We extract cruise itineraries, cabin pricing signals, ship metadata, port schedules, and excursion details from Princess Cruises. 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 Itineraries & Voyages objects from princess.com. All fields typed and schema-versioned.
"voyage_id": "V314", "title": "7-Day Inside Passage", "destination": "Alaska", "ship_name": "Discovery Princess", "duration_days": 7, "embarkation_port": "Seattle, Washington", "departure_date": "2025-05-14", "base_price": 749.0
| # | voyage_id | title | destination | ship_name | duration_days | embarkation_port |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Cabin Pricing objects from princess.com. All fields typed and schema-versioned.
"voyage_id": "V314", "interior_price": 749.0, "oceanview_price": 899.0, "balcony_price": 1149.0, "suite_price": 2499.0, "taxes_fees": 234.5, "currency": "USD", "available_status": true
| # | voyage_id | date_scraped | interior_price | oceanview_price | balcony_price | mini_suite_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Port Schedules objects from princess.com. All fields typed and schema-versioned.
"voyage_id": "V314", "port_name": "Juneau", "country": "USA", "arrival_time": "13:00", "departure_time": "21:00", "day_number": 3, "is_tender": false
| # | voyage_id | port_name | country | arrival_time | departure_time | day_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Shore Excursions objects from princess.com. All fields typed and schema-versioned.
"excursion_id": "JNU-105", "title": "Mendenhall Glacier Explorer", "port_name": "Juneau", "duration_hours": 3.5, "activity_level": "Easy", "price_adult": 89.95, "rating": 4.6, "review_count": 342
| # | excursion_id | title | port_name | duration_hours | activity_level | price_adult |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fleet & Ships objects from princess.com. All fields typed and schema-versioned.
"ship_id": "DI", "ship_name": "Discovery Princess", "passenger_capacity": 3660, "crew_capacity": 1346, "year_built": 2022, "tonnage": 145000, "length_feet": 1083.0
| # | ship_id | ship_name | passenger_capacity | crew_capacity | year_built | refurbished_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our princess.com scraper handles every layer of the platform: itineraries, dynamic pricing, ship metadata, and port schedules - with JavaScript rendering, session management, and anti-bot circumvention built in.
Extract voyages, departure dates, embarkation ports, and full day-by-day port schedules.
Capture base fares for interior, oceanview, balcony, and suite tiers, plus calculated taxes and port fees.
Extract excursion titles, pricing, duration, activity levels, and passenger reviews per port.
Capture passenger capacity, tonnage, dining venues, and MedallionClass amenity details.
Monitor sold-out statuses per cabin tier and track inventory depletion over time.
Maintain region-specific sessions to extract correct local pricing and currency variants (US, UK, AU).
Track base fares versus bundled packages like Princess Plus and Princess Premier.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Navigate Akamai and Cloudflare protections using residential proxies and human-like request patterns.
Brief in. Clean data out.
Provide destination filters, date ranges, or specific ship IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for princess.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 sites invest heavily in scraping detection and dynamic pricing. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Travel sites use advanced bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management - trained on real user behaviour patterns.
Princess.com search interfaces and date pickers are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution, capturing data that headless HTTP clients miss entirely.
Pricing on cruise sites often requires maintaining a strict session state to calculate accurate port taxes and fees. We manage cookie jars and session tokens to ensure the pricing data matches what a real user sees.
DOM structures change frequently. Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and text-pattern matching - so a layout change does not break your data pipeline overnight.
For large itinerary catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs - reducing compute cost, storage bloat, and downstream processing load.
Online travel agencies monitor direct pricing on princess.com to ensure rate parity and competitive positioning.
Rival cruise lines track Princess deployment schedules, itinerary changes, and pricing strategies across regions.
Analysts track capacity deployment, ship repositioning, and new destination launches to identify market trends.
Travel operators use structured itinerary and pricing data to bundle cruises with flights and hotels in real time.
Revenue teams correlate sold-out cabin tiers and price increases with departure dates to model consumer demand.
Third-party tour operators analyse shore excursion pricing and reviews to optimise their own port offerings.
"Princess Cruises surfaces complex, dynamic inventory across hundreds of voyages, but aggregating this data requires navigating heavy JavaScript and session-dependent pricing."
Most teams underestimate the investment required: reliable cruise scraping requires residential proxies, full JavaScript rendering for date pickers, session management for accurate taxes, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our princess.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 US/UK/AU regions. 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 princess.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from princess.com is generally permissible under applicable law. DataFlirt targets only public, non-authenticated itinerary, pricing, and ship data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review the site's ToS and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline. We monitor for rate spikes in real time and trigger pool rotation automatically.
Yes. We can configure pipelines to use region-specific residential proxies and session headers to extract pricing in USD, GBP, AUD, or other supported currencies.
Full catalogue refreshes at daily cadence complete within a 6-12 hour window depending on size. We can configure higher frequency runs for specific high-value itineraries or narrow date ranges.
Yes. Every itinerary record includes an array of port stops, complete with arrival times, departure times, day numbers, and tender requirements.
Absolutely. We provide a sample run of up to 50 voyages as part of the pre-engagement scoping process - so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off itinerary dump or a continuous price-monitoring feed across the entire fleet - we scope, build, and operate the pipeline. Tell us what you need.
