The Ridge Wallet Scraper

The Ridge Wallet Scraper collects detailed product information, pricing, and metadata from ridgewallet.com. Built for e-commerce research and competitive intelligence, it turns The Ridge Wallet store into a structured product feed you can use for analysis, tracking, or integration with your tools.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

This scraper acts as a product data API for The Ridge Wallet online store. Since the site is Shopify-based, the tool reliably extracts product details, variants, pricing, and images across all accessories and product categories. Whether you're tracking competitors, researching product lines, or building a dataset for analysis, this scraper delivers clean and consistent output.

Why It’s Useful

• Scrapes product data without manually browsing ridgewallet.com.
• Provides structured JSON, CSV, Excel, XML, or HTML for maximum flexibility.
• Useful for price monitoring, market research, competition tracking, or catalog analysis.
• Automatically captures variant pricing, titles, images, and product collections.

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Features

Feature	Description
Full Product Extraction	Retrieves all products, variants, descriptions, and media.
Pricing & Availability	Captures prices, compare-at values, and stock details when available.
Multi-Format Output	JSON, CSV, Excel, XML, and HTML exports supported.
Shopify-Compatible	Uses predictable Shopify structures to ensure consistent scraping.
Accessory Category Coverage	Targets wallets, gear, add-ons, and all Ridge accessories.
Structured Output	Clean and uniform data to integrate into reports or datasets.

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What Data This Scraper Extracts

Field Name	Field Description
productId	Unique Shopify product identifier.
title	Product name.
description	Full HTML or text description.
price	Current selling price.
compareAtPrice	Original price if discounted.
variants	List of product variants and their pricing.
images	URLs of product photos.
tags	Tag metadata applied to the product.
productUrl	URL of the product on ridgewallet.com.
category	Product collection or category name.

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Example Output

[
  {
    "productId": "987654321",
    "title": "The Ridge Wallet – Carbon Fiber",
    "description": "<p>A sleek carbon fiber wallet...</p>",
    "price": 125.00,
    "compareAtPrice": 150.00,
    "variants": [
      {
        "variantId": "987654321-1",
        "title": "Carbon Fiber",
        "price": 125.00
      }
    ],
    "images": [
      "https://ridgewallet.com/images/carbonfiber1.jpg",
      "https://ridgewallet.com/images/carbonfiber2.jpg"
    ],
    "tags": ["wallet", "carbon-fiber", "accessories"],
    "productUrl": "https://ridgewallet.com/products/carbon-fiber-wallet",
    "category": "Wallets"
  }
]

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Directory Structure Tree

The Ridge Wallet Scraper/
├── src/
│   ├── main.js
│   ├── scraper/
│   │   ├── product_list_scraper.js
│   │   ├── product_detail_scraper.js
│   │   └── shopify_parser.js
│   ├── utils/
│   │   ├── request_handler.js
│   │   ├── normalizer.js
│   │   └── formatter.js
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_output.json
├── package.json
└── README.md

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Use Cases

• Market researchers compare pricing trends and product updates.
• Competitor analysts monitor new releases and product changes.
• E-commerce teams study product positioning for category benchmarking.
• Developers integrate product feeds into apps, dashboards, or automation workflows.
• Retail analysts enrich databases with structured accessories data.

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FAQs

Does this scraper cover all Ridge Wallet categories?
Yes, it extracts data across wallets, accessories, gear, and all Shopify-listed collections.

What formats can I export the data in?
JSON, CSV, Excel, XML, and HTML are supported.

Is this scrape safe for repeated use?
Yes—Shopify's standard structure enables consistent, stable extraction.

Can it extract variant pricing?
Yes, all variants and their prices are included.

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Performance Benchmarks and Results

Primary Metric:
Scrapes full product catalog in under 30 seconds on average.

Reliability Metric:
98%+ consistent extraction due to stable Shopify templates.

Efficiency Metric:
Batch fetching reduces request overhead to handle catalog-wide scraping.

Quality Metric:
Delivers complete and accurate product metadata suitable for analysis or automation.

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