We extract flight schedules, dynamic pricing, Go Basic to Go Flexi fare tiers, seat availability, and route networks from Cebu Pacific. 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 cebupacificair.com. All fields typed and schema-versioned.
"flight_number": "5J 114", "origin_code": "MNL", "destination_code": "HKG", "departure_time": "2026-08-14T05:40:00Z", "arrival_time": "2026-08-14T08:05:00Z", "duration_minutes": 145, "direct_flight": true, "aircraft_type": "A320neo"
| # | flight_number | origin_code | destination_code | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fares & Bundles objects from cebupacificair.com. All fields typed and schema-versioned.
"flight_number": "5J 114", "departure_date": "2026-08-14", "go_basic_price": 3499.0, "go_easy_price": 4499.0, "go_flexi_price": 5299.0, "currency": "PHP", "seats_remaining": 4, "scraped_at": "2026-06-10T14:22:00Z"
| # | flight_number | departure_date | base_fare | taxes_fees | go_basic_price | go_easy_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Promos & Seat Sales objects from cebupacificair.com. All fields typed and schema-versioned.
"promo_title": "Super Seat Fest", "booking_period_start": "2026-03-03T00:00:00Z", "booking_period_end": "2026-03-05T23:59:59Z", "base_fare_promo": 1.0, "piso_fare_flag": true, "applicable_routes": "['MNL-CEB', 'MNL-DVO', 'CEB-MPH']", "currency": "PHP"
| # | promo_title | booking_period_start | booking_period_end | travel_period_start | travel_period_end | base_fare_promo |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Add-ons & Baggage objects from cebupacificair.com. All fields typed and schema-versioned.
"flight_number": "5J 114", "baggage_20kg_price": 850.0, "baggage_32kg_price": 1400.0, "standard_seat_price": 250.0, "premium_seat_price": 400.0, "ceb_meals_available": true, "currency": "PHP"
| # | flight_number | baggage_20kg_price | baggage_32kg_price | standard_seat_price | premium_seat_price | ceb_meals_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from cebupacificair.com. All fields typed and schema-versioned.
"origin_iata": "MNL", "origin_city": "Manila", "destination_iata": "NRT", "destination_city": "Tokyo", "frequency_per_week": 14, "domestic_route": false, "active_status": true, "last_verified": "2026-06-10"
| # | origin_iata | origin_city | destination_iata | destination_city | frequency_per_week | domestic_route |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our extraction pipeline navigates the Cebu Pacific booking engine, handling session tokens, CAPTCHAs, and dynamic SPA payloads to deliver structured fare and schedule data.
Extract departure times, arrival times, aircraft types, and flight durations across the entire domestic and international network.
Capture real-time pricing for Go Basic, Go Easy, and Go Flexi tiers. Monitor fluctuations based on booking windows and demand.
Track low-stock warnings and remaining seat counts for specific fare classes to gauge route demand and load factors.
Automatically monitor seat sales, Piso Fare events, and promotional base fares across specified route combinations.
Extract pricing for prepaid baggage, seat selection, CEB Meals, and travel insurance add-ons per route.
Capture fares in PHP, USD, JPY, or other local currencies based on origin, normalised into a unified schema.
Run pipelines at hourly or sub-hourly cadences for high-priority routes to capture intra-day yield management adjustments.
Handle complex booking flow session tokens and cookie requirements to access deep fare data without triggering rate limits.
Separate base fares from fuel surcharges, terminal fees, and government taxes for accurate price comparison.
Brief in. Clean data out.
Provide origin-destination pairs, travel date ranges, and polling frequencies. We design the extraction schema.
We configure Playwright crawlers, session handlers, proxy rotation, and anti-bot circumvention for cebupacificair.com.
Schema validation, null-rate checks, and fare anomaly detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines employ aggressive anti-scraping measures to protect their pricing data. Here is how we maintain reliable extraction.
The Cebu Pacific booking engine relies on strict session tokens and cookie validation. Our pipeline manages these stateful interactions, ensuring valid sessions are maintained throughout the search and fare extraction flow.
Airlines block data centre IPs aggressively. We route requests through residential ISP proxies in the Philippines and target markets, mimicking legitimate user traffic to avoid IP bans and rate limiting.
Fares and schedules are loaded via dynamic XHR requests. We use Playwright to execute JavaScript, intercept network payloads, and extract raw JSON data directly from the application layer for maximum reliability.
Airline pricing structures are complex, with base fares, taxes, and optional bundles. We parse and normalise this data into a flat, queryable schema, separating base costs from ancillary fees.
We monitor extraction runs for unexpected null values or massive fare anomalies, alerting our operations team to site layout changes or API payload modifications before they impact your downstream systems.
Online travel agencies monitor direct-channel pricing to adjust their own markups and ensure competitive parity.
Rival airlines track Cebu Pacific fare changes on overlapping routes to optimise their own dynamic pricing algorithms.
Metasearch engines integrate structured schedule and fare data to provide comprehensive flight options to users.
Aviation analysts track route frequencies, capacity changes, and promotional activity to assess market share and regional demand.
Travel management companies ingest schedule and fare data to enforce corporate travel policies and budget limits.
Hospitality groups use forward-looking flight capacity and pricing signals to forecast inbound tourist volumes.
"Cebu Pacific controls the majority of domestic Philippine air traffic, making their dynamic fare data critical for regional OTA pricing models."
Airlines aggressively block automated fare queries. Reliable extraction requires residential proxy rotation, session token management, and reverse engineering of their single page application payloads. DataFlirt handles the extraction infrastructure so your team can focus on yield management and pricing intelligence.
Everything supported by our cebupacificair.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.
Playwright handles the complex JavaScript execution and session state required by the Cebu Pacific booking engine, orchestrated by Scrapy for scale.
We utilise residential ISP proxies mapped to the Philippines and target international markets to ensure access to localised pricing and prevent blocking.
Pipelines scale dynamically on Kubernetes to handle massive parallel searches required for comprehensive route network extraction.
Data delivered to where your team already works — no new tooling required.
About cebupacificair.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available fare and schedule data is generally permissible. DataFlirt extracts only public, non-authenticated information from cebupacificair.com. We do not bypass login walls to access CEB Club accounts or PNR details. Clients should review terms of service and consult legal counsel for their specific use cases.
Our infrastructure orchestrates Playwright browser instances with strict cookie and token management. We rotate sessions and residential IP addresses aggressively to mimic organic user behaviour and avoid triggering rate limits.
Yes. We can configure pipelines to monitor specific routes during promotional periods, capturing discounted base fares and flagging applicable seat sales as soon as they appear in the booking engine.
For targeted route lists, we can run extractions at hourly or sub-hourly cadences. Full network sweeps are typically scheduled daily due to the volume of permutations required.
Yes. We extract the full pricing breakdown, including base fares, taxes, Go Basic/Easy/Flexi bundle costs, prepaid baggage tiers, seat selection fees, and travel insurance.
Yes. We offer sample runs for specific origin-destination pairs and date ranges during the scoping phase, allowing you to validate the schema and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily schedule updates or high-frequency fare monitoring across key routes, we build and operate the extraction infrastructure. Tell us your requirements.
