We extract lighting fixtures, hardware specifications, finish variants, pricing, and inventory states from Schoolhouse. Delivered as clean JSON, CSV, or Parquet to S3 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 Products objects from schoolhouse.com. All fields typed and schema-versioned.
"sku": "SH-LGT-1042", "title": "Factory Light No. 4 Cable", "category": "Lighting > Pendants", "base_price": 299.0, "description": "Inspired by early 20th-century industrial lighting.", "page_url": "https://www.schoolhouse.com/products/factory-light-no-4-cable"
| # | sku | title | category | base_price | description | materials |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Variants objects from schoolhouse.com. All fields typed and schema-versioned.
"parent_sku": "SH-LGT-1042", "variant_sku": "SH-LGT-1042-BLK-10", "finish_colour": "True Black", "cord_length": "10 ft", "price": 349.0, "inventory_status": "In Stock"
| # | parent_sku | variant_sku | finish_colour | shade_size | cord_length | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Specifications objects from schoolhouse.com. All fields typed and schema-versioned.
"sku": "SH-LGT-1042-BLK-10", "dimensions": "14" W x 9.5" H", "weight": "4.5 lbs", "bulb_type": "E26 Medium Base", "max_wattage": "60W", "damp_rating": "Dry Locations Only"
| # | sku | dimensions | weight | bulb_type | max_wattage | voltage |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Media Assets objects from schoolhouse.com. All fields typed and schema-versioned.
"sku": "SH-LGT-1042", "primary_image_url": "https://cdn.schoolhouse.com/images/factory-light-4-black-primary.jpg", "tear_sheet_pdf_url": "https://cdn.schoolhouse.com/docs/factory-light-4-tearsheet.pdf", "assembly_pdf_url": "https://cdn.schoolhouse.com/docs/factory-light-4-assembly.pdf", "alt_text": "Black industrial pendant light hanging in a modern kitchen", "video_url": "None"
| # | sku | primary_image_url | gallery_image_urls | lifestyle_image_urls | tear_sheet_pdf_url | assembly_pdf_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Categories objects from schoolhouse.com. All fields typed and schema-versioned.
"breadcrumb": "Home > Lighting > Pendants", "category_name": "Pendant Lighting", "sub_category": "Industrial Pendants", "product_count": 84, "filter_tags": "['Brass', 'Black', 'Plug-in', 'Hardwired']", "url": "https://www.schoolhouse.com/collections/pendant-lighting"
| # | breadcrumb | category_name | sub_category | product_count | sort_order | filter_tags |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Schoolhouse scraper navigates complex product matrices, extracting finishes, dimensions, pricing, and dynamic inventory states with full JavaScript rendering.
Extract SKUs, titles, descriptions, and category taxonomy across lighting, hardware, and furniture collections.
Map finishes, colours, cord lengths, and shade sizes to parent SKUs, capturing unique pricing for every combination.
Capture dimensions, weights, bulb requirements, max wattage, and damp ratings directly from product detail pages.
Track stock status, backorder notices, and estimated shipping windows for specific variants.
Extract high-resolution product images, lifestyle photography, tear sheets, and assembly instruction PDFs.
Monitor retail pricing, promotional discounts, and clearance markdowns across the entire catalogue.
Reconstruct category hierarchies and filter tags to understand assortment structure and navigation paths.
Extract 'Pairs well with' recommendations and related product carousels to map merchandising strategies.
Run continuous pipelines at daily or weekly cadences with change-detection diffing for price and stock alerts.
Brief in. Clean data out.
Provide target categories, product URLs, or search terms. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for schoolhouse.com.
Schema validation, null-rate checks, and sample data reviews before full pipeline launch.
JSON, CSV, or Parquet pushed to your S3 bucket, Snowflake stage, or via Webhook on agreed cadence.
Extracting data from premium home goods retailers requires navigating deep product variants and dynamic inventory states.
We utilise residential ISP proxies to distribute request volume across realistic IP addresses, preventing rate limits and IP bans during full catalogue crawls.
Schoolhouse product pages rely on JavaScript to load specific variant pricing, imagery, and inventory states. We use Playwright to execute these scripts and capture the correct data for every finish and size combination.
Our selector strategy uses multiple fallback chains per field, ensuring that minor DOM updates to the Schoolhouse storefront do not break your data pipeline.
For ongoing monitoring, we maintain a hash index of last-seen values per SKU. Subsequent runs only push diffs for changed prices, lead times, or stock statuses.
Every run emits structured logs to our observability stack. We alert on null-rate spikes or coverage drops and respond immediately.
Home decor brands and retailers track premium lighting and hardware pricing to inform their own pricing strategies.
Merchandising teams analyse finish trends, category depth, and new product introductions in the premium hardware market.
Design software platforms ingest product specifications and dimensions to populate 3D modelling catalogues.
Analysts monitor lead times and out-of-stock rates to understand supply chain constraints in the lighting sector.
Research firms identify gaps in the premium home goods market by analysing product density across specific categories.
Machine learning teams train visual search and recommendation models on high-quality lifestyle imagery and product taxonomy.
"Schoolhouse sets the benchmark for premium lighting and hardware specifications. Extracting this catalogue requires navigating complex variant matrices and dynamic inventory states."
Most teams underestimate the complexity of extracting multi-variant lighting catalogues. Capturing finishes, lengths, and dynamic lead times requires full JavaScript rendering and precise session state management. DataFlirt handles the infrastructure so your team can focus on assortment analysis and pricing strategy.
Everything supported by our schoolhouse.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 JavaScript rendering and variant selection flows.
We maintain pools of residential ISP proxies to distribute request volume and prevent IP bans during full catalogue crawls.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About schoolhouse.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Schoolhouse is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and specification data. We do not extract personal data or circumvent authentication walls.
We use Playwright to execute the JavaScript on product pages, systematically selecting each combination of finish, colour, and size to capture the unique SKU, price, and inventory status for every variant.
Yes. We extract the direct URLs for all associated PDF documents, including technical tear sheets and assembly instructions, linking them to the parent SKU.
Pipelines can be configured to run daily or weekly. For inventory monitoring, we provide hash-based diffs so you only receive updates when a stock status or lead time changes.
No. Trade pricing requires an authenticated professional account. DataFlirt only extracts publicly available retail pricing and standard promotional discounts.
Our minimum engagement typically starts with a defined category set or full catalogue extraction delivered weekly. Contact us with your specific data requirements for a custom quote.
Yes. We provide a sample run of up to 100 products during the scoping phase, allowing you to validate the schema, variant mapping, and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or continuous monitoring of finishes and lead times, we build and operate the pipeline. Tell us what you need.
