Luma Event Scraper

Extract comprehensive event data from Luma (lu.ma), the leading platform for AI, tech, and community events. This Luma scraper automates data extraction of event details, organizers, hosts, featured guests, ticketing information, and attendance metrics across multiple cities and categories.

Key Features

• Multi-Category Support: Scrape events from 8 categories (AI, Tech, Food & Drink, Arts & Culture, Climate, Fitness, Wellness, Crypto)
• Geographic Flexibility: Search events in any city worldwide with automatic geocoding via OpenStreetMap
• Comprehensive Data Extraction: Get 40+ data fields including organizer profiles, host information, social media handles, ticketing details, and attendance metrics
• Full Social Media URLs: Extract complete LinkedIn, Instagram, Twitter, YouTube, and TikTok URLs (not just handles)
• Efficient HTTP-Based Scraping: Uses Luma's discover API for fast, reliable data extraction without browser overhead
• Automatic Pagination: Handles multiple pages automatically (100 events per page)
• Structured Output: Clean, validated JSON output ready for analysis, CRM import, or database integration
• No API Key Required: Direct access to Luma's public event data
• Geocoding Integration: Automatically converts city names to geographic coordinates
• Real-Time Data: Extract current event information including live attendance counts and ticket availability

What Data Can You Extract?

This Luma event scraper extracts comprehensive information about each event:

Data Category	Fields Extracted	Description
Event Basics	ID, Name, Description, Category, Luma URL	Core event identification and classification
Timing	Start Time, End Time, Timezone	Complete scheduling information in ISO 8601 format
Location	Address, City, Region, Country, Coordinates (lat/lng), Place ID, Virtual URL, Meeting Platform	Both physical and virtual location details
Organizer	Name, Description, Verification Status, Luma Plus Status, Avatar/Cover Images, Website, Social Media URLs	Complete organizer profile and credentials
Hosts	Name, Bio, Verification Status, Avatar, Website, Social Media URLs	Full profiles of event hosts with contact information
Featured Guests	Name, Bio, Verification Status, Avatar, Website, Social Media URLs	VIP attendees and speakers
Ticketing	Price, Currency, Free/Paid Status, Sold Out Status, Approval Requirements	Complete pricing and registration details
Attendance	Guest Count, Ticket Count, Spots Remaining, Capacity Warnings, Waitlist Status	Real-time attendance metrics
Media	Cover Image URL, Dominant Colors	Event visual assets
Engagement	Popularity Score, Scraped Timestamp	Luma platform metrics and data freshness

How to Scrape Luma Events

Follow these simple steps to extract event data from Luma:

1. Select Event Categories

Choose one or more categories from:

• AI - Artificial intelligence and machine learning events
• Tech - Technology and startup events
• Food & Drink - Culinary and dining experiences
• Arts & Culture - Creative and cultural events
• Climate - Environmental and sustainability events
• Fitness - Sports and workout activities
• Wellness - Health and mindfulness events
• Crypto - Blockchain and cryptocurrency meetups

2. Enter Target Cities

Specify cities where you want to find events:

San Francisco, New York, London, Berlin, Tokyo, Austin, Miami

The scraper automatically geocodes city names to coordinates for accurate search results.

3. Set Event Limits (Optional)

Control how many events to scrape per city:

• Leave empty to scrape all available events
• Set a specific number (e.g., 50) to limit results per city

4. Run the Actor

Click Start and the scraper will:

• Query Luma's discover API for each city/category combination
• Extract all event data fields automatically
• Handle pagination for large result sets
• Geocode city coordinates via OpenStreetMap
• Transform and validate output data

5. Download Results

Export your data in multiple formats:

• JSON - for APIs and data processing
• CSV - for Excel and spreadsheet analysis
• Excel - for business reporting
• HTML - for web previews
• RSS - for feed subscriptions

Input Configuration

Configure the scraper with these parameters:

Parameter	Type	Required	Description
Event Categories	Array	Yes	Select one or more categories: tech, food, ai, arts, climate, fitness, wellness, crypto
Cities	Array	Yes	City names to search (e.g., "San Francisco", "London", "Tokyo")
Max Events Per City	Integer	No	Maximum number of events to scrape per city. Leave empty for unlimited.

