We extract photonics specifications, laser parameters, optomechanics pricing, inventory levels, and CAD metadata from newport.com. 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 Product Specifications objects from newport.com. All fields typed and schema-versioned.
"sku": "M-SP-2", "title": "Stainless Steel Optical Post, 12.7 mm Diameter, 50.8 mm Length", "category": "Optomechanics", "sub_category": "Optical Posts and Pedestals", "rohs_compliant": true, "cad_available": true, "price": 14.5
| # | sku | title | category | sub_category | description | specifications_json |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Optics & Photonics objects from newport.com. All fields typed and schema-versioned.
"sku": "KPX043", "material": "N-BK7", "wavelength_range": "350-2000 nm", "diameter": "25.4 mm", "focal_length": "100.0 mm", "surface_quality": "40-20 scratch-dig", "clear_aperture": ">22.86 mm"
| # | sku | material | wavelength_range | diameter | focal_length | surface_quality |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Availability objects from newport.com. All fields typed and schema-versioned.
"sku": "M-SP-2", "list_price": 14.5, "currency": "USD", "stock_status": "In Stock", "lead_time_days": 1, "quote_required": false
| # | sku | list_price | currency | bulk_pricing_tiers | stock_status | lead_time_days |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Product Families objects from newport.com. All fields typed and schema-versioned.
"family_id": "FAM-1029", "family_name": "SP Series Stainless Steel Optical Posts", "category_path": "Optomechanics > Optical Posts", "related_skus": "['M-SP-1', 'M-SP-2', 'M-SP-3']", "manual_urls": "['https://www.newport.com/mam/celum/celum_assets/SP_Series_Manual.pdf']", "application_notes": "[]"
| # | family_id | family_name | description | related_skus | category_path | application_notes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Lasers & Motion Control objects from newport.com. All fields typed and schema-versioned.
"sku": "XPS-Q8", "laser_type": "None", "travel_range": "None", "controller_compatibility": "['XPS-DRV11', 'XPS-DRV01']", "operating_temperature": "10 to 35 °C", "resolution": "0.001 µm"
| # | sku | laser_type | output_power | beam_diameter | travel_range | resolution |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Newport's catalogue is built on complex matrix tables, deep taxonomies, and technical specifications. We parse this structure into flat, queryable records for procurement, R&D, and competitor analysis.
Newport groups products into families with large specification tables. We extract these tables and normalise the data into individual SKU records.
Capture material types, focal lengths, wavelength ranges, and damage thresholds with unit preservation across thousands of optical components.
Extract list prices, bulk discount tiers, inventory status, and estimated lead times. Identify items requiring custom quotes.
Scrape URLs and metadata for 2D/3D CAD models, user manuals, application notes, and RoHs compliance certificates.
Map compatible controllers, mounts, and accessories to their parent SKUs based on Newport's internal recommendation engine.
Crawl the entire category tree from generic optical components down to specific optomechanical assemblies, preserving the hierarchy.
Extract pricing and availability based on specific geographic regions and currencies using session configuration.
Monitor catalogue additions, price adjustments, and specification updates with hash-based diffing to reduce warehouse bloat.
Standardise metric and imperial units (e.g., mm vs inches) across the optomechanics catalogue for consistent downstream querying.
Brief in. Clean data out.
Provide specific category URLs, product families, or a complete catalogue extraction mandate. We design the schema.
We configure Scrapy crawlers, parse matrix tables, handle pagination, and set up proxy rotation for newport.com.
Schema validation, unit consistency checks, and null-rate monitoring on technical specifications before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from newport.com requires handling structural complexity rather than aggressive anti-bot systems. Here is how we process technical B2B catalogues.
Newport displays specifications in complex, horizontally scrolling matrix tables grouped by product family. Our parsers map column headers to individual row SKUs, flattening nested HTML tables into relational JSON records.
Optomechanics data mixes metric and imperial units, often within the same table cell (e.g., '12.7 mm (0.5 in)'). We extract these values, separate the units, and normalise them into structured float fields.
Pricing on newport.com varies by region. We manage Playwright browser sessions with specific cookie states and residential IPs to capture accurate regional pricing and lead times.
Technical buyers require CAD models and datasheets. We scrape the asset URLs, document types, and revision dates, attaching them as arrays to the parent SKU record.
Industrial catalogues change slowly, but price updates are critical. We hash the technical specifications and price fields, emitting only changed records to minimise your ingestion costs.
Photonics manufacturers monitor Newport's pricing tiers and lead times to adjust their own market positioning.
Authorised distributors ingest structured specification data to populate their own eCommerce platforms without manual data entry.
Enterprise R&D departments track inventory levels and lead times across critical optomechanical components to prevent project delays.
Research institutions build internal searchable databases of optical components to speed up experimental design.
Maintenance teams track the availability of replacement laser tubes, motion controllers, and specific mounts for existing equipment.
Analysts track the expansion of Newport's product lines and category depth to evaluate market trends in the photonics sector.
"Newport's technical catalogue contains the foundational specifications for global photonics research — but parsing matrix tables into relational databases requires custom pipelines."
Extracting data from industrial suppliers like Newport involves navigating complex product families, nested specification matrices, and CAD file metadata. DataFlirt handles the structural mapping, unit normalisation, and pagination logic so your procurement and engineering teams receive clean, queryable warehouse records.
Everything supported by our newport.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.
Custom parsing logic designed specifically for B2B industrial catalogues, capable of flattening nested HTML tables and associating specs with the correct child SKU.
Playwright handles cookie consent, region selection, and currency localisation to ensure pricing data matches your procurement context.
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 newport.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available catalogue information, specifications, and retail pricing from newport.com is generally permissible under applicable law. DataFlirt targets only public, non-authenticated data. We do not extract personal data or circumvent authentication walls. Clients should review Newport's Terms of Service and consult legal counsel for specific use cases.
Our parsers are specifically designed for industrial catalogues. We map column headers in product family tables to individual rows, flatten the data, and generate a distinct JSON record for every SKU, complete with all associated specifications.
Yes. Newport often combines values and units in text strings. We parse these fields, separate the numerical value from the unit (e.g., mm, nm, W, N), and structure them as typed fields to enable numerical sorting and filtering in your database.
By default, we extract the metadata and direct URLs to CAD models, datasheets, and manuals. We do not download the binary files themselves to avoid massive storage bloat, but your systems can easily ingest the URLs to fetch the files as needed.
For full catalogue extractions, we recommend weekly or monthly runs due to the slow-moving nature of industrial specifications. For specific high-priority SKUs, we can monitor pricing and inventory on a daily cadence.
Our smallest packages start at a defined category extraction (e.g., all Optomechanics). For full catalogue coverage across all product families, we price based on compute volume and delivery frequency. Contact us with your specific requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of the optomechanics catalogue or continuous price monitoring across all product families — we scope, build, and operate the pipeline. Tell us what you need.
