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Namshi Product Scraper

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Pay per usage

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Namshi Product Scraper

Namshi Product Scraper

Extract detailed product data from Namshi, the Middle East's premier fashion & beauty retailer. Scrape prices, images, descriptions, and metadata instantly for competitor analysis and e-commerce monitoring. Reliable, scalable extraction. Residential proxies recommended for stability.

Pricing

Pay per usage

Rating

0.0

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Developer

Shahid Irfan

Shahid Irfan

Maintained by Community

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0

Bookmarked

4

Total users

1

Monthly active users

9 days ago

Last modified

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Extract comprehensive Namshi product data for fast, reliable market research and pricing analysis using Namshi's internal catalog API. Collect listings, pricing, discounts, ratings, and stock signals at scale.


Features

  • Listing extraction — Gather product listings from Namshi collections and search pages.
  • Rich product details — Capture parent SKU, SKU, brand, pricing, discount, ratings, and stock signals.
  • Pure API extraction — Uses Namshi catalog JSON endpoints only (no DOM parsing, no detail-page visits).
  • Pagination support — Automatically follows listing pages until the limit is reached.
  • Structured dataset output — Receive clean, analysis-ready data in datasets.

Use Cases

Pricing Intelligence

Track product pricing and discount patterns across Namshi collections to stay competitive and identify market shifts.

Catalog Monitoring

Keep tabs on product availability, new arrivals, and seasonal changes across targeted categories.

Brand Performance Analysis

Compare brand coverage, pricing position, and ratings to inform sourcing and merchandising decisions.

Research and Reporting

Build structured datasets for research, analytics dashboards, and reporting workflows.


How it works

This scraper is API-first and production-oriented:

  1. Catalog endpoint discovery: Uses Namshi's internal /_svc/catalog/catalog/{encodedUri}?page=N endpoint.
  2. JSON module parsing: Extracts product objects from API modules and avoids HTML/DOM selectors entirely.
  3. Pagination via API metadata: Traverses pages using API pagination data.
  4. Clean output logic: Deduplicates products and omits null/empty fields.

Input Parameters

ParameterTypeRequiredDefaultDescription
startUrlsArrayNoList of Namshi catalog URLs to scrape.
results_wantedIntegerNo20Target number of products to scrape.
max_pagesIntegerNo10Limit the number of pages crawled per category.
proxyConfigurationObjectNoProxy settings for bypassing anti-bot measures.

Output Data

Each dataset item contains:

FieldTypeDescription
parentSkuStringParent SKU used for variant grouping.
skuStringVariant SKU.
titleStringProduct name.
brandStringBrand name.
normalPriceNumberRegular price.
salePriceNumberSale price (when available).
discountPercentNumberDiscount percentage.
ratingAverageNumberAverage rating.
ratingCountNumberNumber of ratings/reviews.
stockLabelStringStock status label from API.
productUrlStringProduct page URL.
primaryImageStringFirst product image URL.

Usage Examples

Basic Collection Scrape

Extract products from a single collection page:

{
"startUrl": "https://www.namshi.com/uae-en/men/sports-collection/",
"results_wanted": 20
}

Multi-Collection Run

Collect products from multiple collections in one run:

{
"startUrls": [
{ "url": "https://www.namshi.com/uae-en/men/sports-collection/" },
{ "url": "https://www.namshi.com/uae-en/men/shoes/" }
],
"results_wanted": 50,
"max_pages": 5
}

Search URL Input

Run directly on a search URL:

{
"startUrl": "https://www.namshi.com/uae-en/search?q=running",
"results_wanted": 30,
"max_pages": 6
}

Sample Output

{
"parentSku": "Z3BF7E5DAD83175385FDAZ",
"sku": "Z3BF7E5DAD83175385FDAZ-10",
"title": "Barreda Decode Lux",
"brand": "Adidas",
"normalPrice": 429,
"discountPercent": 0,
"stockLabel": "Low Stock",
"ratingAverage": 5,
"ratingCount": 3,
"productUrl": "https://www.namshi.com/buy-adidas-barreda-decode-lux/Z3BF7E5DAD83175385FDAZ/p/",
"primaryImage": "https://f.nooncdn.com/pzsku/Z3BF7E5DAD83175385FDAZ/45/1762604634/8ae67ba8-fbc0-40a5-a980-682b0ea9a490.jpg"
}

Tips for Best Results

Start with Known Collections

  • Use popular Namshi collections to validate output quickly.
  • Swap in new collection URLs once results look correct.

Control Result Volume

  • Begin with results_wanted set to 20–50 for testing.
  • Increase limits for production runs once outputs are validated.

Use Proxy Configuration

  • Keep proxyConfiguration enabled for stable results.
  • Use residential proxy groups for higher success rates when needed.

Integrations

Connect your data with:

  • Google Sheets — Export for pricing reports.
  • Airtable — Build searchable product catalogs.
  • Make — Automate workflows and alerts.
  • Zapier — Trigger downstream actions.

Export Formats

  • JSON — Developer-friendly data access.
  • CSV — Spreadsheet analysis.
  • Excel — Business reporting.
  • XML — Custom integrations.

Frequently Asked Questions

How many products can I collect?

You can collect all available products, limited by results_wanted and max_pages.

Can I scrape multiple collections at once?

Yes. Provide multiple URLs in startUrls to combine collections in one run.

What if some fields are missing?

Some listings may not expose full details; unavailable fields are omitted from the output item.

Does it work on search pages?

Yes. Use any Namshi search URL as the starting point.

How do I keep scraping stable?

Enable proxyConfiguration and limit result counts for the most reliable runs.


Support

For issues or feature requests, contact support through the Apify Console.

Resources


This scraper is designed for legitimate data collection purposes. You are responsible for complying with Namshi’s terms of service and applicable laws. Use the data responsibly and respect rate limits.