We extract destination hierarchies, hotel reviews, restaurant ratings, and attraction data from Frommers. 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 Destinations objects from frommers.com. All fields typed and schema-versioned.
"destination_id": "D-18492", "continent": "Europe", "country": "Italy", "city": "Rome", "currency": "Euro", "language": "Italian", "page_url": "https://www.frommers.com/destinations/rome"
| # | destination_id | continent | country | region | city | description_html |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Hotels objects from frommers.com. All fields typed and schema-versioned.
"poi_id": "H-93812", "name": "Hotel Hassler Roma", "expert_rating": 3, "price_tier": "$$$$", "neighborhood": "Spanish Steps", "address": "Piazza Trinità dei Monti 6, Rome", "latitude": 41.9061, "longitude": 12.4833
| # | poi_id | name | destination_id | expert_rating | price_tier | address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Restaurants objects from frommers.com. All fields typed and schema-versioned.
"poi_id": "R-44102", "name": "Roscioli Salumeria con Cucina", "cuisine_type": "Roman", "expert_rating": 2, "price_tier": "$$$", "neighborhood": "Campo de' Fiori", "address": "Via dei Giubbonari 21/22, Rome"
| # | poi_id | name | destination_id | cuisine_type | expert_rating | price_tier |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Attractions objects from frommers.com. All fields typed and schema-versioned.
"poi_id": "A-11094", "name": "Colosseum", "category": "Historic Site", "expert_rating": 3, "admission_fee": "16 EUR", "neighborhood": "Ancient Rome", "address": "Piazza del Colosseo 1, Rome"
| # | poi_id | name | destination_id | category | expert_rating | admission_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Itineraries objects from frommers.com. All fields typed and schema-versioned.
"itinerary_id": "I-5521", "title": "Rome in 3 Days", "duration_days": 3, "author": "Donald Strachan", "target_audience": "First-time visitors", "page_url": "https://www.frommers.com/destinations/rome/itineraries/in-3-days"
| # | itinerary_id | title | destination_id | duration_days | author | description |
|---|---|---|---|---|---|---|
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Our infrastructure parses deeply nested destination hierarchies, unstructured expert reviews, and dynamic map layers into a normalised schema.
Maintain parent-child relationships across continents, countries, regions, cities, and neighborhoods.
Extract property names, expert star ratings, price tiers, amenities, and full editorial reviews.
Capture cuisine types, pricing indicators, opening hours, and location data for dining POIs.
Aggregate historic sites, museums, and nightlife venues with admission fees and operating schedules.
Standardise the proprietary Frommers star rating system into queryable numerical fields.
Intercept map API payloads to extract exact latitude and longitude coordinates for POIs.
Deconstruct suggested itineraries into structured day-by-day arrays with linked POIs.
Scrape travel tips, news, and best-of lists with author attribution and publication dates.
Monitor guide update timestamps to only re-scrape content that has been modified by editors.
Brief in. Clean data out.
Provide specific continents, countries, or cities. We design the extraction schema together.
We configure Scrapy crawlers, handle pagination, and map the destination taxonomy.
Schema validation, null-rate checks, and nested relationship mapping before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or warehouse on an agreed cadence.
Extracting editorial travel guides requires structural awareness. Here is how we parse unstructured text and nested hierarchies.
Travel guides rely on taxonomy. We inject parent destination IDs into every child POI record, ensuring your database understands that the Colosseum belongs to Ancient Rome, which belongs to Rome, which belongs to Italy.
Frommers relies heavily on prose. We use custom regex pipelines and NLP post-processing to extract implicit amenities, opening hours, and pricing details buried within expert review text.
Exact lat/long coordinates are often hidden within dynamic map renders. Our Playwright instances intercept the background XHR requests to extract precise spatial data for every POI.
Travel content updates sporadically. We monitor publication timestamps and maintain a hash index of last-seen values, pushing only diffs to reduce downstream processing load.
Major cities have hundreds of hotels and restaurants split across complex pagination structures. Our crawlers traverse every page to ensure complete catalogue extraction.
Enrich existing hotel and attraction listings with trusted editorial reviews and expert ratings to increase conversion.
Feed structured POI data and suggested itineraries into proprietary trip planning algorithms and AI assistants.
Map the density of highly rated restaurants and attractions to evaluate real estate or retail opportunities.
Analyse destination popularity trends and pricing tiers across different global regions.
Build comprehensive travel portals by combining Frommers expert reviews with user-generated content from other sources.
Train large language models on high-quality, professionally edited travel writing and destination descriptions.
"Frommers holds decades of curated travel intelligence, but accessing it programmatically requires parsing deeply nested destination hierarchies."
Extracting travel guides at scale involves more than simple HTTP requests. It requires maintaining complex parent-child relationships across continents, countries, and cities while parsing unstructured expert reviews into clean, queryable fields. DataFlirt handles this structural complexity natively.
Everything supported by our frommers.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 and dependency mapping. Playwright executes JavaScript to intercept map APIs and dynamic content.
We route requests through ISP-grade residential IPs to prevent rate limiting during deep catalogue traversal.
Airflow handles scheduling and dependency management, running on AWS Lambda and ECS for sustained throughput.
Data delivered to where your team already works — no new tooling required.
About frommers.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available travel guides and POI data is generally permissible. We target only public, non-authenticated editorial content. We do not circumvent authentication walls or extract personal data. Clients should consult their own legal counsel regarding specific commercial use cases.
We build a relational map during the crawl. Every POI (hotel, restaurant, attraction) is tagged with a parent destination ID, allowing you to easily query all locations within a specific city, region, or country.
Travel guides do not require real-time streaming. We typically run full catalogue refreshes on a weekly or monthly cadence, relying on publication timestamps to detect changes and emit diffs.
Yes. While coordinates are sometimes missing from the raw HTML, our Playwright integration intercepts the background map API calls to extract accurate latitude and longitude for mapping applications.
We typically scope engagements starting at a single continent or major country level. Contact us with your target regions for a specific volume estimate.
Yes. We provide a sample extraction of a single major city (e.g. Rome or Paris) including all associated POIs and itineraries so you can validate the schema before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a specific country guide or the entire global catalogue, we scope, build, and operate the pipeline. Tell us what you need.
