We extract flight schedules, seat availability, dynamic pricing signals, and ancillary fees from flydubai.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 flydubai.com. All fields typed and schema-versioned.
"flight_number": "FZ 81", "origin_iata": "DXB", "destination_iata": "KWI", "departure_time": "2024-11-12T08:30:00Z", "arrival_time": "2024-11-12T09:15:00Z", "duration_minutes": 105, "aircraft_type": "Boeing 737 MAX 8", "is_codeshare": false
| # | flight_number | origin_iata | destination_iata | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from flydubai.com. All fields typed and schema-versioned.
"flight_number": "FZ 81", "currency": "AED", "fare_class_lite": 450.0, "fare_class_value": 550.0, "fare_class_flex": 850.0, "business_class_fare": 2150.0, "total_fare": 450.0, "scraped_at": "2024-10-01T12:00:00Z"
| # | flight_number | departure_date | currency | fare_class_lite | fare_class_value | fare_class_flex |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from flydubai.com. All fields typed and schema-versioned.
"origin_airport": "Dubai International Airport", "origin_iata": "DXB", "destination_airport": "Kuwait International Airport", "destination_iata": "KWI", "distance_km": 853, "flight_frequency": "Daily", "origin_country": "United Arab Emirates"
| # | origin_airport | origin_city | origin_country | destination_airport | destination_city | destination_country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary Fees objects from flydubai.com. All fields typed and schema-versioned.
"flight_number": "FZ 81", "currency": "AED", "baggage_20kg_fee": 150.0, "baggage_30kg_fee": 250.0, "seat_selection_standard": 50.0, "seat_selection_extra_legroom": 120.0, "meal_preorder_fee": 40.0
| # | flight_number | baggage_20kg_fee | baggage_30kg_fee | baggage_40kg_fee | seat_selection_standard | seat_selection_extra_legroom |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from flydubai.com. All fields typed and schema-versioned.
"flight_number": "FZ 81", "departure_date": "2024-11-12", "economy_seats_remaining": 4, "business_seats_remaining": 2, "cabin_configuration": "12J/162Y", "flight_status": "Scheduled", "last_updated": "2024-10-01T12:05:00Z"
| # | flight_number | departure_date | economy_seats_remaining | business_seats_remaining | overbooked_status | seat_map_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Flydubai scraper handles every layer of the booking engine: dynamic pricing matrices, ancillary fees, route schedules, and seat scarcity signals — with full session management and anti-bot circumvention built in.
Extract flight numbers, departure times, arrival times, durations, and aircraft types for all active routes.
Monitor continuous price shifts across Lite, Value, Flex, and Business fare classes.
Capture dynamic pricing for checked baggage, seat selection, meals, and priority boarding.
Extract origin and destination metadata, flight frequencies, and seasonal schedule adjustments.
Capture public scarcity warnings like 'Only 2 seats left at this price' to model booking velocity.
Extract fares across 50+ local currencies with accurate decimal precision.
Parse complex itineraries, layover durations, and code-share flights operated by Emirates.
Separate base fare from government taxes and carrier-imposed surcharges for accurate yield analysis.
Run hourly or daily pipelines to capture intraday fare fluctuations and competitive intelligence.
Brief in. Clean data out.
Provide Origin-Destination pairs, date ranges, and passenger configurations. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for flydubai.com.
Schema validation, null-rate checks, price-outlier detection, and sample routes before full launch.
JSON / CSV / 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's how we stay resilient — and why teams choose managed infrastructure over DIY.
Airlines use strict WAF rules (Akamai/Cloudflare) to block datacenter IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Flydubai's booking engine relies on heavy client-side state. We run full Playwright browser sessions with JavaScript execution and XHR interception to capture the dynamic pricing matrix.
Reaching the final fare breakdown requires maintaining session state from the initial search through passenger selection. We manage cookie jars and session tokens precisely to prevent flow resets.
Airline DOM structures mutate frequently during sales and promotions. Our selector strategy uses multiple fallback chains per field so a layout change doesn't break your data pipeline overnight.
Scanning thousands of O&D pairs requires careful pacing to avoid IP bans. We distribute the crawl payload across vast proxy pools to maintain high throughput without triggering volumetric alarms.
OTAs and competing airlines monitor Flydubai's pricing matrix to adjust their own yields and maintain market parity.
Aviation analysts track flight frequencies, aircraft deployment, and schedule changes to model route profitability.
Metasearch engines enrich their databases with direct Flydubai inventory for comprehensive consumer search results.
Pricing strategists analyse Flydubai's unbundled fare structure, baggage fees, and seat selection pricing.
Data science teams train ML models on fare fluctuation patterns leading up to departure dates to predict pricing curves.
Travel management companies audit booked fares against public availability to ensure corporate policy adherence.
"Flydubai's pricing matrix shifts continuously based on load factors and booking velocity — capturing this requires persistent, high-frequency extraction."
Most teams underestimate the investment required: reliable airline scraping requires residential proxies, full JavaScript rendering for booking engines, session state management, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our flydubai.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, booking engine session state, and XHR interception.
We maintain pools of residential ISP proxies globally. Rotation happens per-session with sticky routing to maintain search context through to the pricing matrix.
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 flydubai.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing is generally permissible. DataFlirt targets only public, non-authenticated route and fare data. We do not extract personal data or circumvent authentication walls. Clients should review Flydubai's ToS 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 manage sticky sessions precisely to navigate the booking engine without triggering WAF blocks.
Yes, we can configure the origin currency preference to extract pricing in AED, USD, EUR, or any supported local currency.
Real-time streaming pipelines achieve sub-60-minute latency for defined O&D pairs. Full network schedule refreshes complete within a 4-8 hour window depending on scale.
Yes, the schema flags operating carriers and code-share status, allowing you to filter for flights operated by Emirates versus Flydubai metal.
Our smallest packages start at a defined list of O&D routes with daily delivery. For full network extraction or high-frequency intraday polling, we price based on volume and compute requirements.
We capture public scarcity signals like 'Only 2 seats left at this price' which serve as strong proxies for load factors and booking velocity.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route schedule dump or a continuous fare-monitoring feed across 1,000 O&D pairs — we scope, build, and operate the pipeline. Tell us what you need.
