We extract flight schedules, dynamic pricing, seat availability, route networks, and FlySmiLes loyalty data from srilankan.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 srilankan.com. All fields typed and schema-versioned.
"flight_number": "UL141", "origin_iata": "CMB", "destination_iata": "BOM", "departure_time": "2023-11-14T23:45:00Z", "arrival_time": "2023-11-15T02:10:00Z", "duration_minutes": 145, "aircraft_type": "Airbus A320neo", "operated_by": "SriLankan Airlines"
| # | flight_number | origin_iata | destination_iata | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from srilankan.com. All fields typed and schema-versioned.
"flight_number": "UL141", "cabin_class": "Economy", "fare_family": "Economy Value", "currency": "LKR", "base_fare": 45000.0, "taxes_fees": 12500.0, "total_price": 57500.0, "tickets_remaining": 4
| # | flight_number | cabin_class | fare_family | currency | base_fare | taxes_fees |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from srilankan.com. All fields typed and schema-versioned.
"flight_number": "UL141", "cabin_class": "Business", "total_capacity": 12, "available_seats": 3, "seat_pitch_inches": 45, "seat_width_inches": 21, "layout": "2-2", "power_outlets": true
| # | flight_number | cabin_class | total_capacity | available_seats | seat_pitch_inches | seat_width_inches |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Routes & Network objects from srilankan.com. All fields typed and schema-versioned.
"origin_airport": "Colombo Bandaranaike (CMB)", "destination_airport": "London Heathrow (LHR)", "distance_km": 8720, "weekly_frequency": 7, "direct_flight": true, "codeshare_partners": "['Qatar Airways', 'Malaysia Airlines']"
| # | origin_airport | destination_airport | distance_km | weekly_frequency | direct_flight | codeshare_partners |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for FlySmiLes Data objects from srilankan.com. All fields typed and schema-versioned.
"route": "CMB-LHR", "cabin_class": "Economy", "miles_required_redemption": 45000, "miles_required_upgrade": 30000, "miles_earned_base": 2715, "tier_bonus_silver": 678, "tier_bonus_gold": 1357, "tier_bonus_platinum": 2715
| # | route | cabin_class | miles_required_redemption | miles_required_upgrade | miles_earned_base | tier_bonus_silver |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our srilankan.com scraper navigates complex booking flows, dynamic price calendars, and multi-currency pricing models. We handle the session state management required to extract deep fare data without triggering anti-bot protections.
Extract origin, destination, departure, arrival, duration, and aircraft type for all active routes and seasonal schedules.
Capture base fares, taxes, surcharges, and total prices across multiple currencies. Monitor price fluctuations over time.
Parse seat availability, remaining ticket warnings, cabin layouts, and fare family distinctions (e.g., Economy Promo vs Economy Value).
Identify flights operated by Oneworld partners or other codeshare airlines, extracting the underlying operating carrier details.
Extract checked baggage allowances, excess baggage fees, and seat selection costs associated with specific fare classes.
Track mileage accrual rates, redemption charts, and upgrade requirements across all routes and elite tier levels.
Extract 30-day or 90-day price matrices to identify the cheapest departure dates and seasonal pricing trends.
Simulate searches from different geographic regions to expose PoS-specific pricing and localized inventory availability.
Run continuous pipelines that only emit records when flight times change or fare buckets shift, reducing downstream processing load.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, or specific flight numbers. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for srilankan.com.
Schema validation, null-rate checks, price-outlier detection, and sample schedules before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airline websites employ strict rate limiting and complex session states. Here is how we maintain pipeline stability against srilankan.com.
Extracting fare data requires progressing through multi-step booking funnels. We maintain strict cookie jars and session states across Playwright instances to simulate legitimate user journeys without triggering session timeouts or bot flags.
Airlines use sophisticated WAFs (like Akamai or Cloudflare) to block automated scraping. We utilise residential ISP proxies and spoof TLS/browser fingerprints to blend in with legitimate passenger traffic.
Matrix views and dynamic pricing widgets rely heavily on client-side JavaScript. We execute full browser sessions to ensure all asynchronous XHR requests complete before extracting the DOM.
Fares display differently based on point of sale and user selection. We force specific currency parameters via URL or session cookies, ensuring all exported data is normalised to your target currency (e.g., USD or LKR).
Airlines frequently update their booking engine UI. Our observability stack monitors for schema drift, null-rate spikes in critical fields like base_fare, and alerts our engineering team before your downstream systems are affected.
Online travel agencies ingest direct pricing and schedule data to supplement GDS feeds and offer comprehensive booking options.
Competitor airlines and revenue management teams track SriLankan Airlines' fare adjustments on overlapping routes to optimise their own pricing strategies.
Aviation consultancies analyse schedule frequencies, aircraft deployment, and codeshare utilisation to assess route profitability and market share.
Enterprise travel managers monitor flight availability and historical pricing trends to negotiate corporate rates and optimise travel budgets.
Frequent flyer program analysts track FlySmiLes accrual and redemption rates to benchmark against competing Oneworld or regional loyalty programs.
Travel risk management firms track schedule changes, delays, and equipment swaps to alert corporate clients of potential travel disruptions.
"Airline pricing is the original dynamic market. Extracting fare buckets directly from the carrier provides visibility that GDS feeds often obscure or delay."
Building a reliable scraper for an airline booking engine is notoriously difficult. It requires managing complex session states, rendering heavy JavaScript applications, and bypassing aggressive WAF protections. DataFlirt handles the infrastructure, delivering clean, normalised aviation data directly to your warehouse.
Everything supported by our srilankan.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 within the booking engine.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions required to maintain booking flow state.
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 srilankan.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible under applicable law, provided it does not disrupt the target servers or extract personally identifiable information (PII). DataFlirt targets only public, non-authenticated route and fare data. We do not extract PNRs or individual FlySmiLes account details. Clients should review SriLankan Airlines' ToS and consult legal counsel for specific use cases.
Airline booking engines use strict WAFs. We use residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and strict session management to simulate legitimate booking flows without triggering rate limits.
Yes. Depending on the scale of the route list, we can configure pipelines to poll specific origin-destination pairs at high frequency (e.g., hourly) to capture intraday fare bucket shifts and yield management adjustments.
Yes. We can simulate points of sale or inject specific currency parameters to extract pricing in your required currency, normalising the output for downstream analysis.
We extract public tier requirements, mileage accrual charts, and redemption tables. We do not support scraping individual user account balances, as this requires authentication and handles PII.
Our minimum engagement typically starts at monitoring a defined set of routes (e.g., top 50 origin-destination pairs) with daily delivery. Pricing scales based on the volume of searches and delivery frequency.
DataFlirt builds forward-looking data pipelines. We do not sell pre-existing historical datasets. Historical time-series data begins accumulating from the day your pipeline is commissioned.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily schedule export or continuous fare monitoring across the SriLankan Airlines network — we scope, build, and operate the pipeline. Tell us what you need.
