We extract flight schedules, dynamic pricing, fare tiers, and seat availability from Turkish Airlines. 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 turkishairlines.com. All fields typed and schema-versioned.
"flight_number": "TK1980", "origin": "LHR", "destination": "IST", "departure_time": "2026-08-14T16:30:00Z", "arrival_time": "2026-08-14T22:20:00Z", "duration": "230", "aircraft_type": "Boeing 777-300ER", "operating_airline": "Turkish Airlines"
| # | flight_number | origin | destination | departure_time | arrival_time | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from turkishairlines.com. All fields typed and schema-versioned.
"flight_number": "TK1980", "date": "2026-08-14", "currency": "GBP", "ecofly_price": 185.5, "extrafly_price": 215.5, "primefly_price": 265.5, "business_price": 890.0, "tax_amount": 65.2
| # | flight_number | date | currency | ecofly_price | extrafly_price | primefly_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route & Network objects from turkishairlines.com. All fields typed and schema-versioned.
"origin_code": "LHR", "destination_code": "IST", "distance": 2495, "direct_flight": true, "layover_airport": "None", "layover_duration": 0, "frequency_per_week": 42, "seasonal_route": false
| # | origin_code | destination_code | distance | direct_flight | layover_airport | layover_duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Baggage & Amenities objects from turkishairlines.com. All fields typed and schema-versioned.
"flight_number": "TK1980", "cabin_class": "EcoFly", "cabin_baggage_kg": 8, "checked_baggage_kg": 23, "meal_included": true, "wifi_available": true, "entertainment": "Seatback screen", "power_outlets": true
| # | flight_number | cabin_class | cabin_baggage_kg | checked_baggage_kg | meal_included | wifi_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Seat Availability objects from turkishairlines.com. All fields typed and schema-versioned.
"flight_number": "TK1980", "departure_date": "2026-08-14", "economy_seats_left": 4, "business_seats_left": 12, "overbooked_status": false, "exit_row_available": true, "upgrade_eligible": true, "seat_map_url": "https://turkishairlines.com/seatmap/TK1980"
| # | flight_number | departure_date | economy_seats_left | business_seats_left | overbooked_status | seat_map_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the complex booking flows: multi-leg itineraries, dynamic fare rendering, session tokens, and IP rate limits, with full JavaScript execution built in.
Origin, destination, layovers, and code-share details across the entire Turkish Airlines network.
Capture EcoFly, ExtraFly, PrimeFly, and Business class prices simultaneously for accurate revenue mapping.
Monitor seat counts and 'few seats left' indicators to model load factors and demand curves.
Extract departure times, arrival times, block times, and aircraft type for any given date range.
Track baggage allowances, seat selection fees, and meal inclusions per fare tier.
Parse complex layover details, connecting flight numbers, and transit times at Istanbul Airport (IST).
Extract pricing in TRY, USD, EUR, or GBP by manipulating regional headers and session cookies.
Maintain valid search tokens and bypass bot protection using residential proxies.
Run continuous pipelines to track price volatility on high-yield routes leading up to departure.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and cabin classes. We design the extraction schema together.
We configure Playwright crawlers, regional proxy rotation, session handling, and bot circumvention for turkishairlines.com.
Schema validation, null-rate checks, price-outlier detection, and itinerary 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 to protect pricing data. Here is how we stay resilient.
Airline booking engines use bot protection to block automated searches. Our crawlers use residential ISP proxies with realistic browser fingerprints, maintaining valid search session tokens.
Turkish Airlines' search results are heavily JavaScript-rendered single-page applications. We run full Playwright browser sessions to execute JS, handle loading states, and hydrate fare matrices.
Flight searches require maintaining state across multiple API calls. We manage cookies, CSRF tokens, and search IDs to ensure complete itinerary extraction without session timeouts.
For large route networks, we maintain a hash index of last-seen fares. 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, and coverage drops. SLA uptime is contractual, not aspirational.
Online travel agencies integrate direct pricing feeds to validate GDS data and display accurate fare tiers.
Rival airlines monitor pricing on overlapping routes to adjust their own dynamic pricing algorithms.
Enterprise travel platforms track historical price curves to predict optimal booking windows for corporate clients.
Aviation analysts track flight frequencies, aircraft types, and load indicators to model route profitability.
Tour operators combine real-time flight pricing with hotel data to generate dynamic holiday packages.
Consultancies monitor capacity changes and new route launches to assess market share shifts at key hubs like IST.
"Airlines obscure their dynamic pricing algorithms behind complex booking flows and bot protection. Extracting this data requires sophisticated session management, not just simple HTTP requests."
Most teams underestimate the investment required: reliable airline scraping requires residential proxies, full JavaScript rendering, session token 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 turkishairlines.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 (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 turkishairlines.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and schedule data is generally permissible under applicable law, provided it does not breach terms of service in a legally binding manner or cause technical harm. DataFlirt targets only public, non-authenticated search results. We do not extract personal data or circumvent authentication walls. Clients should review Turkish Airlines' 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. This ensures our requests are treated as legitimate user traffic.
Yes. Our parsers capture the full fare matrix, including EcoFly, ExtraFly, PrimeFly, and Business class pricing for every flight option presented in the search results.
Real-time streaming pipelines achieve sub-15-minute latency for price and availability signals on a defined route set. Full network refreshes at daily cadence complete within a 4-8 hour window depending on size.
We extract the seat availability indicators displayed on the frontend, which serves as a reliable proxy for load factor and demand.
Our smallest packages start at a defined route list (typically 500-2,000 origin-destination pairs) with daily delivery. For larger networks or high-frequency polling, we price based on volume and delivery cadence.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily schedule export or a high-frequency price-monitoring feed across 5,000 routes, we scope, build, and operate the pipeline. Tell us what you need.
