We extract flight schedules, dynamic pricing signals, airline metadata, and route availability from Cheapflights. 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 Itineraries objects from cheapflights.com. All fields typed and schema-versioned.
"itinerary_id": "CF-LHR-JFK-8492", "departure_airport": "LHR", "arrival_airport": "JFK", "departure_time": "2026-08-14T09:30:00Z", "arrival_time": "2026-08-14T12:15:00Z", "duration_minutes": 465, "stops": 0, "operating_airline": "British Airways", "cabin_class": "Economy"
| # | itinerary_id | departure_airport | arrival_airport | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from cheapflights.com. All fields typed and schema-versioned.
"itinerary_id": "CF-LHR-JFK-8492", "total_price": 482.5, "currency": "GBP", "provider_name": "Expedia", "fare_type": "Basic Economy", "refundable": false, "change_fee": 150.0, "price_timestamp": "2026-05-12T10:14:00Z"
| # | itinerary_id | base_price | taxes_fees | total_price | currency | provider_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Details objects from cheapflights.com. All fields typed and schema-versioned.
"route_id": "LHR-CDG-DXB", "origin_airport": "LHR", "dest_airport": "DXB", "layover_airports": "['CDG']", "layover_duration_minutes": 125, "operating_carrier": "Air France", "alliance": "SkyTeam"
| # | route_id | origin_airport | dest_airport | layover_airports | layover_duration_minutes | total_distance_km |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Baggage & Policies objects from cheapflights.com. All fields typed and schema-versioned.
"itinerary_id": "CF-LHR-JFK-8492", "carry_on_allowance": 1, "checked_allowance": 0, "extra_bag_fee": 65.0, "seat_selection_fee": 25.0, "cancellation_window_hours": 24, "refund_method": "Voucher"
| # | itinerary_id | carry_on_allowance | checked_allowance | extra_bag_fee | seat_selection_fee | boarding_priority |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Provider Comparisons objects from cheapflights.com. All fields typed and schema-versioned.
"itinerary_id": "CF-LHR-JFK-8492", "provider_name": "Booking.com", "provider_type": "OTA", "price": 490.0, "currency": "GBP", "booking_type": "Instant", "deep_link": "https://cheapflights.com/book/...", "mobile_only_price": false
| # | itinerary_id | provider_name | provider_type | price | currency | deep_link |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Cheapflights scraper handles complex multi-city searches, dynamic OTA pricing comparisons, and intricate baggage policies — with JavaScript rendering, IP geo-targeting, and session management built in.
Extract departure times, arrival times, layovers, operating airlines, and aircraft types across single, return, and multi-city searches.
Capture base fares, taxes, and total prices across multiple Online Travel Agencies (OTAs) and direct airline providers.
Simulate searches from specific countries to capture region-locked pricing and currency variations.
Extract cabin class restrictions, checked baggage allowances, seat selection fees, and cancellation policies.
Capture flight emission estimates and eco-friendly badges to build sustainability models.
Extract direct booking URLs to OTAs and airline sites for affiliate tracking and price verification.
Scrape grid pricing for +/- 3 days to identify the cheapest departure and return combinations.
Run one-off route exports or configure continuous pipelines at hourly intervals for high-volatility routes.
Map complex airline fare buckets (Basic Economy, Premium, Business) into a standardised schema.
Brief in. Clean data out.
Provide origin/destination pairs, date ranges, and cabin classes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, geo-targeted proxy rotation, and CAPTCHA handling for cheapflights.com.
Schema validation, null-rate checks, price-outlier detection, and sample itineraries before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators rely on heavy JavaScript execution and strict bot mitigation. Here's how we ensure reliable data delivery.
Travel aggregators block data centre IPs to protect OTA pricing. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Cheapflights search results are entirely JavaScript-rendered and rely on background WebSocket polling to aggregate OTA prices. We run full Playwright browser sessions to capture the final loaded state.
Airlines and OTAs alter pricing based on the searcher's location. We route requests through region-specific residential proxies to capture accurate local pricing and currency conversions.
A/B testing on travel sites frequently alters DOM structures. Our selector strategy uses multiple fallback chains per field, ensuring that a layout change doesn't break your data pipeline.
Because Cheapflights fetches data from hundreds of OTAs in real-time, results load asynchronously over 10-20 seconds. Our crawlers implement intelligent wait states to ensure the complete dataset is captured before extraction.
Airlines and OTAs monitor competitor pricing, fare class availability, and ancillary fees to optimise their own revenue management systems.
Meta-search engines and corporate travel platforms enrich their own inventories with aggregated OTA pricing and route availability.
Aviation analysts track flight frequencies, layover patterns, and operating carriers to identify underserved routes and market opportunities.
Travel agencies use webhook alerts for price drops on high-value routes to automatically reprice consumer-facing packages.
Investors track OTA visibility and pricing competitiveness across key routes to evaluate travel sector performance.
ML teams use historical pricing datasets to train predictive models for flight price forecasting and demand generation.
"Cheapflights aggregates global aviation data and OTA pricing — but querying it programmatically requires dedicated infrastructure."
Most teams underestimate the investment required: reliable Cheapflights scraping requires residential proxies spanning multiple geographies, full JavaScript rendering for dynamic search results, CAPTCHA handling, and complex DOM parsing. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our cheapflights.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 asynchronous polling flows.
We maintain pools of residential ISP proxies across global regions to ensure accurate geo-targeted pricing. Rotation happens per-request with sticky sessions where required.
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 cheapflights.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible under applicable law. DataFlirt targets only public, non-authenticated itinerary and OTA pricing data. We do not extract personal data or circumvent authentication walls. Clients should review Cheapflights ToS and consult legal counsel for specific use cases.
Cheapflights aggregates prices from OTAs over 10-20 seconds. We use full Playwright browser sessions with intelligent DOM polling to wait until network requests settle and all OTA prices are fully rendered before extraction.
Yes. We route requests through residential proxies in specific target countries (e.g., UK, US, IN) to capture the exact pricing and currency presented to users in that region.
Flight pricing is highly volatile. We can configure pipelines to run hourly for high-priority routes, capturing intraday price fluctuations and availability changes. Standard catalogue refreshes run daily.
Yes. We extract cabin class restrictions, carry-on allowances, checked baggage fees, and cancellation policies where surfaced by the aggregator.
Our smallest packages start at a defined route list (typically 500-5,000 origin/destination pairs) with daily delivery. For larger matrices or custom schema requirements, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off historical pricing dump or a continuous feed across 50,000 routes — we scope, build, and operate the pipeline. Tell us what you need.
