We extract yarn weights, fibre blends, tension metrics, pattern requirements, and pricing from Laughing Hens. 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 Yarn Listings objects from laughinghens.com. All fields typed and schema-versioned.
"sku": "ROW-KF-01", "brand": "Rowan", "name": "Kidsilk Haze", "price": 9.95, "currency": "GBP", "weight_category": "Lace", "composition": "70% Mohair, 30% Silk", "tension": "18-25 sts x 23-34 rows to 10cm", "needle_size": "3.25mm - 5mm", "ball_weight": "25g"
| # | sku | brand | name | price | currency | weight_category |
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Complete list of extractable fields for Knitting Patterns objects from laughinghens.com. All fields typed and schema-versioned.
"pattern_id": "PAT-1049", "designer": "Martin Storey", "title": "Cabled Sweater", "garment_type": "Sweater", "difficulty": "Intermediate", "required_yarn_name": "Felted Tweed", "sizes_available": "S, M, L, XL, XXL", "price": 4.5
| # | pattern_id | designer | title | category | garment_type | difficulty |
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Complete list of extractable fields for Pricing & Inventory objects from laughinghens.com. All fields typed and schema-versioned.
"sku": "ROW-KF-01", "product_type": "yarn", "price": 9.95, "list_price": 11.5, "discount_pct": 13, "currency": "GBP", "in_stock": true, "stock_quantity": 42, "price_timestamp": "2023-10-24T08:12:00Z"
| # | sku | product_type | price | list_price | discount_pct | currency |
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Complete list of extractable fields for Needles & Accessories objects from laughinghens.com. All fields typed and schema-versioned.
"sku": "KNP-ZING-35", "brand": "KnitPro", "name": "Zing Single Pointed Needles", "category": "Needles", "material": "Aluminium", "size": "3.5mm", "length": "35cm", "price": 4.2, "in_stock": true
| # | sku | brand | name | category | material | length |
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Complete list of extractable fields for Brands & Collections objects from laughinghens.com. All fields typed and schema-versioned.
"brand_id": "BR-ROWAN", "brand_name": "Rowan", "origin_country": "UK", "total_yarns": 45, "total_patterns": 1204, "active_collections": "['Kidsilk Haze', 'Felted Tweed', 'Alpaca Soft']", "scraped_at": "2023-10-24T08:15:00Z"
| # | brand_id | brand_name | description | origin_country | total_yarns | total_patterns |
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Our Laughing Hens scraper handles every layer of the platform: yarn specifications, designer pattern requirements, stock availability, and historical pricing — with custom parsing for unstructured textile metrics.
Fibre blends mapped accurately. We parse free-text descriptions into structured percentage arrays for wool, alpaca, silk, and synthetic blends.
Extract row and stitch counts precisely. We separate complex tension strings into distinct numerical fields for database querying.
Link required yarns to pattern listings. We traverse pattern requirements to build relational mappings between pattern IDs and exact yarn SKUs.
Monitor stock levels and restock dates. Track availability across thousands of dye lots and colourways.
Extract metric sizes and convert to US/UK standards. Ensure consistency across international needle and hook inventories.
Track sales, clearance events, and bulk discounts. Capture current price, list price, and calculated discount percentages.
Extract washing, drying, and ironing parameters. We parse care symbols and text into boolean flags and temperature values.
Aggregate pattern counts per designer. Monitor new releases and popular garment types from top independent creators.
Extract product image URLs for yarns, swatches, and finished garments. Useful for visual merchandising and machine learning.
Run daily exports or hourly diffs. Receive only updated records to minimise database ingestion load.
Brief in. Clean data out.
Provide target brands, yarn weights, or pattern categories. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and custom regex parsers specifically for laughinghens.com textile data.
Schema validation, tension format checks, null-rate monitoring, and stock outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Textile data is notoriously unstructured. Here is how we convert messy crafting specifications into pristine relational databases.
Laughing Hens lists compositions as free text (e.g., 75% Wool, 25% Nylon). We use custom NLP pipelines to normalise these into structured percentage arrays, ensuring accurate material filtering.
Tension data often mixes stitches, rows, and needle sizes in a single string. We parse this into separate integer fields for rows and stitches per 10cm, enabling precise database querying.
Patterns specify required yarns. Our pipeline traverses these text links to build a strict relational mapping between pattern IDs and the specific yarn SKUs required to knit them.
Yarn and pattern categories span hundreds of pages with varied filtering parameters. We manage pagination state strictly to ensure zero data loss during full catalogue sweeps.
We utilise UK-based residential proxies and randomised request delays to maintain steady extraction without triggering IP bans or geographic blocking from the host server.
Retailers track Laughing Hens pricing on premium brands like Rowan and Sirdar to adjust their own margins and promotional calendars.
Wholesalers monitor out-of-stock rates across specific fibre blends to forecast supply chain gaps and manufacturing demands.
Designers analyse popular pattern difficulties, garment types, and trending yarn weights to inform new collections and publications.
Crafting platforms ingest structured yarn specifications to build comprehensive global databases for knitters and crocheters.
Analysts track total SKU counts across brands and categories to estimate market share within the UK textile and craft sector.
Computer vision teams use extracted garment images and pattern metadata to train knitting classification and recommendation models.
"Laughing Hens holds a wealth of structured textile data — from precise fibre blends to complex pattern requirements — but extracting it cleanly requires domain-specific parsing."
Most generic scrapers fail at textile data. They treat yarn composition and tension metrics as raw text blocks. DataFlirt builds custom parsing logic to separate stitches from rows, normalise metric and US needle sizes, and map pattern requirements to specific yarn SKUs. We manage the infrastructure so your team can focus on analysis, not regex debugging.
Everything supported by our laughinghens.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 orchestrates the crawl while LXML handles rapid parsing of static product pages, ensuring high throughput for the Laughing Hens catalogue without unnecessary overhead.
We route requests through UK-based residential proxies to match the target demographic and avoid geographic rate limiting or blocking from the host server.
Python pipelines using complex regex and NLP normalise messy string data into strict numerical arrays for tension, composition, and needle sizes.
Data delivered to where your team already works — no new tooling required.
About laughinghens.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product data, prices, and specifications is generally permissible. DataFlirt does not extract copyrighted PDF patterns or personal user data. Clients should consult legal counsel for specific use cases.
We use custom regex parsers to convert strings like '75% Wool, 25% Polyamide' into structured JSON arrays containing exact percentage integers and material strings.
Yes. When a pattern specifies a required yarn, we extract the yarn name, required quantity, and link it to the corresponding yarn SKU in our database.
For full catalogue sweeps, we recommend daily runs. For targeted lists of high-priority SKUs, we can configure hourly pipelines to monitor stock levels.
We extract the raw data as displayed on laughinghens.com (typically metric mm and UK sizes) and can normalise these to US sizes via custom transformation logic upon request.
Our selectors use multiple fallback chains. If a structural change causes null-rate spikes, our Prometheus alerts trigger an immediate engineering response to patch the pipeline.
Yes. We provide a sample run of up to 500 yarn SKUs during the scoping phase so you can validate the structure of tension, composition, and needle size fields.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily stock feed or a comprehensive database of yarn specifications — we scope, build, and operate the pipeline. Tell us what you need.
