We extract yarn compositions, independent pattern listings, designer profiles, pricing, and project galleries from LoveCrafts. 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 & Supplies objects from lovecrafts.com. All fields typed and schema-versioned.
"product_id": "YRN-8492", "brand": "Paintbox Yarns", "name": "Simply Chunky", "composition": "100% Acrylic", "yarn_weight": "Chunky", "tension_gauge": "14 stitches, 20 rows to 10cm", "price": 3.5, "currency": "GBP", "stock_status": "In Stock"
| # | product_id | brand | name | composition | yarn_weight | tension_gauge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Digital Patterns objects from lovecrafts.com. All fields typed and schema-versioned.
"pattern_id": "PAT-19384", "title": "Classic Raglan Sweater", "designer_name": "Jane Knits", "craft_type": "Knitting", "difficulty_level": "Intermediate", "yarn_weight_required": "DK", "price": 6.0, "rating": 4.8
| # | pattern_id | title | designer_name | craft_type | difficulty_level | sizes_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Designer Profiles objects from lovecrafts.com. All fields typed and schema-versioned.
"designer_id": "DES-992", "name": "Jane Knits", "pattern_count": 42, "follower_count": 1205, "top_selling_pattern": "Classic Raglan Sweater", "average_rating": 4.7, "profile_url": "https://www.lovecrafts.com/en-gb/user/Jane-Knits"
| # | designer_id | name | bio | joined_date | pattern_count | follower_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from lovecrafts.com. All fields typed and schema-versioned.
"review_id": "REV-38471", "product_id": "YRN-8492", "star_rating": 5, "review_text": "Great stitch definition and very soft for acrylic.", "date_posted": "2025-11-14", "craft_experience_level": "Advanced", "helpful_votes": 12, "verified_buyer": true
| # | review_id | product_id | product_type | reviewer_name | star_rating | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Community Projects objects from lovecrafts.com. All fields typed and schema-versioned.
"project_id": "PRJ-5582", "user_name": "KnitCrafter99", "project_title": "Winter Beanie", "pattern_used": "Basic Ribbed Hat", "yarn_used": "Paintbox Yarns Simply Chunky", "status": "Completed", "likes_count": 45, "image_urls": "['https://images.lovecrafts.com/project-5582-1.jpg']"
| # | project_id | user_name | project_title | pattern_used | yarn_used | status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles the specific metadata of the crafting world: yarn compositions, gauge metrics, independent designer listings, and community project mapping.
Capture composition percentages, weight classifications, tension gauge, and recommended needle sizes for every yarn SKU.
Extract independent designer listings, mapping difficulty levels, required yardage, and craft types across thousands of PDFs.
Monitor base prices, clearance discounts, and multi-buy promotions across GBP, USD, and EUR localised storefronts.
Track availability at the colourway level to identify supply chain constraints and popular dye lots.
Analyse independent creator output, tracking pattern release velocity, pricing strategies, and community ratings.
Extract full review text and star ratings, filtering by the self-reported craft experience level of the reviewer.
Map the relationship between patterns and the actual yarns users choose by scraping community project galleries.
Extract localised catalogues for the UK, US, and EU markets from a unified schema.
Run continuous pipelines that only emit records when prices, stock status, or review counts change.
Brief in. Clean data out.
Provide category URLs, brand lists, or designer profiles. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management tailored for lovecrafts.com.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Extracting data from LoveCrafts requires parsing highly specific variant matrices and managing dynamic frontend filtering.
Yarn listings on LoveCrafts often feature 50+ colour variants on a single product page. Our crawlers iterate through every variant combination to capture specific stock status and pricing per colourway.
Category pages and community galleries rely heavily on client-side rendering. We deploy Playwright to execute JavaScript, ensuring we capture items loaded dynamically via infinite scroll and AJAX filters.
Crafting metadata (gauge, composition, yardage) is often formatted inconsistently across different brands. We use regex and NLP parsing to normalise unstructured text into clean, typed database columns.
To prevent IP bans and rate limiting, our infrastructure routes requests through UK and US residential proxies, mimicking natural browsing patterns across the LoveCrafts catalogue.
For large pattern catalogues, we maintain a hash index of last-seen values. Subsequent runs only push diffs for price changes or new reviews, reducing downstream processing load.
Retailers track pricing, promotions, and clearance events across major yarn brands to optimise their own pricing strategies.
Merchandisers identify trending yarn weights, compositions, and colourways based on review velocity and stock depletion rates.
Publishers and yarn brands track popular independent pattern creators to identify partnership and sponsorship opportunities.
Manufacturers monitor stockouts on specific dye lots and materials to anticipate market demand and adjust production schedules.
Analysts track the shift in popularity between different craft types (knitting vs crochet) over time.
ML teams map patterns to their required yarn types and user execution to build better product recommendation engines.
"LoveCrafts holds the definitive graph mapping independent pattern designers to specific yarn compositions and community execution."
Extracting crafting data requires parsing highly specific metadata: yarn weights, gauge metrics, and dye lot variations. DataFlirt handles the complex variant mapping and JavaScript rendering so your analysts can focus on market trends rather than broken DOM selectors.
Everything supported by our lovecrafts.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 retry logic. Playwright handles JavaScript rendering for dynamic category filters and community galleries.
We maintain pools of residential ISP proxies across UK and US regions. Rotation happens per-request to bypass rate limits.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About lovecrafts.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from LoveCrafts is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not bypass payment gateways to download PDF patterns or extract personal user data.
Yes. Our pipeline iterates through the frontend variant selectors to capture exact pricing, stock status, and image URLs for every individual dye lot and colourway listed on a product page.
Yes. We extract designer bios, social links, follower counts, and aggregate metrics for their entire pattern catalogue.
Crafting metadata can be messy. We use custom parsing logic to normalise tension gauge formats, composition percentages, and recommended needle sizes into structured database columns.
Yes. We can configure daily or hourly pipelines to monitor stock status across specific brands or categories, emitting alerts when items go out of stock.
We deliver data in JSON, CSV, XLS, or Parquet formats. Files can be pushed directly to AWS S3, Google Cloud Storage, or streamed via Webhook.
Yes. We provide a sample run of up to 500 products or patterns during the scoping phase so you can validate the schema and data quality before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily yarn pricing feed or a complete pattern catalogue export, we scope, build, and operate the pipeline. Tell us what you need.
