We extract event listings, ticket availability, pricing tiers, venue coordinates, and organiser profiles from Townscript. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Event Details objects from townscript.com. All fields typed and schema-versioned.
"event_id": "bengaluru-tech-summit-2026", "title": "Bengaluru Tech Summit 2026", "category": "Technology", "format": "Offline", "start_date": "2026-11-15T09:00:00+05:30", "end_date": "2026-11-17T18:00:00+05:30", "timezone": "Asia/Kolkata"
| # | event_id | url | title | description | category | format |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ticket Tiers objects from townscript.com. All fields typed and schema-versioned.
"event_id": "bengaluru-tech-summit-2026", "tier_name": "Early Bird Delegate", "price": 4999.0, "currency": "INR", "availability_status": "Available", "max_purchase": 10, "sales_end_date": "2026-10-01T23:59:59+05:30"
| # | event_id | tier_name | price | currency | availability_status | min_purchase |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Venue & Location objects from townscript.com. All fields typed and schema-versioned.
"event_id": "bengaluru-tech-summit-2026", "venue_name": "Bangalore Palace Grounds", "address": "Bellary Rd, Vasanth Nagar", "city": "Bengaluru", "state": "Karnataka", "pincode": "560052", "latitude": 12.9982, "longitude": 77.5921
| # | event_id | venue_name | address | city | state | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Organiser Profile objects from townscript.com. All fields typed and schema-versioned.
"organiser_id": "karnataka-digital-economy-mission", "name": "KDEM", "total_events": 24, "followers": 15420, "website": "https://kdem.in", "contact_email": "events@kdem.in"
| # | organiser_id | name | profile_url | description | total_events | followers |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search & Discovery objects from townscript.com. All fields typed and schema-versioned.
"keyword": "marathon", "city_filter": "Pune", "position": 1, "event_id": "pune-international-marathon-2026", "title": "Pune International Marathon", "price_range": "INR 999 - 2499", "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | city_filter | category_filter | position | event_id | title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Townscript scraper handles every layer of the platform: event discovery, dynamic ticket pricing, venue details, and organiser intelligence, with JavaScript rendering and anti-bot circumvention built in.
Title, description, dates, times, and categories extracted accurately for every listed event.
Capture early bird, regular, VIP, and dynamic pricing tiers along with currency and purchase limits.
Extract venue names, full addresses, city mapping, and precise latitude and longitude data.
Profile data, historical event counts, follower metrics, and contact details for event hosts.
Iterate through marathons, workshops, and comedy shows across specific Indian cities systematically.
Monitor ticket depletion, sales end dates, and sold-out flags to gauge event popularity.
Extract local event data from Mumbai, Bengaluru, Delhi, Pune, and tier-2 cities simultaneously.
Extract complex multi-day event itineraries, speaker lists, and session timings.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide city lists, categories, or organiser URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for townscript.com.
Schema validation, null-rate checks, date-parsing accuracy, and sample events before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Event platforms deploy rate limiting and geo-blocking to protect ticketing inventory. Here is how our infrastructure maintains stable extraction.
Ticketing platforms monitor request velocity and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing, trained on real user behaviour patterns.
Townscript relies on client-side rendering for ticket widgets and dynamic availability. We run full Playwright browser sessions with JavaScript execution to capture data that headless HTTP clients miss entirely.
DOM structures change without warning. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and structured data extraction, ensuring layout changes do not break your data pipeline.
For continuous monitoring, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, date-parsing errors, and coverage drops, responding immediately to maintain data integrity.
Populate local event discovery applications with accurate schedules, pricing, and ticketing links.
Rival ticketing platforms track organiser defection, event volume, and market share across regions.
Hospitality and transport sectors predict local footfall and surge pricing based on event scale and venue locations.
Brands identify large-scale marathons, tech conferences, and cultural festivals for targeted sponsorship opportunities.
Analyse ticket price elasticity across different event categories and cities to optimise future event pricing.
Track the recovery and growth of offline events post-pandemic across tier-1 and tier-2 Indian cities.
"Townscript hosts the most comprehensive catalogue of grassroots and mid-tier events in India, but accessing that schedule programmatically requires dedicated extraction infrastructure."
Most teams underestimate the investment required: reliable event scraping requires handling complex date-time normalisation, dynamic ticket widgets, and aggressive rate limiting. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our townscript.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering and interaction flows for complex event pages.
We maintain pools of residential ISP proxies across Indian regions. Rotation happens per-request with sticky sessions where required to bypass rate limits.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About townscript.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Townscript is generally permissible under applicable law. DataFlirt targets only public, non-authenticated event, pricing, and venue data. We do not extract personal attendee data or violate GDPR guidelines. Clients should review Townscript's terms of service.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for rate limit spikes in real time and trigger pool rotation automatically.
Yes. We can configure the pipeline to target specific cities, filtering by categories like marathons, tech events, or workshops to ensure you only receive relevant data.
Pipelines can be configured to run daily or multiple times a day depending on your requirements, ensuring you have accurate visibility into sold-out statuses and pricing tier changes.
Yes. Event dates and times are parsed and converted into standardised ISO 8601 formats, complete with accurate timezone information to simplify downstream database insertion.
Our minimum engagements typically start with a defined city or category list delivered on a weekly schedule. We price based on data volume and extraction frequency. Contact us for a scoped quote.
Absolutely. We provide a sample run of up to 100 events as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off dump of tech conferences or a continuous feed of marathon registrations, we scope, build, and operate the pipeline. Tell us what you need.