Input Example

{
  "slugs": ["ai", "tech"],
  "cities": ["San Francisco", "New York", "London"],
  "maxEventsPerCity": 50
}

This configuration will scrape up to 50 AI and Tech events from each of the three cities (maximum 300 events total).

Output Example

Each event is returned as a structured JSON object with all available data:

{
  "id": "evt-Y4qM1PtptJqDRnU",
  "lumaUrl": "https://lu.ma/s7b2tohw",
  "category": "tech",
  "name": "Impact Night — From startup to scale up: Hiring, culture, and the path to 9-figure ARR",
  "description": null,
  "eventType": "independent",
  "visibility": "public",
  "startAt": "2026-02-18T17:00:00.000Z",
  "endAt": "2026-02-18T21:00:00.000Z",
  "timezone": "Europe/Prague",
  "location": {
    "locationType": "offline",
    "fullAddress": null,
    "address": null,
    "city": null,
    "region": null,
    "country": null,
    "latitude": null,
    "longitude": null,
    "placeId": null,
    "virtualUrl": null,
    "meetingPlatform": null
  },
  "organizer": {
    "id": "cal-nZ91u1bNYmhfTfg",
    "name": "Uppersky",
    "description": null,
    "isVerified": true,
    "isLumaPlus": false,
    "avatarUrl": "https://images.lumacdn.com/calendars/ow/ebd78838-9901-4b80-9dec-07e3d5484905.png",
    "coverUrl": null,
    "websiteUrl": null,
    "socialHandles": {
      "linkedin": "https://www.linkedin.com/company/uppersky",
      "instagram": "https://www.instagram.com/uppersky/",
      "twitter": null,
      "youtube": null,
      "tiktok": null
    }
  },
  "hosts": [
    {
      "id": "usr-BcdItsLqEbZXwkY",
      "name": "Ricardo Monagas",
      "bio": null,
      "isVerified": false,
      "avatarUrl": "https://images.lumacdn.com/avatars/1a/9f893b5e-0e27-4967-a537-3655ee974d23.jpg",
      "websiteUrl": null,
      "socialHandles": {
        "linkedin": "https://www.linkedin.com/in/ricardomonagas",
        "instagram": "https://www.instagram.com/ricardo.monagas/",
        "twitter": null
      }
    }
  ],
  "featuredGuests": [],
  "ticketing": {
    "isFree": false,
    "priceCents": 20000,
    "currency": "czk",
    "isSoldOut": false,
    "soldOutAt": null,
    "requiresApproval": false
  },
  "attendance": {
    "guestCount": 0,
    "ticketCount": null,
    "spotsRemaining": null,
    "capacityWarning": null,
    "hasWaitlist": false,
    "waitlistCount": null,
    "isGuestListPublic": false
  },
  "coverImageUrl": "https://images.lumacdn.com/event-covers/47/fdb3421d-6cc4-4a38-9d6c-8afcf08a0a79.png",
  "dominantColors": [],
  "popularityScore": null,
  "scrapedAt": "2026-02-14T14:39:18.943Z"
}

Use Cases

Event Managers & Community Builders

• Monitor competitor events in your city and category
• Discover trending event formats and topics
• Identify popular venues and timeslots
• Track attendance patterns and pricing strategies

Marketers & Sales Teams

• Build targeted outreach lists from event organizers and hosts
• Identify potential partnership opportunities
• Track industry events for sponsorship opportunities
• Extract social media profiles for influencer outreach

Researchers & Data Analysts

• Analyze event trends across categories and geographies
• Study community engagement patterns
• Compare pricing strategies across markets
• Track the growth of specific event categories (e.g., AI events)

Recruiters & Talent Teams

• Find industry events for recruiting opportunities
• Identify thought leaders and speakers in your domain
• Build contact lists from host and guest profiles
• Track networking events in target cities

Troubleshooting and FAQ

Why are some cities returning no events?

Luma's event distribution varies by location and category. Some cities may have limited events in specific categories. Try:

• Searching broader categories (e.g., "tech" instead of just "crypto")
• Using major tech hub cities (San Francisco, New York, London, Berlin)
• Checking the Luma website directly to confirm events exist for that city/category

How do I get events for a specific time period?

