We extract flight schedules, dynamic fares, hotel inventory, and bus routes from Cleartrip. 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 Itineraries objects from cleartrip.com. All fields typed and schema-versioned.
"flight_id": "6E-2054-DEL-BOM", "airline": "IndiGo", "flight_number": "6E-2054", "origin": "DEL", "destination": "BOM", "departure_time": "2026-08-14T06:30:00Z", "duration_minutes": 135, "layover_count": 0
| # | flight_id | airline | flight_number | origin | destination | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight Pricing objects from cleartrip.com. All fields typed and schema-versioned.
"flight_id": "6E-2054-DEL-BOM", "total_fare": 5490.0, "taxes": 750.0, "currency": "INR", "ct_flex_price": 5990.0, "ezcancel_fee": 399.0, "baggage_allowance_kg": 15, "scraped_at": "2026-07-01T10:15:22Z"
| # | flight_id | base_fare | taxes | total_fare | currency | ct_flex_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hotel Listings objects from cleartrip.com. All fields typed and schema-versioned.
"hotel_id": "HTL-99214", "name": "Taj Mahal Tower", "star_rating": 5, "city": "Mumbai", "review_score": 4.8, "review_count": 4129, "property_type": "Hotel", "check_in_time": "14:00"
| # | hotel_id | name | star_rating | location | city | review_score |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Room Rates objects from cleartrip.com. All fields typed and schema-versioned.
"hotel_id": "HTL-99214", "room_type": "Superior Sea View", "board_basis": "Breakfast Included", "price_per_night": 18500.0, "currency": "INR", "refundable": false, "max_occupancy": 2, "scraped_at": "2026-07-01T10:18:45Z"
| # | hotel_id | room_type | board_basis | price_per_night | taxes | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Bus Routes objects from cleartrip.com. All fields typed and schema-versioned.
"bus_id": "BUS-VRL-441", "operator": "VRL Travels", "route_origin": "Bangalore", "route_destination": "Goa", "departure_time": "2026-08-14T21:30:00+05:30", "bus_type": "Volvo Multi-Axle A/C", "seat_type": "Sleeper", "price": 1450.0
| # | bus_id | operator | route_origin | route_destination | departure_time | arrival_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Cleartrip scraper navigates complex search forms, dynamic pricing logic, and strict session limits to extract structured travel inventory at scale.
Capture flight numbers, airlines, departure times, arrival times, durations, and layover details across domestic and international routes.
Track base fares, taxes, total prices, and currency variations in real time to monitor yield management strategies.
Extract proprietary Cleartrip add-on pricing, including CT Flex, CT FlexMax, and EzCancel fees per itinerary.
Scrape hotel names, star ratings, review scores, locations, and property amenities across thousands of destinations.
Capture room types, board basis, nightly rates, tax structures, and cancellation policies for specific check-in dates.
Extract bus schedules, operators, seat types, boarding points, and dropping points for intercity travel.
Map complex multi-city itineraries including transit airports, layover durations, and terminal changes.
Extract cabin baggage limits, check-in baggage allowances, and specific fare rules associated with each ticket tier.
Run pipelines at sub-hourly cadences to capture intra-day fare volatility and seat availability changes.
Brief in. Clean data out.
Provide origin-destination pairs, travel dates, or hotel locations. We design the extraction schema together.
We configure Playwright crawlers, proxy rotation, session management, and payload parsing for cleartrip.com.
Schema validation, null-rate checks, price-outlier detection, and route coverage verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators heavily protect their inventory data. Here is how we maintain stable extraction pipelines despite aggressive bot mitigation.
Cleartrip flight searches generate temporary session tokens that expire rapidly. Our pipeline manages these stateful search sessions, ensuring subsequent price checks and availability requests use valid tokens without triggering security blocks.
Travel sites aggressively rate-limit datacenter IPs. We route all requests through ISP-grade residential proxies in India and global regions, rotating IPs per session while maintaining consistent TLS and browser fingerprints.
Cleartrip relies heavily on Single Page Application architecture. We intercept backend XHR/Fetch API responses directly where possible, or use Playwright to render the DOM and extract nested flight and hotel data structures.
Extracting accurate pricing requires navigating multi-step search parameters including passenger counts, cabin classes, and date ranges. Our crawlers programmatically execute these flows to reach the final pricing pages.
Travel aggregators frequently update their frontend code. We monitor schema integrity continuously, alerting our engineering team the moment a DOM change affects data completeness.
Online Travel Agencies monitor Cleartrip to ensure their own flight and hotel pricing remains competitive across key routes.
Airlines track competitor fares, discount strategies, and availability on Cleartrip to optimise their own dynamic pricing models.
Revenue managers at hotel chains track their property rankings, room rates, and competitor pricing on Cleartrip's platform.
Meta-search engines ingest Cleartrip pricing data to provide comprehensive fare comparisons to end consumers.
Analysts track flight frequency, route additions, and hotel inventory growth to evaluate Cleartrip's market position.
Enterprises audit historical fare data to negotiate better corporate rates and verify travel agency billing accuracy.
"Cleartrip processes millions of dynamic fare changes daily. Capturing this volatility requires infrastructure built specifically for high-frequency travel data."
Extracting travel inventory involves navigating complex multi-step search forms, strict session timeouts, and aggressive IP rate-limiting. DataFlirt handles the proxy rotation, JavaScript execution, and payload parsing required to convert Cleartrip's proprietary DOM into structured, queryable warehouse records.
Everything supported by our cleartrip.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 concurrency and scheduling while Playwright executes the JavaScript required to load Cleartrip's dynamic search results.
We route traffic through Indian and global residential proxy pools, managing session stickiness to complete multi-step search requests.
Pipelines execute on AWS ECS with Airflow managing route scheduling, ensuring high-frequency price polling meets SLA requirements.
Data delivered to where your team already works — no new tooling required.
About cleartrip.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight, hotel, and bus data from Cleartrip is generally permissible under applicable law. DataFlirt extracts only public inventory and pricing data. We do not bypass authentication walls to access private user accounts or corporate rates. Clients should review their specific use case with legal counsel.
We utilise ISP-grade residential proxies, manage strict session tokens, and employ Playwright to mimic legitimate browser behaviour. Our infrastructure automatically detects rate limits and rotates IPs to maintain pipeline stability.
Yes. Our pipeline extracts the base fare along with Cleartrip's proprietary add-on pricing, including CT Flex, CT FlexMax, and EzCancel fees, providing a complete view of the booking cost.
For high-priority routes, we can configure pipelines to poll pricing at sub-hourly intervals. Full catalogue sweeps of thousands of routes typically complete within a 12-hour window.
Yes. We capture bus operators, departure times, seat types, boarding points, and pricing across Cleartrip's entire domestic bus inventory.
Our minimum engagement starts with a defined list of origin-destination pairs or hotel locations, typically polled daily. Pricing scales based on the frequency of extraction and the volume of routes.
Yes. We provide a sample extraction of up to 100 flight routes or hotel listings during the scoping phase, allowing your engineering team to validate the schema before deployment.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily hotel rate tracking or high-frequency flight fare monitoring, we scope, build, and operate the pipeline. Tell us what you need.
