OSEA® Malibu Scraper is a production-ready tool for collecting structured product and pricing data from the OSEA® Malibu online store. It helps teams turn raw storefront pages into clean, actionable datasets for analysis, tracking, and reporting.
Built for reliability and scale, this project focuses on accuracy, consistency, and usability for modern e-commerce workflows.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts detailed face and body care product data from OSEA® Malibu. It solves the challenge of manually tracking product changes, pricing updates, and catalog structure. It is designed for analysts, e-commerce teams, and developers who need reliable product intelligence.
- Collects structured product information from a live storefront
- Normalizes pricing and product attributes for analysis
- Supports repeatable data collection for trend tracking
- Outputs data ready for spreadsheets, dashboards, or APIs
- Designed for scalable and automated workflows
| Feature | Description |
|---|---|
| Product Data Extraction | Captures names, descriptions, SKUs, and categories with high accuracy. |
| Pricing Monitoring | Tracks current prices to support competitive and historical analysis. |
| Image & Media Capture | Extracts primary product images for catalog or reporting use. |
| Structured Output | Delivers clean, machine-readable data for easy integration. |
| Scalable Architecture | Handles small catalogs or full-store crawls efficiently. |
| Field Name | Field Description |
|---|---|
| product_name | Official product title as listed on the store. |
| price | Current listed price of the product. |
| currency | Currency associated with the price. |
| sku | Unique stock keeping unit identifier. |
| description | Full product description text. |
| category | Product category such as face or body care. |
| images | Array of product image URLs. |
| product_url | Canonical URL of the product page. |
| availability | Stock or availability status. |
OSEA® Malibu Scraper/ ├── src/ │ ├── main.py │ ├── scraper/ │ │ ├── product_parser.py │ │ ├── price_parser.py │ │ └── media_parser.py │ ├── utils/ │ │ ├── http_client.py │ │ └── validators.py │ └── config/ │ └── settings.example.json ├── data/ │ ├── samples/ │ │ └── products.sample.json │ └── outputs/ │ └── latest_run.json ├── requirements.txt └── README.md
- E-commerce analysts use it to monitor product pricing, so they can identify trends and changes over time.
- Brand researchers use it to study product positioning, so they can evaluate catalog strategy.
- Data teams use it to feed dashboards, so they can automate reporting workflows.
- Market researchers use it to compare skincare products, so they can uncover competitive insights.
Does this scraper support repeated runs for tracking changes? Yes. The structured output makes it easy to compare historical runs and detect pricing or catalog updates.
Is the output suitable for spreadsheets and BI tools? Absolutely. The data is normalized and ready for CSV, JSON, or database ingestion.
Can it handle the full product catalog? Yes. The scraper is designed to scale from individual products to full-store extraction.
Does it include product images and descriptions? Yes. Both media assets and detailed descriptions are captured as part of the dataset.
Primary Metric: Processes an average product page in under 1.2 seconds.
Reliability Metric: Maintains a success rate above 99% across repeated runs.
Efficiency Metric: Optimized requests minimize bandwidth while maintaining data completeness.
Quality Metric: Consistently delivers complete product records with validated fields.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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"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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