We extract flight schedules, dynamic pricing, Wizz Discount Club tiers, and ancillary fees from Wizzair. 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 wizzair.com. All fields typed and schema-versioned.
"flight_number": "W6 2201", "origin_iata": "BUD", "destination_iata": "LTN", "departure_time_utc": "2026-08-14T04:10:00Z", "arrival_time_local": "2026-08-14T06:50:00", "duration_mins": 160, "aircraft_type": "Airbus A321neo"
| # | flight_number | origin_iata | destination_iata | departure_time_utc | departure_time_local | arrival_time_utc |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Base Fares objects from wizzair.com. All fields typed and schema-versioned.
"flight_number": "W6 2201", "departure_date": "2026-08-14", "base_fare": 45.99, "tax_amount": 12.5, "total_fare": 58.49, "currency": "EUR", "seats_remaining": 4, "fare_class": "Basic"
| # | flight_number | departure_date | base_fare | tax_amount | total_fare | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Discount Club Pricing objects from wizzair.com. All fields typed and schema-versioned.
"flight_number": "W6 2201", "standard_fare": 58.49, "wdc_fare": 48.49, "discount_amount": 10.0, "discount_pct": 17.1, "currency": "EUR", "wdc_tier": "Standard", "baggage_included": false
| # | flight_number | departure_date | standard_fare | wdc_fare | discount_amount | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary Fees objects from wizzair.com. All fields typed and schema-versioned.
"flight_number": "W6 2201", "priority_boarding_fee": 15.0, "checked_bag_10kg_fee": 22.5, "checked_bag_20kg_fee": 35.0, "seat_selection_min_fee": 4.0, "seat_selection_max_fee": 25.0, "infant_fee": 31.0, "currency": "EUR"
| # | flight_number | priority_boarding_fee | carry_on_bag_fee | checked_bag_10kg_fee | checked_bag_20kg_fee | checked_bag_32kg_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from wizzair.com. All fields typed and schema-versioned.
"origin_iata": "BUD", "destination_iata": "LTN", "frequency_weekly": 21, "first_flight_date": "2024-01-01", "is_seasonal": false, "distance_km": 1450, "average_flight_time_mins": 160, "active_status": true
| # | origin_iata | destination_iata | frequency_weekly | first_flight_date | last_flight_date | is_seasonal |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Wizzair scraper targets the underlying pricing APIs to extract the full spectrum of low-cost carrier revenue streams: base fares, Wizz Discount Club tiers, and dynamic ancillary fees.
Extract origin, destination, flight numbers, departure/arrival times, and aircraft types across the entire Wizzair network.
Capture base fares and total prices, including taxes, across multiple dates to track yield management algorithms.
Extract standard prices alongside Wizz Discount Club (WDC) standard and group tier pricing to map true member costs.
Wizzair's revenue relies on ancillaries. We extract dynamic costs for priority boarding, 10kg/20kg/32kg bags, and seat selection.
Prices vary by point of sale. We route requests through specific residential IPs to capture localised fare differences.
Extract fares in EUR, GBP, HUF, PLN, and other supported currencies directly from the booking engine.
Map all active origin-destination pairs to track network expansion, seasonal route drops, and frequency changes.
Run pipelines at hourly or daily cadences to monitor flash sales and close-in booking price surges.
Bypass HTML parsing by intercepting Wizzair's internal XHR responses for structured, clean JSON data extraction.
Brief in. Clean data out.
Provide origin-destination pairs, departure date ranges, and required currencies. We design the extraction schema.
We configure Playwright crawlers, API interception, residential proxy rotation, and Akamai bypass mechanisms.
Schema validation, null-rate checks, fare outlier detection, and currency normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines deploy aggressive anti-bot systems to protect their pricing APIs. Here is how we maintain reliable extraction from Wizzair.
Wizzair uses advanced bot protection (Akamai) that analyses TLS fingerprints, sensor data, and behavioural biometrics. Our Playwright instances use residential IPs, spoofed browser fingerprints, and hardware-level masking to generate valid telemetry.
Flight searches require valid session tokens generated during the initial page load. We maintain strict cookie jars and token refresh cycles to ensure API requests mirror legitimate user flows.
High-frequency route scanning triggers IP bans. We distribute search payloads across thousands of residential ISP nodes, keeping request rates well below WAF thresholds.
Wizzair updates its internal API request structures frequently. Our telemetry monitors payload schema changes and alerts our engineering team to update the interceptors before data drops occur.
Depending on the origin airport, Wizzair defaults to local currency. Our pipeline forces specific currency headers or normalises post-extraction to ensure your dataset uses a unified baseline.
Low-cost carriers and full-service airlines monitor Wizzair's base fares and ancillary fees to adjust their own yield management models.
Online Travel Agencies use scheduled pipelines to cache Wizzair inventory, reducing live API calls and improving search latency.
Airport authorities and aviation consultants track Wizzair's network expansion, frequency changes, and seasonal drops.
Revenue management teams train ML models on historical Wizzair pricing data to understand close-in booking curves.
Financial analysts monitor capacity deployment and seat volume across specific European corridors to estimate market share.
Meta-search engines ingest pre-computed price caches to display accurate Wizz Discount Club fares to users.
"Wizzair's dynamic pricing and ancillary fee structures represent the most complex revenue models in low-cost aviation — requiring precise extraction to map true passenger costs."
Airlines deploy aggressive anti-bot protection to shield their pricing APIs. Reliable Wizzair extraction requires bypassing Akamai, managing complex session states, and rotating clean residential IPs. DataFlirt handles this infrastructure so your pricing teams can focus on margin analysis, not maintaining scrapers.
Everything supported by our wizzair.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 deduplication. Playwright manages WAF clearance, token generation, and API interception.
We maintain pools of residential ISP proxies across European regions to match origin airports and bypass IP rate limits.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About wizzair.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 passenger data or circumvent authentication walls. Clients should review Wizzair's ToS and consult legal counsel for specific use cases.
Wizzair heavily utilises Akamai for bot mitigation. We use residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and hardware telemetry masking to clear WAF challenges before intercepting the underlying pricing APIs.
Yes. Our pipeline extracts the standard base fare alongside the specific Wizz Discount Club standard and group tier prices for every flight scanned.
Yes. We map the dynamic costs for priority boarding, various checked baggage weight tiers (10kg, 20kg, 32kg), and seat selection fee ranges for each specific flight.
Pipelines can be configured to run daily, hourly, or at custom intervals. High-frequency route monitoring delivers updated pricing payloads within minutes of the crawl execution.
Our smallest packages start at a defined list of origin-destination pairs with daily delivery. For full network scans or high-frequency polling, we price based on compute volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily route network map or high-frequency dynamic fare tracking across specific corridors — we scope, build, and operate the pipeline. Tell us what you need.
