We extract flight schedules, dynamic pricing signals, fare class availability, and route intelligence from aa.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 aa.com. All fields typed and schema-versioned.
"flight_number": "AA 105", "origin": "JFK", "destination": "LHR", "departure_time": "2023-10-25T19:30:00Z", "arrival_time": "2023-10-26T07:30:00Z", "duration_minutes": 420, "aircraft_type": "Boeing 777-200"
| # | flight_number | origin | destination | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from aa.com. All fields typed and schema-versioned.
"flight_number": "AA 105", "departure_date": "2023-10-25", "basic_economy_price": 450.0, "main_cabin_price": 520.0, "premium_economy_price": 850.0, "currency": "USD", "tax_included": true
| # | flight_number | departure_date | basic_economy_price | main_cabin_price | premium_economy_price | business_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from aa.com. All fields typed and schema-versioned.
"flight_number": "AA 105", "departure_date": "2023-10-25", "cabin_class": "Main Cabin", "seats_remaining": 4, "pitch_inches": 31, "wi_fi_available": true, "power_outlets": true
| # | flight_number | departure_date | cabin_class | seats_remaining | seat_map_url | pitch_inches |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Intelligence objects from aa.com. All fields typed and schema-versioned.
"origin": "JFK", "destination": "LHR", "direct_flights_count": 4, "min_price": 450.0, "avg_duration_minutes": 435, "operating_carriers": "['American Airlines', 'British Airways']", "scraped_at": "2023-10-15T08:12:00Z"
| # | origin | destination | direct_flights_count | connecting_flights_count | min_price | max_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Baggage & Extras objects from aa.com. All fields typed and schema-versioned.
"flight_number": "AA 105", "fare_class": "Basic Economy", "carry_on_allowance": 1, "checked_bag_allowance": 0, "first_bag_fee": 75.0, "currency": "USD", "priority_boarding_fee": 45.0
| # | flight_number | fare_class | carry_on_allowance | checked_bag_allowance | first_bag_fee | second_bag_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our aa.com scraper handles complex search flows: multi-city itineraries, dynamic fare calendars, partner airline mapping, and anti-bot circumvention.
Extract departure, arrival, duration, aircraft type, and operating carrier for all AA and Oneworld partner flights.
Capture real-time pricing across Basic Economy, Main Cabin, Premium Economy, Business, and Flagship First.
Track remaining seat counts per cabin class to infer load factors and booking velocity.
Map direct routes, connection hubs, and layover durations across the entire American Airlines network.
Extract 30-day and 330-day fare calendars to identify pricing trends and seasonal fluctuations.
Capture baggage fees, seat selection costs, and priority boarding upgrades associated with specific fare classes.
Identify codeshare flights operated by British Airways, Iberia, Japan Airlines, and other partners.
Monitor specific routes with sub-hourly polling to capture intraday price volatility.
Navigate Akamai and advanced bot protection using residential proxies and TLS fingerprinting.
Brief in. Clean data out.
Provide origin-destination pairs, dates, or flight numbers. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for aa.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 employ aggressive anti-scraping measures. Here is how we maintain data flow without interruption.
American Airlines uses Akamai bot management. We deploy US-based residential proxies and carefully mimic human TLS fingerprints to prevent IP bans and CAPTCHA walls.
Flight searches require interacting with complex JavaScript calendars and autocomplete dropdowns. We use Playwright to execute these flows reliably.
Extracting detailed fare rules and seat maps often requires maintaining session state across multiple page loads. Our pipeline handles cookie jars automatically.
We map AA-specific fare codes and cabin classes into a normalised schema, making the data immediately usable for downstream analysis.
If a route suddenly returns zero flights or extreme fare drops, our monitoring stack flags it for manual review to distinguish between real airline errors and scraper failures.
OTAs and competing airlines monitor AA pricing strategies to adjust their own fares and maintain market parity.
Travel management companies track fare fluctuations to advise clients on optimal booking windows.
Analysts use historical pricing and seat availability data to train predictive models for airline revenue management.
Aviation consultants analyze schedule changes and aircraft deployment to understand AA's network strategy.
Hedge funds track flight volume and pricing trends as alternative data signals for airline stock performance.
Travel aggregators combine scraped flight data with hotel pricing to create real-time dynamic vacation packages.
"American Airlines operates over 6,700 flights daily. Capturing that pricing volatility requires infrastructure, not just a script."
Airline pricing is notoriously dynamic, with fares changing multiple times per day based on load factors and algorithmic revenue management. Extracting this data reliably from aa.com means navigating complex search forms, aggressive bot protection, and high-frequency polling requirements. DataFlirt manages this entire stack.
Everything supported by our aa.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 across US regions. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About aa.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing from aa.com is generally permissible under US law. DataFlirt targets only public, non-authenticated data. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
We use US-based residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and human-like interaction patterns to navigate Akamai bot management.
Yes. Any codeshare flight displayed on aa.com (e.g., British Airways, Japan Airlines, Iberia) is captured, including operating carrier details.
We support high-frequency polling for specific routes, achieving sub-hourly updates to capture intraday fare volatility.
Yes. We extract pricing for Basic Economy, Main Cabin, Premium Economy, Business, and Flagship First, where available.
Yes. We can extract the flexible dates calendar view to identify the lowest fares across a month-long window.
We can parse seat maps to count available versus occupied seats per cabin class, providing signals on flight load factors.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily schedule dump or continuous price-monitoring across thousands of routes — we scope, build, and operate the pipeline. Tell us what you need.
