We extract flight routes, hotel inventory, Opodo Prime pricing tiers, and package availability from Opodo. 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 Itineraries objects from opodo.com. All fields typed and schema-versioned.
"flight_id": "OP-LON-BCN-8492", "airline": "British Airways", "flight_number": "BA472", "departure_airport": "LHR", "arrival_airport": "BCN", "base_price": 142.5, "prime_price": 102.5, "duration_minutes": 135
| # | flight_id | airline | flight_number | departure_airport | arrival_airport | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Hotel Inventory objects from opodo.com. All fields typed and schema-versioned.
"property_id": "HTL-99482", "hotel_name": "W Barcelona", "star_rating": 5, "review_score": 8.8, "room_type": "Fabulous Room, 1 King Bed", "base_rate": 450.0, "prime_rate": 410.0, "cancellation_policy": "Free cancellation before 24h"
| # | property_id | hotel_name | location_city | star_rating | review_score | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Ancillary Fees objects from opodo.com. All fields typed and schema-versioned.
"route_id": "OP-LON-BCN-8492", "checked_bag_fee": 35.0, "carry_on_fee": 15.0, "seat_selection_min": 8.0, "seat_selection_max": 45.0, "service_fee": 12.5, "currency": "GBP"
| # | route_id | airline | checked_bag_fee | carry_on_fee | seat_selection_min | seat_selection_max |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Car Rentals objects from opodo.com. All fields typed and schema-versioned.
"provider": "Hertz", "car_class": "Compact", "model_example": "Volkswagen Golf", "daily_rate": 42.0, "prime_rate": 35.0, "transmission": "Automatic", "fuel_policy": "Full to Full", "insurance_included": false
| # | rental_id | provider | car_class | model_example | pickup_location | dropoff_location |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Package Holidays objects from opodo.com. All fields typed and schema-versioned.
"package_id": "PKG-BCN-7D", "destination": "Barcelona", "duration_days": 7, "total_price": 890.0, "prime_discount": 120.0, "meal_plan": "Half Board", "transfer_included": true, "passenger_count": 2
| # | package_id | destination | departure_city | hotel_name | duration_days | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Opodo scraper handles every layer of the OTA platform. We extract dynamic flight pricing, Opodo Prime membership rates, complex multi-city itineraries, and ancillary fee structures with full JavaScript execution.
Extract flight numbers, departure times, layover durations, operating carriers, and cabin classes across millions of routes.
Capture the standard base fare alongside the discounted Opodo Prime membership rate for flights, hotels, and rentals.
Scrape property details, room configurations, board basis, and cancellation policies mapped to specific travel dates.
Track dynamic pricing for checked bags, carry-on luggage, priority boarding, and seat selection costs.
Emulate searches from specific countries to capture point-of-sale pricing discrepancies and currency conversions.
Extract vehicle classes, daily rates, insurance policies, and supplier details from Opodo car rental search results.
Monitor fare fluctuations at an hourly or daily cadence to track airline revenue management behaviour.
Configure complex multi-city search queries to extract pricing for non-standard travel itineraries.
Extract bundled flight and hotel packages including total price, prime discounts, and included transfers.
Brief in. Clean data out.
Provide origin-destination pairs, travel dates, or hotel IDs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and CAPTCHA handling for opodo.com.
Schema validation, null-rate checks, price-outlier detection, and sample payloads before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
OTAs invest heavily in scraping detection. Here is how we stay resilient and deliver structured travel data without interruption.
Opodo uses aggressive bot protection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass detection.
Flight and hotel results on Opodo load asynchronously via complex API calls. We run full Playwright browser sessions to wait for network idle states and capture fully populated pricing grids.
Travel prices change based on the user IP address. We route requests through region-specific proxy pools to capture accurate point-of-sale pricing for your target market.
Opodo frequently updates its DOM structure. Our selector strategy uses multiple fallback chains per field, including JSON payload extraction from network responses, ensuring pipeline stability.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops, responding automatically to maintain data integrity.
Online travel agencies monitor Opodo pricing to ensure rate parity and adjust their own dynamic pricing algorithms.
Airlines track how their fares and ancillary fees are displayed and marked up on third-party OTA platforms.
Hospitality groups extract room availability and Prime pricing to benchmark against direct booking channels.
Aviation analysts track baggage and seat selection costs to understand unbundled fare strategies.
Investment firms track flight volumes and pricing trends to forecast travel demand and airline performance.
Travel management companies audit OTA prices against corporate negotiated rates to ensure compliance and value.
"Opodo aggregates complex travel inventories and dynamic pricing models across flights and hotels, but extracting it requires navigating aggressive bot protection and asynchronous search APIs."
Most teams underestimate the investment required. Reliable Opodo scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our opodo.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 asynchronous API hydration.
We maintain pools of residential ISP proxies across multiple regions. Rotation happens per-request with sticky sessions where required for complex search flows.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About opodo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and availability information from Opodo is generally permissible under applicable law. DataFlirt targets only public, non-authenticated search data. We do not extract personal user data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for CAPTCHA challenges in real time and trigger solver queues automatically.
Yes. Our pipeline extracts both the standard base fare and the discounted Opodo Prime membership rate for flights, hotels, and car rentals.
Streaming pipelines achieve sub-30-minute latency for price and availability signals on a defined route set. Full catalogue refreshes complete within agreed time windows depending on volume.
Yes. We capture the dynamic pricing for checked bags, carry-on luggage, and seat selection minimums during the booking flow simulation.
Absolutely. We provide a sample run of up to 100 routes or hotel properties as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off hotel catalogue dump or a continuous flight price monitoring feed across 50,000 routes, we scope, build, and operate the pipeline. Tell us what you need.
