# ResidentAdvisor Events (`aitorsm/ra-events`) Actor Get electronic-music events from Resident Advisor (RA.co): title, date, venue, lineup, and ticket status. Every event includes enriched promoter leads — name, website, Instagram/Facebook/Twitter handles, and follower count. Built for music-industry BD, booking, and sponsorship targeting. - **URL**: https://apify.com/aitorsm/ra-events.md - **Developed by:** [Aitor Sanchez-Mansilla](https://apify.com/aitorsm) (community) - **Categories:** Automation, Lead generation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 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 ## Resident Advisor Events Scraper — Electronic Music Lead-Gen with Enriched Promoter Data [![Resident Advisor Events Scraper status](https://apify.com/actor-badge?actor=aitorsm/ra-events)](https://apify.com/aitorsm/ra-events) The **Resident Advisor Events Scraper** extracts structured event data from [Resident Advisor (RA.co)](https://ra.co) — the global directory for electronic music events, clubs, festivals, and promoters. Each scraped event returns: - Event title, date, start/end time, RA event URL, flyer image - **Enriched promoter (organizer) data** — name, RA profile URL, website, **social links (Instagram, Facebook, Twitter, SoundCloud)**, follower count, upcoming events count, area, country, blurb, festival flag. The one feature competing RA scrapers don't expose. - Full venue record — name, RA venue URL, live-status flag - Artist lineup (every act on the bill, with their RA artist IDs and names) - Ticket availability + interested count (RSVP-equivalent for the electronic music crowd) - Editorial "pick" blurb when RA features the event ### Why this scraper Resident Advisor is where indie electronic-music promoters publish their entire programming calendar. With `enrichPromoters` on (default), every event comes back as a self-contained lead row — the promoter's name, website, social links, audience size, and activity level — so there's no follow-up enrichment step to run. ### Use Cases #### 1. **Electronic-Music Promoter Lead Generation** Pull every active promoter in a city ranked by `followerCount` + `upcomingEventsCount`. Direct input for ticketing-platform BD (Posh, vivenu, Ticket Fairy, Showpass), event-marketing CRMs (Audience Republic, Bizzabo), and music-industry sponsorship outreach. #### 2. **Festival + Club Booking Intelligence** Each event carries the full venue record. Run the scraper for London / Berlin / Barcelona / Tokyo to map the active club ecosystem — useful for booking agents, music-tech vendors, and AV / production companies. #### 3. **Artist / DJ Tracking** Each event's `artists[]` array gives every act on the lineup. Useful for talent agencies (which DJs are headlining where), labels (gauging act-deployment frequency), and music-data SaaS. #### 4. **Cross-Platform Organizer Database** Combine RA output with Eventbrite, Posh, Luma, and DICE datasets for unified multi-source organizer intelligence. RA covers the global electronic-music niche that those platforms don't index deeply. #### 5. **Sponsorship + Brand Activation Targeting** Filter for `interestedCount > X` + `isFestival: true` → list of high-traffic festival promoters who'd consider sponsorship deals. #### 6. **Editorial / Press Picks Aggregation** The `editorialPickBlurb` field surfaces events RA's editorial team has highlighted — useful for press-coverage tracking, taste-making research, and curation-as-a-service products. #### 7. **Audience-Size Validation for Underwriting** Promoter `followerCount` + `upcomingEventsCount` are signals an underwriter can use to assess whether a festival/promoter is a legitimate operator (vs. someone running their first event). Direct input for credit-underwriting products like Ticket Fairy Capital. > **On the roadmap**: per-event genre filtering, a venue-specific input mode, and event-ID lookup. [Drop me a line](mailto:business@aitorsm.com) if any of these would unblock a use case — it helps me prioritize. ### Cost This Actor uses **pay-per-event** pricing: - **$0.03 per event scraped** - **$0.02 per unique promoter enriched** — only charged when `enrichPromoters` is on (the default), and only once per promoter per run (deduplicated across all events). Turn `enrichPromoters` off to pay for events alone. Apify's platform costs are included, so the total is predictable. A typical city sweep of 250 events with enrichment on costs roughly $7.50 (events) + ~$4 (promoters) ≈ **$11.70 for ~200 enriched promoter leads** with names, websites, social links, and follower counts. ### Input - **`city`** — name of any major RA-covered city (e.g. `"Los Angeles"`, `"London"`, `"Berlin"`, `"Barcelona"`, `"Tokyo"`, `"Berlin"`, `"Mexico City"`). The actor resolves the name against RA's areaId table — ~40 major cities are hardcoded for instant lookup, others fall back to a runtime catalog query. - **`areaId`** *(advanced)* — RA's internal numeric area ID. Pass this directly if you have it (skips the city-resolution lookup). E.g. `23` for LA, `13` for London, `34` for Berlin. - **`listingDateGte`** — earliest event date to include (YYYY-MM-DD). Defaults to today. - **`listingDateLte`** — latest event date to include (YYYY-MM-DD). Leave empty for no upper bound. - **`maxItems`** — global cap on events returned (deduped across all paginated pages). 