We extract daily schedules, real-time fare availability, bundle pricing, and ancillary fees from FlyFrontier. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
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 flyfrontier.com. All fields typed and schema-versioned.
"flight_number": "F9 1234", "origin_code": "DEN", "destination_code": "LAS", "departure_time": "2026-10-12T08:00:00Z", "arrival_time": "2026-10-12T09:45:00Z", "duration_minutes": 105, "aircraft_type": "Airbus A320neo", "stops": 0
| # | flight_number | origin_code | destination_code | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fares & Availability objects from flyfrontier.com. All fields typed and schema-versioned.
"flight_id": "F9_1234_20261012", "travel_date": "2026-10-12", "base_fare": 39.0, "discount_den_fare": 29.0, "taxes_fees": 21.5, "total_price": 60.5, "currency": "USD", "seats_remaining": 4
| # | flight_id | travel_date | base_fare | discount_den_fare | taxes_fees | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Bundle Pricing objects from flyfrontier.com. All fields typed and schema-versioned.
"flight_id": "F9_1234_20261012", "bundle_name": "The Works", "price": 85.0, "currency": "USD", "includes_carry_on": true, "includes_checked_bag": true, "includes_seat_selection": true, "refundability": true
| # | flight_id | bundle_name | price | currency | includes_carry_on | includes_checked_bag |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary Fees objects from flyfrontier.com. All fields typed and schema-versioned.
"route_code": "DEN-LAS", "travel_date": "2026-10-12", "carry_on_bag_fee": 59.0, "checked_bag_1_fee": 54.0, "checked_bag_2_fee": 75.0, "standard_seat_fee_min": 17.0, "stretch_seat_fee_min": 55.0, "currency": "USD"
| # | route_code | travel_date | carry_on_bag_fee | checked_bag_1_fee | checked_bag_2_fee | standard_seat_fee_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from flyfrontier.com. All fields typed and schema-versioned.
"origin_code": "DEN", "origin_city": "Denver", "destination_code": "LAS", "destination_city": "Las Vegas", "distance_miles": 628, "frequency_weekly": 21, "seasonal_route": false, "start_date": "2020-01-01"
| # | origin_code | origin_city | destination_code | destination_city | distance_miles | frequency_weekly |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our FlyFrontier scraper handles the entire booking flow: origin-destination pairs, dynamic pricing, Discount Den tracking, and ancillary fees - with JavaScript rendering and session management built in.
Origin-destination pairs, departure and arrival times, flight duration, and aircraft type across the entire Frontier network.
Capture base fares, taxes, and total prices for specific dates, tracking fluctuations over time.
Extract exclusive Discount Den member pricing versus standard passenger fares.
Track the exact cost of The Works and The Perks bundles per flight and route.
Baggage and seat selection fees are highly dynamic on Frontier. We extract exact costs per route and booking window.
Fares captured in USD, MXN, CAD, or other supported currencies based on point of sale.
Real-time departure, arrival, delay, and cancellation data for operational tracking.
Extract 30-day low-fare calendar grids in a single pass to map broad pricing trends.
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, travel dates, or specific flight numbers. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and anti-bot handling for flyfrontier.com.
Schema validation, null-rate checks, fare-outlier detection, and sample payloads 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. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
Airline booking engines use advanced bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and TLS spoofing to bypass perimeter defenses.
Frontier's booking flow relies heavily on client-side rendering. We run full Playwright browser sessions to hydrate dynamic fare matrices and ancillary fee widgets.
Extracting accurate baggage and seat fees requires maintaining session state through the multi-step booking process. Our infrastructure handles cookie persistence automatically.
Airline DOM structures change frequently. Our selector strategy uses multiple fallback chains per field so a layout change does not break your data pipeline overnight.
For large route networks, we maintain a hash index of last-seen fares. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
OTAs and competing airlines monitor Frontier's base fares and ancillary pricing strategies.
Analyse discount strategies and bundle attach rates to optimise pricing models.
Track frequency and capacity on specific O&D pairs to identify underserved markets.
Metasearch engines integrate direct pricing data where API access is restricted or delayed.
Audit booked fares against actual available fares on the day of booking.
Power consumer-facing fare drop alerts and low-fare calendar tools.
"Frontier Airlines operates a complex unbundled pricing model. Tracking true cost requires deep booking flow extraction, not just surface-level fare scraping."
Scraping low-cost carriers requires navigating multi-step booking engines designed to obscure total costs. DataFlirt manages the JavaScript rendering, session state, and proxy rotation needed to extract base fares, Discount Den rates, and dynamic ancillary fees at scale.
Everything supported by our flyfrontier.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.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required for booking flows.
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 flyfrontier.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from flyfrontier.com is generally permissible under applicable law. DataFlirt targets only public, non-authenticated schedule and fare data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to bypass perimeter protections.
Yes, we extract the public Discount Den member rates displayed in the standard booking flow alongside base fares.
Yes, we navigate the multi-step booking process to extract dynamic ancillary fees specific to the route and travel date.
Pipelines can be configured for daily batch runs or high-frequency intra-day polling depending on your SLA requirements.
Our smallest packages start at a defined list of origin-destination pairs with daily delivery. Contact us for a scoped quote.
Yes. We provide a sample run of specific routes as part of the pre-engagement scoping process so you can validate data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off schedule dump or continuous fare monitoring across the entire route network, we scope, build, and operate the pipeline. Tell us what you need.
