Building a Standardised Multi-Platform Event Scraper: The Architecture Behind Smart Event Scraper
Event data is scattered by design. AllEvents.in, EventsEye.com, District.in, and Meetup.com each structure their listings differently different field names, different date formats, different ways of representing price and location. Pull from more than one of these sources and you inherit the reconciliation problem: matching fields, renaming columns, deduplicating, before the data is usable for anything downstream.
The Smart Event Scraper by Techforce Global is an Apify actor that solves this by running all four platforms in a single pass and returning one standardised, deduplicated schema regardless of source. This article walks through the technical decisions behind it: why a fixed category taxonomy beats free-text tagging, how the normalisation layer guarantees identical output fields, the full input/output reference, a working n8n pipeline, and code examples for calling it directly from Python or Node.
Try it: https://apify.com/techforce.global/smart-event-scraper
The Core Problem: Four Sources, Four Shapes
Each of the four source platforms exposes event data with a different shape. Dates might be ISO strings on one platform and human-readable text on another. Price might be a number, a currency-formatted string, or simply absent. Location might be a full address or just a city name. None of this is a bug in any individual platform it's just what happens when four independent systems solve the same problem differently.
The naive approach to combining them is to write four separate scrapers and reconcile the output afterward in your own code four sets of field mappings to maintain, four sets of edge cases to handle, and a reconciliation step that has to be re-run mentally every time you add a fifth source.
Why a Fixed Category Taxonomy
Free-text tags look flexible but create long-term inconsistency "tech", "technology", and "Tech & Software" all describe the same events but don't group cleanly when you're filtering across sources. Smart Event Scraper uses six fixed categories Tech & Software, Business & Networking, Food & Beverages, Health & Wellness, Art & Culture, and Education & Learning applied identically across all four platforms. A single category filter reliably returns the same type of event no matter which site it originated from. Leave category blank to pull every event type from all four sources in one run.
How It Works : Four Steps
- Step 1 : Parallel source queries: each platform receives the same category, keyword, location, and date-range parameters, queried independently with per-source result limits controlled by maxEventsPerSource.
- Step 2 : Field mapping: each platform's native response is mapped onto a fixed 9-field schema (title, date, location, venue, price, url, category, source, description). Fields with no equivalent on a given platform return "N/A" rather than being omitted or left null.
- Step 3 : Category normalization: where a platform doesn't natively support the same 6-category system, category is auto-detected from the event title/description and mapped onto the closest fixed category.
- Step 4 : Consolidation: all four sources' results merge into a single output list, each record tagged with its source platform, ready for direct import without further transformation.
Input Configuration
{
"category": "Tech & Software",
"location": "Berlin",
"maxEventsPerSource": 40,
"dateFrom": "2026-09-01",
"dateTo": "2026-09-30"
}
Output Schema
n8n Weekly Event Digest Pipeline
- Schedule Trigger : every Monday 9:00 AM
- HTTP Request : POST to Apify API to start Smart Event Scraper with category + location + coming week's date range
- Wait/Poll : every 60 seconds until run = SUCCEEDED
- HTTP Request : GET results from the Apify dataset API
- Google Sheets or Slack node : push results, grouped by source
Because every event record shares the same 9-field schema regardless of source, the Slack/Sheets node requires no conditional field mapping.
Frequently Asked
How do I find tech events in a specific city automatically?
Set category to "Tech & Software" and location to your target city the actor pulls matching events from all four platforms in one run.
Why does this return "N/A" instead of leaving fields blank?
So every output record is safe to import directly into a spreadsheet or database without conditional null handling.
Can I call this from a language other than Python or JavaScript?
Yes, it's a standard REST API. Any language that can make an HTTP POST request can start a run and fetch results.
Getting Started
- Go to the Smart Event Scraper on Apify apify.com/techforce.global/smart-event-scraper
- Click 'Try for Free' : no credit card required
- Set category, location, and date range, or call the API directly using either code example above
- Click Run : first results in 1-5 minutes
Actor: https://apify.com/techforce.global/smart-event-scraper
Consultation: calendly.com/techforce-infotech-pvt-ltd/intro-meeting
Website: techforceglobal.com
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