We extract clothing catalogues, pricing signals, brand intelligence, and stock availability from Namshi. 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 namshi.com. All fields typed and schema-versioned.
"sku": "NI126SH48PTN", "title": "Air Force 1 '07", "brand": "Nike", "price": 549.0, "currency": "AED", "colour": "White", "available_sizes": "['US 7', 'US 8', 'US 9', 'US 10']"
| # | sku | title | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Offers objects from namshi.com. All fields typed and schema-versioned.
"sku": "NI126SH48PTN", "current_price": 439.0, "original_price": 549.0, "discount_pct": 20, "currency": "AED", "sale_badge": "SALE"
| # | sku | current_price | original_price | discount_pct | currency | promo_code_eligible |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Inventory & Sizing objects from namshi.com. All fields typed and schema-versioned.
"sku": "NI126SH48PTN", "size_system": "US", "sizes_in_stock": "['7', '8', '9', '10']", "sizes_out_of_stock": "['11', '12']", "low_stock_warning": "['9']", "last_checked": "2026-05-12T09:14:00Z"
| # | sku | size_system | sizes_in_stock | sizes_out_of_stock | low_stock_warning | stock_depth_estimate |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Brand Data objects from namshi.com. All fields typed and schema-versioned.
"brand_id": "B_NIKE", "brand_name": "Nike", "total_products": 4281, "active_categories": "['Shoes', 'Clothing', 'Accessories']", "average_price": 385.5, "discount_frequency": 0.35
| # | brand_id | brand_name | total_products | active_categories | average_price | discount_frequency |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Category Results objects from namshi.com. All fields typed and schema-versioned.
"keyword": "sneakers", "position": 1, "sku": "NI126SH48PTN", "title": "Air Force 1 '07", "brand": "Nike", "price": 549.0, "is_new": false
| # | keyword | category_path | position | sku | title | brand |
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Our Namshi scraper handles regional localization, dynamic pricing, sizing matrices, and deep category taxonomies with JavaScript rendering and anti-bot circumvention built in.
Title, brand, description, high-resolution imagery, and material composition extracted at the SKU level.
Track AED, SAR, QAR, KWD, BHD, and OMR pricing variations across different GCC storefronts.
Map available versus out-of-stock sizes per variant. Detect low-stock warnings and inventory depth signals.
Capture sale badges, percentage discounts, and promo code eligibility rules applied to specific catalogues.
Track brand catalogue size, category penetration, and average price points across the entire platform.
Extract deep category trees from top-level departments down to specific product sub-categories.
High-frequency polling for hype items and exclusive releases to track sell-through velocity.
Extract dual-language metadata by orchestrating parallel sessions with precise language headers.
Run one-off bulk exports or configure continuous pipelines at daily or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide brand lists, category URLs, or target regions. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for namshi.com.
Schema validation, null-rate checks, price-outlier detection, and size matrix verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Fashion e-commerce requires complex variant mapping and regional session handling. Here is how we stay resilient.
Namshi routes users based on geolocation and session cookies. We maintain strict cookie jars per region (AE, SA, QA) to prevent currency bleed and ensure accurate local pricing extraction.
Size availability is often managed via complex frontend state. We intercept backend API responses and parse dynamic DOM elements to build accurate in-stock arrays per SKU.
Data center IPs are frequently rate-limited by regional CDNs. We utilize residential proxy pools localized to the Middle East to mimic legitimate shopper behaviour and maintain high concurrency.
For large catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Fashion sites update their frontend frameworks frequently. We alert on null-rate spikes and schema drift, updating selectors before you notice data loss.
Retailers track Namshi's discount strategies across regions to optimise their own pricing rules.
Brands audit their visibility, category rank, and stock availability against competitors on the platform.
Analytics teams ingest historical discount data to optimise their own sale periods and clear seasonal inventory.
Buyers analyze category growth, colour velocity, and new arrivals over time to predict upcoming seasonal trends.
Brands monitor pricing across different GCC storefronts to detect regional price arbitrage.
ML teams use Namshi's extensive high-resolution product imagery and metadata to train computer vision models.
"Namshi dictates fashion pricing trends in the GCC - but extracting accurate, localized stock data across six countries requires dedicated infrastructure."
Most teams underestimate the complexity of regional e-commerce scraping. Reliable Namshi extraction requires Middle Eastern residential proxies, precise session handling for currency localization, and daily maintenance of variant selectors. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our namshi.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 interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across key Middle Eastern regions. Rotation happens per-request with sticky sessions where required for currency stability.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 namshi.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Namshi is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and inventory data. We do not extract personal data or circumvent authentication walls.
We use strict session management and localized residential proxies. Each pipeline run is configured with the correct regional cookies and headers to ensure the API returns the exact currency and pricing rules for that specific GCC country.
Yes. Our variant mapping extracts the full size matrix per SKU, detailing exactly which sizes are in stock, out of stock, or triggering low-stock warnings.
Yes. We can run parallel extraction pipelines using Arabic language headers to capture localized titles, descriptions, and category taxonomies alongside the English data.
Full catalogue refreshes typically run daily. For high-priority categories or sneaker drops, we configure high-frequency polling pipelines that capture pricing and stock changes hourly or sub-hourly.
Our smallest packages start at a defined brand list or category subset (typically 10,000 SKUs) with weekly delivery. For full-site extraction across multiple regions, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily brand assortment dump or continuous price-monitoring across multiple GCC regions, we scope, build, and operate the pipeline. Tell us what you need.
