Rocketbook Scraper is a focused data extraction tool designed to collect structured product information and pricing from the Rocketbook online store. It helps businesses, analysts, and developers turn raw product listings into usable e-commerce data for tracking, research, and decision-making.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Rocketbook Scraper extracts detailed product data from getrocketbook.com and converts it into clean, structured datasets. It solves the problem of manually monitoring product catalogs and pricing changes by automating data collection. This project is ideal for e-commerce teams, data analysts, and developers who need reliable Rocketbook product data.
- Collects up-to-date product listings from a live online catalog
- Structures raw product pages into consistent, machine-readable data
- Supports pricing analysis, catalog audits, and competitive research
- Designed for repeatable runs to track changes over time
| Feature | Description |
|---|---|
| Product Listing Extraction | Collects all available Rocketbook products from the store. |
| Price Monitoring | Captures current prices for comparison and trend analysis. |
| Product Metadata Parsing | Extracts titles, descriptions, SKUs, and availability. |
| Image URL Collection | Gathers product images for catalogs or dashboards. |
| Structured Output | Exports clean, structured data ready for analytics tools. |
| Field Name | Field Description |
|---|---|
| product_id | Unique identifier assigned to the product. |
| product_name | Official name of the Rocketbook product. |
| sku | Stock keeping unit used by the store. |
| price | Current listed price of the product. |
| currency | Currency in which the price is listed. |
| availability | Stock status such as in stock or out of stock. |
| product_url | Direct link to the product page. |
| image_urls | List of image links associated with the product. |
| description | Short or full product description text. |
[
{
"product_id": "rb-core-a5",
"product_name": "Rocketbook Core Reusable Notebook A5",
"sku": "RB-A5-CORE",
"price": 34.00,
"currency": "USD",
"availability": "in_stock",
"product_url": "https://getrocketbook.com/products/rocketbook-core",
"image_urls": [
"https://cdn.getrocketbook.com/images/core-front.jpg",
"https://cdn.getrocketbook.com/images/core-back.jpg"
],
"description": "Reusable smart notebook that connects handwritten notes to the cloud."
}
]
Rocketbook Scraper/
├── src/
│ ├── main.js
│ ├── crawler/
│ │ ├── productCrawler.js
│ │ └── paginationHandler.js
│ ├── parsers/
│ │ ├── productParser.js
│ │ └── priceParser.js
│ ├── utils/
│ │ └── normalizeText.js
│ └── config/
│ └── settings.example.json
├── data/
│ ├── sample-output.json
│ └── inputs.sample.json
├── package.json
├── package-lock.json
└── README.md
- E-commerce analysts use it to track Rocketbook pricing so they can identify pricing trends and changes.
- Retail researchers use it to collect product catalogs to support market research and reports.
- Developers use it to integrate Rocketbook product data into internal tools or dashboards.
- Product managers use it to monitor availability and catalog updates for planning decisions.
Does this scraper support repeated runs for price tracking? Yes, it is designed to be run multiple times so pricing and availability changes can be compared over time.
What type of products can be extracted? It focuses on Rocketbook notebooks and related accessories available on the official store.
Is the output suitable for spreadsheets or databases? The structured output is well-suited for spreadsheets, BI tools, and database ingestion.
Can the scraper handle large product catalogs? Yes, it processes paginated listings and scales reliably with catalog size.
Primary Metric: Average extraction speed of 40–60 product pages per minute under normal conditions.
Reliability Metric: Over 99% successful page processing across repeated runs on stable connections.
Efficiency Metric: Optimized requests minimize redundant page loads, reducing bandwidth usage.
Quality Metric: Consistently high data completeness with accurate pricing and metadata coverage.
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