PRINTFRESH Scraper is a focused data extraction tool designed to collect structured product and pricing information from printfresh.com. It helps teams and analysts turn raw product pages into clean, usable datasets for research, monitoring, and reporting. Built with scalability in mind, it supports consistent data collection across the entire catalog.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts product-level data from the PRINTFRESH online store and converts it into structured formats ready for analysis. It solves the challenge of manually tracking product details and price changes across a growing e-commerce catalog. It’s ideal for developers, analysts, and e-commerce teams who need reliable product data without manual effort.
- Collects consistent product and pricing data from a Shopify-based storefront
- Eliminates repetitive manual data collection and copy-paste work
- Produces structured outputs suitable for tools, reports, and dashboards
- Scales easily as product listings change or grow
| Feature | Description |
|---|---|
| Product catalog crawling | Automatically scans category and product pages to discover items. |
| Pricing extraction | Captures current prices to support monitoring and comparison. |
| Structured output | Exports clean, machine-readable data for downstream use. |
| Shopify-aware parsing | Designed to work reliably with Shopify-based layouts. |
| Re-runnable jobs | Can be executed repeatedly to track updates over time. |
| Field Name | Field Description |
|---|---|
| product_name | The full name of the product as listed on the store. |
| product_url | Direct link to the product detail page. |
| price | Current listed price of the product. |
| currency | Currency used for pricing. |
| category | Product category or collection name. |
| availability | Stock or availability status if visible. |
| images | One or more image URLs associated with the product. |
[
{
"product_name": "Floral Pajama Set",
"product_url": "https://www.printfresh.com/products/floral-pajama-set",
"price": 128.00,
"currency": "USD",
"category": "Sleepwear",
"availability": "In stock",
"images": [
"https://cdn.printfresh.com/images/floral-pajama-front.jpg"
]
}
]
PRINTFRESH Scraper/
├── src/
│ ├── main.py
│ ├── crawler/
│ │ ├── category_crawler.py
│ │ └── product_crawler.py
│ ├── parsers/
│ │ └── product_parser.py
│ ├── exporters/
│ │ └── json_exporter.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── samples/
│ │ └── sample_output.json
├── requirements.txt
└── README.md
- E-commerce analysts use it to track product pricing, so they can identify trends and changes over time.
- Market researchers use it to collect catalog data, so they can compare offerings across brands.
- Product teams use it to monitor inventory visibility, helping them spot gaps or opportunities.
- Data engineers use it to feed dashboards and reports with up-to-date product information.
Is this scraper limited to specific product categories? No. It can crawl across all categories available on the site as long as they are publicly accessible.
What output formats are supported? The default output is structured JSON, which can be easily converted into CSV or other formats if needed.
Can it be run multiple times for price tracking? Yes. It’s designed to be re-run periodically, making it suitable for ongoing price and catalog monitoring.
Does it require advanced configuration to start? Basic usage works with default settings, while configuration files allow fine-tuning for advanced needs.
Primary Metric: Processes an average product page in under one second under normal conditions.
Reliability Metric: Maintains a high success rate when crawling standard product and category pages.
Efficiency Metric: Minimizes redundant requests by reusing discovered URLs during a run.
Quality Metric: Extracted datasets consistently include complete product names, prices, and URLs suitable for analysis.
