We extract route schedules, dynamic pricing signals, fare class availability, and aircraft configurations from united.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 united.com. All fields typed and schema-versioned.
"flight_number": "UA412", "origin_airport": "SFO", "destination_airport": "EWR", "departure_time_local": "2026-08-14T08:30:00", "flight_duration_minutes": 325, "aircraft_type": "Boeing 777-200", "operating_carrier": "United Airlines", "stop_count": 0
| # | flight_number | origin_airport | destination_airport | departure_time_local | arrival_time_local | flight_duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from united.com. All fields typed and schema-versioned.
"flight_number": "UA412", "departure_date": "2026-08-14", "basic_economy_price": 249.0, "standard_economy_price": 299.0, "polaris_business_price": 1249.0, "currency": "USD", "fare_basis_code": "KAA2AQEN", "refundable_flag": false
| # | flight_number | search_date | departure_date | basic_economy_price | standard_economy_price | premium_plus_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from united.com. All fields typed and schema-versioned.
"flight_number": "UA412", "departure_date": "2026-08-14", "total_capacity": 276, "economy_seats_available": 42, "polaris_seats_available": 4, "exit_row_premium_fee": 89.0, "blocked_seats_count": 12, "seat_map_timestamp": "2026-07-01T14:22:00Z"
| # | flight_number | departure_date | total_capacity | economy_seats_available | premium_plus_seats_available | polaris_seats_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for MileagePlus Rewards objects from united.com. All fields typed and schema-versioned.
"flight_number": "UA412", "origin": "SFO", "destination": "EWR", "saver_award_miles_economy": 15000, "everyday_award_miles_economy": 32500, "saver_award_miles_polaris": 60000, "taxes_fees_cash": 5.6, "currency": "USD", "mixed_cabin_flag": false
| # | flight_number | origin | destination | departure_date | saver_award_miles_economy | everyday_award_miles_economy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight Status objects from united.com. All fields typed and schema-versioned.
"flight_number": "UA412", "flight_date": "2026-08-14", "scheduled_departure": "2026-08-14T08:30:00", "estimated_departure": "2026-08-14T09:15:00", "status_code": "Delayed", "gate_origin": "G3", "terminal_origin": "3", "delay_minutes": 45
| # | flight_number | flight_date | scheduled_departure | estimated_departure | actual_departure | status_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our United scraper navigates complex booking flows, dynamic inventory loading, and heavy edge protection to deliver accurate flight and pricing data.
Extract origin, destination, layovers, flight duration, and operating carrier details for any specified route network.
Capture real-time pricing across all cabins, from Basic Economy up to Polaris Business, including tax breakdowns.
Track Saver versus Everyday award availability and monitor mileage requirements alongside cash copays.
Parse seat maps to calculate remaining available seats per cabin, blocked inventory, and premium seating fees.
Extract equipment type, tail number, WiFi availability, and cabin configuration for specific flight legs.
Extract point-of-sale specific pricing in USD, EUR, GBP, INR, and other supported currencies.
Monitor real-time delays, gate changes, and cancellations to build historical punctuality datasets.
Capture checked baggage fee matrices, seat selection costs, and priority boarding upgrade prices.
Run one-off bulk route exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide origin-destination pairs, travel dates, or hub codes. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and edge protection bypass for united.com.
Schema validation, null-rate checks, price-outlier detection, and sample route checks 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 to protect yield management strategies. Here is how we stay resilient.
United uses aggressive edge protection to block automated searches. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass these challenges.
Flight searches require maintaining strict cookie state across multiple redirects. We handle the complete session lifecycle to ensure pricing data loads correctly without triggering security resets.
United loads fare matrices asynchronously via XHR after the initial page load. We use Playwright to intercept these specific network requests, extracting clean JSON payloads directly from the backend.
The United booking engine updates frequently. Our selector strategy uses multiple fallback chains so a minor layout change does not break your data pipeline overnight.
High-frequency flight searches from a single IP trigger rate limits instantly. We distribute requests across thousands of residential IPs to maintain high throughput without burning proxy nodes.
Online Travel Agencies monitor direct-channel pricing to ensure parity and optimise their own commission structures.
Competitor airlines track United fare class inventory and pricing adjustments to calibrate their own revenue management algorithms.
Metasearch engines populate their cache with high-frequency pricing updates to improve user search latency.
Enterprise travel managers validate negotiated corporate rates against public fares to ensure contract compliance.
Analysts track MileagePlus devaluation trends and Saver award availability to assess program liability and consumer value.
Aviation consultants analyse frequency, equipment deployment, and capacity on specific hubs to identify market opportunities.
"Airline pricing is the original dynamic market. United adjusts fares and inventory thousands of times daily, data that remains invisible without automated, high-frequency extraction."
Extracting flight data from legacy carriers requires navigating aggressive edge protection, complex multi-step booking flows, and heavy asynchronous rendering. DataFlirt manages the proxy rotation, session state, and schema maintenance so your analysts can focus on yield optimisation rather than bot mitigation.
Everything supported by our united.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 retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows for complex flight searches.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-session to maintain state while avoiding rate limits and IP bans.
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 united.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from united.com is generally permissible under applicable law. DataFlirt targets only public, non-authenticated flight schedules, pricing, and seat availability. We do not extract personal data or circumvent authentication walls. Clients should review United terms of service 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 monitor for blocking patterns in real time and trigger pool rotation automatically.
Yes. We track Saver and standard award availability, extracting the required mileage and the associated cash copay for taxes and fees.
Real-time streaming pipelines achieve sub-30-minute latency for pricing signals on a defined route list. Full network refreshes at daily cadence complete within a defined execution window.
Yes. We parse the seat map payload to calculate available seats, blocked seats, and premium seating fees for specific flights.
Our packages start at a defined route list, typically 500 to 10,000 origin-destination pairs, with daily delivery. We price based on volume and delivery frequency.
Yes. We provide a sample run of up to 50 routes as part of the pre-engagement scoping process so you can validate schema fit and data quality.
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 thousands of flights, we scope, build, and operate the pipeline. Tell us what you need.
