Extract apparel listings, home decor catalogues, fabric specifications, artisan cluster data, and pricing signals from Fabindia. Delivered as clean JSON, CSV, or Parquet to your warehouse.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Apparel Listings objects from fabindia.com. All fields typed and schema-versioned.
"sku": "10712345", "title": "Cotton Hand Block Print Long Kurta", "category": "Women", "sub_category": "Kurtas", "price": 2499.0, "fabric": "Cotton", "craft": "Hand Block Print", "colour": "Indigo", "sizes_available": "['S', 'M', 'L', 'XL']"
| # | sku | title | category | sub_category | price | fabric |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Home Decor objects from fabindia.com. All fields typed and schema-versioned.
"sku": "20598761", "title": "Ceramic Hand Painted Dinner Plate", "category": "Dining", "material": "Ceramic", "dimensions": "10.5 inches", "price": 899.0, "artisan_cluster": "Khurja", "origin_state": "Uttar Pradesh", "in_stock": true
| # | sku | title | category | material | dimensions | weight |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Inventory objects from fabindia.com. All fields typed and schema-versioned.
"sku": "10712345", "base_price": 2499.0, "discount_price": 1999.0, "discount_pct": 20, "currency": "INR", "stock_status": "In Stock", "size_availability": "Partial", "last_updated": "2026-05-12T09:14:00Z"
| # | sku | base_price | discount_price | discount_pct | currency | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Craft & Artisan Data objects from fabindia.com. All fields typed and schema-versioned.
"craft_name": "Ajrakh", "region": "Kutch", "state": "Gujarat", "artisan_community": "Khatri", "products_associated": 142, "sustainability_tags": "['Natural Dyes', 'Handcrafted', 'Water Efficient']"
| # | craft_name | region | state | technique_description | artisan_community | products_associated |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Store Locations objects from fabindia.com. All fields typed and schema-versioned.
"store_id": "FIB-BLR-01", "name": "Fabindia Indiranagar", "format": "Experience Centre", "city": "Bengaluru", "state": "Karnataka", "pincode": "560038", "phone": "+91-80-41123456", "operating_hours": "10:30 AM - 9:00 PM"
| # | store_id | name | format | address | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our Fabindia pipeline handles category pagination, variant matrices, and craft metadata extraction. We manage JavaScript execution and anti-bot headers to deliver clean retail datasets.
Extract sizes, colours, fit metrics, and fabric compositions mapped to parent SKUs across all clothing categories.
Capture dimensions, materials, weights, and care instructions for furniture, ceramics, and soft furnishings.
Isolate metadata regarding artisan techniques, regional origins, and traditional printing methods associated with products.
Monitor base prices, sale discounts, and promotional pricing across the entire catalogue on a daily cadence.
Track out-of-stock indicators and size-level availability to model inventory depth and demand signals.
Extract geolocation, operating hours, and contact details for all Fabindia retail outlets and experience centres.
Capture primary, secondary, and detail-view image URLs for computer vision training and catalogue mirroring.
Extract specific wash care instructions, dry clean mandates, and fabric handling warnings per item.
Receive only new products, updated prices, or stock status changes to minimise downstream processing costs.
Brief in. Clean data out.
Specify target categories, craft types, or store regions. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for fabindia.com.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting accurate retail data requires handling dynamic frontend frameworks and complex product hierarchies.
Category pages rely heavily on client-side rendering. We deploy Playwright to execute JavaScript, trigger lazy-loaded product grids, and ensure complete category coverage.
A single product page often contains multiple colour and size variants with distinct SKUs and stock states. Our pipeline maps these relationships into a flattened, queryable schema.
To prevent rate limiting during deep catalogue crawls, we route requests through Indian residential proxy networks, mimicking legitimate shopper traffic patterns.
Textile descriptions are often unstructured. We normalise fabric compositions, craft names, and care instructions into consistent categorical fields.
Product images are served via dynamic CDNs. We extract the highest resolution asset URLs, bypassing thumbnail compression for accurate visual analysis.
Ethnic wear brands monitor Fabindia pricing, fabric choices, and category expansion to inform their own assortment planning.
Researchers and sustainable fashion advocates track the prevalence of specific regional crafts and natural dyes in commercial retail.
Real estate analysts extract store location data to model retail density and identify premium high-street expansion patterns.
Supply chain analysts track out-of-stock rates across size variants to estimate demand velocity for specific product categories.
Computer vision teams ingest high-resolution product imagery and structural metadata to train ethnic wear classification algorithms.
Retail strategists monitor discount depths during festive sales to benchmark promotional intensity in the ethnic wear segment.
"Fabindia represents the largest structured repository of Indian craft and artisan textile data available commercially, provided you can extract it reliably."
Scraping Fabindia requires navigating complex variant matrices, high-resolution image CDNs, and deeply nested category trees. DataFlirt manages the residential proxy rotation and JavaScript execution required to build a stable pipeline, allowing your analysts to focus purely on textile trends and pricing intelligence.
Everything supported by our fabindia.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 and interaction flows for dynamic category pages.
We maintain pools of Indian residential proxies. Rotation happens per-request with sticky sessions to maintain reliable access during deep crawls.
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 fabindia.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We parse product descriptions and metadata to extract specific craft techniques (e.g., Kalamkari, Ajrakh), regional origins, and fabric compositions into structured fields.
Our pipeline navigates the variant matrix on each product page, creating a flattened record for every unique SKU combination of size, colour, and fit.
Yes. We capture inventory status at the variant level, allowing you to track which specific sizes or colours are currently unavailable.
We support daily, weekly, or custom schedules. For pricing intelligence, daily delta crawls capture new products and price changes efficiently.
Yes. We can extract the complete network of Fabindia experience centres and retail stores, including addresses, operating hours, and geographic coordinates.
We extract and deliver the high-resolution image URLs from the CDN. If raw image files are required, we can configure an S3 sync pipeline for the assets.
DataFlirt captures snapshots from the day your pipeline is commissioned. We maintain a time-series record of price changes and stock states going forward.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue extraction or continuous tracking of craft trends and pricing — we scope, build, and operate the pipeline. Tell us what you need.
