We extract flight schedules, dynamic pricing, fare classes, route networks, and baggage policies from omanair.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 omanair.com. All fields typed and schema-versioned.
"flight_number": "WY 283", "origin": "MCT", "destination": "BLR", "departure_time": "2026-10-12T08:45:00Z", "arrival_time": "2026-10-12T13:30:00Z", "duration": "285", "aircraft_type": "Boeing 737 MAX 8", "operating_carrier": "Oman Air"
| # | flight_number | origin | destination | departure_time | arrival_time | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from omanair.com. All fields typed and schema-versioned.
"flight_number": "WY 283", "fare_class": "Economy Lite", "price": 14250.0, "currency": "INR", "taxes": 3450.0, "base_fare": 10800.0, "sindbad_miles": 1200, "price_timestamp": "2026-05-12T09:14:00Z"
| # | flight_number | fare_class | price | currency | taxes | base_fare |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from omanair.com. All fields typed and schema-versioned.
"origin_airport": "LHR", "destination_airport": "BKK", "direct_flight": false, "layover_airport": "MCT", "layover_duration": "145", "total_duration": "980", "frequency": "Daily", "distance_miles": 5940
| # | origin_airport | destination_airport | direct_flight | layover_airport | layover_duration | total_duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Baggage & Policies objects from omanair.com. All fields typed and schema-versioned.
"flight_number": "WY 283", "fare_type": "Economy Prime", "cabin_baggage": "7kg", "checked_baggage_kg": 30, "change_fee": 0.0, "cancellation_fee": 5000.0, "lounge_access": false, "priority_boarding": false
| # | flight_number | fare_type | cabin_baggage | checked_baggage_kg | extra_baggage_fee | change_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from omanair.com. All fields typed and schema-versioned.
"flight_number": "WY 283", "date": "2026-10-12", "cabin_class": "Business", "seats_remaining": 4, "exit_row_available": false, "bassinet_available": true, "upgrade_eligible": true, "scraped_at": "2026-05-12T09:14:33Z"
| # | flight_number | date | cabin_class | seats_remaining | seat_map_url | exit_row_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our airline scraper handles every layer of the booking platform: flight schedules, dynamic pricing, fare classes, and route networks, with JavaScript rendering and anti-bot circumvention built in.
Extract departure times, arrival times, durations, aircraft types, and operating carriers for all active routes.
Capture base fares, taxes, and total prices across all cabin classes, timestamped per crawl.
Extract pricing in OMR, INR, GBP, EUR, and other supported currencies directly from the booking engine.
Map Economy Lite, Economy Prime, Business, and First Class fare conditions and availability.
Track miles required for redemption flights and upgrades across the network.
Identify flights operated by partner airlines under Oman Air flight numbers.
Extract checked baggage allowances, cabin baggage limits, and excess baggage fees per fare type.
Log specific aircraft models assigned to routes for capacity and comfort analysis.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and required currencies. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for omanair.com.
Schema validation, null-rate checks, price-outlier detection, and sample payloads 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 pricing data. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
Airline bot detection operates on TLS fingerprints, browser headers, and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management.
Oman Air booking flows are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering, capturing data that headless HTTP clients miss entirely.
Flight searches require maintaining complex session states across multiple requests. We handle token negotiation and cookie persistence to ensure valid search results without triggering rate limits.
For large route catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops, and respond before you notice.
OTAs and competing airlines monitor pricing and fare class availability to optimise their own pricing strategies.
Network planners analyse frequency, aircraft deployment, and layover connections through the Muscat hub.
Travel aggregators use direct scraping to supplement GDS feeds, capturing lower-tier fares and web-only promotions.
Analysts track route expansion, seasonal frequency adjustments, and capacity changes in the Middle East aviation market.
Revenue management teams correlate seat availability signals and pricing curves with market demand models.
Airlines benchmark baggage policies, change fees, and lounge access inclusions against Oman Air fare families.
"Oman Air operates a critical network connecting the Middle East with Asia and Europe. Extracting this pricing data requires bypassing complex bot mitigation."
Most teams underestimate the investment required: reliable airline scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our omanair.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. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
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 omanair.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and schedule information is generally permissible. DataFlirt targets only public, non-authenticated flight data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review airline 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. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline.
Yes. We can configure the pipeline to request pricing in OMR, INR, GBP, EUR, USD, or any other currency supported by the Oman Air booking engine.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined route set. Full network refreshes complete within a 4-8 hour window depending on size.
Yes. We extract remaining seat counts for specific cabin classes as displayed during the booking flow, providing signals for load factor estimation.
Our smallest packages start at a defined route list with daily delivery. For larger networks or custom schema requirements, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route schedule export or a continuous price-monitoring feed across the entire network, we scope, build, and operate the pipeline. Tell us what you need.
