We extract flight schedules, dynamic fare classes, tax breakdowns, and route availability from flysaa.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 flysaa.com. All fields typed and schema-versioned.
"flight_number": "SA286", "origin_iata": "JNB", "destination_iata": "HKG", "departure_time": "2026-08-14T17:30:00Z", "arrival_time": "2026-08-15T12:15:00Z", "duration_minutes": 765, "aircraft_type": "Airbus A340-300", "stops": 0
| # | flight_number | origin_iata | destination_iata | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from flysaa.com. All fields typed and schema-versioned.
"flight_number": "SA286", "departure_date": "2026-08-14", "cabin_class": "Economy", "base_fare": 8450.0, "taxes_and_fees": 3120.5, "total_price": 11570.5, "currency": "ZAR", "seats_remaining": 4
| # | flight_number | departure_date | cabin_class | fare_basis_code | base_fare | taxes_and_fees |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Network objects from flysaa.com. All fields typed and schema-versioned.
"origin_airport": "O.R. Tambo International", "origin_code": "JNB", "dest_airport": "Cape Town International", "dest_code": "CPT", "distance_km": 1271, "flight_time_mins": 130, "frequency_weekly": 45, "codeshare_partner": "None"
| # | origin_airport | origin_code | dest_airport | dest_code | distance_km | flight_time_mins |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fleet Information objects from flysaa.com. All fields typed and schema-versioned.
"aircraft_model": "A330-300", "manufacturer": "Airbus", "passenger_capacity": 249, "business_seats": 46, "economy_seats": 203, "wifi_available": false, "in_flight_entertainment": true, "seat_pitch_inches": 31
| # | aircraft_model | manufacturer | registration_prefix | passenger_capacity | business_seats | economy_seats |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Baggage & Ancillaries objects from flysaa.com. All fields typed and schema-versioned.
"flight_number": "SA286", "cabin_class": "Economy", "baggage_allowance_kg": 23, "extra_bag_fee": 850.0, "seat_selection_fee": 150.0, "meal_included": true, "change_fee": 1200.0, "cancellation_penalty": "Non-refundable"
| # | flight_number | cabin_class | baggage_allowance_kg | extra_bag_fee | seat_selection_fee | meal_included |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Flysaa scraper handles the complexities of airline booking engines: session timeouts, dynamic tax rendering, and strict rate limits, delivering clean fare data via managed infrastructure.
Extract origin and destination matrices across the entire South African Airways network, including seasonal route variations.
Monitor dynamic pricing fluctuations across different cabin classes and departure dates. Timestamped for accurate historical analysis.
Split the total ticket price into base fare, YQ/YR surcharges, and government taxes for precise margin calculations.
Capture inventory indicators such as 'only 3 seats left at this price' to model booking velocity and demand.
Extract pricing in ZAR, USD, GBP, EUR, or any supported local currency based on the point of sale.
Map distinct fare families across Economy and Business classes, including flexible and non-refundable ticket conditions.
Flag flights operated by partner airlines within the Star Alliance network versus native SAA metal.
Capture weight limits, piece concepts, and ancillary fees for extra luggage specific to the route and fare class.
Run one-off bulk exports or configure continuous pipelines at daily or real-time cadences to track fare changes.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and cabin classes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, manage booking session states, and handle proxy rotation for flysaa.com.
Schema validation, null-rate checks, tax calculation verification, and sample datasets before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airline booking engines use aggressive session management and rate limiting. Here is how we maintain stable extraction.
Flight searches require maintaining state across multiple HTTP requests. We manage the full cookie lifecycle and session tokens to ensure searches do not time out or return cached inventory.
Flysaa.com loads fare matrices via asynchronous JavaScript. We use Playwright to execute the booking engine code, wait for network idle states, and extract the hydrated DOM.
Airlines throttle IPs that query too many dates rapidly. We distribute requests across ZA and global residential proxy pools, throttling concurrency to mimic organic user behaviour.
Total prices obscure the base fare. Our selectors drill into the fare breakdown modals to extract exact tax components, YQ surcharges, and base prices accurately.
We monitor extraction outputs for zero-dollar fares, missing tax fields, or sudden inventory drops, alerting our infrastructure team before bad data hits your warehouse.
Online Travel Agencies aggregate direct SAA pricing to compare against GDS feeds and optimise markup strategies.
Competing airlines monitor SAA fare changes on overlapping routes to adjust their own dynamic pricing models.
Aviation analysts track flight frequencies, aircraft types, and pricing tiers to model route revenue and profitability.
Tourism boards use flight schedule data to measure inbound capacity and forecast visitor numbers from key source markets.
Revenue management teams correlate seat availability signals with pricing curves to understand booking windows.
Enterprise procurement teams audit historical fare data to negotiate better corporate rates based on actual market pricing.
"Airline pricing is the original dynamic market. Flysaa.com adjusts fares constantly based on inventory and demand - data that remains opaque until you build the extraction pipeline."
Extracting aviation data requires navigating complex session states, strict rate limits, and JavaScript-heavy booking engines. DataFlirt manages the residential proxies, concurrency controls, and browser rendering so your engineering team receives clean, structured fare datasets without maintaining scraping infrastructure.
Everything supported by our flysaa.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 search orchestration and retry logic. Playwright manages the complex JavaScript interactions required by the airline booking engine.
We maintain pools of residential ISP proxies. Rotation happens per booking session to bypass strict airline rate limits and IP bans.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling for daily fare sweeps, ensuring data arrives on time.
Data delivered to where your team already works — no new tooling required.
About flysaa.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 booking flows. We do not extract personal passenger data (PNR) or frequent flyer information. Clients should review the airline ToS and consult legal counsel for specific commercial use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and strict session management. We throttle our concurrency to mimic human search behaviour, preventing IP blocks and rate limiting.
Yes. We interact with the fare breakdown modals in the DOM to extract the base fare, YQ/YR airline surcharges, and individual government taxes separately.
We configure pipelines based on your requirements. We can run daily sweeps across specific route networks or trigger on-demand searches via API for real-time pricing.
Yes. We can configure the extraction to capture fares in ZAR, USD, GBP, EUR, or other supported currencies by manipulating the point-of-sale settings during the session.
Our smallest packages start at a defined list of origin-destination pairs with daily delivery. For global network extraction or high-frequency real-time queries, we price based on compute volume. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily schedule export or continuous fare tracking across the SAA network, we scope, build, and operate the pipeline. Tell us what you need.
