We extract schedule availability, dynamic fare pricing, route maps, and ancillary fees from Egyptair. 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 egyptair.com. All fields typed and schema-versioned.
"flight_number": "MS777", "origin": "CAI", "destination": "LHR", "departure_time": "2026-08-14T09:10:00Z", "arrival_time": "2026-08-14T13:35:00Z", "duration": "5h 25m", "aircraft_type": "Boeing 777-300ER", "stops": 0, "operated_by": "Egyptair"
| # | flight_number | origin | destination | departure_time | arrival_time | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from egyptair.com. All fields typed and schema-versioned.
"flight_number": "MS777", "departure_date": "2026-08-14", "fare_class": "Economy Best Offer", "cabin_class": "Economy", "price": 412.5, "currency": "GBP", "tax_amount": 85.0, "base_fare": 327.5, "total_fare": 412.5
| # | flight_number | departure_date | fare_class | cabin_class | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Availability objects from egyptair.com. All fields typed and schema-versioned.
"origin_airport": "CAI", "dest_airport": "LHR", "date": "2026-08-14", "available_seats": 9, "status": "Scheduled", "connection_airport": "None", "layover_duration": "None", "days_of_operation": "Daily", "route_id": "CAI-LHR-MS777"
| # | origin_airport | dest_airport | date | available_seats | status | connection_airport |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary & Baggage objects from egyptair.com. All fields typed and schema-versioned.
"flight_number": "MS777", "fare_type": "Economy Good", "cabin_baggage": "1 x 8kg", "checked_baggage": "2 x 23kg", "seat_selection_fee": 15.0, "refund_policy": "Permitted with fee", "change_fee": 50.0, "meal_included": true
| # | flight_number | fare_type | cabin_baggage | checked_baggage | seat_selection_fee | refund_policy |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fleet & Aircraft objects from egyptair.com. All fields typed and schema-versioned.
"aircraft_code": "77W", "aircraft_model": "777-300ER", "manufacturer": "Boeing", "total_capacity": 346, "business_seats": 49, "economy_seats": 297, "wifi_available": true, "power_outlets": true
| # | aircraft_code | aircraft_model | manufacturer | total_capacity | business_seats | economy_seats |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Egyptair scraper handles every layer of the booking platform: flight schedules, dynamic pricing, route maps, and ancillary fees, with JavaScript rendering, session management, and anti-bot circumvention built in.
Flight numbers, departure and arrival times, durations, aircraft types, and operating carriers scraped across the entire network.
Capture dynamic pricing, base fares, taxes, and total costs across different cabin classes and fare families.
Extract remaining seat counts and cabin class availability for specific flights to gauge route demand.
Baggage allowances, seat selection fees, change penalties, and refund policies tied to specific fare rules.
Extract pricing in EGP, USD, GBP, EUR, and other supported currencies based on point of sale configuration.
Parse complex itineraries, layover durations, and connection airports for multi-leg journeys.
Identify flights operated by Star Alliance partners but marketed under Egyptair flight numbers.
Force fresh availability checks to bypass aggressive CDN caching and retrieve real-time inventory.
Run one-off bulk route exports or configure continuous pipelines at hourly, daily, or real-time cadences.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, or cabin classes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for egyptair.com.
Schema validation, null-rate checks, price-outlier detection, and route coverage verification 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. 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, randomised request timing, and full cookie session management.
Egyptair flight search results are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution, lazy-load triggering, and dynamic price hydration, capturing data that headless HTTP clients miss.
Extracting fare families requires navigating complex, multi-step booking flows. We maintain session state across requests, handling cookies and tokens to reach the final pricing pages without triggering session timeouts.
For large route networks, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost, storage bloat, 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, responding before you notice.
Airlines and OTAs monitor competitor pricing, fare family structures, and dynamic price changes to optimise their own revenue models.
Travel aggregators ingest direct airline pricing to supplement GDS data, ensuring price parity and capturing exclusive web fares.
Aviation analysts track flight frequencies, aircraft deployment, and seat availability to model route demand and profitability.
Consultancies monitor network expansion, seasonal capacity adjustments, and codeshare partnerships to evaluate market share.
Travel management companies track schedule changes, cancellations, and delays to proactively manage corporate client itineraries.
Data science teams use historical fare data to train predictive models for flight price forecasting and demand elasticity.
"Egyptair operates a critical network connecting Africa, Europe, and Asia, but their dynamic pricing and route data remain locked behind complex booking flows unless you build the extraction pipeline."
Most teams underestimate the investment required: reliable airline scraping requires bypassing aggressive bot protection, managing complex multi-step search sessions, maintaining residential proxies, and handling dynamic inventory caching. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our egyptair.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 EG, US, and EU regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 egyptair.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available schedule and pricing information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated flight and fare data. We do not extract personal passenger data, circumvent authentication walls, or access private PNRs. Clients should review the airline'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 monitor for rate spikes in real time and trigger pool rotation or solver queues automatically.
Real-time streaming pipelines achieve sub-15-minute latency for price and availability signals on a defined route set. Full network schedule refreshes at daily cadence complete within a 4-8 hour window depending on size.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per route and departure date for price, cabin availability, and fare rules from the date your pipeline starts.
Yes. We capture the marketing flight number, the operating carrier, and the aircraft type, clearly distinguishing between Egyptair-operated metal and Star Alliance partner flights.
Our smallest packages start at a defined route list (typically 50-500 origin-destination pairs) with daily delivery. For larger networks or custom schema requirements, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 20 routes and departure dates as part of the pre-engagement scoping process, so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off schedule dump or a continuous price-monitoring feed across 10,000 routes, we scope, build, and operate the pipeline. Tell us what you need.
