signalpilot 0.2.0

SignalPilot CLI - Your Trusted CoPilot for Data Analysis

SignalPilot CLI (sp-cli)

Your Trusted CoPilot for Data Analysis - A simple CLI tool to bootstrap Jupyter-powered data science workspaces with AI agent support.

Features

• 🚀 One-command setup - Get from zero to Jupyter Lab in under 3 minutes
• 🐍 Python 3.12 - Uses the latest Python with uv for fast package management
• 📊 Pre-configured workspace - Includes pandas, numpy, matplotlib, seaborn, plotly
• 🤖 AI-ready - Built-in SignalPilot AI agent support
• ⚡ Fast - Optimized Jupyter cache for quick startups
• 🎨 Beautiful CLI - Clean, colorful terminal output

Installation

# Install uv (if you don't have it)
brew install uv  # macOS
# OR
curl -LsSf https://astral.sh/uv/install.sh | sh  # Linux/macOS

# Run SignalPilot init
uvx sp-cli

That's it! The tool will:

1. Create ~/SignalPilotHome directory structure
2. Download starter notebook and dependencies
3. Set up Python 3.12 virtual environment
4. Install Jupyter Lab and data science packages
5. Optimize for fast startup

Usage

After running uvx sp-cli, follow the next steps:

cd ~/SignalPilotHome && source .venv/bin/activate
jupyter lab

What Gets Installed

Python Packages:

• signalpilot-ai - AI agent integration
• jupyterlab - Modern Jupyter interface
• pandas, numpy - Data manipulation
• matplotlib, seaborn, plotly - Visualization
• python-dotenv, tomli - Configuration utilities

Directory Structure:

~/SignalPilotHome/
├── user-skills/       # Custom agent skills
├── user-rules/        # Custom agent rules
├── team-workspace/    # Shared team notebooks
├── demo-project/      # Example notebooks
├── start-here.ipynb   # Quick start guide
└── .venv/             # Python environment

Requirements

• Python 3.10 or higher
• uv package manager

License

MIT License - See LICENSE file for details

Links

• Homepage
• Documentation
• GitHub