We extract flight schedules, dynamic fare pricing, seat availability, and route metadata from Bangkok Airways. 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 bangkokair.com. All fields typed and schema-versioned.
"flight_number": "PG211", "origin_code": "BKK", "destination_code": "USM", "departure_time": "2024-11-12T08:00:00+07:00", "arrival_time": "2024-11-12T09:10:00+07:00", "duration_minutes": 70, "aircraft_type": "Airbus A319", "stops": 0, "operated_by": "Bangkok Airways"
| # | flight_number | origin_code | destination_code | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Fare Pricing objects from bangkokair.com. All fields typed and schema-versioned.
"flight_number": "PG211", "departure_date": "2024-11-12", "fare_class": "Web Saver", "price_total": 3250.0, "price_base": 2800.0, "taxes_fees": 450.0, "currency": "THB", "seats_remaining": 4, "refundable": false
| # | flight_number | departure_date | fare_class | fare_basis | price_total | price_base |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Route Intelligence objects from bangkokair.com. All fields typed and schema-versioned.
"origin_airport": "Suvarnabhumi Airport", "destination_airport": "Samui International Airport", "direct_flight": true, "codeshare_partners": "['Emirates', 'Qatar Airways']", "frequency_weekly": 42, "distance_km": 466
| # | origin_airport | destination_airport | distance_km | frequency_weekly | direct_flight | connection_airport |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Baggage & Ancillaries objects from bangkokair.com. All fields typed and schema-versioned.
"fare_class": "Web Promo", "checked_baggage_kg": 20, "cabin_baggage_kg": 5, "lounge_access": true, "meal_included": true, "change_fee": 1500.0, "cancellation_fee": -1.0
| # | fare_class | checked_baggage_kg | cabin_baggage_kg | lounge_access | meal_included | seat_selection_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Availability & Status objects from bangkokair.com. All fields typed and schema-versioned.
"flight_number": "PG211", "flight_date": "2024-11-12", "status": "Scheduled", "on_time_performance_pct": 92.4, "delay_minutes": 0, "gate_departure": "A4", "waitlist_available": false
| # | flight_number | flight_date | status | on_time_performance_pct | delay_minutes | gate_departure |
|---|---|---|---|---|---|---|
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Our infrastructure bypasses flight search rate limits and session expirations to deliver structured airline pricing and scheduling data without manual intervention.
Extract departure times, arrival times, flight durations, aircraft types, and stopover details for all domestic and international routes.
Monitor base fares, taxes, and total prices across Web Promo, Web Saver, and Web Freedom classes.
Capture 'seats remaining' thresholds and sold-out statuses to model demand curves and load factors.
Map baggage allowances, cancellation fees, modification penalties, and lounge access rules per fare class.
Extract pricing in THB, USD, EUR, or local currencies based on point-of-sale configurations.
Identify flights operated by partners (e.g., Emirates, Qatar) versus Bangkok Airways metal.
Scan availability calendars up to 330 days in advance to build predictive pricing models.
Track volatile routes with sub-hourly polling to capture flash sales and yield management adjustments.
Extract complex itineraries and connection logic through BKK and USM hubs.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and frequency requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for bangkokair.com.
Schema validation, null-rate checks, price-outlier detection, and sample routes before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airline booking engines utilise strict session controls and rate limiting. Here is how we maintain stable data extraction.
Flight search endpoints require valid session tokens and cookies. We maintain active browser sessions, automatically refreshing tokens and handling expirations before they interrupt the extraction flow.
Airlines aggressively block datacentre IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Instead of parsing complex HTML, we intercept the underlying JSON payloads powering the booking engine, ensuring higher accuracy for tax breakdowns and seat counts.
We distribute search queries across wide proxy pools and control concurrency to avoid triggering rate limits while maintaining high extraction throughput.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and schema drift — and respond before you notice.
Online travel agencies cache flight schedules and baseline pricing to reduce API calls to GDS providers.
Competing airlines monitor Web Saver and Web Promo fare adjustments on overlapping routes to optimise their own yield management.
Metasearch engines index direct booking prices to compare against third-party agent offers.
Aviation analysts track route frequencies, code-share density, and aircraft deployment to model regional market share.
Enterprise travel platforms ingest schedule data to optimise employee routing and enforce corporate booking policies.
Financial analysts correlate seat availability trends and pricing volatility with macroeconomic tourism indicators.
"Airline pricing is highly dynamic, yet critical for market intelligence. We convert complex booking flows into queryable datasets."
Extracting data from airline booking engines requires managing session state, bypassing rate limits, and parsing complex tax structures. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our bangkokair.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 regional locations. 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 bangkokair.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing is generally permissible. DataFlirt targets only public, non-authenticated route and fare data. We do not extract personal data or circumvent authentication walls. Clients should review terms of service and consult legal counsel for specific use cases.
Our infrastructure maintains active session tokens and automatically refreshes cookies. If a session expires mid-extraction, the crawler seamlessly re-initialises the search parameters to resume data capture without data loss.
Yes. We intercept the underlying data payloads to separate base fares from airport taxes, carrier surcharges, and optional fees, providing a clean financial breakdown.
Pipelines can be configured for sub-hourly polling on high-priority routes, capturing yield management adjustments and flash sales as they occur.
Yes. The operating carrier is explicitly mapped for every flight segment, allowing you to distinguish between Bangkok Airways metal and partner operations.
Our packages start at a defined list of origin-destination pairs with daily delivery. For broader network coverage or high-frequency polling, we price based on request volume and compute requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily schedule export or continuous fare monitoring across specific routes — we scope, build, and operate the pipeline. Tell us what you need.
