# Luma Events Search Scraper (`stealth_mode/luma-events-search-scraper`) Actor Extract comprehensive event data from Luma.com with detailed host info, ticket counts, guest lists, and registration details. Perfect for event aggregators, market researchers, and marketing analysts — collect up to 200 events per search page. - **URL**: https://apify.com/stealth\_mode/luma-events-search-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Automation, Developer tools, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 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. 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 ## Luma Events Search Scraper: Capture Event Data Instantly --- ### What Is Luma.com? Luma.com is a modern event discovery and management platform connecting hosts, organizers, and attendees. It aggregates events across categories — from tech conferences to social gatherings — and provides a centralized calendar for discovering upcoming events. The platform emphasizes community-driven event hosting with detailed RSVP tracking, ticket management, and guest interaction features. Manually collecting event data across multiple search pages is tedious and error-prone — the **Luma Events Search Scraper** automates this workflow, delivering structured event intelligence at scale. --- ### Overview The **Luma Events Search Scraper** harvests event listings from Luma search pages (e.g., category or city-specific results), extracting 23 data fields per event. It's built for: - **Event aggregators** building multi-source event databases - **Market researchers** analyzing event trends by category, location, or time - **Marketing analysts** tracking competitor events and sponsorship opportunities - **Event platforms** benchmarking their catalog against Luma's offerings - **Developers** integrating event data into custom discovery tools The scraper supports bulk collection with configurable limits, automatic failure handling, and clean, structured output ready for analysis or database import. --- ### Input Format The scraper accepts a JSON configuration object with three primary parameters: ```json { "urls": [ "https://luma.com/nytw" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` #### Parameter Guide | Parameter | Type | Description | |---|---|---| | `urls` | Array | Event search page URLs from Luma.com (e.g., category pages, city calendars, hashtag results). Paste full URLs one by one or use bulk edit for prepared lists. | | `ignore_url_failures` | Boolean | If `true`, the scraper continues running even if some URLs fail. Useful for large-scale runs where individual page timeouts shouldn't halt the entire job. Set to `false` for strict runs where all URLs must succeed. | | `max_items_per_url` | Integer | Maximum number of event records to extract per URL. Set between 1–200 (default: `20`). Higher limits capture more events but increase runtime. | > **Example URL:** `https://luma.com/search?query=tech` or `https://luma.com/nytw` (New York Tech Week calendar). *** ### Output Format **Sample output** ```json { "api_id": "calev-4iE70cE95JGiUym", "event": { "api_id": "evt-FA3v4MgRgI04fBk", "calendar_api_id": "cal-YGzECkzDDBA9DbM", "cover_url": "https://images.lumacdn.com/uploads/ce/cf0e9244-a7c8-4a57-b1fa-f8964bab310d.png", "end_at": "2026-06-06T08:00:00.000Z", "event_type": "independent", "hide_rsvp": false, "location_type": "offline", "name": "NYTW Closing Rooftop Private Table at PhD Lounge", "one_to_one": true, "recurrence_id": null, "show_guest_list": true, "social_image_url": "https://images.lumacdn.com/event-social/kn/f2a15f79-6516-4acd-af17-ca7653cb5ea5.png", "start_at": "2026-06-06T02:30:00.000Z", "timezone": "America/New_York", "url": "PHDtechweek", "user_api_id": "usr-5narmUEx2UKv6bk", "visibility": "public", "virtual_info": { "has_access": false }, "geo_address_info": { "city": "New York", "type": "google", "region": "New