We extract flight schedules, dynamic fares, ancillary pricing, and route availability from Air Arabia. 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 airarabia.com. All fields typed and schema-versioned.
"flight_number": "G9 115", "origin": "SHJ", "destination": "AMM", "departure_time": "2026-08-14T08:00:00Z", "arrival_time": "2026-08-14T10:30:00Z", "duration": "150", "aircraft_type": "A320"
| # | flight_number | origin | destination | departure_time | arrival_time | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Fares & Pricing objects from airarabia.com. All fields typed and schema-versioned.
"flight_number": "G9 115", "fare_class": "Basic", "base_fare": 450.0, "taxes": 120.0, "total_fare": 570.0, "currency": "AED", "air_rewards_points": 114
| # | flight_number | fare_class | base_fare | taxes | total_fare | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary Fees objects from airarabia.com. All fields typed and schema-versioned.
"flight_number": "G9 115", "baggage_20kg_fee": 50.0, "baggage_30kg_fee": 100.0, "meal_fee": 35.0, "seat_standard_fee": 15.0, "currency": "AED"
| # | flight_number | baggage_20kg_fee | baggage_30kg_fee | meal_fee | seat_standard_fee | seat_extra_legroom_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from airarabia.com. All fields typed and schema-versioned.
"origin_code": "SHJ", "origin_city": "Sharjah", "destination_code": "AMM", "destination_city": "Amman", "flight_frequency": 7, "days_of_week": "Daily"
| # | origin_code | origin_city | destination_code | destination_city | flight_frequency | days_of_week |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Baggage Policies objects from airarabia.com. All fields typed and schema-versioned.
"route_zone": "Zone 1", "weight_allowance": "20kg", "pre_book_fee": 50.0, "airport_fee": 150.0, "excess_kg_fee": 30.0, "currency": "AED"
| # | route_zone | weight_allowance | pre_book_fee | airport_fee | excess_kg_fee | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the entire booking flow: search initiation, session tokens, dynamic fare hydration, and ancillary fee extraction. We bypass travel bot protection automatically.
Departure times, arrival times, flight durations, and aircraft types scraped across the entire Air Arabia network.
Capture base fares, taxes, and total costs across Basic, Value, and Extra fare tiers. Timestamped per crawl.
Extract baggage costs, meal prices, seat selection fees, and insurance add-ons directly from the booking flow.
Scrape fares in AED, EUR, USD, or any supported local currency based on point of sale configuration.
Track active routes, seasonal changes, and flight frequencies across all Air Arabia hubs.
Maintain valid booking sessions to navigate through flight selection and reach the ancillary pricing pages.
Circumvent Akamai and Datadome protections common on airline sites using residential proxies and fingerprinting.
Capture the Air Rewards points earned per flight and fare class to model loyalty program value.
Run one-off bulk exports or configure continuous pipelines at hourly or daily intervals.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and required currencies. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for airarabia.com.
Schema validation, null-rate checks, and fare anomaly detection 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 their pricing data. Here is how we stay resilient.
Extracting ancillary fees requires advancing through the booking flow. We maintain stateful Playwright sessions, handling cookies and session tokens to reach the seat selection and baggage pages without triggering timeouts.
Airline websites use advanced bot mitigation. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to blend in with legitimate passenger traffic.
Fares change based on the user location. We route requests through specific geographic proxy pools to capture accurate point-of-sale pricing in the target currency.
Flight results and price grids load dynamically via XHR. We execute full JavaScript rendering to ensure all fare tiers and availability statuses are captured accurately.
Airlines update their booking engines frequently. We monitor selector health and alert on null-rate spikes, ensuring layout changes do not break your data pipeline.
Rival airlines track Air Arabia base fares and ancillary fees on overlapping routes to optimise their own pricing strategies.
Online travel agencies integrate direct scraped feeds when official API access is restricted or cost-prohibitive.
Revenue management teams analyse pricing curves and seat availability over time to model competitor load factors.
Market intelligence firms aggregate route frequencies and capacity changes to forecast regional travel demand.
Large enterprises monitor specific route costs to optimise corporate travel budgets and negotiate bulk rates.
Economists use historical fare data to study dynamic pricing behaviour and low-cost carrier market impacts.
"Air Arabia operates a highly dynamic pricing model where base fares and ancillary fees shift constantly based on load factors and booking velocity."
Extracting low cost carrier data requires more than simple HTTP requests. Travel booking engines use sophisticated session management and bot mitigation. DataFlirt handles the proxy rotation, session hydration, and booking flow traversal required to extract accurate fares and ancillary costs at scale.
Everything supported by our airarabia.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 rendering and complex booking flow navigation.
We maintain pools of residential ISP proxies across multiple regions to ensure accurate point-of-sale pricing and bypass bot mitigation.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About airarabia.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible. We do not bypass authentication walls or extract personal user data. Clients should review relevant terms of service and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions, and realistic request timing to mimic human behaviour. This allows us to navigate booking flows without triggering standard mitigation blocks.
Yes. Our crawlers navigate past the initial flight selection screen to reach the ancillary pages, capturing baggage tier costs, meal prices, and seat selection fees.
We can configure pipelines to run daily, hourly, or at custom intervals depending on your required latency and the size of the route list.
Yes. We can configure the scraper to request fares in specific currencies by passing the appropriate parameters and routing through regional proxy IPs.
Our packages start at a defined route list with weekly or daily delivery. We price based on route volume, delivery frequency, and the depth of the booking flow required.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily schedule updates or continuous fare monitoring across thousands of routes, we build and operate the pipeline. Tell us what you need.
