We extract flight schedules, dynamic fare classes, seat availability, and route metadata from Aeromexico. 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 aeromexico.com. All fields typed and schema-versioned.
"flight_number": "AM 1", "origin": "MEX", "destination": "MAD", "departure_time": "2024-10-12T18:15:00", "arrival_time": "2024-10-13T12:00:00", "duration": "10h 45m", "aircraft_type": "Boeing 787-9"
| # | flight_number | origin | destination | departure_time | arrival_time | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from aeromexico.com. All fields typed and schema-versioned.
"flight_number": "AM 1", "cabin_class": "Premier One", "total_price": 3450.0, "currency": "USD", "point_of_sale": "US", "taxes": 450.0, "scrape_timestamp": "2024-05-12T09:14:00Z"
| # | flight_number | cabin_class | fare_basis | base_fare | taxes | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from aeromexico.com. All fields typed and schema-versioned.
"flight_number": "AM 1", "departure_date": "2024-10-12", "cabin_class": "Main Cabin", "available_seats": 42, "total_seats": 238, "pitch": "31 in"
| # | flight_number | departure_date | cabin_class | total_seats | available_seats | occupied_seats |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from aeromexico.com. All fields typed and schema-versioned.
"origin_airport": "MEX", "destination_airport": "JFK", "direct_flight": true, "frequency_per_week": 21, "terminal_origin": "2", "terminal_destination": "4"
| # | origin_airport | destination_airport | distance_miles | direct_flight | frequency_per_week | seasonal_route |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Baggage & Ancillaries objects from aeromexico.com. All fields typed and schema-versioned.
"fare_type": "Classic", "carry_on_allowance": "1 piece, 10kg", "checked_bag_allowance": "1 piece, 23kg", "extra_bag_fee": 55.0, "wifi_available": true, "lounge_access": false
| # | fare_type | carry_on_allowance | checked_bag_allowance | extra_bag_fee | overweight_fee | wifi_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Aeromexico scraper navigates complex booking flows, handles dynamic API tokens, and circumvents anti-bot systems to deliver accurate pricing and schedule data.
Capture departure times, arrival times, aircraft types, and operational days for the entire Aeromexico network.
Extract base fares, taxes, and total prices across all cabin classes, updated at your specified frequency.
Utilise geographic proxy routing to capture price variations based on the user's location and currency.
Distinguish between Basic, Classic, AM Plus, and Premier fare conditions and inclusions.
Analyse seat maps to determine available versus blocked seats and track flight load factors.
Identify flights operated by Delta and other SkyTeam partners versus mainline Aeromexico operations.
Extract pricing for round-trip and multi-city itineraries, handling complex fare construction rules.
Document baggage allowances, seat selection fees, and other ancillary charges tied to specific fare codes.
Execute minute-level price updates on critical routes to monitor flash sales and dynamic revenue management.
Maintain long-term datasets to track fare curves and seasonal pricing trends over time.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and frequency requirements. We design the extraction schema together.
We configure Scrapy crawlers, manage session state, and implement proxy rotation to bypass airline bot protection.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or 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 reliable data extraction.
Airlines use advanced bot protection. We utilise residential proxies and precise TLS fingerprinting to mimic human browsing behaviour and maintain session continuity.
Extracting final prices requires navigating multi-step booking funnels. Our Playwright scripts maintain cookie state and execute JavaScript to render final fare calculations.
Aeromexico alters prices based on the user's IP address. We route requests through specific geographic nodes to capture accurate point-of-sale pricing.
The modern Aeromexico site relies heavily on client-side rendering. We intercept underlying API calls or execute full browser sessions to capture data before it hits the DOM.
Where possible, we analyse network traffic to construct direct queries to Aeromexico's internal APIs, reducing latency and increasing data density.
Rival airlines and OTAs monitor Aeromexico's fare changes to adjust their own pricing algorithms in real time.
Travel platforms integrate direct scraped fares when official API access is restricted or cost-prohibitive.
Aviation analysts calculate load factors and yield metrics by tracking seat maps and fare classes.
Agencies monitor specific itineraries to alert clients when prices drop below defined thresholds.
Large enterprises audit booked fares against public pricing to ensure compliance with travel policies.
Researchers analyse long-term pricing trends and network expansion strategies within the Latin American market.
"Aeromexico processes thousands of dynamic fare changes daily. Without direct API access, reverse-engineering their booking flow is the only way to build competitive intelligence."
Airlines employ aggressive anti-scraping measures. Extracting accurate fares requires session preservation, geographic proxy routing, and handling token-based API authentication. DataFlirt manages this infrastructure so you receive clean pricing data without the operational overhead.
Everything supported by our aeromexico.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 manages JavaScript execution and complex booking flows.
We maintain pools of residential proxies to bypass airline bot protection and capture accurate point-of-sale pricing.
Pipelines run on Kubernetes. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About aeromexico.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible. DataFlirt extracts only public, non-authenticated data. We do not bypass login screens to access Club Premier accounts or PNR data. Clients should review applicable terms of service.
Airlines utilise advanced mitigation systems. We deploy residential ISP proxies, maintain realistic browser fingerprints via Playwright, and manage session cookies to ensure uninterrupted data extraction.
Yes. We route extraction requests through specific geographic proxy nodes to capture accurate pricing for different markets and currencies.
We can configure pipelines for daily schedule updates or high-frequency polling (e.g., every 15 minutes) for specific high-value routes.
Our minimum engagement typically starts with a defined list of 500 origin-destination pairs monitored daily. Contact us for custom volume requirements.
Yes. Our extraction process identifies the operating carrier, distinguishing between Aeromexico mainline flights and those operated by Delta or other SkyTeam partners.
Yes. We provide a sample extraction of up to 50 routes during the scoping phase to validate schema and data quality.
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 build and operate the pipeline. Tell us your requirements.