York", "address": "PHD Rooftop Lounge at Dream Downtown", "country": "United States", "place_id": "ChIJMRV7375ZwokRAfltF6Y-wYw", "localized": null, "city_state": "New York, NY", "description": "https://tickets.dreamhospitalitygroup.com/e/phd12-98-3-4/tickets?utm_source=promoter&utm_name=Stephen&utm_campaign=Stephen&utm_id=6a13a9aac04c4dd3a29c66700a1e6243", "sublocality": "Chelsea", "country_code": "US", "full_address": "PHD Rooftop Lounge at Dream Downtown, 355 W 16th St, New York, NY 10011, USA", "region_short": "NY", "short_address": "355 W 16th St, New York", "apple_maps_place_id": "I97CA87CE11D2EE66", "mode": "shown" }, "geo_address_visibility": "public", "coordinate": { "longitude": -74.00352199999999, "latitude": 40.7421711 }, "waitlist_enabled": false, "waitlist_status": "disabled" }, "cover_image": { "colors": [ "#1b5e88", "#5ac3c4" ], "palette": { "neutral": [], "vibrant": [ { "color": "#1b5e88", "percentage": 18.43 }, { "color": "#5ac3c4", "percentage": 3.72 } ] } }, "calendar": { "access_level": "public", "api_id": "cal-YGzECkzDDBA9DbM", "avatar_url": "https://images.lumacdn.com/uploads/b0/d16915da-d372-4706-b07e-88f562b59283.jpg", "coordinate": null, "cover_image_url": "https://images.lumacdn.com/calendar-defaults/patterns/diamonds-100.png", "description_short": "with Stephen Michael", "event_submission_restriction": "open", "google_measurement_id": null, "instagram_handle": "stephenmichael.vip", "is_blocked": false, "launch_status": "launched", "linkedin_handle": null, "location": null, "luma_plan": "plus", "luma_plus_active": true, "meta_pixel_id": null, "name": "Never Look Back", "personal_user_api_id": null, "refund_policy": null, "slug": null, "social_image_url": null, "stripe_account_id": null, "tax_config": null, "tiktok_handle": null, "tint_color": "#310303", "track_meta_ads_from_luma": false, "twitter_handle": null, "verified_at": "2026-05-28T22:32:58.934Z", "website": null, "youtube_handle": null, "city": null, "is_personal": false, "personal_user": null, "geo_city": null, "geo_country": null, "geo_region": null, "timezone": null }, "start_at": "2026-06-06T02:30:00.000Z", "hosts": [ { "name": "Stephen Michael", "api_id": "usr-5narmUEx2UKv6bk", "website": "https://www.propel.earth", "timezone": "America/New_York", "username": "stephenpropel", "bio_short": "Propelling innovators globally", "last_name": "Michael", "avatar_url": "https://images.lumacdn.com/uploads/t5/b9520efc-c135-4dc7-a40e-8ba66e20c494.jpg", "first_name": "Stephen", "is_verified": false, "tiktok_handle": "staystephen", "last_online_at": "2026-06-06T02:27:18.830Z", "twitter_handle": "stephmichael88", "youtube_handle": "propelearth", "linkedin_handle": "/in/stephennmichael", "instagram_handle": "stephmichael88" } ], "guest_count": 122, "ticket_count": 122, "ticket_info": { "price": null, "is_free": true, "max_price": null, "is_sold_out": false, "spots_remaining": null, "is_near_capacity": false, "require_approval": false }, "registration_availability": "open", "featured_guests": [ { "api_id": "usr-OL6kLDAHZomNbko", "avatar_url": "https://images.lumacdn.com/avatars/1o/3d47e882-f01c-46b5-9f07-bb444d6729d1.jpg", "bio_short": "", "first_name": "Illia", "last_name": "Pashkov", "instagram_handle": "ipashkov", "is_verified": false, "last_online_at": "2026-06-06T02:47:10.430Z", "linkedin_handle": "/in/pashkov", "name": "Illia Pashkov", "tiktok_handle": "ipashkov", "timezone": "America/New_York", "twitter_handle": "sinthive", "username": "pshkv", "website": "http://www.sint.gg", "youtube_handle": "pshkv" }, { "api_id": "usr-V8Xu3NllALRD0Z2", "avatar_url": "https://images.lumacdn.com/avatars/cd/028c8a70-3a41-4d5c-9fed-4a009fdf9823.png", "bio_short": "Founder & CEO @Ligandal:\nTissue targeted delivery with AI + nanotech. Biomedical Engineer & Nanoscientist. Forbes 30 Under 30 in