We extract fabric listings, yardage pricing, composition metadata, swatch availability, and stock levels from Fashionfabricsclub. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 fashionfabricsclub.com. All fields typed and schema-versioned.
"sku": "FFC-89214", "title": "Navy Blue 100% Linen Woven Fabric", "material": "Linen", "colour_family": "Blue", "width_inches": 54, "price_per_yard": 12.95, "in_stock": true
| # | sku | title | primary_category | sub_category | material | colour_family |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from fashionfabricsclub.com. All fields typed and schema-versioned.
"sku": "FFC-89214", "price_per_yard": 12.95, "list_price": 18.0, "discount_pct": 28, "swatch_available": true, "swatch_price": 1.5, "yardage_available": 145.5, "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | price_per_yard | list_price | discount_pct | swatch_available | swatch_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Composition & Specs objects from fashionfabricsclub.com. All fields typed and schema-versioned.
"sku": "FFC-89214", "fiber_content": "100% Linen", "weave_type": "Plain Weave", "stretch_pct": "0%", "care_instructions": "Machine Wash Cold, Tumble Dry Low", "usage_recommendations": "['Apparel', 'Home Decor', 'Curtains']", "opacity": "Opaque"
| # | sku | fiber_content | weave_type | stretch_pct | opacity | drape |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Taxonomy & Navigation objects from fashionfabricsclub.com. All fields typed and schema-versioned.
"sku": "FFC-89214", "breadcrumb_1": "Apparel Fabrics", "breadcrumb_2": "Linen Fabrics", "breadcrumb_3": "Solid Linen", "theme": "Classic", "designer_brand": "Generic", "related_skus": "['FFC-89215', 'FFC-89216']"
| # | sku | breadcrumb_1 | breadcrumb_2 | breadcrumb_3 | theme | season |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Feedback objects from fashionfabricsclub.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "FFC-89214", "star_rating": 5, "review_title": "Perfect weight for summer trousers", "review_date": "2026-04-18", "verified_buyer": true, "project_type": "Garment Sewing"
| # | review_id | sku | reviewer_name | star_rating | review_title | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the complexities of textile eCommerce: yardage pricing calculations, swatch variations, deep category hierarchies, and detailed fiber composition parsing.
Title, fiber content, weave type, width, weight, and stretch percentages scraped at the SKU level.
Capture price per yard, bulk discount tiers, and swatch sample pricing accurately.
Monitor available yardage and out-of-stock statuses across the entire catalogue.
Extract colour families, specific shades, and pattern types (floral, geometric, stripe) for precise filtering.
Parse washing, drying, and ironing guidelines into structured fields.
Capture full-resolution image URLs for texture analysis and visual merchandising.
Navigate complex hierarchical menus to map every fabric to its correct end-use category.
Track organic positions for specific textile keywords and material queries.
Run continuous pipelines that only output changed records for pricing and inventory updates.
Brief in. Clean data out.
Provide category URLs, specific material types, or full catalogue requirements. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and parsing logic for Fashionfabricsclub's specific DOM structure.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or BigQuery dataset on agreed cadence.
Scraping fabric sites requires parsing unstructured descriptions into structured metadata. Here is how we manage the Fashionfabricsclub pipeline.
Fabric specifications like width, weight, and fiber content are often bundled in unstructured description text. We use regex and NLP pipelines to parse '54 inch', '8 oz', and '95% Cotton / 5% Spandex' into strict numerical and categorical fields.
Textile sites display multiple prices per SKU. Our scrapers isolate the price per yard from the swatch sample price, ensuring downstream pricing models are not skewed by $1.50 swatch data.
We monitor stock levels by interacting with the quantity selectors, capturing the maximum available continuous yardage before the site throws an out-of-stock error.
Fashionfabricsclub uses deep nested categories (e.g., Apparel > Knits > Jersey > Cotton Jersey). We capture the full breadcrumb trail to maintain accurate product hierarchies.
To prevent IP bans during full catalogue sweeps, we route requests through US-based residential proxies with realistic rate limiting and header rotation.
Fabric retailers track yardage pricing and bulk discount tiers to optimise their own pricing strategies.
Apparel manufacturers monitor stock depth of specific materials to anticipate supply chain bottlenecks.
Designers analyse new arrivals and category expansion to identify trending colours, patterns, and materials.
Marketplaces enrich their own product listings with detailed fiber composition and care instructions.
Computer vision teams use high-res fabric images mapped to structural metadata to train texture recognition models.
Merchants sync available yardage and pricing to their storefronts to prevent selling out-of-stock materials.
"Fashionfabricsclub holds a massive repository of structured textile data. Extracting it cleanly requires parsing complex fiber compositions and distinguishing swatch prices from yardage."
Most teams struggle with textile eCommerce scraping because specifications are buried in unstructured text blocks. DataFlirt builds parsers that normalise fiber percentages, fabric weights, and widths into clean, queryable database columns. You get structured material data, not raw HTML dumps.
Everything supported by our fashionfabricsclub.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 inventory and pricing widgets.
Python-based NLP pipelines parse unstructured product descriptions into strict numerical fields for weight, width, and stretch.
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 fashionfabricsclub.com scraping, legality, and pipeline operations.
Ask us directly →Yes. Our parsers extract unstructured text like '90% Rayon / 10% Spandex' into structured JSON objects, separating the material type from the percentage for easy database filtering.
We specifically target the DOM elements associated with continuous yardage for the primary price field, and map swatch prices to a separate optional field. This prevents your average price metrics from being skewed.
Yes. We can traverse all top-level categories and paginate through every sub-category to extract the full product database, typically yielding tens of thousands of SKUs.
For targeted SKU lists (e.g., your top 5,000 tracked materials), we can run hourly pipelines. Full catalogue refreshes are typically scheduled daily or weekly to respect target server load.
Yes. Washing, drying, and ironing instructions are parsed from the product description and normalised into standard strings.
We deliver data via Webhook, API, or CSV, which your engineering team or middleware (like Make or Zapier) can use to update Shopify inventory and pricing automatically.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous inventory monitoring feed across 40K fabrics, we scope, build, and operate the pipeline. Tell us what you need.