0 = uncapped. - **`enrichPromoters`** *(boolean, default `true`)* — when true, each event's promoters[] array is enriched with full detail (name, website, social links — Instagram, Facebook, Twitter, SoundCloud — follower count, upcoming events count, blurb, area, country, isFestival). Enriched once per unique promoter and cached for the run. **Recommended for lead-generation use cases** — without it you only get promoter IDs. #### Sample inputs **Quick city preview**: ```json { "city": "Los Angeles", "maxItems": 20 } ```` **Wide lead-gen sweep** (2 months of LA events, enriched promoters): ```json { "city": "Los Angeles", "listingDateGte": "2026-06-01", "listingDateLte": "2026-07-31", "maxItems": 500, "enrichPromoters": true } ``` **Direct area access** (London by ID, skips lookup): ```json { "areaId": 13, "maxItems": 100 } ``` ### Output The data is returned in **JSON format**, ideal for direct ingestion into analytics platforms, CRMs, dashboards, or downstream pipelines. #### Example entry Input: `{ "city": "Los Angeles", "maxItems": 1, "enrichPromoters": true }` ```json { "eventId": "2384905", "listingDate": "2026-05-23", "areaId": 23, "name": "Into The Woods presents Ben UFO (Extended Set)", "date": "2026-05-23T00:00:00.000", "startTime": "2026-05-23T22:00:00.000", "endTime": "2026-05-24T04:00:00.000", "url": "https://ra.co/events/2384905", "contentUrl": "/events/2384905", "flyerFront": "https://static.ra.co/images/events/flyer/...", "isTicketed": true, "interestedCount": 423, "venueId": "139125", "venueName": "Sound Nightclub", "venueUrl": "https://ra.co/clubs/139125", "venueLive": true, "promoterIds": ["65088"], "promoterNames": ["Into The Woods LA"], "promoters": [ { "id": "65088", "name": "Into The Woods LA", "url": "https://ra.co/promoters/65088", "blurb": "Into The Woods is a music series, label, and collective that bridges the sonic gap between Los Angeles, Detroit and beyond to amplify diverse voices in electronic dance music.", "logoUrl": "https://static.ra.co/images/promoter/us-intothewoods.jpg", "coverUrl": null, "website": "https://www.facebook.com/intothewoodsrecordings/", "followerCount": 1076, "upcomingEventsCount": 0, "isFestival": false, "areaName": "Los Angeles", "countryName": "United States of America", "socialMediaLinks": [ { "platform": "instagram", "link": "https://instagram.com/intothewoodsla" }, { "platform": "facebook", "link": "https://facebook.com/intothewoodsrecordings" }, { "platform": "twitter", "link": "https://twitter.com/intothewoodsla" } ], "instagram": "https://instagram.com/intothewoodsla", "facebook": "https://facebook.com/intothewoodsrecordings", "twitter": "https://twitter.com/intothewoodsla", "soundcloud": null } ], "artists": [ { "id": "5294", "name": "Ben UFO" } ], "ticketsAvailable": 2, "editorialPickBlurb": null, "imageUrl": "us/2026/5/us-0523-into-the-woods-flyer.jpg", "scrapedAt": "2026-05-23T02:18:40.184Z" } ``` #### Fields | Field | Purpose | |---|---| | `eventId`, `contentUrl`, `url` | RA event identifiers + canonical URL | | `title`, `date`, `startTime`, `endTime` | Event basics | | `flyerFront`, `imageUrl` | Event flyer URLs | | `isTicketed`, `interestedCount`, `ticketsAvailable` | Availability + popularity signals | | `venueId`, `venueName`, `venueUrl`, `venueLive` | Venue record | | **`promoters[]`** | When `enrichPromoters=true`: full promoter records with name, website, social links (`socialMediaLinks[]` + flat `instagram`/`facebook`/`twitter`/`soundcloud`), follower count, upcoming events count, blurb, area, country, isFestival. When false: just IDs. | | `promoterIds[]`, `promoterNames[]` | Convenience flat arrays for filtering / joining | | `artists[]` | Lineup acts `[{id, name}]` | | `editorialPickBlurb` | RA editorial-pick blurb when featured | | `listingDate`, `scrapedAt` | Audit metadata | #### Simplified Overview A simplified view of this data is shown directly in the **Apify console**: ```json { "name": "Into The Woods presents Ben UFO (Extended Set)", "flyerFront": "https://static.ra.co/images/events/flyer/...", "date": "2026-05-23T00:00:00.000", "venueName": "Sound Nightclub", "promoterNames": ["Into The Woods LA"], "artists": [{"id":"5294","name":"Ben UFO"}], "interestedCount": 423, "isTicketed": true, "url": "https://ra.co/events/2384905" } ``` *** ### How to Use 1. **Pick a city** — type any major RA-covered city (LA, London, Berlin, Barcelona, Tokyo, ~40+ in fast lookup). 