We extract tour itineraries, pricing tiers, availability calendars, accommodation listings, and destination reviews from braziltour.com. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Tour Packages objects from braziltour.com. All fields typed and schema-versioned.
"tour_id": "BT-84921", "title": "Amazon Rainforest Expedition 5 Days", "destination": "Manaus, Amazonas", "duration_days": 5, "operator_name": "EcoTours Brazil", "base_price": 450.0, "currency": "USD", "rating": 4.8, "review_count": 342
| # | tour_id | title | destination | duration_days | operator_name | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Itineraries objects from braziltour.com. All fields typed and schema-versioned.
"tour_id": "BT-84921", "day_number": 2, "day_title": "Meeting of the Waters", "accommodation_name": "Juma Amazon Lodge", "meals_included": "['Breakfast', 'Lunch', 'Dinner']", "transit_time_mins": 120, "guide_provided": true
| # | tour_id | day_number | day_title | description | accommodation_name | meals_included |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Dates objects from braziltour.com. All fields typed and schema-versioned.
"tour_id": "BT-84921", "departure_date": "2026-08-14", "return_date": "2026-08-18", "price_single": 550.0, "price_double": 450.0, "availability_status": "Available", "discount_pct": 10
| # | tour_id | departure_date | return_date | price_single | price_double | availability_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Accommodations objects from braziltour.com. All fields typed and schema-versioned.
"property_id": "ACC-9932", "name": "Juma Amazon Lodge", "type": "Eco Lodge", "destination": "Amazon Rainforest", "star_rating": 4, "amenities": "['WiFi', 'Restaurant', 'Bar', 'Tour Desk']", "latitude": -3.119, "longitude": -60.021
| # | property_id | name | type | destination | star_rating | amenities |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from braziltour.com. All fields typed and schema-versioned.
"review_id": "REV-551928", "target_id": "BT-84921", "target_type": "Tour", "rating": 5, "review_text": "Incredible experience seeing the pink dolphins. Highly recommend EcoTours.", "date_posted": "2025-11-04", "verified_booking": true, "language": "en"
| # | review_id | target_id | target_type | author_name | rating | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline extracts the entire Braziltour catalogue: complex itineraries, dynamic availability calendars, seasonal pricing, and operator metadata, delivering clean tabular data.
Title, destination, duration, operator details, and inclusion/exclusion lists extracted for every tour package.
Parse interactive calendar widgets to extract departure dates, return dates, and real-time booking availability.
Capture base prices, single/double occupancy rates, and seasonal discounts across multiple currencies.
Extract structured daily schedules, including activities, meals provided, transit times, and overnight accommodations.
Scrape property names, star ratings, amenity lists, and coordinate data for lodges and hotels linked to tours.
Extract full review text, star ratings, verified booking flags, and traveler types across all paginated review pages.
Capture tour operator profiles, aggregate ratings, response times, and total active listings on the platform.
Extract localized descriptions, itineraries, and reviews across Portuguese, English, and Spanish site versions.
Run continuous pipelines to detect price changes, new tour additions, and availability shifts on your defined cadence.
Brief in. Clean data out.
Provide destination URLs, tour categories, or operator IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for braziltour.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators use dynamic pricing, complex stateful calendars, and strict rate limits. Here is how we maintain reliable extraction.
Availability and pricing on braziltour.com are loaded via asynchronous API calls when a user clicks a calendar date. We run full Playwright browser sessions to trigger these events and capture the underlying JSON responses.
Braziltour employs geo-fencing and rate limiting. Our crawlers use residential ISP proxies located in Brazil and the US, rotating IPs per request to prevent blocks and ensure access to region-specific pricing.
Tour descriptions often contain unstructured text. We use custom parsing logic to normalise day-by-day itineraries into structured arrays, separating activities, meals, and accommodations into distinct fields.
For large tour 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.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops — and respond before you notice.
Travel agencies and tour operators monitor competitor pricing, seasonal discounts, and package inclusions to adjust their own offerings.
Global travel aggregators ingest Braziltour listings to expand their South American catalogue and offer broader inventory.
Tourism boards and analysts track popular destinations, average duration, and pricing trends to understand market demand.
Hospitality brands analyse review corpora to assess customer satisfaction, identify common complaints, and improve service delivery.
Revenue managers use historical availability and pricing data to train models that optimise their own yield management systems.
B2B travel agents use structured Braziltour data to populate internal booking portals and generate custom client proposals.
"Braziltour holds the definitive dataset for Brazilian tourism operators, itineraries, and seasonal pricing — but it requires a managed pipeline to query."
Extracting travel data requires navigating dynamic availability calendars, complex itinerary structures, and seasonal pricing variants. DataFlirt manages the JavaScript rendering and residential proxy rotation required to maintain state and extract clean, normalised records without manual intervention. Your engineers focus on analysis, we handle the extraction.
Everything supported by our braziltour.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, calendar interaction, and dynamic pricing hydration.
We maintain pools of residential ISP proxies across Brazil and the US. Rotation happens per-request with sticky sessions where required to prevent geo-blocking.
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 braziltour.com scraping, legality, and pipeline operations.
Ask us directly →We extract public data including tour package details, day-by-day itineraries, pricing tiers, availability calendars, accommodation metadata, operator profiles, and customer reviews.
We use Playwright to simulate user interactions, clicking through calendar widgets to trigger the underlying API requests, and capturing the JSON responses containing real-time availability and pricing.
Yes. We can target specific language subdirectories (e.g., /en/, /pt/, /es/) to extract localised descriptions, itineraries, and reviews.
We support daily, weekly, or custom cadences. For price monitoring, we can configure high-frequency runs on specific high-value tour URLs to capture intra-day availability changes.
We extract all publicly visible operator details listed on the platform, which typically includes operator name, profile URL, aggregate rating, and sometimes public business addresses.
Itineraries are delivered as nested JSON arrays or flattened into distinct relational tables, depending on your database requirements. Each day includes activities, meals, and accommodations.
Yes. We provide a sample run of up to 100 tour listings as part of the pre-engagement scoping process to validate schema fit and field completeness.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price-monitoring across thousands of tours — we scope, build, and operate the pipeline. Tell us what you need.
