CLI Usage Guide

🤖 Two CLI Versions: Smart Design

miniROS provides two complementary CLI tools, following the “mini” philosophy: core functionality, minimum complexity.

🦀 Rust CLI: mini_ros

Primary Choice - High-Performance System Operations

# Core functionality - fast and reliable
mini_ros launch turtlebot simulation
mini_ros run turtlebot controller  
mini_ros pkg list

Use Cases:

• Production deployments
• High-performance requirements
• Complex system orchestration
• Package management and launch files

🐍 Python CLI: mini_ros_py

Python Ecosystem Specialized Tool

# Python-specific operations
mini_ros_py run minimal_publisher
mini_ros_py examples list
mini_ros_py test --coverage

Use Cases:

• Python development and testing
• Example code management
• Rapid prototyping
• Teaching and learning

🚀 Quick Start

1. Build Both CLIs

# Build Rust CLI (recommended first)
bash scripts/setup.sh

# Or manual build
cargo build --bin mini_ros
cd python && pip install -e .

2. Verify Installation

# Test Rust CLI
mini_ros --help

# Test Python CLI
mini_ros_py --help

3. Smart Wrapper (Optional)

# Use universal wrapper that auto-selects best CLI
bash scripts/mini_ros_wrapper.sh pkg list

📋 Command Comparison

🔧 Advanced Usage

Rust CLI Features

Package Management

# List all packages with details
mini_ros pkg list

# Create new package with Python support
mini_ros pkg create my_robot --path ./packages --python

# Show detailed package information
mini_ros pkg info turtlebot

Launch System

# Launch complete systems
mini_ros launch turtlebot full_system

# Launch with custom arguments
mini_ros launch my_pkg simulation --args debug verbose

Shell Completions

# Generate completions for your shell
mini_ros completions bash > ~/.bash_completion
mini_ros completions zsh > ~/.zsh_completions/_mini_ros

Python CLI Features

Example Management

# List available Python examples
mini_ros_py examples list

# Run specific example with arguments
mini_ros_py run turtlebot_controller --args --speed 0.5

# Install examples to custom directory
mini_ros_py examples install ~/my_examples

Testing and Development

# Run full test suite with coverage
mini_ros_py test --coverage --verbose

# Run specific test pattern
mini_ros_py test test_basic

# Install package in development mode
mini_ros_py install --dev

⚡ Performance Tips

When to Use Rust CLI

• Production deployments
• Multi-node systems
• High-frequency operations
• System integration

When to Use Python CLI

• Python development workflow
• Testing and validation
• Learning and tutorials
• Quick prototyping

🐛 Troubleshooting

Common Issues

CLI Not Found

# Rust CLI
bash scripts/setup.sh build
export PATH="$PWD/target/debug:$PATH"

# Python CLI
cd python && pip install -e .

Permission Errors

# Make scripts executable
chmod +x target/debug/mini_ros
chmod +x scripts/*.sh

Python Module Not Found

# Ensure Python package is installed
cd python && pip install -e .

# Check if mini_ros module is available
python -c "import mini_ros; print('✅ Available')"

Environment Variables

# Control logging level
export MINI_ROS_LOG=debug

# Override default package paths
export MINI_ROS_PACKAGE_PATH=/path/to/packages

🎯 Best Practices

1. Use the Right Tool

• Rust CLI for system operations
• Python CLI for Python development

2. Setup Shell Completions

# Add to your shell config
mini_ros completions $(basename $SHELL) > ~/.completion_mini_ros
source ~/.completion_mini_ros

3. Alias for Convenience

# Add to ~/.bashrc or ~/.zshrc
alias mrs="mini_ros"
alias mrspy="mini_ros_py"
alias mrsw="bash scripts/mini_ros_wrapper.sh"

4. Development Workflow

# Start with Python for rapid development
mini_ros_py run my_example

# Move to Rust for production
mini_ros run my_pkg my_node

📚 Examples

Complete Development Cycle

# 1. Create package (Rust CLI)
mini_ros pkg create my_robot --python

# 2. Develop with Python
mini_ros_py run minimal_publisher

# 3. Test thoroughly
mini_ros_py test --coverage

# 4. Deploy with Rust
mini_ros launch my_robot production

Cross-Language Development

# Run Rust node
mini_ros run turtlebot controller

# In another terminal, run Python utilities
mini_ros_py run turtlebot_monitor

# Both communicate via miniROS middleware

Philosophy: Maximum robotics performance, minimum complexity 🤖⚡