2. **Set a date range** — defaults to "today onwards"; tighten for narrower scrape windows. 3. **Keep `enrichPromoters: true`** — that's the lead-gen feature. 4. **Set `maxItems`** — 100 for a quick test, thousands for a city's full forward calendar. 5. **Run the Actor** — check the Overview tab to see events as they arrive. 6. **Export the dataset** — JSON, CSV, Excel, or HTML. *** Start scraping Resident Advisor events today by running this Actor on Apify. ### Contact - **Email**: — for custom features, advanced filtering, tailored data products, or anything off-spec. - **Apify Discord**: find me as `aitor.sm`. If this actor has been useful to you, please consider adding it to your bookmarks 📑 on Apify. # Actor input Schema ## `city` (type: `string`): City to filter events by (e.g. "Los Angeles", "Berlin", "Tokyo"). Resolves to an internal RA areaId. Leave empty if providing `areaId` directly. ## `areaId` (type: `integer`): RA's internal numeric areaId. Overrides `city`. Useful for cities the resolver doesn't recognise. ## `listingDateGte` (type: `string`): Earliest listing date to include. Defaults to today. ## `listingDateLte` (type: `string`): Latest listing date (inclusive). Leave empty for no upper bound. ## `maxItems` (type: `integer`): Maximum number of events to return. 0 = uncapped. ## `enrichPromoters` (type: `boolean`): If true, each event's promoters\[] array is enriched with full data — name, website, social URLs (Instagram, Facebook, Twitter, SoundCloud), follower count, upcoming events count, area, country. Costs ~1 extra request per unique promoter (cached for the run). Recommended for lead-generation use cases. ## Actor input object example ```json { "city": "Los Angeles", "maxItems": 100, "enrichPromoters": true } ``` # Actor output Schema ## `overview` (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 = { "city": "Los Angeles", "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("aitorsm/ra-events").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 = { "city": "Los Angeles", "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("aitorsm/ra-events").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 '{ "city": "Los Angeles", "maxItems": 100 }' | apify call aitorsm/ra-events --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=aitorsm/ra-events", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ResidentAdvisor Events", "description": "Get electronic-music events from Resident Advisor (RA.co): title, date, venue, lineup, and ticket status. Every event includes enriched promoter leads — name, website, Instagram/Facebook/Twitter handles, and follower count. Built for music-industry BD, booking, and sponsorship targeting.", "version": "0.0", "x-build-id": "fE0ttTJa3PfoP2Ige" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/aitorsm~ra-events/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-aitorsm-ra-events", "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/aitorsm~ra-events/runs": { "post": { "operationId": "runs-sync-aitorsm-ra-events", "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/aitorsm~ra-events/run-sync": { "post": { "operationId": "run-sync-aitorsm-ra-events", "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": { "city": { "title": "City", "type": "string", "description": "City to filter events by (e.g. \"Los Angeles\", \"Berlin\", \"Tokyo\"). Resolves to an internal RA areaId. Leave empty if providing `areaId` directly." }, "areaId": { "title": "Area ID (advanced)", "type": "integer", "description": "RA's internal numeric areaId. Overrides `city`. Useful for cities the resolver doesn't recognise." }, "listingDateGte": { "title": "Listing date — from (YYYY-MM-DD)", "type": "string", "description": "Earliest listing date to include. Defaults to today." }, "listingDateLte": { "title": "Listing date — to (YYYY-MM-DD)", "type": "string", "description": "Latest listing date (inclusive). Leave empty for no upper bound." }, "maxItems": { "title": "Max events", "minimum": 0, "type": "integer", "description": "Maximum number of events to return. 0 = uncapped.", "default": 100 }, "enrichPromoters": { "title": "Enrich promoters (billed per promoter)", "type": "boolean", "description": "If true, each event's promoters[] array is enriched with full data — name, website, social URLs (Instagram, Facebook, Twitter, SoundCloud), follower count, upcoming events count, area, country. Costs ~1 extra request per unique promoter (cached for the run). Recommended for lead-generation use cases.", "default": true } } }, "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 } } } } } } } } } } ```