We extract product specifications, manufacturer part numbers, branch-level inventory, and list pricing from Platt Electric Supply. 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 Basics objects from platt.com. All fields typed and schema-versioned.
"platt_item_number": "063124", "mfg_part_number": "QO120", "upc": "785901400103", "title": "Square D QO120 Miniature Circuit Breaker", "brand": "Square D", "category": "Distribution Equipment", "sub_category": "Circuit Breakers"
| # | platt_item_number | mfg_part_number | upc | title | brand | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Technical Specs objects from platt.com. All fields typed and schema-versioned.
"platt_item_number": "063124", "voltage": "120/240 VAC", "amperage": "20 A", "poles": 1, "mounting_type": "Plug-On", "wire_size": "AWG 14...AWG 8 (copper)", "certifications": "['UL Listed', 'CSA']"
| # | platt_item_number | voltage | amperage | poles | material | colour |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from platt.com. All fields typed and schema-versioned.
"platt_item_number": "063124", "list_price": 9.45, "uom": "EA", "standard_package_qty": 10, "min_order_qty": 1, "stock_status": "In Stock", "currency": "USD"
| # | platt_item_number | list_price | uom | standard_package_qty | min_order_qty | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Documents & Media objects from platt.com. All fields typed and schema-versioned.
"platt_item_number": "063124", "spec_sheet_url": "https://www.platt.com/CutSheets/SquareD/QO120.pdf", "installation_guide_url": "https://www.platt.com/CutSheets/SquareD/QO_Install.pdf", "compliance_rohs": true, "primary_image": "https://images.plattstatic.com/Products/Large/063124.jpg", "warranty_pdf": "None", "cad_drawing_url": "None"
| # | platt_item_number | spec_sheet_url | msds_url | installation_guide_url | cad_drawing_url | warranty_pdf |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Taxonomy & Hierarchy objects from platt.com. All fields typed and schema-versioned.
"platt_item_number": "063124", "category_l1": "Distribution Equipment", "category_l2": "Circuit Breakers", "category_l3": "Miniature Circuit Breakers", "category_l4": "Plug-On Breakers", "related_items": "['063125', '063126']", "accessories": "['071299']"
| # | platt_item_number | category_l1 | category_l2 | category_l3 | category_l4 | breadcrumbs |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Platt scraper navigates complex B2B taxonomies, extracts deep technical specifications, and tracks regional branch inventory levels across millions of electrical SKUs.
Extract exact MPNs, UPCs, and Platt internal item numbers to map supplier catalogues directly to your MDM systems.
Capture voltage, amperage, material, dimensions, and compliance certifications normalising unstructured text into typed JSON fields.
Query stock levels across specific Platt branches or regional distribution centres to build accurate supply chain models.
Harvest links to manufacturer spec sheets, MSDS documents, installation guides, and CAD drawings attached to product pages.
Extract standard list prices, Units of Measure (UOM), minimum order quantities, and standard package sizes.
Reconstruct the full category hierarchy from L1 down to L4, ensuring items map correctly into your procurement software.
Extract related items, recommended accessories, and alternative SKUs surfaced on the product detail page.
Handle complex product variations like cut-to-length wire, spool sizes, and colour options accurately.
Track price changes and stockouts on critical components with daily or hourly pipeline runs.
Brief in. Clean data out.
Provide target categories, manufacturer names, or specific Platt item numbers. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for platt.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
B2B distribution sites present unique structural challenges. Here is how we ensure reliable data extraction from platt.com.
Platt displays inventory based on selected branches. We manage cookie sessions and zip code initialisation to extract accurate stock levels for your target geographic regions.
MRO sites have deeply nested categories. Our crawlers systematically traverse the entire L1-L4 taxonomy tree, ensuring no obscure sub-category or niche component is missed during full catalogue runs.
Technical specs are often rendered in inconsistent HTML tables or flat text. We use pattern matching and layout analysis to normalise attributes like voltage and dimensions into structured key-value pairs.
To prevent IP bans during large-scale catalogue extraction, we route requests through US-based residential proxies, maintaining appropriate request delays to respect site infrastructure.
For daily inventory tracking across millions of SKUs, we compute hashes of the stock status and only deliver records that have changed, drastically reducing your ingestion costs.
Electrical distributors monitor Platt's list pricing, brand assortment, and stock availability to adjust their own market positioning.
Contractors and industrial buyers feed Platt catalogue data into their estimating and procurement systems to streamline purchasing workflows.
Electrical equipment manufacturers audit product pages to ensure technical specifications are accurate and Minimum Advertised Price (MAP) policies are respected.
Data teams use Platt's structured attributes and MPN mappings to enrich their internal product information management (PIM) systems.
Construction estimation platforms ingest list pricing and UOM data to provide accurate material cost baselines to their users.
Analysts track regional stockouts on critical components like breakers and transformers to anticipate supply chain bottlenecks.
"Platt's catalogue represents the backbone of electrical distribution data, but extracting clean, dimensional specs from nested MRO hierarchies requires dedicated infrastructure."
B2B distribution sites present unique scraping challenges: deeply nested taxonomies, branch-specific inventory states, and crucial technical data locked behind complex DOM structures. DataFlirt engineers custom extraction logic for platt.com, normalising complex electrical attributes so your procurement and pricing models ingest clean data without the maintenance burden.
Everything supported by our platt.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. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 platt.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available list pricing, product specifications, and inventory data is generally permissible. DataFlirt targets only public, non-authenticated catalogue data. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
No. DataFlirt operates on publicly accessible data. We extract the standard list prices displayed to anonymous users. We do not manage client credentials or scrape authenticated B2B portals.
We configure our crawlers to initialise sessions with specific zip codes or branch IDs. This allows us to extract stock levels for the exact distribution centres relevant to your supply chain.
Our standard pipeline extracts the URLs to the PDF documents. If you require text extraction from within the PDFs, we can build custom parsing logic as an add-on service.
For targeted SKU lists (e.g., top 10,000 items), we can run pipelines hourly or daily. Full catalogue refreshes (millions of SKUs) are typically scheduled weekly to respect target site load.
We normalise unstructured HTML tables into structured JSON key-value pairs. For CSV deliveries, we can flatten these attributes into dedicated columns or provide a single JSON-encoded string column for specs.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or a continuous inventory feed across 500K SKUs — we scope, build, and operate the pipeline. Tell us what you need.
