We extract flight schedules, fare classes, vacation packages, and route availability from airtransat.com. 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 Schedules objects from airtransat.com. All fields typed and schema-versioned.
"flight_number": "TS123", "origin_iata": "YUL", "destination_iata": "CDG", "duration_minutes": 420, "aircraft_model": "Airbus A330", "stops": 0, "operated_by": "Air Transat"
| # | flight_number | origin_iata | destination_iata | departure_time_utc | arrival_time_utc | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Fare Classes objects from airtransat.com. All fields typed and schema-versioned.
"flight_number": "TS123", "fare_class": "Eco Standard", "total_price": 542.5, "currency": "CAD", "baggage_pieces": 1, "cancellation_fee": 50.0
| # | flight_number | departure_date | fare_class | base_fare | tax_amount | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Vacation Packages objects from airtransat.com. All fields typed and schema-versioned.
"package_id": "PKG-8492", "resort_name": "Majestic Elegance", "destination_city": "Punta Cana", "star_rating": 4.5, "duration_nights": 7, "price_per_person": 1249.0
| # | package_id | resort_name | destination_city | star_rating | duration_nights | departure_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Intelligence objects from airtransat.com. All fields typed and schema-versioned.
"origin_airport": "YYZ", "destination_airport": "LGW", "is_direct": true, "weekly_frequency": 5, "distance_km": 5700, "average_delay_mins": 14
| # | origin_airport | destination_airport | operating_days | seasonality_start | seasonality_end | is_direct |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Ancillary Fees objects from airtransat.com. All fields typed and schema-versioned.
"flight_number": "TS123", "fee_type": "Seat Selection", "amount": 25.0, "currency": "CAD", "is_mandatory": false, "booking_window_start": "T-24h"
| # | flight_number | route | fee_type | fee_description | amount | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Our Air Transat scraper handles every layer of the booking platform: flight search forms, dynamic pricing grids, vacation packages, and ancillary fees - with session management and anti-bot circumvention built in.
Extract departure times, aircraft types, layovers, and operating carrier details for all transatlantic and sun destinations.
Capture real-time pricing across Eco Budget, Eco Standard, Eco Flex, and Club Class tiers. Timestamped per crawl.
Extract combined flight and hotel deals, resort ratings, meal plans, and room categories for all leisure destinations.
Extract pricing in CAD, USD, EUR, or GBP directly from the booking engine to match your regional requirements.
Scrape seat selection costs, checked baggage fees, and onboard meal pricing associated with specific fare classes.
Navigate complex multi-step search forms while maintaining valid booking sessions to extract accurate final pricing.
Bypass airline rate limits and bot challenges using residential proxies and realistic browser fingerprinting.
Run bulk route exports daily or configure continuous pipelines for high-frequency price monitoring.
Track seasonal route launches, operating days, and frequency adjustments across the entire Air Transat network.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, or vacation package criteria. We design the extraction schema together.
We configure Playwright crawlers, proxy rotation, session management, and form traversal for airtransat.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines invest heavily in scraping detection to protect their pricing engines. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Airlines block data centre IPs immediately. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management - trained on real user behaviour patterns.
Air Transat's booking engine relies on complex JavaScript execution. We run full Playwright browser sessions to trigger search forms, handle lazy-loading, and hydrate dynamic price grids.
Extracting accurate taxes and ancillary fees requires progressing through multiple steps of the booking funnel. Our system maintains session state and cookies to reach final pricing pages without triggering timeouts.
Airline websites update their layouts frequently. Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and text-pattern matching - so a layout change does not break your data pipeline.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops - and respond before you notice.
Online travel agencies ingest direct pricing to ensure parity and supplement their GDS feeds with accurate ancillary fees.
Rival airlines monitor Air Transat's transatlantic and leisure route pricing to adjust their own revenue management models.
Aviation analysts track seasonal capacity, flight frequencies, and new destination launches across the network.
Revenue management teams correlate base fares, seat availability, and booking curves to optimise their own pricing strategies.
Tourism boards and hospitality groups analyse vacation package pricing to forecast seasonal demand for specific resort destinations.
Industry analysts extract baggage fees, seat selection costs, and upgrade pricing to benchmark ancillary revenue strategies.
"Air Transat operates dynamic pricing across thousands of transatlantic and leisure routes. Capturing this requires rigorous session management, not simple HTTP GET requests."
Airlines deploy aggressive rate-limiting and session validation to protect their pricing engines. DataFlirt manages the residential proxies, browser fingerprinting, and search-form traversal required to extract Air Transat fares at scale. Your engineers get clean data, not blocked IPs.
Everything supported by our airtransat.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, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across CA/US/EU regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 airtransat.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight and pricing information is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal passenger data, frequent flyer profiles, or violate privacy regulations. Clients should review airline terms of service and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for rate limits in real time and trigger pool rotation automatically.
Yes. We extract full vacation package details including resort names, star ratings, meal plans, room categories, and combined flight-hotel pricing for specific departure dates.
High-priority routes can be monitored at hourly intervals for dynamic pricing changes. Full network scans are typically executed on a daily cadence. Delivery schedules are configured based on your requirements.
Yes. We extract the full pricing matrix including Eco Budget, Eco Standard, Eco Flex, and Club Class, along with the specific baggage allowances and cancellation policies tied to each fare.
Our minimum engagement typically starts with a defined list of origin-destination pairs or vacation routes monitored daily. We price based on query volume and delivery frequency. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need continuous fare tracking or a full route network export, we scope, build, and operate the pipeline. Tell us what you need.
