We extract jewelry mountings, loose stones, findings, and metallurgical data from Stuller. 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 Mountings objects from stuller.com. All fields typed and schema-versioned.
"sku": "122001:100:P", "title": "Solitaire Engagement Ring", "metal_type": "14K White Gold", "center_stone_shape": "Round", "center_stone_size": "1.00 ct", "weight_grams": 3.45, "public_price": 450.0
| # | sku | title | collection | metal_type | center_stone_shape | center_stone_size |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Loose Diamonds objects from stuller.com. All fields typed and schema-versioned.
"stock_number": "LD-98421", "shape": "Oval", "carat": 1.52, "color": "E", "clarity": "VS1", "cut": "Excellent", "lab": "GIA", "public_price": 12450.0
| # | stock_number | shape | carat | color | clarity | cut |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Findings objects from stuller.com. All fields typed and schema-versioned.
"sku": "2001:100:P", "category": "Findings", "sub_category": "Clasps", "metal_quality": "18K Yellow Gold", "style": "Lobster Claw", "weight": 0.85, "public_price": 45.5
| # | sku | category | sub_category | metal_quality | style | dimensions |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Tools & Supplies objects from stuller.com. All fields typed and schema-versioned.
"sku": "14-4122", "brand": "Foredom", "category": "Flex Shafts", "voltage": "110V", "weight": 4.5, "public_price": 285.0, "hazardous_material": false
| # | sku | brand | category | description | voltage | dimensions |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for 3C Customisation objects from stuller.com. All fields typed and schema-versioned.
"base_sku": "65322", "metal_choices": "['14K White', '14K Yellow', 'Platinum']", "stone_choices": "['Diamond', 'Sapphire', 'Ruby']", "size_range": "4.0 - 9.0", "default_price": 850.0, "lead_time": "3-5 Business Days"
| # | base_sku | configurable_options | metal_choices | stone_choices | size_range | default_price |
|---|---|---|---|---|---|---|
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Our Stuller scraper navigates complex product matrices, dynamic diamond grids, and infinite variant combinations to deliver clean, structured catalogue data.
Extract base SKUs alongside all child variants mapped by metal type, finger size, and center stone dimensions.
Scrape the dynamic diamond search grid for natural and lab-grown stones, capturing grading reports and pricing.
Traverse deeply nested categories to extract clasps, shanks, and settings with precise metallurgical weights.
Extract exact gram weights for precious metals across all variations, essential for dynamic pricing models.
Map the parametric choices for custom jewelry, capturing all possible permutations in the Choose, Change, Create engine.
Extract technical specifications, voltage, and hazardous material flags for bench jeweler supplies.
Capture product imagery, 360-degree video URLs, and schematic diagrams for local hosting.
Link thousands of child SKUs to parent designs, maintaining relational integrity in your database.
Run daily pipelines to capture new product additions and public price adjustments without full catalogue rebuilds.
Brief in. Clean data out.
Provide categories, search parameters, or base SKUs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for stuller.com.
Schema validation, variant explosion checks, and sample data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Stuller's catalogue is built on combinatorial variants and dynamic rendering. Here is how we extract it reliably.
We utilise US-based residential proxies and Playwright browser sessions to navigate bot protection, ensuring consistent access to catalogue pages.
Stuller's 3C customisation tool relies entirely on client-side rendering. We execute the JavaScript to expose all metal and stone permutations.
A single ring design can have hundreds of SKUs based on size, metal, and stone. Our pipeline maps these relationships without duplicating base metadata.
We use layered CSS and XPath selectors to handle structural changes in Stuller's product detail pages, preventing pipeline failures.
We maintain state across runs to only deliver records where prices, stock status, or specifications have changed, reducing your processing load.
Retail jewelers track Stuller's public MSRP to benchmark their own pricing strategies and margin models.
Independent stores sync loose diamond and mounting availability to their own eCommerce platforms.
Digital storefronts map Stuller catalogue data directly to Shopify or WooCommerce for virtual inventory.
Industry analysts track the introduction of new lab-grown stone options and metal preferences over time.
Manufacturing jewelers build internal databases of findings and components to streamline ordering.
Designers aggregate base mounting specifications to inform their own custom CAD modelling workflows.
"Stuller's catalogue represents the backbone of the independent jewelry trade, but extracting its millions of variant permutations requires serious infrastructure."
Most teams underestimate the complexity of jewelry data: parsing combinatorial variants of metal type, ring size, and center stone dimensions requires heavy JavaScript rendering and precise state management. DataFlirt handles the extraction so your developers can focus on building your marketplace or inventory system.
Everything supported by our stuller.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 deduplication. Playwright handles the JavaScript rendering required for Stuller's dynamic product configurators.
We maintain pools of residential ISP proxies to avoid bot detection and rate limiting, ensuring consistent access to the Stuller catalogue.
Pipelines run on scalable cloud infrastructure. Airflow handles scheduling and dependency management, with all state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About stuller.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available catalogue information is generally permissible. DataFlirt targets only public, non-authenticated product and retail pricing data from stuller.com. We do not circumvent authentication walls to access wholesale pricing.
We use Playwright to execute the client-side JavaScript, programmatically iterating through the available metal types, stone shapes, and sizes to capture all valid permutations and their corresponding public prices.
No. Wholesale pricing on Stuller requires a verified jeweler account and login credentials. Our service extracts the publicly visible retail pricing (MSRP) and product specifications.
We can configure pipelines to run daily or at specific intra-day intervals to capture changes in loose diamond availability and pricing on the public search grid.
No. Raw 3D CAD files are gated behind authentication and purchase requirements. We extract the metadata, specifications, and public render images.
We scope engagements based on the number of SKUs or categories required. Contact us with your target list for a specific infrastructure quote.
Yes. We provide a sample extraction of specific mountings or loose stones during the scoping phase to ensure the schema meets your database requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily sync of loose diamonds or a one-off extraction of the findings catalogue, we scope, build, and operate the pipeline. Tell us what you need.
