xonsh

🥇Gold

Xonsh is a Python-powered shell that enables operations teams to automate tasks across platforms. It connects to tools like Alacritty, VSCode, and Raspberry Pi, streamlining workflows for data engineering, DevOps, and security automation.

9,2246950Updated Today

Intermediate30min to implementautomation

Saves ~60 min per use

Quick InstallView Source

git clone https://github.com/xonsh/xonsh.git

Works with:

Claude

Overview

About This Skill

The xonsh skill is a powerful automation tool that combines the flexibility of a Python-powered shell with the functionality of traditional shell commands. This full-featured, cross-platform environment allows users to seamlessly integrate Python scripts into their command-line workflows. With its intermediate complexity, xonsh is designed for developers and AI practitioners who are looking to enhance their automation capabilities without sacrificing the power of Python's extensive libraries. One of the key benefits of using xonsh is its ability to save time by automating repetitive tasks. Users can streamline data processing by combining shell commands with Python scripts, allowing for efficient manipulation and analysis of data. Additionally, xonsh facilitates the creation of custom command-line tools that leverage both shell and Python functionalities, enabling users to manage system configurations and deployments effectively. By enhancing existing shell workflows with Python libraries, users can achieve greater productivity and focus on higher-level tasks. This skill is particularly beneficial for developers, product managers, and AI practitioners who are involved in data engineering, system administration, or workflow automation. By integrating xonsh into their daily operations, these professionals can significantly reduce the time spent on manual processes and improve their overall efficiency. The practical use cases for xonsh include automating data processing tasks, integrating with cloud services and APIs, and managing deployments with Python-based scripts, making it a versatile tool in any tech stack. Implementing xonsh requires an intermediate understanding of both shell environments and Python programming. With a time commitment of approximately 30 minutes, users can quickly set up and start leveraging this skill to enhance their AI-first workflows. As organizations increasingly adopt AI automation, xonsh stands out as a valuable asset for those looking to optimize their processes and drive innovation.

Use Cases

Automate data processing tasks by combining shell commands with Python scripts.

Integrate with cloud services and APIs seamlessly using Python's rich ecosystem.

Create custom command-line tools that utilize both shell and Python functionalities.

Manage system configurations and deployments using Python-based scripts in a shell environment.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/xonsh/xonsh

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Create a script using Xonsh to automate the process of backing up files from [SOURCE_DIRECTORY] to [DESTINATION_DIRECTORY]. Ensure that the script includes error handling and logs the backup process to a file named [LOG_FILE].

Example Output

```python
# Xonsh script to backup files
import os
import shutil
from datetime import datetime

SOURCE_DIRECTORY = '/path/to/source'
DESTINATION_DIRECTORY = '/path/to/destination'
LOG_FILE = '/path/to/log_file.log'

def backup_files(src, dest):
    try:
        shutil.copytree(src, dest)
        with open(LOG_FILE, 'a') as log:
            log.write(f'Backup successful from {src} to {dest} at {datetime.now()}\n')
    except Exception as e:
        with open(LOG_FILE, 'a') as log:
            log.write(f'Error during backup: {e} at {datetime.now()}\n')

backup_files(SOURCE_DIRECTORY, DESTINATION_DIRECTORY)
``` This script successfully copies all files from the specified source directory to the destination directory, logging the outcome of the operation in the designated log file. If an error occurs, it captures the exception and logs it as well, ensuring that users are informed of any issues during the backup process.