We extract flight schedules, pricing signals, fare matrices, and seat availability from Philippine 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 philippineairlines.com. All fields typed and schema-versioned.
"flight_number": "PR104", "origin": "MNL", "destination": "SFO", "departure_time": "2026-10-12T22:30:00Z", "arrival_time": "2026-10-12T19:45:00Z", "duration_minutes": 795, "aircraft_type": "Boeing 777-300ER", "operating_carrier": "Philippine Airlines"
| # | flight_number | origin | destination | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from philippineairlines.com. All fields typed and schema-versioned.
"flight_number": "PR104", "departure_date": "2026-10-12", "currency": "PHP", "economy_supersaver": 42500.0, "economy_saver": 48900.0, "economy_flex": 56200.0, "business_value": 145000.0, "tax_breakdown": 4500.0
| # | flight_number | departure_date | currency | economy_supersaver | economy_saver | economy_flex |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from philippineairlines.com. All fields typed and schema-versioned.
"flight_number": "PR104", "date": "2026-10-12", "cabin_class": "Economy", "seats_remaining": 4, "waitlist_status": false, "booking_class_code": "O", "equipment_change": false
| # | flight_number | date | cabin_class | seats_remaining | waitlist_status | seat_map_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from philippineairlines.com. All fields typed and schema-versioned.
"origin_airport": "MNL", "destination_airport": "JFK", "distance_miles": 8520, "direct_flight": false, "stopover_airports": "['YVR']", "frequency_per_week": 3, "seasonal_route": false
| # | origin_airport | destination_airport | distance_miles | direct_flight | stopover_airports | frequency_per_week |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Flight Status objects from philippineairlines.com. All fields typed and schema-versioned.
"flight_number": "PR112", "scheduled_departure": "2026-05-12T08:00:00Z", "estimated_departure": "2026-05-12T08:15:00Z", "status": "Delayed", "terminal": "Terminal 1", "gate": "A4", "delay_minutes": 15
| # | flight_number | scheduled_departure | estimated_departure | actual_departure | scheduled_arrival | status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Philippine Airlines scraper navigates complex booking engines, session management requirements, and strict anti-bot systems to deliver structured fare and schedule data.
Extract schedules and availability across the entire Philippine Airlines domestic and international network.
Capture pricing across all tiers: Economy Supersaver, Saver, Value, Flex, Premium Economy, and Business Class.
Extract baggage allowances, seat selection fees, and meal options tied to specific fare codes.
Monitor fare changes over time with high-frequency scraping for specific O&D (Origin and Destination) pairs.
Capture base fares, taxes, and surcharges in PHP, USD, or any supported local currency.
Track required miles for award tickets and upgrades across different routes and dates.
Monitor departure times, arrival times, delays, and gate changes for operational dashboards.
Distinguish between flights operated by PAL, PAL Express, and international code-share partners.
Configure pipelines to poll specific routes at hourly intervals for competitive intelligence.
Brief in. Clean data out.
Provide O&D pairs, date ranges, and required data points. We design the extraction schema together.
We configure Scrapy crawlers, Playwright sessions, and proxy rotation for philippineairlines.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage.
Airlines employ aggressive bot mitigation and complex session states. Here is how we maintain data flow.
Airlines use advanced web application firewalls. We use residential proxies and realistic browser fingerprints to bypass Akamai and Cloudflare protections.
Fare matrices require sequential requests. Our Playwright scripts maintain cookie state and session tokens throughout the search process.
The booking engine relies heavily on client-side rendering. We execute the full JavaScript bundle to extract data that simple HTTP clients miss.
We automate the calendar selection matrix to extract +/- 3 day pricing grids in a single session, reducing total request volume.
Airline fare rules are notoriously complex. We map raw fare codes into a clean, normalised schema ready for immediate database ingestion.
Online travel agencies integrate direct pricing and availability feeds to supplement GDS data.
Rival airlines monitor pricing strategies on overlapping routes to adjust their own revenue management models.
Booking tools capture fare families and baggage rules to enforce corporate travel policies.
Market researchers analyse route frequency and pricing trends to forecast regional travel demand.
Tour operators combine real-time flight pricing with hotel inventory to build custom holiday packages.
Insurers and logistics firms track flight status and delays to trigger automated compensation or rerouting.
"Philippine Airlines operates a complex dynamic pricing engine. Capturing accurate fare families across their network requires persistent session management and residential proxy infrastructure."
Most teams underestimate the investment required: reliable airline scraping requires handling strict bot mitigation, maintaining booking flow session state, and parsing complex fare matrices. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our philippineairlines.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. 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 philippineairlines.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We use a combination of ISP-grade residential proxies, realistic browser fingerprinting via Playwright, and algorithmic pacing to navigate the site without triggering blocks.
For targeted O&D pairs, we can configure pipelines to poll pricing and availability at hourly intervals. Full network sweeps are typically run on a daily cadence.
Yes. We extract the base fare, government taxes, airport fees, and carrier-imposed surcharges as separate fields in the JSON payload.
Yes. We can extract the required miles for award flights and upgrades across the public booking engine.
Our selector strategy uses multiple fallback chains. If a major DOM change occurs, our monitoring stack alerts our engineers, and we update the parsers within our SLA window.
Data is extracted at the time of the crawl. For real-time requirements, we can configure webhook delivery to push pricing updates the moment they are captured.
No. We extract all data from the public-facing website. We do not require any GDS credentials or API access.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily route network dump or high-frequency pricing updates across key O&D pairs, we scope, build, and operate the pipeline. Tell us what you need.
