We extract flight schedules, dynamic pricing signals, seat availability, and route networks from Air China. 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 airchina.com. All fields typed and schema-versioned.
"flight_number": "CA981", "origin_airport": "PEK", "destination_airport": "JFK", "departure_time_local": "2026-10-12T13:00:00", "arrival_time_local": "2026-10-12T14:30:00", "duration_minutes": 870, "aircraft_type": "Boeing 747-8", "stops": 0, "operated_by": "Air China"
| # | flight_number | origin_airport | destination_airport | departure_time_local | arrival_time_local | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from airchina.com. All fields typed and schema-versioned.
"flight_number": "CA981", "departure_date": "2026-10-12", "cabin_class": "Economy", "total_price": 1245.5, "base_fare": 950.0, "tax_amount": 295.5, "currency": "USD", "refundable": false, "change_fee_applies": true
| # | flight_number | departure_date | cabin_class | fare_basis_code | total_price | base_fare |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Seat Availability objects from airchina.com. All fields typed and schema-versioned.
"flight_number": "CA981", "departure_date": "2026-10-12", "cabin_class": "Business", "seats_remaining": 4, "booking_class": "J", "waitlist_open": false, "seat_pitch_inches": 60, "seat_width_inches": 21, "layout": "2-2-2"
| # | flight_number | departure_date | cabin_class | seats_remaining | booking_class | waitlist_open |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from airchina.com. All fields typed and schema-versioned.
"origin_iata": "PEK", "destination_iata": "LHR", "route_type": "International", "distance_km": 8140, "weekly_frequency": 7, "seasonality": "Year-round", "codeshare_partners": "['VS', 'BA']", "hub_connection": true
| # | origin_iata | destination_iata | route_type | distance_km | weekly_frequency | seasonality |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Baggage & Extras objects from airchina.com. All fields typed and schema-versioned.
"flight_number": "CA981", "fare_type": "Economy Standard", "cabin_bag_allowance_kg": 5, "checked_bag_allowance_kg": 23, "checked_bag_pieces": 2, "extra_bag_fee": 150.0, "wifi_available": false, "meal_included": true
| # | flight_number | fare_type | cabin_bag_allowance_kg | checked_bag_allowance_kg | checked_bag_pieces | extra_bag_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Air China scraper navigates complex booking flows, bypasses rate limits, and extracts structured pricing and schedule data across all cabin classes and international routes.
Capture departure times, arrival times, aircraft types, and flight durations across Air China's entire domestic and international network.
Extract real-time fares across Economy, Premium Economy, Business, and First Class. Includes tax breakdowns and base fare splits.
Monitor remaining seats per booking class to gauge load factors and predict price fluctuations on specific routes.
Extract cancellation policies, change fees, and refundability status for every fare option presented in the booking flow.
Capture piece concepts, weight limits, and excess baggage fees specific to the route and fare class.
Simulate searches from different geographic regions to capture point-of-sale pricing variations and currency differences.
Scrape complex routing options, layover durations, and connection viability through major hubs like PEK and PVG.
Extract public mileage accrual rates and upgrade eligibility for specific fare classes and routes.
Configure pipelines to poll competitive routes at sub-hourly intervals to capture intraday yield management adjustments.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and target cabin classes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for airchina.com.
Schema validation, null-rate checks, price-outlier detection, and schedule verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airline booking engines are notoriously difficult to scrape. Here is how we maintain reliable data flow from airchina.com.
Airline search flows rely on strict session tokens and cookies. Our Playwright instances maintain full browser state, handling multi-step form submissions without triggering session expiration errors.
Air China employs aggressive rate limiting on IP addresses making repeated search queries. We distribute requests across a global pool of ISP-grade residential proxies to mimic legitimate user traffic.
Flight results often load asynchronously via hidden API calls. We intercept the underlying XHR responses directly, extracting clean JSON payloads rather than parsing volatile DOM elements.
Booking engines restrict searches to specific date windows. Our orchestrator automatically increments search dates and handles calendar widget interactions to build comprehensive future-looking datasets.
Airlines sometimes return cached or error-state pricing. We validate all extracted fares against historical baselines, automatically retrying requests if prices deviate beyond expected yield management parameters.
Online travel agencies ingest direct inventory and pricing to validate GDS data and ensure price parity.
Rival airlines monitor Air China's pricing strategies on overlapping routes to adjust their own yield management algorithms.
Aviation consultants track frequency changes, equipment swaps, and new route launches to map capacity trends.
TMCs scrape schedule and fare data to optimise booking windows and enforce corporate travel policies.
Insurers and logistics firms monitor schedule adjustments and historical delay patterns to model risk.
Tourism boards analyse inbound flight capacity and pricing to forecast visitor volumes from the Chinese market.
"Airline pricing is the original dynamic market. Capturing Air China's fare adjustments in real time requires sophisticated session management and residential proxy infrastructure."
Most teams fail at scraping airline booking engines because they treat them like static websites. Air China's search flow requires maintaining complex cookie states, executing JavaScript to calculate taxes, and rotating IPs to avoid aggressive rate limits. DataFlirt handles this infrastructure so you receive clean pricing data.
Everything supported by our airchina.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 global regions to simulate local Point of Sale pricing. Rotation happens per-session to maintain booking flow integrity.
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 airchina.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible. DataFlirt targets only public, non-authenticated search interfaces. We do not extract personal data, access PNRs, or circumvent authentication walls. Clients should review Air China's terms of service and consult legal counsel for specific use cases.
We use residential ISP proxies, maintain strict session cookies throughout the search flow, and emulate human interaction patterns using Playwright. We also throttle request concurrency to stay within acceptable limits while meeting delivery SLAs.
Yes. We can simulate searches originating from different countries using geo-targeted proxies, capturing the specific Point of Sale pricing and currency offered to users in that region.
We can extract schedule and pricing data up to the maximum booking window allowed by Air China's system, which is typically 330 to 350 days in advance.
Yes. We navigate to the final fare breakdown stage to extract the base fare, carrier-imposed surcharges, and individual government taxes where available in the DOM or XHR response.
Our smallest packages start with a defined list of origin-destination pairs (typically 50-500 routes) tracked daily. For larger networks or high-frequency polling, we price based on compute volume and proxy bandwidth.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off schedule dump or a continuous price-monitoring feed across 1,000 routes - we scope, build, and operate the pipeline. Tell us what you need.
