We extract flight schedules, dynamic pricing across Basic, Plus, and Max fare tiers, route maps, and seat availability from Transavia. 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 transavia.com. All fields typed and schema-versioned.
"flight_number": "HV5671", "origin_iata": "AMS", "destination_iata": "ALC", "departure_time_utc": "2026-08-14T06:00:00Z", "arrival_time_utc": "2026-08-14T08:40:00Z", "duration_minutes": 160, "aircraft_type": "Boeing 737-800", "operating_airline": "Transavia Airlines"
| # | flight_number | origin_iata | destination_iata | departure_time_utc | arrival_time_utc | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from transavia.com. All fields typed and schema-versioned.
"flight_number": "HV5671", "departure_date": "2026-08-14", "currency": "EUR", "basic_fare": 89.0, "plus_fare": 124.0, "max_fare": 169.0, "taxes_included": true, "lowest_price_available": 89.0
| # | flight_number | departure_date | currency | basic_fare | plus_fare | max_fare |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from transavia.com. All fields typed and schema-versioned.
"origin_airport": "Amsterdam Schiphol", "origin_code": "AMS", "destination_airport": "Alicante", "destination_code": "ALC", "country_destination": "Spain", "direct_flight": true, "frequency_per_week": 14, "route_active": true
| # | origin_airport | origin_code | destination_airport | destination_code | country_destination | direct_flight |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary Services objects from transavia.com. All fields typed and schema-versioned.
"flight_number": "HV5671", "cabin_bag_fee": 15.0, "hold_bag_15kg_fee": 26.0, "hold_bag_20kg_fee": 31.0, "seat_selection_min": 6.0, "seat_selection_max": 18.0, "fast_track_fee": 5.0, "currency": "EUR"
| # | flight_number | cabin_bag_fee | hold_bag_15kg_fee | hold_bag_20kg_fee | hold_bag_25kg_fee | seat_selection_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Availability Signals objects from transavia.com. All fields typed and schema-versioned.
"flight_number": "HV5671", "departure_date": "2026-08-14", "seats_remaining_warning": 4, "basic_available": true, "plus_available": true, "max_available": true, "sold_out": false, "scraped_at": "2026-05-12T10:15:22Z"
| # | flight_number | departure_date | seats_remaining_warning | basic_available | plus_available | max_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Transavia scraper navigates complex flight search flows, manages session state for accurate pricing, and bypasses airline anti-bot systems to deliver structured aviation data.
Extract timetables, flight numbers, operating carriers, and aircraft types across the entire Transavia network.
Capture pricing for Basic, Plus, and Max fare classes simultaneously to analyse upsell strategies.
Track time-stamped price fluctuations based on booking curves, departure proximity, and demand signals.
Map origin-destination pairs, seasonal route changes, and frequency adjustments across European hubs.
Extract hidden costs like cabin baggage fees, hold luggage tiers, seat selection, and fast-track boarding.
Execute one-way, round-trip, and multi-passenger search flows to capture accurate, context-dependent pricing.
Extract fares in EUR, GBP, or other supported currencies directly from the booking engine.
Capture low-stock warnings like 'only 3 seats left at this price' to estimate load factors and demand.
Run daily network-wide sweeps or configure high-frequency monitoring for specific competitive O&D pairs.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and frequency requirements. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and bot mitigation bypass for transavia.com.
Schema validation, null-rate checks, price-outlier detection, and sample route tests before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines deploy aggressive rate limiting and bot mitigation. Here is how we maintain steady extraction without IP bans or session drops.
Airlines use sophisticated edge protection to block automated searches. Our crawlers use European residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to blend in with legitimate passenger traffic.
Flight pricing is highly dependent on session state and search history. We maintain isolated, sticky sessions for each search query to prevent price caching or penalisation, ensuring you receive the exact fare a real user would see.
Transavia's booking engine requires sequential interactions: selecting origins, destinations, calendars, and passenger counts. We use Playwright to automate these complex UI flows, triggering necessary background API calls that static scrapers miss.
Airline booking funnels undergo frequent A/B testing. Our extraction logic relies on a mix of API interception and multi-layered DOM selectors, ensuring that a minor frontend update does not break your pricing feeds.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing fare classes, and coverage drops, responding to issues before they impact your downstream revenue management systems.
Low-cost carriers and full-service airlines track Transavia's fares on overlapping routes to optimise their own pricing algorithms.
Online Travel Agencies integrate direct scraped pricing when official API access is restricted or lacks specific ancillary fee data.
Aviation analysts monitor route frequencies, seasonal additions, and cancellations to assess market demand and network strategy.
Consultancies track base fares versus ancillary costs to understand unbundling strategies in the European low-cost sector.
Revenue management teams ingest historical pricing curves to train machine learning models for demand forecasting.
Travel tech companies monitor flight status changes and schedule adjustments to power passenger re-accommodation tools.
"Transavia's dynamic pricing and route network hold critical signals for European travel demand, but the data is locked behind complex search flows and anti-bot perimeters."
Aviation scraping requires managing session state, solving edge security challenges, and executing precise search queries across thousands of route combinations. DataFlirt absorbs this complexity, delivering clean flight data so your analysts can focus on yield management and market intelligence.
Everything supported by our transavia.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, booking engine interactions, and session state. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across European regions. Rotation happens per-session to ensure consistent pricing without triggering rate limits.
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 transavia.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible for market research and competitive intelligence. DataFlirt extracts only public, non-authenticated information. We do not bypass login walls or scrape PNR passenger data. Clients should review Transavia's terms of service and consult legal counsel for specific commercial use cases.
We use EU-based residential ISP proxies, full Playwright browser sessions with realistic device fingerprints, and human-like request timing. Our infrastructure automatically handles edge security challenges without dropping the search session.
Yes. Our pipeline captures the Basic, Plus, and Max fare tiers simultaneously, along with the specific baggage and seat selection rules associated with each tier on the date of extraction.
For targeted Origin-Destination pairs, we can run high-frequency polling at hourly intervals. Full network sweeps covering all active Transavia routes are typically executed daily during off-peak hours.
We build time-series datasets from the moment your pipeline is commissioned. Every extraction is timestamped, allowing you to plot booking curves and track how fares increase as the departure date approaches.
Our smallest deployments start with a defined list of up to 500 routes tracked daily. For full network extraction or complex multi-passenger search logic, we price based on compute volume and proxy bandwidth required.
Absolutely. We provide a sample run of up to 50 routes as part of the pre-engagement scoping process, allowing your data engineers to validate our schema and pricing accuracy before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily route network map or high-frequency price monitoring for specific O&D pairs, we scope, build, and operate the pipeline. Tell us what you need.
