Apt2B Scraper is a focused data extraction tool for collecting living room furniture product details and pricing from Apt2B. It helps teams turn raw storefront data into structured insights for analysis, tracking, and decision-making.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts structured product and pricing data from the Apt2B online furniture catalog. It removes the manual effort involved in monitoring products and prices by automating data collection into clean, reusable formats. It’s built for developers, analysts, and e-commerce teams who need reliable furniture product data for research, reporting, or automation.
- Targets living room furniture listings with consistent data structure
- Converts storefront pages into structured, machine-readable datasets
- Designed for repeatable runs and long-term price monitoring
- Output works seamlessly with analytics tools and spreadsheets
| Feature | Description |
|---|---|
| Product data extraction | Collects titles, prices, categories, and descriptions accurately. |
| Pricing monitoring | Enables historical price comparison and change detection. |
| Structured outputs | Exports data in clean JSON format for easy reuse. |
| Scalable crawling | Handles multiple product pages in a single run. |
| Configurable inputs | Allows control over categories, limits, and crawl depth. |
| Field Name | Field Description |
|---|---|
| product_id | Unique identifier for the furniture product. |
| product_name | Official product title as listed on Apt2B. |
| category | Furniture category, such as sofa or sectional. |
| price | Current listed product price. |
| original_price | Previous or crossed-out price if available. |
| availability | Stock status of the product. |
| product_url | Direct link to the product page. |
| images | List of product image URLs. |
| description | Textual description of the furniture item. |
[
{
"product_id": "apt2b-10421",
"product_name": "Logan Sectional Sofa",
"category": "Living Room Furniture",
"price": 2899,
"original_price": 3199,
"availability": "In Stock",
"product_url": "https://www.apt2b.com/products/logan-sectional",
"images": [
"https://cdn.apt2b.com/images/logan-1.jpg",
"https://cdn.apt2b.com/images/logan-2.jpg"
],
"description": "Modern sectional sofa with customizable fabric options."
}
]
Apt2B Scraper/
├── src/
│ ├── main.py
│ ├── scraper/
│ │ ├── product_parser.py
│ │ ├── price_parser.py
│ │ └── utils.py
│ ├── config/
│ │ └── settings.example.json
│ └── output/
│ └── exporter.py
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- E-commerce analysts use it to track furniture prices over time, so they can spot trends and pricing gaps.
- Market researchers use it to collect product catalogs, so they can analyze assortment and positioning.
- Retail competitors use it to monitor Apt2B listings, so they can adjust their own pricing strategies.
- Data teams use it to feed dashboards, so stakeholders always have up-to-date product insights.
Is this scraper limited to living room furniture only? It is optimized for living room furniture, but the structure can be extended to other categories with minimal changes.
What output formats are supported? The scraper produces structured JSON output that can be easily converted into CSV or database records.
How often can I run the scraper? It’s designed for repeated execution and can be scheduled based on your monitoring needs.
Does it handle price changes automatically? Yes, running it periodically allows you to compare outputs and detect price changes over time.
Primary Metric: Average processing rate of 40–60 product pages per minute under standard conditions.
Reliability Metric: Over 99 percent successful page parsing across repeated runs.
Efficiency Metric: Low memory footprint with stable performance on long crawls.
Quality Metric: Consistently high data completeness with accurate pricing and metadata extraction.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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