We extract fabric specifications, haberdashery catalogues, pricing tiers, and stock availability from myfabrics.co.uk. Delivered as clean JSON, CSV, or Parquet to S3 or your data warehouse 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 myfabrics.co.uk. All fields typed and schema-versioned.
"sku": "MF-84921", "title": "Organic Cotton Jersey Floral", "category": "Apparel Fabrics > Jersey", "material_composition": "95% Cotton, 5% Elastane", "fabric_width_cm": 150, "fabric_weight_gsm": 220, "price_per_metre": 14.95, "oeko_tex_certified": true
| # | sku | title | category | material_composition | fabric_width_cm | fabric_weight_gsm |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Stock objects from myfabrics.co.uk. All fields typed and schema-versioned.
"sku": "MF-84921", "base_price": 14.95, "discounted_price": 12.5, "discount_pct": 16, "currency": "GBP", "stock_availability": "In Stock", "minimum_order_qty": 0.5, "delivery_time_days": "3-5"
| # | sku | base_price | discounted_price | discount_pct | currency | stock_availability |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Haberdashery objects from myfabrics.co.uk. All fields typed and schema-versioned.
"item_id": "HB-1029", "title": "Gutermann Sew-All Thread 100m", "brand": "Gutermann", "category": "Haberdashery > Threads", "colour": "Navy Blue 339", "material": "100% Polyester", "price": 2.15, "in_stock": true
| # | item_id | title | brand | category | sub_category | colour |
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| 1 | ||||||
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Complete list of extractable fields for Sewing Patterns objects from myfabrics.co.uk. All fields typed and schema-versioned.
"pattern_id": "SP-BURDA-6483", "brand": "Burda", "difficulty_level": "Intermediate", "garment_type": "Dresses", "size_range": "EU 34-44", "price": 9.9, "stock_status": "In Stock", "recommended_fabrics": "['Cotton', 'Linen', 'Viscose']"
| # | pattern_id | brand | difficulty_level | garment_type | recommended_fabrics | size_range |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from myfabrics.co.uk. All fields typed and schema-versioned.
"review_id": "REV-99382", "sku": "MF-84921", "reviewer_name": "Sarah J.", "rating": 5, "review_date": "2023-11-14", "review_text": "Excellent drape and very easy to sew. Washes well without shrinking.", "verified_purchase": true, "helpful_votes": 12
| # | review_id | sku | reviewer_name | rating | review_date | review_text |
|---|---|---|---|---|---|---|
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Our Myfabrics scraper handles the entire textile catalogue: fabric specifications, dynamic pricing per metre, stock availability, and haberdashery variants.
Extract exact material percentages like 95% Cotton and 5% Elastane into structured database columns.
Capture fabric width in cm, weight in GSM, and pattern repeat dimensions for accurate inventory modelling.
Track base prices, promotional discounts, and bulk-buy tier pricing across the entire fabric catalogue.
Identify Oeko-Tex Standard 100, GOTS, and other sustainability labels attached to specific SKUs.
Scrape threads, buttons, zips, and trimmings with exact colour matching codes and brand details.
Monitor real-time inventory status and expected delivery timelines for popular seasonal prints.
Extract washing temperatures, ironing limits, and tumble dry suitability into structured boolean fields.
Capture difficulty levels, size ranges, and recommended fabric pairings for commercial sewing patterns.
Run daily or weekly diffs to update your internal textile database with fresh pricing and stock data.
Brief in. Clean data out.
Provide category URLs or specific textile types. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and custom text parsers for material compositions.
Schema validation, null-rate checks, and GSM outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on agreed cadence.
Textile data requires precise parsing of dimensional and material strings. Here is how we ensure data quality.
Textile sites often mix languages and abbreviations. We parse strings like '95% BW, 5% EL' into structured JSON arrays of material types and percentages.
We normalise fabric width into centimetres and fabric weight into GSM across all product pages, regardless of how it is formatted in the raw HTML.
We map different colourways of the same base fabric to a single parent SKU, maintaining the relationship between pattern variations.
We rotate UK-based residential proxies to bypass rate limits and geographic blocking during full catalogue crawls.
We maintain a hash index of last-seen values. Subsequent runs only push diffs when price per metre or stock status changes.
Track pricing per metre against other UK fabric retailers to optimise your own pricing strategy.
Analyse material composition trends and popular colourways to inform seasonal fabric buying.
Monitor stock availability signals to predict supply shortages in specific textile categories.
Populate craft and sewing aggregator platforms with structured, highly detailed fabric data.
Track the prevalence of GOTS and Oeko-Tex certified fabrics over time across the catalogue.
Train computer vision models using high-resolution fabric texture images linked to exact material labels.
"Textile retail data is notoriously unstructured. Extracting clean composition percentages and GSM weights requires a pipeline built specifically for fabric catalogues."
Most generic scrapers fail at parsing textile specifications. They treat composition strings as raw text and miss critical dimensional data. DataFlirt builds custom parsers for Myfabrics to normalise weights, widths, and material blends into queryable database columns. We handle the extraction complexity so you can focus on merchandising and pricing analysis.
Everything supported by our myfabrics.co.uk 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 dynamic interactions and client-side rendering where required.
We maintain pools of UK residential ISP proxies. Rotation happens per-request to prevent rate limiting during deep catalogue crawls.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About myfabrics.co.uk scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from retail sites is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and stock data. We do not extract personal data or bypass authentication walls.
We use custom regex parsers to split raw text strings into structured arrays. A string like '80% Cotton, 20% Polyester' becomes a queryable JSON object with exact percentages mapped to standardised material names.
Yes. We scrape in-stock flags, low stock warnings, and estimated delivery timelines for every SKU.
Yes. We parse the care instruction icons and text into structured boolean fields indicating washing temperature, tumble dry suitability, and ironing limits.
We recommend daily or weekly cadences for full catalogue refreshes. We can run delta crawls more frequently on a targeted subset of high-priority SKUs.
Yes. We extract the direct CDN URLs for the highest resolution images available, including pattern overviews and close-up texture shots.
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 fabrics. Tell us what you need.