Healthcare.", "first_name": "Andre", "last_name": "Watson", "instagram_handle": "nanogenomic", "is_verified": false, "last_online_at": "2026-06-06T02:03:58.578Z", "linkedin_handle": "/in/nanogenomic", "name": "Andre Watson", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": "nanogenomic", "username": "nanogenomic", "website": "https://www.ligandal.com", "youtube_handle": "" }, { "api_id": "usr-oY320Jy6LsCQFp9", "avatar_url": "https://images.lumacdn.com/avatars/fk/41288aee-4dc3-4793-8c6a-6b5ec301cdda.jpg", "bio_short": "", "first_name": "Hasanul", "last_name": "Chowdhury", "instagram_handle": "thehasan.vc", "is_verified": false, "last_online_at": "2026-06-06T02:01:08.084Z", "linkedin_handle": "/in/hasanul-chowdhury", "name": "Hasanul Chowdhury", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": null, "username": null, "website": null, "youtube_handle": null }, { "api_id": "usr-4Tc8EwBZ0EUyEg1", "avatar_url": "https://images.lumacdn.com/avatars/y0/295aa5fa-be61-4894-9317-e9223b2284e1.jpg", "bio_short": "", "first_name": "Ankur", "last_name": "Tyagi", "instagram_handle": "ank.2007", "is_verified": false, "last_online_at": "2026-06-06T00:11:16.434Z", "linkedin_handle": "/in/ankurtyagi2007", "name": "Ankur Tyagi", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": null, "username": "ankurtyagi", "website": null, "youtube_handle": null }, { "api_id": "usr-uzrtGbcZyEkB0jq", "avatar_url": "https://images.lumacdn.com/avatars/fj/c90e9a06-1578-4e4c-ad00-6a56f89abd85.jpg", "bio_short": "", "first_name": "Anas", "last_name": "Hoque", "instagram_handle": "anashoque", "is_verified": false, "last_online_at": "2026-06-05T23:15:27.094Z", "linkedin_handle": "/in/anas-hoque", "name": "Anas Hoque", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": "anashoque", "username": null, "website": null, "youtube_handle": "" }, { "api_id": "usr-XDlyL1cuSKKdgFS", "avatar_url": "https://images.lumacdn.com/avatars/0c/08e468cc-d897-4c72-a562-fd704d6faa9c.jpg", "bio_short": "", "first_name": "Andrea", "last_name": "Doucette", "instagram_handle": "lifeofcryptogal", "is_verified": false, "last_online_at": "2026-06-06T01:30:04.070Z", "linkedin_handle": "/in/cryptogal", "name": "Andrea Doucette", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": "onlycryptogal", "username": null, "website": "https://ascensionholdings.global", "youtube_handle": null }, { "api_id": "usr-b1rWrGO6j8hkExH", "avatar_url": "https://images.lumacdn.com/uploads/0t/544fcc81-8a0b-4d4d-a9ac-51cfb1d12e8e.jpg", "bio_short": "", "first_name": "Neel", "last_name": "Gajiwala", "instagram_handle": "neelgaji", "is_verified": false, "last_online_at": "2026-06-05T23:27:25.449Z", "linkedin_handle": "/in/neelgaji", "name": "Neel Gajiwala", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": null, "username": null, "website": null, "youtube_handle": null }, { "api_id": "usr-vLkl90LBVnucdL6", "avatar_url": "https://images.lumacdn.com/avatars/zx/959e67e9-c44a-4a3d-b66d-0d0451a425d8", "bio_short": "Blockchain Architect\nCo-founder at @NoFunLabs\n\nVisit nofunlabs.xyz to sign up for beta access to our upcoming games!", "first_name": "Evan", "last_name": "Gottschalk", "instagram_handle": "EvanOnEarth_eth", "is_verified": false, "last_online_at": "2026-06-05T18:58:29.122Z", "linkedin_handle": "/in/evan-gottschalk", "name": "Evan Gottschalk", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": "EvanOnEarth_eth", "username": "EvanOnEarth", "website": "https://evanonearth.xyz", "youtube_handle": "EvanOnEarth_eth" }, { "api_id": "usr-6vMaSER2Qshhlhe", "avatar_url": "https://images.lumacdn.com/avatars/ii/c3b798ac-b11d-42ac-b0c8-9fc03e522710.png", "bio_short": "We collect, sell, manage, and Curate Art Events Globally 🌎 Consulting for General design projects 📋🌆💻\nArt Agency 🎨 🥂Est 2014", "first_name": "Irving", "last_name": "Ortega", "instagram_handle": "irvohh", "is_verified": false, "last_online_at": "2026-06-05T23:57:15.628Z", "linkedin_handle": "/in/irving-ortega-43617377", "name": "Irving