We extract fabric metadata, sewing pattern inventories, haberdashery pricing, and maker community projects from Minerva Crafts. 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 Fabric Listings objects from minervacrafts.com. All fields typed and schema-versioned.
"sku": "MC-123456", "title": "Minerva Core Range Cotton Jersey", "fabric_type": "Jersey", "composition": "95% Cotton, 5% Elastane", "width": "150cm", "weight": "200gsm", "price_per_metre": 12.99, "stock_status": "In Stock"
| # | sku | title | brand | fabric_type | composition | width |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Sewing Patterns objects from minervacrafts.com. All fields typed and schema-versioned.
"pattern_number": "M7969", "brand": "McCall's", "garment_type": "Dress", "difficulty": "Easy", "size_range": "Y (XSM-SML-MED)", "price": 16.5, "stock_status": "In Stock"
| # | pattern_number | brand | designer | garment_type | difficulty | size_range |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Maker Community objects from minervacrafts.com. All fields typed and schema-versioned.
"post_id": "MK-847291", "author": "SewingEnthusiast99", "project_title": "Summer Wrap Dress", "tagged_products": "['MC-123456', 'M7969']", "likes": 342, "comments": 28, "post_date": "2026-05-10T14:22:00Z"
| # | post_id | author | project_title | description | tagged_products | fabric_used |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Haberdashery objects from minervacrafts.com. All fields typed and schema-versioned.
"sku": "GUT-250-1000", "category": "Thread", "brand": "Gutermann", "colour": "Black 000", "size": "250m", "price": 3.45, "stock_status": "In Stock"
| # | sku | category | sub_category | brand | colour | size |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Inventory objects from minervacrafts.com. All fields typed and schema-versioned.
"sku": "MC-123456", "current_price": 10.39, "list_price": 12.99, "currency": "GBP", "discount_pct": 20, "stock_depth": 45, "scraped_at": "2026-05-12T09:14:00Z"
| # | sku | current_price | list_price | currency | discount_pct | stock_depth |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Minerva Crafts scraper handles the entire platform: fabric specifications, dynamic stock levels, pattern metadata, and user-generated maker content, complete with JavaScript rendering and session management.
Extract composition, weight, width, stretch percentage, and care instructions for every fabric listing.
Capture brand, difficulty level, size ranges, garment types, and recommended fabric lists for all patterns.
Extract user-generated projects, linked products, descriptions, and engagement metrics from the maker community pages.
Map complex unit variations such as half-metres, fat quarters, and full rolls to parent product records.
Capture URLs for high-resolution fabric textures, pattern envelopes, and community project photos.
Track stock availability, restock dates, and low-stock warnings across the entire haberdashery and fabric catalogue.
Extract deep category trees for threads, zips, buttons, and trims with precise colour and size mapping.
Monitor base prices, sale discounts, bulk purchase tiers, and clearance markers timestamped per crawl.
Run continuous pipelines at daily or weekly cadences with change-detection diffing to monitor fast-moving inventory.
Brief in. Clean data out.
Provide category URLs, brand filters, or maker profiles. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for minervacrafts.com.
Schema validation, null-rate checks, and data normalisation for fabric compositions before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Minerva Crafts features complex product variations and infinite-scroll community pages. Here is how we maintain stable extraction.
The Minerva maker community relies heavily on client-side rendering and infinite scroll. We run full Playwright browser sessions to trigger lazy-loading and capture user-generated content that static HTTP requests miss.
Fabric is sold in metres, half-metres, and fat quarters. Our pipeline normalises these variations into structured pricing tiers, ensuring accurate price-per-metre calculations across the catalogue.
Textile analysis requires high-quality imagery. We extract the original, uncompressed image URLs for fabric swatches and pattern line art, bypassing thumbnail compression.
We route requests through UK-based residential proxies to match expected geographic traffic patterns, preventing rate limits and IP bans during deep catalogue crawls.
For the massive fabric catalogue, we maintain a hash index of last-seen values. Subsequent runs only push diffs for stock and price changes, reducing compute cost and downstream processing load.
Online fabric retailers track Minerva's pricing, clearance events, and bulk discount tiers to remain competitive.
Fashion analysts monitor the maker community to identify trending fabrics, colours, and pattern combinations.
Suppliers track stock depletion rates on popular fabrics and haberdashery to predict wholesale demand.
Machine learning teams use the mapping between sewing patterns and recommended fabrics to train recommendation engines.
New independent pattern designers analyse the difficulty levels, size ranges, and pricing of established brands.
Boutique craft stores synchronise their local inventory pricing with national market rates.
"Minerva Crafts holds the most comprehensive structured dataset of modern textiles, sewing patterns, and maker projects in the UK market."
Scraping textile variants requires handling complex unit conversions, infinite-scroll community pages, and high-resolution image asset management. DataFlirt manages the proxy rotation, JavaScript execution, and schema normalisation so your data engineering team can focus on downstream analytics rather than maintaining fragile DOM selectors.
Everything supported by our minervacrafts.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 infinite scroll community pages. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across the UK. Rotation happens per-request to prevent rate limiting during deep catalogue crawls.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About minervacrafts.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from minervacrafts.com is generally permissible under UK law. DataFlirt targets only public, non-authenticated product, pricing, and community data. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
We use Playwright to simulate user scrolling behaviour, triggering the necessary API calls to load older posts. This ensures we capture the full history of user projects and tagged products.
Yes. Minerva sells fabric by the metre, half-metre, and fat quarter. Our pipeline detects these variations and maps them to a standard price-per-metre format for accurate competitor analysis.
We can configure pipelines to run daily or weekly depending on your requirements. Daily runs are typical for monitoring stock depth on popular haberdashery items.
Yes. We locate and extract the URLs for the highest resolution images available on the product page, bypassing the compressed thumbnails used in search results.
Our selector strategy uses multiple fallback chains per field. If a layout change occurs, our monitoring stack detects null-rate spikes and alerts our engineering team to update the selectors, usually within hours.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete catalogue export or continuous price monitoring across the haberdashery range, we scope, build, and operate the pipeline. Tell us what you need.
