We extract flight schedules, dynamic pricing, fare tiers (Basic, Optima, Family, TimeFlex), and route networks from Vueling. 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 vueling.com. All fields typed and schema-versioned.
"flight_number": "VY8982", "origin_iata": "BCN", "destination_iata": "LHR", "departure_time": "2026-11-14T08:30:00Z", "arrival_time": "2026-11-14T10:05:00Z", "duration_minutes": 155, "aircraft_type": "A320", "operating_carrier": "Vueling Airlines"
| # | flight_number | origin_iata | destination_iata | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from vueling.com. All fields typed and schema-versioned.
"flight_date": "2026-11-14", "flight_number": "VY8982", "basic_fare": 45.99, "optima_fare": 85.99, "timeflex_fare": 115.99, "currency": "EUR", "price_timestamp": "2026-10-01T14:22:11Z"
| # | flight_date | flight_number | basic_fare | optima_fare | family_fare | timeflex_fare |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Route Network objects from vueling.com. All fields typed and schema-versioned.
"origin_airport": "BCN", "origin_city": "Barcelona", "destination_airport": "LHR", "destination_city": "London", "direct_flight": true, "frequency_per_week": 28, "route_active": true
| # | origin_airport | origin_city | destination_airport | destination_city | distance_km | direct_flight |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Ancillary Fees objects from vueling.com. All fields typed and schema-versioned.
"flight_number": "VY8982", "cabin_bag_fee": 24.5, "checked_bag_15kg_fee": 35.0, "checked_bag_20kg_fee": 42.0, "seat_selection_min": 6.0, "seat_selection_max": 22.0, "priority_boarding_fee": 18.0
| # | flight_number | cabin_bag_fee | checked_bag_15kg_fee | checked_bag_20kg_fee | checked_bag_25kg_fee | seat_selection_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Airport Info objects from vueling.com. All fields typed and schema-versioned.
"airport_code": "BCN", "airport_name": "Josep Tarradellas Barcelona-El Prat", "terminal": "T1", "gate_closure_minutes": 20, "lounge_available": true, "country_code": "ES", "timezone": "Europe/Madrid"
| # | airport_code | airport_name | terminal | check_in_desk | gate_closure_minutes | lounge_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Vueling scraper handles every layer of the booking engine: flight schedules, dynamic pricing grids, ancillary fees, and route availability. Built with JavaScript rendering, session management, and anti-bot circumvention.
Flight numbers, departure times, arrival times, aircraft types, and operating carriers scraped across all active Vueling routes.
Capture pricing across all fare tiers: Basic, Optima, Family, and TimeFlex. Timestamped per crawl to track yield management changes.
Extract dynamic baggage fees, seat selection costs, priority boarding, and fast track pricing tied to specific flight segments.
Extract fares in EUR, GBP, USD, or any supported local currency to match your internal normalisation requirements.
Track active routes, seasonal suspensions, and frequency changes across Vueling's entire European and North African network.
Capture 'only X seats left at this price' warnings to model flight load factors and booking velocity.
Extract the Vueling Club Avios required for reward flights and the associated cash component for taxes and fees.
Identify flights operated by partner airlines like Iberia or British Airways sold through the Vueling portal.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, or full network requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for vueling.com.
Schema validation, null-rate checks, price-outlier detection, and sample schedules before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airline booking engines invest heavily in scraping detection. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
Airlines use strict WAF and bot mitigation platforms. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management trained on real user behaviour patterns.
Flight searches require complex token exchange and stateful POST requests. We manage the entire session lifecycle, ensuring search tokens remain valid across paginated date grids and fare selection steps.
Vueling's booking flow relies heavily on client-side rendering. We run full Playwright browser sessions with JavaScript execution, lazy-load triggering, and dynamic price widget hydration.
For large route networks, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost, storage bloat, and downstream processing load. You get a clean changelog rather than full re-dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops. SLA uptime is contractual, not aspirational.
Online Travel Agencies integrate direct Vueling pricing feeds to offer comprehensive flight options without relying on expensive GDS fees.
Rival airlines monitor Vueling's fare adjustments on competing routes to optimise their own yield management systems.
Revenue managers analyse Vueling's pricing curves across booking windows to understand market demand and pricing elasticity.
Aviation analysts track flight frequencies, seasonal changes, and estimated load factors to evaluate route performance.
Consumer travel applications use schedule and pricing data to power multi-modal journey planners and price prediction alerts.
Economists and researchers use historical fare data to study inflation, travel trends, and consumer behaviour in the European aviation market.
"Vueling operates one of Europe's densest low-cost carrier networks. Tracking their dynamic pricing at scale requires reverse-engineering complex booking flows, not just scraping static HTML."
Scraping airline booking engines involves stateful sessions, token exchange, and aggressive anti-bot mitigation. DataFlirt manages the proxy rotation, JavaScript execution, and calendar-grid parsing so your engineering team can consume clean, normalised fare data directly from your warehouse.
Everything supported by our vueling.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 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 vueling.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible under applicable law. DataFlirt targets only public, non-authenticated route and fare data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review Vueling 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. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline. We monitor for WAF blocks in real time and trigger pool rotation automatically.
Real-time streaming pipelines achieve sub-30-minute latency for price and availability signals on a defined route set. Full network refreshes at daily cadence complete within a 4-8 hour window depending on size.
We support extraction across Vueling's entire active network, including all domestic Spanish routes, European short-haul, and North African destinations.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per flight number and date for all fare tiers from the date your pipeline starts.
Our smallest packages start at a defined route list (typically 50-500 origin-destination pairs) with daily delivery. For full network extraction, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route schedule dump or a continuous price-monitoring feed across 4,000 routes, we scope, build, and operate the pipeline. Tell us what you need.
