We extract product specifications, dynamic gold pricing, making charges, and collection data from Joyalukkas. 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 Product Listings objects from joyalukkas.com. All fields typed and schema-versioned.
"sku": "JA23491", "title": "22k Gold Floral Necklace", "category": "Necklace", "metal_type": "Gold", "purity": "22K", "weight_grams": 24.5, "total_price": 185400.0, "collection": "Veda"
| # | sku | title | category | sub_category | metal_type | purity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Gold Rates objects from joyalukkas.com. All fields typed and schema-versioned.
"sku": "JA23491", "base_gold_rate": 6850.0, "metal_weight": 24.5, "making_charge_pct": 14.0, "making_charge_abs": 23495.0, "final_price": 185400.0, "price_timestamp": "2026-05-12T10:15:00Z"
| # | sku | base_gold_rate | metal_weight | making_charge_pct | making_charge_abs | stone_charge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Diamond & Gemstones objects from joyalukkas.com. All fields typed and schema-versioned.
"sku": "JD98210", "stone_type": "Diamond", "total_carat_weight": 1.2, "diamond_colour": "G-H", "diamond_clarity": "VVS-VS", "certification_body": "IGI", "number_of_stones": 14
| # | sku | stone_type | total_carat_weight | diamond_colour | diamond_clarity | setting_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Inventory & Availability objects from joyalukkas.com. All fields typed and schema-versioned.
"sku": "JR11204", "ring_size": "14", "in_stock": true, "shipping_days": 3, "try_at_home_eligible": false, "store_pickup_available": true, "stock_status": "In Stock"
| # | sku | ring_size | bangle_size | chain_length | in_stock | shipping_days |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Collections objects from joyalukkas.com. All fields typed and schema-versioned.
"collection_name": "Eleganza", "product_count": 142, "min_price": 45000.0, "max_price": 450000.0, "gender": "Women", "occasion": "Wedding", "style_type": "Polki"
| # | collection_name | category_url | product_count | min_price | max_price | featured_image |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Joyalukkas pricing is highly dynamic, relying on live metal rates, variable making charges, and stone weights. We capture the exact pricing breakdown alongside high-resolution media and certification data.
Title, SKU, metal purity, weight, stone details, and every metadata field Joyalukkas surfaces — scraped at the individual product level.
Capture the base gold rate applied, making charges, stone values, and GST breakdown to understand the exact final price calculation.
Extract clarity, colour, carat weight, and certification bodies (IGI, GIA) for all diamond and gemstone jewellery.
Track availability across ring sizes, bangle diameters, and chain lengths, mapping parent products to their specific size variants.
Extract URLs for high-resolution product images, 360-degree views, and video assets for visual analysis or catalogue building.
Categorise products by internal Joyalukkas collections like Veda, Apurva, and Eleganza to analyse brand assortment.
Monitor 'Try at Home' eligibility and in-store pickup availability across different pin codes and retail locations.
Isolate the percentage and absolute value of making charges per SKU to benchmark against competitor pricing structures.
Run continuous pipelines at daily or hourly cadences to track gold rate fluctuations and their immediate impact on SKU pricing.
Brief in. Clean data out.
Provide category URLs, collections, or specific metal types. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and dynamic price hydration logic for joyalukkas.com.
Schema validation, null-rate checks, and price-calculation verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Jewellery eCommerce data is uniquely complex due to real-time metal rates and multi-variable pricing. Here is how we ensure accuracy.
Joyalukkas calculates final prices dynamically based on the daily gold rate. Our crawlers execute the necessary JavaScript to hydrate these prices, capturing both the final retail price and the base rate used in the calculation.
Making charges vary by design intricacy and collection. We parse the specific DOM elements that break down the price into metal value, making charges, and taxes, providing a clean financial breakdown per SKU.
In jewellery, changing a ring size often changes the total gold weight and consequently the price. We iterate through available size variants to capture the specific weight and price for each permutation.
Jewellery analysis relies heavily on visuals. We extract the source URLs for zoom-level images and 360-degree product spins, bypassing the compressed thumbnails served on category pages.
Gold rates and taxes can vary by region. We route requests through specific regional proxies to capture the correct pricing and availability for your target market.
Jewellery retailers track Joyalukkas making charges and base rates to optimise their own pricing strategies.
Merchandisers analyse collection sizes, metal purities, and weight brackets to identify gaps in their own catalogues.
Analysts track the introduction of new collections and the ratio of diamond to plain gold jewellery to understand consumer trends.
Computer vision teams use high-resolution jewellery images and structured metadata to train style-matching and virtual try-on models.
Retail strategists monitor 'Try at Home' and store pickup availability to map Joyalukkas's omnichannel fulfilment capabilities.
Financial analysts correlate global gold spot prices with retail pricing adjustments to model margin compression.
"Jewellery eCommerce data is uniquely complex—every SKU's price fluctuates daily with base gold rates, stone weights, and variable making charges."
Extracting data from Joyalukkas requires more than simple HTML parsing. You need to capture the exact matrix of metal weight, diamond clarity, and real-time gold rates that dictate the final price. DataFlirt handles these dynamic calculations and variant matrices so your data engineers don't have to worry about broken schemas or stale prices.
Everything supported by our joyalukkas.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and price hydration.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to maintain consistent regional pricing.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About joyalukkas.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We can schedule pipelines to run daily or multiple times a day to capture the updated base gold rate and the resulting price adjustments across the entire SKU catalogue.
Yes. Where Joyalukkas provides the price breakdown, we extract the metal value, the making charge (both percentage and absolute value), and the applicable GST as distinct fields.
We iterate through the available size variants on the product page. Since weight and price often change with size, we capture the specific data points for each size permutation.
Yes. We parse the stone details section to extract total carat weight, colour, clarity, setting type, and the certification body (such as IGI or GIA).
We extract the direct URLs to the highest resolution images available on the product page, bypassing compressed thumbnails. We can also provide URLs for 360-degree product views if present.
Full catalogue refreshes typically complete within a 2-4 hour window depending on proxy routing. We can configure specific categories to update more frequently if required.
Yes. We provide a sample run of up to 200 SKUs as part of the pre-engagement scoping process so you can validate schema fit and price calculation accuracy.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price-monitoring across all collections — we scope, build, and operate the pipeline. Tell us what you need.
