We extract flight schedules, dynamic pricing, fare families, and route availability from swiss.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 Schedules & Routes objects from swiss.com. All fields typed and schema-versioned.
"flight_number": "LX 14", "origin": "ZRH", "destination": "JFK", "departure_time": "2026-08-14T13:10:00Z", "arrival_time": "2026-08-14T16:05:00Z", "duration_minutes": 535, "aircraft_type": "Airbus A330-300", "operated_by": "Swiss International Air Lines"
| # | flight_number | origin | destination | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Live Pricing & Fares objects from swiss.com. All fields typed and schema-versioned.
"flight_number": "LX 14", "fare_family": "Economy Classic", "cabin_class": "Economy", "currency": "CHF", "total_price": 645.5, "refundable": false, "rebookable": true, "seats_remaining_alert": 4
| # | flight_number | fare_family | cabin_class | currency | base_fare | taxes_fees |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Ancillaries & Rules objects from swiss.com. All fields typed and schema-versioned.
"fare_family": "Economy Light", "carry_on_allowance": "1 x 8kg", "checked_bag_allowance": "0kg", "seat_selection_fee": 35.0, "priority_boarding": false, "lounge_access": false, "meal_included": true
| # | flight_number | fare_family | carry_on_allowance | checked_bag_allowance | seat_selection_fee | priority_boarding |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Aircraft & Fleet Data objects from swiss.com. All fields typed and schema-versioned.
"aircraft_model": "Boeing 777-300ER", "wifi_equipped": true, "seat_pitch_economy": "31 inches", "lie_flat_business": true, "first_class_cabin": true, "total_capacity": 340
| # | flight_number | aircraft_model | registration | wifi_equipped | seat_pitch_economy | lie_flat_business |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for CO2 & Sustainability objects from swiss.com. All fields typed and schema-versioned.
"flight_number": "LX 14", "distance_km": 6311, "co2_emissions_kg": 412.5, "saf_contribution_available": true, "saf_cost": 85.0, "climate_compensation_cost": 12.5, "green_fare_premium": 110.0
| # | flight_number | distance_km | co2_emissions_kg | saf_contribution_available | saf_cost | climate_compensation_cost |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our swiss.com scraper handles every layer of the booking engine: origin-destination pairs, multi-tier fare families, codeshares, and dynamic pricing changes - with session management and anti-bot circumvention built in.
Departure times, arrival times, flight numbers, aircraft types, and operating carriers scraped across all available dates.
Capture base fares, taxes, and total prices across all classes: Economy Light, Classic, Flex, Business, and First.
Extract low-stock warnings (e.g., 'Only 3 seats left at this price') to model yield management behaviour.
Parse complex itineraries including layover durations, terminal changes, and mixed-carrier codeshare flights within the Lufthansa Group.
Extract pricing in CHF, EUR, USD, or any supported currency natively from the Swiss booking engine.
Map carry-on limits, checked baggage allowances, and seat selection fees to specific fare families.
Extract CO2 estimates and Sustainable Aviation Fuel (SAF) contribution costs surfaced during the booking flow.
Monitor volatile routes with sub-hourly polling to capture intraday price drops and yield adjustments.
Navigate airline-grade WAFs and bot challenges using residential proxies and human-like interaction flows.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and passenger configurations. We design the extraction schema together.
We configure Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for swiss.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.
Airlines invest heavily in scraping detection. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Booking engines utilise strict bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass Akamai and Datadome challenges.
Flight searches require stateful POST requests and session tokens. We maintain persistent browser contexts to navigate multi-step search forms, date selections, and passenger configurations without dropping state.
Airline frontends update frequently. Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and API payload interception - so a layout change does not break your data pipeline.
Swiss defaults to origin-country currency. We force consistent currency states via session headers and cookie injection, ensuring your downstream models receive normalised pricing data.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing fare classes, and coverage drops - responding before you notice.
Rival airlines and OTAs track Swiss pricing on overlapping routes to adjust their own yield management algorithms.
Metasearch engines ingest direct pricing to display accurate comparisons when API access is restricted or delayed.
Enterprise travel managers audit public fares against negotiated corporate rates to ensure contract compliance.
Aviation analysts track schedule frequency, aircraft deployment, and seat availability signals to estimate route loads.
ESG platforms aggregate aircraft types and flight distances to model aviation carbon footprints and offset costs.
Consultancies track unbundled fare costs - like baggage and seat selection - to benchmark airline revenue strategies.
"Swiss operates one of Europe's premium networks, but extracting its dynamic pricing and multi-tier fare structures requires stateful session management."
Most teams underestimate the investment required: reliable airline scraping requires residential proxies, full JavaScript rendering for booking engines, CAPTCHA handling, and session persistence. DataFlirt absorbs that complexity so your engineers can focus on the analysis - not the infrastructure.
Everything supported by our swiss.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.
Playwright handles complex booking flows, session cookies, and interaction flows. Scrapy manages crawl orchestration, deduplication, and retry logic.
We maintain pools of residential ISP proxies across European regions. Rotation happens with sticky sessions to maintain booking flow continuity.
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 swiss.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing is generally permissible. DataFlirt targets only public, non-authenticated route and fare data. We do not extract personal data or circumvent authentication walls. Clients should review airline 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 intercept backend API payloads where possible to bypass frontend obfuscation.
Yes. Our pipeline iterates through the fare family matrix, capturing Economy Light, Classic, Flex, Business, and First Class pricing in a single structured record.
We configure polling frequency based on your needs. Highly volatile routes can be scraped sub-hourly, while full network schedules are typically refreshed daily.
Absolutely. We provide a sample run of up to 50 origin-destination pairs as part of the pre-engagement scoping process - so you can validate schema fit and data quality.
Yes. We parse the full itinerary breakdown, including layover durations, terminal changes, and the operating carrier for each specific leg.
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 500 origin-destination pairs. Tell us what you need.
