A lightweight CVS scraper that collects structured product data from CVS product pages with minimal setup. It helps teams and developers quickly turn raw product pages into clean, usable data for analysis, monitoring, and automation.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts detailed product information from CVS product pages and returns it in a clean JSON format. It removes the manual work of copying prices, descriptions, and images one by one. The tool is ideal for developers, analysts, and e-commerce teams who need reliable CVS product data at scale.
- Accepts a list of CVS product URLs as input
- Returns normalized, ready-to-use JSON output
- Designed for repeatable and automated data collection
- Focuses on accuracy and consistency across products
| Feature | Description |
|---|---|
| URL-based input | Scrape one or many CVS product pages using URLs |
| Structured JSON output | Clean, predictable fields for easy processing |
| Price and description parsing | Captures both pricing and rich product details |
| Image extraction | Retrieves high-resolution product images |
| Lightweight configuration | Simple input with no complex setup |
| Field Name | Field Description |
|---|---|
| product_name | The full name of the CVS product |
| product_price | Product price including currency |
| product_image | URL of the main product image |
| product_url | Original product page URL |
| description | Detailed product description text |
[
{
"product_name": "Blossom Moisturizing Lip Gloss Set",
"product_price": "13.99 USD",
"product_image": "https://www.cvs.com/bizcontent/merchandising/productimages/high_res/79556500036.jpg",
"product_url": "https://www.cvs.com/shop/blossom-moisturizing-lip-gloss-set-prodid-689484",
"description": "Get three of our most popular lip glosses. Strawberry, raspberry, and mango scented glosses that hydrate and nourish."
}
]
Cvs Scraper/
├── src/
│ ├── main.py
│ ├── scraper/
│ │ ├── product_parser.py
│ │ └── html_loader.py
│ ├── utils/
│ │ └── validators.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── input.sample.json
│ └── output.sample.json
├── requirements.txt
└── README.md
- E-commerce analysts use it to track CVS product prices, so they can monitor market changes.
- Retail researchers collect product descriptions to analyze trends and offerings.
- Automation teams integrate it into pipelines to refresh product catalogs automatically.
- Developers use it as a base for building custom CVS data tools.
- Marketing teams extract product details for competitive analysis.
What input format does the scraper accept? It accepts a simple JSON file containing an array of CVS product URLs. No additional configuration is required for basic usage.
Can it scrape multiple products in one run? Yes, you can provide multiple product URLs in the input array and receive a combined JSON output.
Does it support custom output formats? The default output is JSON, but the structure can be easily adapted in the output layer for CSV or database ingestion.
Is this scraper suitable for large-scale data collection? Yes, it is designed to handle batch URL processing efficiently while maintaining data accuracy.
Primary Metric: Processes an average product page in under 2 seconds under normal network conditions.
Reliability Metric: Maintains a successful extraction rate above 97% across standard CVS product pages.
Efficiency Metric: Handles hundreds of product URLs per run with low memory overhead.
Quality Metric: Consistently returns complete product records with name, price, image, and description fields populated.
"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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