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Extract E-commerce Products

This example shows how to extract large amounts of product data from an e-commerce site and save it to files.

Use Case

Extract 1000s of products from multiple categories with:

• Product URLs
• Names and descriptions
• Original and sale prices
• Discount percentages

Save everything to a CSV file for further analysis.

Code

import asyncio
from browser_use.code_use import CodeAgent

async def main():
    task = """
    Go to https://www.flipkart.com.
    Collect approximately 50 products from:

    1. Books & Media - 15 products
    2. Sports & Fitness - 15 products
    3. Beauty & Personal Care - 10 products

    Save to products.csv
    """

    agent = CodeAgent(task=task)
    await agent.run()

asyncio.run(main())

How It Works

1. Agent navigates to the e-commerce site
2. Writes JavaScript to extract product data from each page
3. Loops through categories collecting products
4. Stores in variables that persist across steps
5. Saves to CSV using pandas or csv module
6. Returns deterministic code you can modify and rerun

Key Benefits

• Function reuse: Extraction code is written once, used many times
• Scale: Easily collect 100s or 1000s of items
• Deterministic: The generated Python code can be saved and rerun
• Data processing: Built-in pandas support for cleaning and transforming data

View full example on GitHub

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