Enhanced Dev Env

🚀 Enhanced Development Environment and MCP Server

A comprehensive development environment that includes the UV package manager, Open Interpreter (development branch), and a model context protocol server.

✨ Features

• UV package manager for rapid Python package management.
• Modern CLI tools (exa, bat, ripgrep, etc.).
• Zsh shell with Oh My Zsh and useful plugins.
• Development tools (git, vim, tmux, etc.).
• Rust-based performance tools.
• Docker and Vagrant configurations.
• Optimized Python development environment.

🛠️ Included Tools

Python Tools

• UV package manager
• IPython
• Black (code formatter)
• isort (import sorter)
• mypy (type checker)
• ruff (code linter)
• pytest (testing framework)
• debugpy (debugger)
• pre-commit (pre-commit hook)

Modern CLI Tools

• exa (modern ls replacement)
• bat (modern cat replacement)
• ripgrep (modern grep replacement)
• fd-find (modern find replacement)
• delta (git diff enhancer)
• zoxide (intelligent cd tool)
• starship (shell prompt tool)
• dust (modern du replacement)
• hyperfine (benchmarking tool)

Development Tools

• Git
• Vim
• Tmux
• HTTPx
• Docker
• Docker Compose

🚀 Quick Start

Using Docker

# Build and start the container
docker-compose up -d

# Enter the container
docker-compose exec dev zsh

# Or use the run command
docker-compose run --rm dev

Using Vagrant

# Start the virtual machine
vagrant up

# Enter the virtual machine via SSH
vagrant ssh

# Destroy the virtual machine
vagrant destroy

📁 Directory Structure

.
├── Dockerfile           # Container definition file
├── docker-compose.yml   # Container orchestration file
├── Vagrantfile         # Virtual machine definition file
├── .zshrc              # Shell configuration file
├── workspace/          # Your project directory
└── .config/
    └── uv/            # UV configuration directory

💻 Usage Examples

Package Management

# Install packages
python-install pandas numpy

# Create a virtual environment
venv-create

# Activate the virtual environment
venv-activate

# Install project dependencies
python-deps

Development Workflow

# Initialize a new project
uv-init myproject

# Create a project from a template
uv-scaffold fastapi myapi

# Set up testing
uv-test-setup

# Check the project structure
uv-project-check

Maintenance

# Clean the UV cache
uv-clean

# Rebuild the virtual environment
uv-venv-rebuild

# Check the system
uv-doctor

🔧 Custom Configuration

Adding Local Configuration

Create ~/.zshrc.local for machine-specific settings:

# Local environment variables
export MY_VAR="value"

# Local aliases
alias myalias="mycommand"

Modifying UV Configuration

Edit ~/.config/uv/uvconfig.toml:

[cache]
max_capacity = "10GB"
shared = true

[network]
concurrent_downloads = 8

🛠️ Troubleshooting

Common Issues

1. Package Installation Issues

   uv-clean
   uv-doctor
   

2. Virtual Environment Issues

   uv-venv-rebuild
   

3. Performance Issues

   bench "your-command"  # Use hyperfine for benchmarking
   

📦 Maintenance

Container Updates

# Rebuild the container without cache to get updates
docker-compose build --no-cache

# Pull the latest base image
docker-compose pull

Virtual Machine Updates

# Update the virtual machine
vagrant provision

# Update the virtual machine image
vagrant box update

🔒 Security Precautions

• The container runs as a non-root user.
• SSH keys are mounted read-only.
• Git configuration is mounted read-only.
• Use the smallest base image.
• Perform regular security updates.