We extract flight schedules, dynamic pricing signals, vacation package details, and hotel inventory from Transat. 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 Routes objects from transat.com. All fields typed and schema-versioned.
"origin_iata": "YUL", "destination_iata": "CDG", "flight_number": "TS110", "departure_time": "2026-06-15T20:00:00Z", "arrival_time": "2026-06-16T08:45:00Z", "duration_minutes": 405, "aircraft_type": "Airbus A330", "stops": 0
| # | origin_iata | destination_iata | flight_number | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Flight Pricing objects from transat.com. All fields typed and schema-versioned.
"flight_number": "TS110", "departure_date": "2026-06-15", "class_eco_standard": 845.0, "class_eco_flex": 995.0, "class_club": 1850.0, "currency": "CAD", "taxes_included": true, "price_timestamp": "2026-05-12T10:14:00Z"
| # | flight_number | departure_date | return_date | class_eco_standard | class_eco_flex | class_club |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Vacation Packages objects from transat.com. All fields typed and schema-versioned.
"package_id": "PKG-CUN-7D", "package_name": "Cancun All-Inclusive Escape", "destination": "Cancun, Mexico", "hotel_name": "Moon Palace Cancun", "star_rating": 4.5, "duration_days": 7, "price_per_person": 1250.0, "board_basis": "All Inclusive"
| # | package_id | package_name | destination | hotel_name | star_rating | duration_days |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hotel Details objects from transat.com. All fields typed and schema-versioned.
"hotel_id": "HTL-MOON-CUN", "name": "Moon Palace Cancun", "location": "Riviera Maya", "star_rating": 4.5, "user_rating": 4.2, "review_count": 3412, "beach_access": true, "family_friendly": true
| # | hotel_id | name | location | star_rating | amenities | room_types |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Deals & Promos objects from transat.com. All fields typed and schema-versioned.
"promo_id": "PROMO-SOUTH-26", "title": "South Sun Sale", "destination_region": "Caribbean", "discount_amount": 200.0, "discount_type": "absolute", "valid_to": "2026-05-31", "scraped_at": "2026-05-12T10:15:33Z"
| # | promo_id | title | destination_region | discount_amount | discount_type | valid_from |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Transat scraper handles every layer of the platform: flight schedules, dynamic pricing grids, vacation packages, and hotel inventory, with session management and anti-bot circumvention built in.
Origin, destination, departure times, arrival times, aircraft type, and stopover details extracted across all active Transat routes.
Capture pricing for Eco Standard, Eco Flex, and Club classes. Timestamped per crawl to track yield adjustments.
Extract bundled hotel and flight packages, including board basis, room types, and per-person pricing for southern and European destinations.
Extract hotel names, star ratings, amenities, user review scores, and location metadata for properties listed on Transat.
Parameterise extraction runs to capture pricing in CAD, USD, EUR, or GBP depending on your target market requirements.
Handle complex stateful search flows, managing search tokens and cookies required to access deep pricing grids.
Bypass rate limits and bot protection using residential proxy rotation and realistic browser fingerprinting.
Track sold out statuses and limited seat warnings to gauge demand velocity on specific departure dates.
Run one-off bulk exports or configure continuous pipelines at daily or hourly cadences with change-detection diffing.
Brief in. Clean data out.
Provide origin-destination pairs, departure date ranges, or package destinations. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for transat.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines invest heavily in scraping detection and dynamic caching. Here is how we stay resilient, and why teams choose managed infrastructure over DIY.
Transat flight and package searches require sequential HTTP requests that pass specific session tokens. Our crawlers maintain stateful cookie jars and handle token hydration automatically to access deep pricing grids.
Flight pricing and availability are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering, capturing data that headless HTTP clients miss entirely.
Airlines use strict rate limiting and IP reputation scoring. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing, trained on real user behaviour patterns.
Transat updates its booking engine structure frequently. Our selector strategy uses multiple fallback chains per field, so a layout change does not break your data pipeline overnight.
For large route catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Online travel agencies monitor pricing and package bundles to ensure competitive parity and adjust their own margins.
Competing airlines track Transat yield adjustments on transatlantic and southern routes to optimise their own pricing models.
Analysts track route expansion, frequency changes, and destination focus to identify market trends and investment opportunities.
Meta-search engines ingest scheduled pricing data to provide comprehensive price comparison features for users.
B2B travel platforms monitor vacation package inventory and all-inclusive deals to alert agents to high-value booking opportunities.
Revenue teams correlate seat availability warnings and price escalations with seasonal demand to improve forecasting models.
"Transat holds critical inventory data for transatlantic and southern leisure routes, but tracking yield changes requires a highly concurrent, session-aware extraction pipeline."
Most engineering teams underestimate the complexity of travel data extraction. Reliable Transat scraping requires stateful session management, residential proxies, full JavaScript rendering for dynamic pricing grids, and strict anomaly monitoring. DataFlirt absorbs that infrastructure burden so your analysts can focus on yield optimisation and market intelligence.
Everything supported by our transat.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 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 transat.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Transat is generally permissible. DataFlirt targets only public, non-authenticated schedule, pricing, and package data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review applicable ToS 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 limit spikes in real time and trigger pool rotation automatically.
Yes. Every pipeline run produces timestamped snapshots. We can run daily or hourly diffs to track price fluctuations for specific vacation packages.
Yes. We can parameterise the extraction pipeline to request pricing in CAD, USD, EUR, or GBP based on the point of sale you need to monitor.
Our smallest packages start at a defined route list or destination set with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 50 routes or packages as part of the pre-engagement scoping process, so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off schedule dump or a continuous price-monitoring feed across thousands of routes, we scope, build, and operate the pipeline. Tell us what you need.
