We extract bulb specifications, fixture details, photometric data, bulk pricing, and stock levels from 1000Bulbs. 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 Bulbs & Lamps objects from 1000bulbs.com. All fields typed and schema-versioned.
"sku": "LED-10045", "brand": "TCP", "wattage": 9.0, "lumens": 800, "colour_temp": "2700K", "base_type": "E26 Medium", "bulb_shape": "A19", "dimmable": true, "cri": 80
| # | sku | brand | wattage | lumens | colour_temp | base_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Fixtures objects from 1000bulbs.com. All fields typed and schema-versioned.
"sku": "FIX-20091", "brand": "Lithonia Lighting", "mounting_type": "Surface Mount", "voltage": "120-277V", "finish": "White", "dimensions": "48 x 10 x 3.5 inches", "ip_rating": "Damp Location", "warranty": "5 Years"
| # | sku | brand | mounting_type | voltage | finish | dimensions |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from 1000bulbs.com. All fields typed and schema-versioned.
"sku": "LED-10045", "base_price": 4.95, "case_price": 4.5, "case_quantity": 24, "bulk_tiers": "['1-23: $4.95', '24+: $4.50']", "stock_status": "In Stock", "lead_time": "Ships in 1 business day", "currency": "USD"
| # | sku | base_price | case_price | case_quantity | bulk_tiers | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Technical Docs objects from 1000bulbs.com. All fields typed and schema-versioned.
"sku": "LED-10045", "spec_sheet_url": "https://1000bulbs.com/pdf/tcp-led-spec.pdf", "energy_star": true, "dlc_listed": false, "ul_listed": true, "rohs_compliant": true, "photometric_data_url": "None"
| # | sku | spec_sheet_url | installation_guide_url | photometric_data_url | energy_star | dlc_listed |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from 1000bulbs.com. All fields typed and schema-versioned.
"review_id": "REV-99382", "sku": "LED-10045", "reviewer_name": "Commercial Electrician", "rating": 5, "review_date": "2023-11-14", "review_title": "Great value for bulk retrofits", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | reviewer_name | rating | review_date | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our 1000Bulbs scraper handles highly variable technical specification tables, dynamic bulk pricing tiers, and document extraction with anti-bot circumvention built in.
Extract data across all categories: LEDs, incandescents, fixtures, ballasts, and electrical supplies.
Capture wattage, lumens, colour temperature, CRI, base type, and dimensions normalised into a unified schema.
Extract base price, case quantity pricing, and pallet discounts to optimise procurement models.
Monitor stock availability, backorder status, and expected shipping dates per SKU.
Capture URLs for PDF specification sheets, installation guides, and LM-79 photometric reports.
Extract alternative and replacement SKUs for discontinued or out-of-stock items.
Track product lines from TCP, Sylvania, Philips, Lithonia, and other major lighting manufacturers.
Extract customer feedback, star ratings, and verified buyer flags across the product catalogue.
Capture precise technical data for ballasts, drivers, transformers, and wiring accessories.
Brief in. Clean data out.
Provide SKU lists, category URLs, or brand filters. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for 1000bulbs.com.
Schema validation, null-rate checks, and specification normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting highly structured technical data requires precise schema mapping. Here is how we maintain accuracy across thousands of varied lighting products.
A commercial high-bay fixture has different specifications than a decorative LED bulb. We use dynamic field mapping to ensure all technical attributes map to a clean, queryable database schema regardless of how 1000Bulbs formats the product page.
B2B lighting procurement relies on case and pallet pricing. Our crawlers extract the full matrix of quantity breaks, case sizes, and discounted rates, structuring them as nested JSON arrays for easy downstream calculation.
Critical compliance data is often locked in PDF spec sheets. We extract the direct URLs for these documents and can optionally run OCR pipelines to parse compliance ratings, photometric charts, and warranty details.
For large product catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load. You get a clean changelog for price and stock updates.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing specification tables, and coverage drops, responding before you notice.
Lighting distributors monitor base and case pricing across thousands of SKUs to adjust their own pricing models and protect margins.
Retailers and wholesalers analyse 1000Bulbs category depth to identify missing product lines in their own catalogues.
Facility managers and electrical contractors ingest pricing and lead times into their ERP systems to optimise bulk purchasing.
Estimating software providers use specification and pricing data to keep their material cost databases accurate for contractors.
eCommerce sites extract technical specifications and cross-reference SKUs to enrich their own product detail pages.
Analysts track the shift from fluorescent to LED technologies by monitoring inventory levels and new product introductions over time.
"1000Bulbs holds one of the most comprehensive digital catalogues for lighting specifications, but extracting structured technical data across thousands of varied SKUs requires precision engineering."
Most teams underestimate the complexity of scraping technical B2B catalogues. Varied specification tables, dynamic bulk pricing tiers, and nested category structures break standard web scrapers. DataFlirt absorbs that complexity so your engineers can focus on analysis, not infrastructure maintenance.
Everything supported by our 1000bulbs.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 for dynamic pricing tables and interaction flows.
We maintain pools of residential ISP proxies to avoid IP bans. Rotation happens per-request with sticky sessions where required.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. State is stored in Postgres.
Data delivered to where your team already works — no new tooling required.
About 1000bulbs.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from 1000Bulbs is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and specification data. We do not extract personal data or circumvent authentication walls.
We use dynamic field mapping. Our parsers recognise the attribute labels across different product categories and normalise them into a unified, predictable JSON schema.
Yes. We extract the base price, case quantity, and all subsequent volume discount tiers, structuring them as nested arrays for easy calculation.
We extract the direct URLs for all attached PDF documents, including spec sheets, installation guides, and photometric reports.
We can configure pipelines to run at daily or sub-daily cadences to monitor stock status and lead times for your specific target SKUs.
Our smallest packages start at a defined SKU list with weekly delivery. For full catalogue extraction, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 500 SKUs as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or continuous price monitoring across thousands of SKUs, we scope, build, and operate the pipeline. Tell us what you need.
