We extract flight schedules, dynamic base fares, ancillary baggage fees, and seat availability from spirit.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 Flight Schedules objects from spirit.com. All fields typed and schema-versioned.
"flight_number": "NK142", "origin_iata": "FLL", "destination_iata": "LGA", "departure_time": "2024-11-14T08:30:00-05:00", "arrival_time": "2024-11-14T11:15:00-05:00", "duration_minutes": 165, "aircraft_type": "Airbus A320neo", "stops": 0
| # | flight_number | origin_iata | destination_iata | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Base Fares objects from spirit.com. All fields typed and schema-versioned.
"flight_number": "NK142", "departure_date": "2024-11-14", "standard_fare": 84.5, "saver_club_fare": 69.5, "currency": "USD", "tax_amount": 14.2, "passenger_usage_fee": 22.99, "total_price": 121.69
| # | flight_number | departure_date | standard_fare | saver_club_fare | currency | tax_amount |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary Fees objects from spirit.com. All fields typed and schema-versioned.
"flight_number": "NK142", "carry_on_fee_booking": 59.0, "carry_on_fee_gate": 99.0, "checked_bag_1_fee": 54.0, "checked_bag_2_fee": 75.0, "shortcut_security_fee": 7.0, "shortcut_boarding_fee": 9.0
| # | flight_number | departure_date | carry_on_fee_booking | carry_on_fee_gate | checked_bag_1_fee | checked_bag_2_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Maps objects from spirit.com. All fields typed and schema-versioned.
"flight_number": "NK142", "seat_number": "2A", "seat_type": "Big Front Seat", "availability_status": "AVAILABLE", "price": 85.0, "is_big_front_seat": true, "is_exit_row": false, "position": "WINDOW"
| # | flight_number | departure_date | seat_number | seat_type | availability_status | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from spirit.com. All fields typed and schema-versioned.
"origin_code": "FLL", "destination_code": "LGA", "frequency_per_week": 21, "is_direct": true, "is_seasonal": false, "distance_miles": 1076, "equipment_list": "['A320', 'A321']", "scrape_timestamp": "2024-05-12T09:14:00Z"
| # | origin_code | destination_code | frequency_per_week | is_direct | is_seasonal | season_start_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Spirit scraper handles the entire booking flow: search grids, dynamic fare calendars, ancillary fee calculation, and seat map rendering - with anti-bot circumvention built in.
Extract all available flights for a given route and date. Capture departure times, arrival times, durations, and flight numbers.
Spirit dynamically prices baggage based on route and date. We traverse the booking flow to extract exact carry-on and checked bag fees.
Parse seat maps to determine Big Front Seat pricing and availability for specific flights, alongside standard seat selection fees.
Extract both standard fares and discounted Spirit Saver Club fares simultaneously from the search results grid.
Capture the full breakdown of the base fare, including government taxes and Spirit's Passenger Usage Charge.
Scrape low-fare calendar views to identify pricing trends and minimum fares across a 30-day window.
Monitor active routes, seasonal adjustments, and flight frequencies across the entire Spirit network.
Extract costs for Shortcut Security, Shortcut Boarding, and Wi-Fi streaming packages presented during checkout.
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, and required data points. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for spirit.com.
Schema validation, null-rate checks, price-outlier detection, and sample routes 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.
Airline sites deploy strict Web Application Firewalls. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass Akamai and similar protections.
Extracting ancillary fees requires maintaining session state deep into the booking funnel. We handle the complex token exchanges required to reach the baggage and seat selection pages without triggering session timeouts.
Spirit's seat maps and dynamic pricing calendars are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering to capture data that headless HTTP clients miss entirely.
Baggage fees on Spirit are not static; they change based on the route and travel date. Our pipeline specifically targets these dynamic endpoints to ensure you receive the exact fee a user would pay.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops - and respond before you notice. SLA uptime is contractual, not aspirational.
Online travel agencies verify unbundled fares and baggage fees to display accurate total costs to consumers.
Rival airlines monitor Spirit's base fares and ancillary pricing strategies on overlapping routes to adjust their own yield management systems.
Analysts track discounting velocity and Saver Club promotions to understand ultra-low-cost carrier demand curves.
Consultancies track dynamic baggage and Big Front Seat pricing to benchmark airline ancillary revenue strategies.
Aviation analysts monitor route additions, frequency changes, and seasonal drops to map network expansion.
ML teams use historical flight pricing datasets to train fare prediction and demand forecasting models.
"Spirit Airlines unbundles every component of the fare. Capturing the true cost of a flight requires traversing the entire booking funnel, not just the initial search grid."
Most teams underestimate the investment required: reliable Spirit scraping requires residential proxies, WAF bypass, full JavaScript rendering for seat maps, and session token management through the booking flow. DataFlirt absorbs that complexity so your engineers can focus on the analysis - not the infrastructure.
Everything supported by our spirit.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 US 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 spirit.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from airline websites is generally permissible under applicable law. DataFlirt targets only public, non-authenticated flight schedules, pricing, and ancillary fee data. We do not extract personal data or circumvent authentication walls. Clients should 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 monitor for WAF blocks or CAPTCHA rate spikes in real time and trigger pool rotation or solver queues automatically.
Yes. Spirit prices baggage based on the route and date. Our pipeline navigates through the initial search grid into the booking flow to extract the exact carry-on and checked bag fees for a specific itinerary.
Real-time streaming pipelines achieve sub-60-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.
Yes. We extract both the standard base fare and the discounted Spirit Saver Club fare presented on the search results page.
Absolutely. We provide a sample run of up to 50 routes as part of the pre-engagement scoping process - so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route network dump or a continuous price-monitoring feed across 5,000 routes - we scope, build, and operate the pipeline. Tell us what you need.
