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Relocate deprecated doc sections from customize/ to legacy/ under Customize OS nav. Add redirects for all old paths and update cross-references in AGENTS.md and related mdx files. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
130 lines
3.6 KiB
Plaintext
130 lines
3.6 KiB
Plaintext
---
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title: "Basics"
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description: "Write Python code locally with browser automation"
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icon: "code"
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---
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CodeAgent writes and executes Python code locally with browser automation capabilities. It's designed for repetitive data extraction tasks where the agent can write reusable functions.
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<Warning>
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CodeAgent executes Python code on your local machine like Claude Code.
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</Warning>
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## Quick Start
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```python
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import asyncio
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from browser_use import CodeAgent
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from dotenv import load_dotenv
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load_dotenv()
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async def main():
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task = "Extract all products from example.com and save to products.csv"
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agent = CodeAgent(task=task)
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await agent.run()
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asyncio.run(main())
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```
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```bash .env
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BROWSER_USE_API_KEY=your-api-key
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```
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<Note>
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CodeAgent currently only works with [ChatBrowserUse](/supported-models) which is optimized for this use case.
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Don't have one? We give you $10 to try it out [here](https://cloud.browser-use.com/new-api-key).
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</Note>
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## When to Use
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**Best for:**
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- Data extraction at scale (100s-1000s of items)
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- Repetitive interactions where functions can be reused
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- Tasks requiring data processing and file operations
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- Deterministic workflows you want to rerun
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**Performance:**
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- Best performance for data collection tasks
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- Slightly slower for one-off interactions vs standard Agent
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**Output:**
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- Generates Python code that can be rerun deterministically
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- Perfect for refining extraction logic
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The agent will write code blocks in different languages. This combines the power of js for browser interaction and python for data processing:
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```js extract_products
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(function(){
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return Array.from(document.querySelectorAll('.product')).map(p => ({
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name: p.querySelector('.name').textContent,
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price: p.querySelector('.price').textContent
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}))
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})()
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```
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```python
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import pandas as pd
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products = await evaluate(extract_products) # reuse other code blocks
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df = pd.DataFrame(products)
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df.to_csv('products.csv', index=False)
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```
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## Available Libraries
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The agent can use common Python libraries:
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- **Data processing:** `pandas`, `numpy`
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- **Web:** `requests`, `BeautifulSoup`
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- **File formats:** `csv`, `json`, `openpyxl` (Excel)
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- **Visualization:** `matplotlib`
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- **Utilities:** `tabulate`, `datetime`, `re`
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- and all which you install ...
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## Available Tools
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The agent has access to browser control functions:
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- `navigate(url)` - Navigate to a URL
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- `click(index)` - Click an element by index
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- `input(index, text)` - Type text into an input
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- `scroll(down, pages)` - Scroll the page
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- `upload_file(path)` - Upload a file
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- `evaluate(code, variables={})` - Execute JavaScript and return results
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- `done(text, success, files_to_display=[])` - Mark task complete
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## Exporting Sessions
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CodeAgent automatically saves all executed code and JavaScript blocks during your session. You can export your complete automation workflow for sharing, version control, or re-running later.
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### Quick Export
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```python
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from browser_use.code_use.notebook_export import export_to_ipynb, session_to_python_script
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# After running your agent
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await agent.run()
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# Export to Jupyter notebook
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notebook_path = export_to_ipynb(agent, "my_automation.ipynb")
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# Export to Python script
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script = session_to_python_script(agent)
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with open("my_automation.py", "w") as f:
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f.write(script)
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```
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### Export Formats
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- **Jupyter Notebook (.ipynb)**: Interactive development, sharing, documentation
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- **Python Script (.py)**: Production deployment, version control, automation
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Both formats include:
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- Setup code with browser initialization
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- JavaScript code blocks as Python variables
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- All executed Python cells with outputs
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- Ready-to-run automation workflows
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