---
title: "Claude Code Automation Python"
description: "Streamlines Python automation for web scraping, task scheduling, and system integration with robust error handling."
category: "configuration"
tags: ["claude-code", "automation", "python", "scripting", "web-scraping", "scheduling", "error-handling", "api-integration"]
tech_stack: ["python", "selenium", "beautiful-soup", "requests", "schedule", "celery", "cron"]
---

This configuration makes it easier to automate tasks using Python, whether you're scraping the web, scheduling tasks, or integrating systems, all while keeping error handling in check.

### Configuration Overview
This setup leverages Python for smooth automation. You'll focus on web scraping using `Selenium` and `BeautifulSoup`, task scheduling through `cron` and `Celery`, and managing system scripts with solid error handling.

### Prerequisites
Before you start, make sure you have the following:
- **Python**: Version 3.7 or higher
- **Pip**: The Python package manager
- **Selenium**: A tool for web automation
- **BeautifulSoup**: A library for parsing HTML
- **Requests**: For making API calls
- **Schedule**: A simple job scheduler for Python
- **Celery**: A distributed task queue
- **Cron**: A Unix-based job scheduler

### Installation & Setup
Let’s get everything set up:

1. **Install Python**: First, check if Python is installed by running:
   ```bash
   python --version
   ```
2. **Install Required Packages**: Next, grab the necessary packages:
   ```bash
   pip install selenium beautifulsoup4 requests schedule celery
   ```
3. **Set Up Web Driver**: Download the WebDriver for your browser (like ChromeDriver for Chrome) and add it to your system PATH.
4. **Configure Celery**:
   - Create a new file called `celery_config.py` with the following code:
     ```python
     from celery import Celery
     app = Celery('tasks', broker='redis://localhost:6379/0')
     ```
5. **Create a Task**:
   - In a file named `tasks.py`, set up your tasks:
     ```python
     from celery_config import app
     import requests

     @app.task
     def fetch_data(url):
         response = requests.get(url)
         return response.json()
     ```
6. **Set Up Cron Jobs**: Edit your crontab by running:
   ```bash
   crontab -e
   ```
   Then, add a line to schedule your Python script:
   ```bash
   * * * * * /usr/bin/python /path/to/your_script.py
   ```

### File Structure
Here’s how your project should look:
```
/project-root
│
├── celery_config.py
├── tasks.py
├── web_scraper.py
├── requirements.txt
└── cron_jobs.txt
```

### Key Configuration Files
- **`requirements.txt`**: This file lists your dependencies:
  ```plaintext
  selenium
  beautifulsoup4
  requests
  schedule
  celery
  ```
- **`web_scraper.py`**: An example of a web scraping script:
  ```python
  from selenium import webdriver
  from bs4 import BeautifulSoup

  def scrape_website(url):
      driver = webdriver.Chrome()
      driver.get(url)
      soup = BeautifulSoup(driver.page_source, 'html.parser')
      driver.quit()
      return soup
  ```

### Advanced Options
Consider these additional features:
- **Error Handling**: Use try-except blocks in your scripts to catch errors.
- **Logging**: Implement the `logging` module to track errors and significant events.
- **Environment Variables**: Store sensitive data like API keys in environment variables.

### Troubleshooting
If you run into issues, here are some tips:
- **WebDriver Not Found**: Make sure the WebDriver is in your PATH.
- **Celery Not Starting**: Check if Redis is running and accessible.
- **Cron Job Not Executing**: Verify that the script has the right permissions and that the path is correct.

### Best Practices
To keep your project organized, try these tips:
- **Use Virtual Environments**: Keep your project dependencies separate with `venv` or `virtualenv`.
- **Version Control**: Use Git to manage your scripts and configurations.
- **Documentation**: Add comments to your code and maintain a README file for clarity.

### Performance Optimizations
Here are some ways to boost performance:
- **Batch Processing**: For API calls, consider batching requests to cut down overhead.
- **Caching**: Use caching to store frequently accessed data and speed up load times.
- **Asynchronous Tasks**: Implement asynchronous programming with `asyncio` for I/O-bound tasks to enhance performance.