We extract timepiece references, calibre specifications, material compositions, and retailer networks from Patek Philippe. 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 Timepiece Details objects from patek.com. All fields typed and schema-versioned.
"reference_number": "5236P-001", "collection": "Grand Complications", "case_material": "Platinum", "case_diameter": 41.3, "case_thickness": 11.07, "water_resistance": "30 m"
| # | reference_number | collection | sub_collection | description | case_material | case_diameter |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Calibre Specs objects from patek.com. All fields typed and schema-versioned.
"calibre_name": "31-260 PS QL", "movement_type": "Self-winding mechanical", "parts_count": 503, "jewels": 58, "power_reserve": "48 hours", "frequency": "28800 vph"
| # | calibre_name | movement_type | diameter | thickness | parts_count | jewels |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Dial & Gem Setting objects from patek.com. All fields typed and schema-versioned.
"reference_number": "5236P-001", "dial_colour": "Blue", "dial_finish": "Black-gradient, vertical satin finish", "numerals": "Applied gold faceted", "gem_type": "Diamond", "gem_count": 1, "setting_location": "Dial"
| # | reference_number | dial_colour | dial_finish | numerals | luminescence | gem_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Strap & Clasp objects from patek.com. All fields typed and schema-versioned.
"reference_number": "5236P-001", "strap_material": "Alligator leather with square scales", "strap_colour": "Navy blue", "stitching": "Hand-stitched", "clasp_type": "Fold-over clasp", "clasp_material": "Platinum"
| # | reference_number | strap_material | strap_colour | stitching | clasp_type | clasp_material |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Retailer Network objects from patek.com. All fields typed and schema-versioned.
"store_name": "Patek Philippe Salon", "retailer_type": "Salon", "city": "Geneva", "country": "Switzerland", "phone": "+41 22 804 14 14", "latitude": 46.2044, "longitude": 6.1432
| # | store_name | retailer_type | address | city | country | phone |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Patek Philippe scraper handles every layer of the platform: current collections, deeply nested calibre specifications, high resolution assets, and the global retailer network.
Reference numbers, collections, and detailed descriptions mapped across the entire catalogue.
Deep extraction of movement specifications, including parts count, jewels, and balance spring materials.
Case diameters, thicknesses, water resistance, and precious metal compositions.
URLs for front, back, and angled timepiece imagery intercepted from network requests.
Global extraction of authorised dealers, salons, and service centres with geolocation coordinates.
Monitoring models moving from current collections to the historical archive.
Specific fields for perpetual calendars, minute repeaters, and tourbillon mechanisms.
Carat weights, cut types, and setting locations for high jewellery pieces.
Extraction across EN, FR, DE, and CH locales for global market analysis.
Brief in. Clean data out.
Provide target collections, specific references, or regional retailer requirements. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for patek.com.
Schema validation, null-rate checks, and sample data reviews before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Luxury watchmakers invest heavily in complex digital experiences. Here is how we stay resilient.
The Patek Philippe website relies heavily on WebGL and scroll animations. We use Playwright to execute full browser sessions, ensuring all lazy loaded elements and movement specifications render before extraction.
High resolution images and 360 degree views are embedded within complex JavaScript viewers. Our pipeline intercepts the underlying network requests to capture original asset URLs.
Retailer locators often serve different results based on the visitor IP address. We route requests through residential proxies in target countries to map the complete global network.
Horological data is deeply nested. A single watch reference can contain multiple sub assemblies. We normalise this into flat or relational JSON structures.
For low volume, high value catalogues, knowing when a model is discontinued or a specification changes is critical. We hash every field and only emit records when diffs occur.
Secondary market platforms use retail specifications to authenticate and price pre owned inventory.
Luxury watchmakers track Patek Philippe material usage, complication combinations, and calibre metrics.
Brands map the global distribution of Patek Philippe salons to identify premium retail corridors.
Collectors and media outlets populate their internal databases with verified manufacturer specifications.
Analysts correlate specific complications and materials with secondary market appreciation rates.
Tracking the introduction of new materials and movement architectures across the catalogue.
"Patek Philippe's digital catalogue contains the most precise horological specifications available, but extracting it requires navigating heavy rendering and complex hierarchies."
Extracting data from luxury watchmakers involves parsing deeply nested movement specifications and handling heavily animated frontends. DataFlirt manages the JavaScript rendering, proxy rotation, and schema normalisation so your analysts receive structured timepiece data without maintaining brittle extraction scripts.
Everything supported by our patek.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.
We maintain pools of residential ISP proxies. Rotation happens per request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. 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 patek.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from patek.com is generally permissible under applicable law. DataFlirt targets only public, non authenticated product and retailer data. We do not extract personal data or circumvent authentication walls.
We use full Playwright browser sessions to execute all JavaScript, trigger lazy loading, and wait for complex animations to finish before parsing the DOM.
We extract all models currently listed on the public site, including those in the official historical archive sections.
Yes. We intercept the network requests made by the image viewers to extract the highest resolution asset URLs available.
Given the static nature of luxury watch catalogues, we typically run weekly or monthly pipelines, though daily runs are available for tracking immediate catalogue changes.
Yes. We can configure the pipeline to iterate through the locale selectors and extract specifications in English, French, German, and other supported languages.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one off catalogue dump or continuous tracking across the horological market, we scope, build, and operate the pipeline. Tell us what you need.