Ortega", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": "IrvingOrtega88", "username": "irvohh", "website": null, "youtube_handle": "" }, { "api_id": "usr-lALBWJ5TNiHnXVA", "avatar_url": "https://images.lumacdn.com/avatars/sz/bf5f3c27-f1aa-4b0b-9159-048702f16e9f.jpg", "bio_short": "Founder of Nuwa Marketing, Forbes 2X", "first_name": "Yanyi", "last_name": "Li", "instagram_handle": "Yanyi_Nuwa", "is_verified": false, "last_online_at": "2026-06-06T01:30:02.808Z", "linkedin_handle": "/in/yanyi-li-nuwa", "name": "Yanyi Li", "tiktok_handle": null, "timezone": "America/New_York", "twitter_handle": "NA", "username": null, "website": null, "youtube_handle": "" } ], "manager_info": null, "guest_info": null, "host_info": null, "waitlist_active": false, "featured_city": null, "role": null, "calendar_api_id": "cal-Byhuy8VcnWMbGWA", "is_manager": false, "platform": "luma", "status": "approved", "submitted_by_user_api_id": "usr-QkGeDxzjcR2zjs3", "tags": [], "from_url": "https://luma.com/nytw" } ``` Each scraped event returns a rich record with 23 fields capturing event details, host info, ticket metadata, and engagement metrics: #### Event Identification | Field | Meaning | |---|---| | `API ID` | Unique Luma identifier for the event (use for deduplication or linking) | | `Event` | Event title as displayed on Luma | | `Calendar` | Calendar or series the event belongs to | | `Calendar API ID` | Unique identifier for the parent calendar | #### Event Timing & Location | Field | Meaning | |---|---| | `Start At` | Event start date and time in ISO 8601 format | | `Featured City` | Primary city where the event is held or featured | #### Event Media | Field | Meaning | |---|---| | `Cover Image` | URL to the event's cover/hero image | #### Attendance & Capacity | Field | Meaning | |---|---| | `Guest Count` | Total number of confirmed attendees/RSVPs | | `Ticket Count` | Total number of tickets across all tiers | | `Ticket Info` | Structured data on available ticket types, pricing, and availability | | `Registration Availability` | Current registration status (e.g., open, closed, waitlist only) | | `Waitlist Active` | Boolean indicating if a waitlist is currently open | #### Host & Guest Data | Field | Meaning | |---|---| | `Hosts` | Array of primary event organizers/hosts | | `Host Info` | Detailed host profile data (name, bio, follower count, links) | | `Featured Guests` | VIP attendees or speakers highlighted on the event page | | `Guest Info` | Metadata on featured guests or notable attendees | #### Operational Fields | Field | Meaning | |---|---| | `Manager Info` | Event manager/organizer contact and permission details | | `Is Manager` | Boolean flag indicating if the user is an event manager | | `Role` | User's role relative to the event (e.g., host, attendee, moderator) | | `Submitted By User API ID` | Unique ID of the user who submitted/created the event listing | #### Platform & Status | Field | Meaning | |---|---| | `Platform` | Source platform identifier (e.g., "Luma") | | `Status` | Event status (e.g., published, draft, cancelled, completed) | | `Tags` | Categorization tags assigned to the event (e.g., #tech, #networking) | *** ### How to Use 1. **Identify target URLs** — Find Luma event search pages by category, city, or hashtag. Examples: `https://luma.com/nytw`, `https://luma.com/search?query=blockchain`, or specific calendar URLs. 2. **Prepare input** — Add URLs to the `urls` array in JSON format. Use bulk edit for multiple URLs. 3. **Set collection limits** — Adjust `max_items_per_url` based on your needs (20–200). Higher values take longer but capture more events. 4. **Enable error resilience** — Set `ignore_url_failures: true` for large runs to skip problematic pages automatically. 