The scraper returns all upcoming events from Luma's discover API. To filter by date:

1. Run the scraper without date filters
2. Post-process the results by filtering the startAt and endAt fields
3. Use the scrapedAt timestamp to track data freshness

Can I scrape multiple categories in one run?

Yes! The slugs parameter accepts an array. Simply include multiple categories:

{
  "slugs": ["ai", "tech", "crypto"],
  "cities": ["San Francisco"]
}

What happens if an event doesn't have certain fields?

The scraper returns null for missing optional fields. All events include core fields (id, name, category, startAt, endAt, location, organizer) but may have:

• Missing descriptions
• Incomplete location details (especially for virtual events)
• Empty featured guests arrays
• Null popularity scores

How often should I run the Actor?

It depends on your use case:

• Real-time monitoring: Daily runs to catch new events
• Weekly analysis: Weekly runs for trend tracking
• Monthly reports: Monthly runs for comprehensive market analysis
• Event-based: Run before major conferences or seasons

Is this Actor compliant with Luma's terms of service?

This Actor scrapes publicly available event data from Luma's discover API. It respects rate limits and uses HTTP-based scraping (not browser automation) to minimize server load. However:

Legal Disclaimer: Users are responsible for ensuring their use of scraped data complies with:

• Luma's Terms of Service
• Local data protection laws (GDPR, CCPA, etc.)
• Intended use restrictions

Recommended practices:

• Use data for personal research and analysis
• Respect event organizers' intellectual property
• Don't republish scraped data without permission
• Implement reasonable rate limiting for large-scale scraping
• Consider contacting event organizers for commercial use

Can I scrape past events?

This scraper focuses on upcoming events from Luma's discover API. Past events may have limited availability depending on Luma's data retention policies.

Integration and Export

Export Formats

Download your scraped data in multiple formats:

• JSON - Raw structured data for APIs and databases
• CSV - Import into Excel, Google Sheets, or data analysis tools
• Excel (XLSX) - Business-ready spreadsheet format with formatted columns
• HTML - Human-readable table view
• RSS Feed - Subscribe to scraper results
• XML - Legacy system integration

Apify Integrations

Connect this scraper to 1,000+ apps with no code:

• Zapier - Automate workflows and data delivery
• Make (Integromat) - Build complex automation scenarios
• Google Sheets - Direct export to spreadsheets
• Slack - Get notifications with new events
• Airtable - Create event databases
• Email - Automatic report delivery
• Webhooks - Push data to your own API

API Access

Access your data programmatically with the Apify API:

// Node.js example
const ApifyClient = require('apify-client');
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('YOUR_USERNAME/luma-event-scraper').call({
  slugs: ['ai', 'tech'],
  cities: ['San Francisco', 'London'],
  maxEventsPerCity: 50
});

const dataset = await client.dataset(run.defaultDatasetId).listItems();
console.log(dataset.items);

# Python example
from apify_client import ApifyClient

client = ApifyClient('YOUR_API_TOKEN')

run = client.actor('YOUR_USERNAME/luma-event-scraper').call(
    run_input={
        'slugs': ['ai', 'tech'],
        'cities': ['San Francisco', 'London'],
        'maxEventsPerCity': 50
    }
)

dataset_items = client.dataset(run['defaultDatasetId']).list_items().items
print(dataset_items)

Database Integration

Import scraped data into databases:

• PostgreSQL - Use JSON columns or normalized tables
• MongoDB - Direct JSON import
• MySQL - Convert JSON to relational schema
• BigQuery - Load for large-scale analytics
• Snowflake - Data warehouse integration

Support and Resources

Get Help

• Discord Community: Join Apify Discord - Get help from Apify developers and community
• Documentation: Apify Platform Docs - Complete platform documentation

Learn More

• Apify Academy: Web Scraping Courses - Learn web scraping fundamentals
• Blog: Apify Blog - Web scraping tutorials and best practices
• Video Tutorials: YouTube Channel - Step-by-step guides
• API Documentation: Apify API Reference - Complete API documentation

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