We extract flight schedules, dynamic pricing, train availability, bus routes, and hotel listings from Ixigo. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Flight Data objects from ixigo.com. All fields typed and schema-versioned.
"origin_code": "DEL", "destination_code": "BOM", "airline": "IndiGo", "flight_number": "6E-2021", "price_inr": 5430.0, "stops": 0, "baggage_allowance_kg": 15, "scrape_timestamp": "2026-05-12T09:14:00Z"
| # | origin_code | destination_code | airline | flight_number | departure_time | arrival_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Train Schedules objects from ixigo.com. All fields typed and schema-versioned.
"train_number": "12952", "train_name": "MMCT TEJAS RAJ", "origin_station": "NDLS", "dest_station": "MMCT", "classes_available": "['1A', '2A', '3A']", "ticket_fare_inr": 2855.0, "availability_status": "WL12", "waitlist_probability": "High"
| # | train_name | train_number | origin_station | dest_station | departure_time | arrival_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Bus Routes objects from ixigo.com. All fields typed and schema-versioned.
"operator_name": "IntrCity SmartBus", "bus_type": "A/C Sleeper (2+1)", "origin_city": "Bangalore", "dest_city": "Hyderabad", "price_inr": 1250.0, "seats_available": 14, "user_rating": 4.6, "duration_hours": 9.5
| # | operator_name | bus_type | origin_city | dest_city | departure_time | arrival_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hotel Listings objects from ixigo.com. All fields typed and schema-versioned.
"hotel_id": "HTL-98231", "hotel_name": "Taj Mahal Tower", "location": "Colaba, Mumbai", "star_rating": 5, "user_rating": 4.8, "price_per_night": 18500.0, "room_type": "Superior City View", "cancellation_policy": "Free cancellation before 24 hrs"
| # | hotel_id | hotel_name | location | star_rating | user_rating | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fare Prediction objects from ixigo.com. All fields typed and schema-versioned.
"route_id": "DEL-BLR", "travel_date": "2026-06-15", "current_fare": 6200.0, "predicted_fare_trend": "increasing", "confidence_score": 88, "ixigo_advice": "Book Now", "historical_avg_fare": 5800.0
| # | route_id | travel_date | current_fare | predicted_fare_trend | confidence_score | historical_avg_fare |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Ixigo scraper handles dynamic pricing grids, AJAX-heavy search results, and complex route combinations. We manage the proxy rotation and session states so you get clean, normalised data.
Track dynamic pricing across domestic and international routes with multi-hop itineraries.
Extract seat availability across 1A, 2A, 3A, and Sleeper classes for IRCTC routes.
Scrape schedules, boarding points, and seat availability across private and state bus operators.
Capture nightly rates, room types, amenities, and user ratings for domestic accommodations.
Extract Ixigo's proprietary fare prediction advice and historical price trend indicators.
Parse structured penalty tiers, refund timelines, and free-cancellation windows per booking.
Execute complex search queries mapping multi-city flight itineraries and layover durations.
Extract cabin baggage limits, check-in allowances, and meal inclusion flags per fare class.
Run continuous pipelines at 15-minute intervals for high-volatility routes or daily bulk exports.
Standardise airport codes, station codes, and currency formats across all extracted records.
Brief in. Clean data out.
Provide origin-destination pairs, travel dates, or hotel IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for ixigo.com.
Schema validation, null-rate checks, price-outlier detection, and sample payloads before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Flight and train aggregators aggressively throttle repetitive searches. Here is how we maintain high-throughput extraction while avoiding IP bans.
Aggregators block data centre IPs immediately. We route requests through residential ISP proxies with realistic browser fingerprints and randomised request timing.
Ixigo loads search results dynamically via XHR. We execute full browser sessions to wait for DOM hydration and capture complete pricing grids.
Travel searches require valid session tokens and search IDs. Our middleware maintains valid session states across paginated results.
We map multiple XPath and CSS selectors for critical fields like fare and availability, preventing pipeline failures when DOM structures change.
Every run emits structured logs. We alert on null-rate spikes, fare outliers, and coverage drops, ensuring SLA compliance.
Online travel agencies monitor flight and bus fares to adjust their own markup and discount strategies in real time.
Airlines and bus operators track aggregator pricing to optimise revenue management systems and inventory allocation.
Procurement teams audit booked fares against market rates to ensure travel policy compliance and identify savings.
Analysts correlate search volume proxies and seat availability drops to predict regional travel demand.
Transport operators analyse underserved routes and high-fare corridors to plan new bus or flight schedules.
Private equity firms track OTA inventory size, pricing parity, and operator partnerships to evaluate market position.
"Aggregated travel data is highly volatile. Fares change every minute, and capturing this pricing history requires infrastructure that can absorb aggressive rate limiting."
Most internal data teams fail at travel scraping because they rely on static IP pools and basic HTTP clients. Extracting accurate pricing from Ixigo requires residential proxies, JavaScript rendering for dynamic grids, and sophisticated session management. DataFlirt handles the extraction layer so your analysts can focus on pricing models, not proxy bans.
Everything supported by our ixigo.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 and retry logic. Playwright handles JavaScript rendering and session flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required for complex search flows. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About ixigo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available travel data, such as flight schedules and bus routes, is generally permissible. DataFlirt extracts only public, non-authenticated pricing and availability data. We do not bypass login walls or extract PII. Clients should consult legal counsel for their specific use cases.
We use residential ISP proxies, full Playwright browser sessions, and request timing modelled on human behaviour. Our infrastructure distributes searches across thousands of IPs to avoid triggering aggregator bot defences.
Yes. We scrape the train schedules, class-wise seat availability, and pricing directly from the search result grids displayed on Ixigo.
For high-priority routes, we can configure pipelines to poll pricing at 15-minute intervals. Standard bulk extractions typically run on daily or hourly cadences depending on your budget and requirements.
Yes. Our schema includes structural fields for cabin baggage limits, check-in allowances, and tiered cancellation penalty windows.
Yes. We extract comprehensive bus data including operator names, bus types, boarding/dropping points, and seat availability across all supported routes.
Our smallest packages start at a defined list of origin-destination pairs or hotel IDs with daily delivery. We price based on search volume and extraction frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily hotel pricing dumps or 15-minute flight fare tracking across thousands of routes - we scope, build, and operate the pipeline. Tell us what you need.