5. **Execute & monitor** — Start the scraper and watch the progress log. 6. **Export results** — Download structured data as JSON, CSV, or Excel for analysis, database import, or downstream processing. **Troubleshooting tips:** - Verify URLs point to Luma search/calendar pages, not individual event detail pages. - If timeouts occur, reduce `max_items_per_url` or enable `ignore_url_failures`. - Check exported data for duplicate events across multiple runs using the `API ID` field. *** ### Use Cases & Business Value - **Event discovery platforms:** Aggregate Luma events alongside your own database for competitive breadth. - **Market intelligence:** Track event supply, trends, and organizer activity across regions and categories. - **Community analysis:** Identify emerging communities and networking hubs based on event frequency and attendee overlap. - **Sponsorship prospecting:** Find high-attendance events matching your target audience for partnership outreach. By automating event collection, you eliminate manual browsing, ensure consistent data quality, and unlock insights for strategy, marketing, and product development. *** ### Conclusion The **Luma Events Search Scraper** transforms event discovery into a scalable, data-driven process. With 23 actionable fields per event and flexible input parameters, it streamlines research, aggregation, and competitive analysis. Start scraping today and turn Luma's event calendar into structured intelligence for your business. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the events search urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `ignore_url_failures` (type: `boolean`): If true, the scraper will continue running even if some URLs fail to be scraped. ## `max_items_per_url` (type: `integer`): The maximum number of items to scrape per URL. ## Actor input object example ```json { "urls": [ "https://luma.com/nytw" ], "ignore_url_failures": true, "max_items_per_url": 20 } ``` # 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 = { "urls": [ "https://luma.com/nytw" ], "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("stealth_mode/luma-events-search-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 = { "urls": ["https://luma.com/nytw"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/luma-events-search-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 '{ "urls": [ "https://luma.com/nytw" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/luma-events-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/luma-events-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Luma Events Search Scraper", "description": "Extract comprehensive event data from Luma.com with detailed host info, ticket counts, guest lists, and registration details. Perfect for event aggregators, market researchers, and marketing analysts — collect up to 200 events per search page.", "version": "0.0", "x-build-id": "HhUFmpJlQ2hEYDSEw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~luma-events-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-luma-events-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~luma-events-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-luma-events-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~luma-events-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-luma-events-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "urls": { "title": "URLs of the events search urls to scrape", "type": "array", "description": "Add the URLs of the events search urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.", "items": { "type": "string" } }, "ignore_url_failures": { "title": "Continue running even if some URLs fail to be scraped", "type": "boolean", "description": "If true, the scraper will continue running even if some URLs fail to be scraped." }, "max_items_per_url": { "title": "Max items per URL", "type": "integer", "description": "The maximum number of items to scrape per URL." } } }, "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 } } } } } } } } } } ```