", "both" ], "type": "string", "description": "leaderboard = fetch ranked products from leaderboard pages. feed = fetch from Atom feed by category. both = fetch from leaderboard then add feed categories. Ignored when startUrls is set.", "default": "leaderboard" }, "leaderboardType": { "title": "Leaderboard type", "enum": [ "daily", "weekly", "monthly", "yearly" ], "type": "string", "description": "Type of leaderboard to scrape. Only used when mode is leaderboard or both.", "default": "daily" }, "date": { "title": "Date", "type": "string", "description": "Date for the leaderboard. Format: daily='2026/7/4', weekly='2026/27', monthly='2026/6', yearly='2026'. Leave empty for today (daily only).", "default": "" }, "categories": { "title": "Categories (feed mode)", "type": "array", "description": "Product Hunt categories for feed mode. Examples: ai-software, tech, design-tools, developer-tools, marketing, productivity.", "items": { "type": "string" } }, "maxEntries": { "title": "Max entries per category (feed)", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum entries per category from Atom feed (max 50).", "default": 50 }, "enrichProducts": { "title": "Enrich product pages", "type": "boolean", "description": "Fetch each product page for full data: scores, followers, makers, reviews, ratings, pricing, screenshots, topics, and website.", "default": true }, "maxProducts": { "title": "Max products to enrich", "minimum": 0, "type": "integer", "description": "Limit number of products to enrich (0 = all). Useful to control time/cost.", "default": 0 }, "includeComments": { "title": "Include comments text", "type": "boolean", "description": "Extract visible Product Hunt comments from Apollo SSR data when available. Some launch comments are loaded separately by Product Hunt and may not be SSR-visible.", "default": false }, "maxCommentsPerProduct": { "title": "Max comments per product", "minimum": 0, "maximum": 200, "type": "integer", "description": "Maximum number of SSR-visible comments to return per product.", "default": 20 }, "includeBuiltWith": { "title": "Include Product Hunt Built With tools", "type": "boolean", "description": "Extract tools/products shown in Product Hunt Built With / launch shoutouts, e.g. GitHub, Figma, AWS.", "default": true }, "includeMedia": { "title": "Include media and videos", "type": "boolean", "description": "Extract Product Hunt media gallery entries including images, videos, platforms, video IDs, and thumbnails.", "default": true }, "includePromotedAds": { "title": "Include explicit promoted/ad signals", "type": "boolean", "description": "Extract explicit Product Hunt promoted ad blocks found on the page and mark the current product as promoted only if the ad slug matches.", "default": true }, "enrichCommenters": { "title": "Enrich commenter profiles", "type": "boolean", "description": "Fetch profile pages for unique commenters to extract headline, bio, follower counts, and social links. Useful for lead generation from comment sections.", "default": false }, "maxCommentersPerProduct": { "title": "Max commenters per product", "minimum": 0, "maximum": 500, "type": "integer", "description": "Maximum number of commenter profiles to enrich per product (0 = all).", "default": 50 }, "includeMomentum": { "title": "Include momentum scores", "type": "boolean", "description": "Compute derived momentum signals: launch_age_hours, score_per_comment, score_per_hour, comment_rate, momentum_signal.", "default": true }, "enrichMakers": { "title": "Enrich maker profiles", "type": "boolean", "description": "Fetch maker profile pages to extract headline, follower counts, review counts, product counts, Twitter handle, and external links.", "default": false }, "maxMakersPerProduct": { "title": "Max makers per product", "minimum": 0, "maximum": 20, "type": "integer", "description": "Maximum number of maker profiles to enrich per product (0 = all).", "default": 3 }, "featuredOnly": { "title": "Featured launches only", "type": "boolean", "description": "Keep only products with a featuredAt timestamp or leaderboard rank.", "default": false }, "excludePromoted": { "title": "Exclude promoted products", "type": "boolean", "description": "Exclude products only when Product Hunt exposes an explicit promoted marker. Conservative: does not guess from hideVotesCount.", "default": false }, "minScore": { "title": "Minimum score / votes proxy", "minimum": 0, "type": "integer", "description": "Keep only products with latestScore >= this value. 0 disables the filter.", "default": 0 }, "minComments": { "title": "Minimum comments count", "minimum": 0, "type": "integer", "description": "Keep only products with commentsCount >= this value. 0 disables the filter.", "default": 0 }, "includeLaunchHistory": { "title": "Include launch history", "type": "boolean", "description": "Fetch /products/{slug}/launches and extract best-effort historical launch records from Apollo SSR.", "default": false }, "includeWebsiteText": { "title": "Include website raw text", "type": "boolean", "description": "Fetch each product website and add cleaned visible text as website_text. Useful for lead scoring and search.", "default": false }, "maxWebsiteTextChars": { "title": "Max website text chars", "minimum": 0, "maximum": 50000, "type": "integer", "description": "Maximum characters to keep from the cleaned website text.", "default": 5000 }, "detectTechStack": { "title": "Detect website tech stack", "type": "boolean", "description": "Detect common website technologies from HTML and response headers: Next.js, Vercel, Webflow, Shopify, WordPress, Stripe, PostHog, GA, Cloudflare, etc.", "default": false }, "extractEmails": { "title": "Extract emails from websites", "type": "boolean", "description": "Visit product websites and scan for email addresses.", "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 } } } } } } } } } } ```