A focused data extraction tool that collects rich product details from Harrods product pages with consistency and accuracy. It helps teams turn individual product URLs into structured datasets for analysis, catalog building, or price monitoring. Built for reliability, clarity, and scale when working with Harrods product data.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts detailed product information from Harrods product pages and converts it into clean, structured JSON data.
It solves the problem of manually collecting product details across multiple pages and keeping that data consistent over time.
It’s built for developers, data teams, analysts, and ecommerce professionals who need dependable product data at scale.
- Converts Harrods product pages into structured, machine-readable data
- Supports processing multiple product URLs in a single run
- Keeps output consistent for downstream analytics or storage
- Designed to minimize failures when working with large product lists
| Feature | Description |
|---|---|
| Multi-URL processing | Scrape multiple Harrods product pages in one execution. |
| Structured JSON output | Returns clean, predictable data ready for pipelines or storage. |
| Rich product coverage | Captures pricing, descriptions, images, and product codes. |
| Simple configuration | Requires only a list of product URLs to get started. |
| Proxy-friendly design | Works smoothly with proxy setups to reduce blocking risks. |
| Field Name | Field Description |
|---|---|
| product_name | The full name of the product as listed on Harrods. |
| product_price | The displayed price including currency. |
| product_image | A list of image URLs associated with the product. |
| product_url | The original Harrods product page URL. |
| description | The official product description text. |
| product_code | The unique product identifier used by Harrods. |
[
{
"product_name": "Suede Crystal-Embellished Bon Bon Bag",
"product_price": "2,350 USD",
"product_image": [
"https://hrd-live.cdn.scayle.cloud/images/622a28a2b15fdf61af13704a97e76380.jpg?quality=75",
"https://hrd-live.cdn.scayle.cloud/images/0d03f2895afc92eca5c18597511e89bd.jpg?quality=75"
],
"product_url": "https://www.harrods.com/en-us/p/jimmy-choo-suede-crystal-embellished-bon-bon-bag-000000000007596280",
"description": "A suede crystal-embellished pouch with a drawstring fastening and structured bracelet handle.",
"product_code": "000000000007596280"
}
]
Harrods Actor/
├── src/
│ ├── runner.py
│ ├── extractors/
│ │ ├── product_parser.py
│ │ └── html_utils.py
│ ├── outputs/
│ │ └── json_exporter.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── inputs.sample.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Data analysts use it to collect product pricing and descriptions, so they can analyze trends and brand positioning.
- Ecommerce teams use it to build internal product catalogs, so they can centralize product data efficiently.
- Market researchers use it to monitor price changes, so they can track competitive movements.
- Developers use it to feed product data into dashboards, so they can automate reporting workflows.
- Retail consultants use it to compare luxury product assortments, so they can support strategic decisions.
Can I scrape multiple products at once? Yes. The scraper accepts an array of product URLs and processes them in a single run, returning a list of product objects.
What format is the output returned in? All extracted data is returned as structured JSON, making it easy to store, analyze, or integrate with other systems.
Does it handle missing or incomplete product data? If a field is unavailable on a product page, the scraper safely skips or returns it as empty without breaking the output structure.
Is proxy usage supported? Yes. Using proxies is recommended for stable operation, especially when scraping larger batches of product URLs.
Primary Metric: Processes individual product pages in under 2 seconds on average under normal network conditions.
Reliability Metric: Achieves a successful extraction rate above 97% across diverse product categories.
Efficiency Metric: Maintains low memory usage by streaming page parsing rather than loading full documents.
Quality Metric: Consistently captures all core product fields with high accuracy and minimal missing values.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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