Olive Piper Scraper

Olive Piper Scraper is a focused data extraction tool designed to collect structured product information from the Olive + Piper online store. It helps businesses, analysts, and developers turn raw product listings into actionable datasets for pricing, catalog, and market analysis.

     

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

This project extracts detailed product and pricing data from an online accessories store in a clean, structured format. It solves the challenge of manually tracking product catalogs, pricing changes, and availability. It is built for e-commerce teams, data analysts, and developers who need reliable product data.

E-commerce Product Intelligence

• Collects complete product listings with structured fields
• Standardizes data for analytics, reporting, and integrations
• Supports scalable extraction for large catalogs
• Designed for repeatable and consistent data collection

Features

Feature	Description
Product Catalog Extraction	Retrieves structured product listings from category and product pages.
Pricing Data Collection	Captures current prices to support monitoring and comparison.
Image & Media Capture	Extracts product images for catalog or merchandising use.
Structured Output	Outputs clean, machine-readable data ready for analysis or storage.
Scalable Design	Handles small to large product catalogs efficiently.

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What Data This Scraper Extracts

Field Name	Field Description
product_name	Name of the product as listed in the store.
product_url	Direct link to the product detail page.
price	Current product price.
currency	Currency used for the listed price.
description	Product description text.
images	List of product image URLs.
availability	Stock or availability status.
category	Product category or collection.
sku	Product or variant identifier if available.

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Example Output

[
    {
        "product_name": "Gold Chain Bracelet",
        "product_url": "https://www.oliveandpiper.com/products/gold-chain-bracelet",
        "price": 38.00,
        "currency": "USD",
        "description": "Minimal gold-tone bracelet designed for everyday wear.",
        "images": [
            "https://cdn.example.com/images/bracelet1.jpg",
            "https://cdn.example.com/images/bracelet2.jpg"
        ],
        "availability": "In stock",
        "category": "Bracelets",
        "sku": "OP-BRC-1021"
    }
]

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Directory Structure Tree

olive-piper-scraper/
├── src/
│   ├── runner.py
│   ├── extractors/
│   │   ├── product_parser.py
│   │   └── category_parser.py
│   ├── outputs/
│   │   └── exporters.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── inputs.sample.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• E-commerce managers use it to track product pricing, so they can optimize competitive positioning.
• Data analysts use it to build pricing and catalog datasets, enabling trend analysis.
• Developers use it to integrate product data into dashboards or internal tools.
• Market researchers use it to monitor accessory trends and product launches.

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FAQs

Is this tool suitable for large product catalogs? Yes, it is designed to scale efficiently and handle both small and large catalogs with consistent output.

What output format does it provide? The scraper produces structured, machine-readable data suitable for databases, spreadsheets, or analytics pipelines.

Can it be adapted for other similar stores? The modular structure allows it to be extended or adapted to similar e-commerce platforms with minimal changes.

Does it support repeated runs for monitoring? Yes, it can be run repeatedly to track changes in pricing, availability, and catalog updates.

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Performance Benchmarks and Results

Primary Metric: Processes an average product page in under one second under standard conditions.

Reliability Metric: Achieves a high success rate with consistent extraction across full catalog runs.

Efficiency Metric: Optimized for low overhead, enabling high throughput without excessive resource usage.

Quality Metric: Delivers complete and well-structured records with minimal missing fields.

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