We extract flight routes, dynamic pricing signals, hotel availability, and bundled package deals from edreams.es. 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 edreams.es. All fields typed and schema-versioned.
"origin": "MAD", "destination": "BCN", "airline": "Iberia", "flight_number": "IB3012", "price": 45.99, "prime_price": 32.99, "currency": "EUR"
| # | flight_id | origin | destination | departure_time | arrival_time | airline |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Hotel Listings objects from edreams.es. All fields typed and schema-versioned.
"name": "Hotel Arts Barcelona", "star_rating": 5, "review_score": 8.9, "price_per_night": 250.0, "prime_discount": 25.0, "currency": "EUR", "free_cancellation": true
| # | hotel_id | name | location | star_rating | review_score | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Bundled Packages objects from edreams.es. All fields typed and schema-versioned.
"destination": "Tenerife", "hotel_name": "Hard Rock Hotel", "nights": 5, "total_price": 850.5, "prime_price": 790.0, "baggage_included": false, "currency": "EUR"
| # | package_id | destination | outbound_flight | return_flight | hotel_name | nights |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Ancillaries objects from edreams.es. All fields typed and schema-versioned.
"base_price": 45.99, "taxes": 12.5, "booking_fee": 5.0, "carry_on_bag_fee": 25.0, "checked_bag_fee": 40.0, "total_estimated": 128.49, "currency": "EUR"
| # | route_id | base_price | taxes | booking_fee | prime_subscription_fee | carry_on_bag_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Search Results (SERP) objects from edreams.es. All fields typed and schema-versioned.
"rank_position": 1, "airline": "Vueling", "price": 35.5, "is_cheapest": true, "is_fastest": false, "prime_eligible": true, "scraped_at": "2026-05-12T10:15:00Z"
| # | search_id | origin | destination | dates | rank_position | airline |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our eDreams scraper handles dynamic rendering, session state, and bot protection to deliver accurate flight, hotel, and pricing data.
Capture direct and multi-city itineraries, including operating carriers, layover durations, and terminal changes.
Monitor base fares, taxes, and hidden booking fees across different date ranges and passenger configurations.
Extract both standard prices and eDreams Prime member rates to calculate exact discount margins.
Scrape room types, board basis, cancellation policies, and nightly rates for any destination.
Extract baggage costs, seat selection fees, and insurance add-ons that heavily influence total trip cost.
Monitor Flight + Hotel combinations, calculating the implied discount versus booking components separately.
Extract prices in EUR, GBP, USD, and other supported currencies with accurate locale formatting.
Scan flexible date grids to identify the cheapest departure and return combinations over a 30-day window.
Run continuous pipelines at 15-minute intervals to detect flash sales and inventory drops before they expire.
Brief in. Clean data out.
Provide origin-destination pairs, hotel locations, date ranges, and passenger counts. We map the extraction schema.
We configure Playwright spiders, session management, and CAPTCHA handling for edreams.es dynamic endpoints.
Schema validation, price-outlier detection, and null-rate checks before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
eDreams uses strict rate limiting and dynamic rendering. Here is how we stay resilient.
eDreams uses strict rate limiting and bot protection. Our crawlers utilise residential ISP proxies with realistic browser fingerprints and full cookie session management.
Flight search results and pricing matrices are heavily JavaScript-rendered. We run full Playwright browser sessions with JS execution to capture the final loaded DOM.
Extracting ancillary fees requires advancing through the booking funnel. We manage stateful sessions to reach the final checkout page without triggering fraud alerts.
eDreams frequently A/B tests its UI. Our selector strategy uses multi-layer fallback chains: CSS, XPath, and API interception, so layout changes do not break the pipeline.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops, responding before data is compromised.
Online travel agencies monitor eDreams to ensure pricing parity and adjust their own markups dynamically.
Carriers track how their inventory is priced and bundled on third-party aggregators to optimise direct-channel pricing.
Analysts track route popularity, average booking values, and destination demand trends over time.
Competitors analyse the eDreams Prime discount structure to model subscription profitability and conversion rates.
Airlines and OTAs benchmark baggage and seat selection fees to optimise their own post-booking revenue streams.
Metasearch engines ingest eDreams pricing to display comprehensive comparison grids for end-users.
"eDreams controls a massive share of European travel bookings, but extracting accurate pricing requires navigating complex dynamic rendering and aggressive bot protection."
Most teams underestimate the engineering required for OTA scraping: reliable eDreams data demands residential proxies, full JavaScript execution, session state management across booking funnels, and constant schema maintenance. DataFlirt absorbs that complexity so your engineers can focus on yield analysis, not infrastructure.
Everything supported by our edreams.es 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 and retry logic. Playwright handles JavaScript rendering, cookie sessions, and multi-step booking flows.
We maintain pools of residential ISP proxies across EU regions. Rotation happens per-request with sticky sessions for funnel traversal.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. State stored in Postgres.
Data delivered to where your team already works — no new tooling required.
About edreams.es scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available travel data is generally permissible. DataFlirt extracts only public, non-authenticated flight and hotel pricing. We do not extract personal data or bypass authenticated user areas.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour to bypass Akamai and Datadome.
Yes. Our pipelines capture both the standard retail price and the discounted eDreams Prime price for flights, hotels, and packages.
We can traverse the booking funnel up to the final payment page to extract accurate ancillary fees, including baggage, seat selection, and insurance costs.
For high-priority routes, pipelines can run at 15-minute intervals to capture flash sales. Standard bulk catalogues are typically refreshed every 12 to 24 hours.
Yes. We can input complex multi-city parameters and extract the resulting combined itineraries, layovers, and total pricing.
Our minimum engagement typically starts at 5,000 route-date combinations refreshed daily. We price based on compute intensity and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route extraction or continuous price monitoring across thousands of destinations. Tell us what you need.
