Dokman

Dokman is a Python CLI tool for centralized Docker Compose deployment management. It provides a unified interface to manage Docker Compose deployments from any directory without navigating to individual compose file locations.

Features

• List and monitor all Docker Compose deployments from a single location
• Start, stop, restart, and redeploy services without changing directories
• View logs, execute commands, and inspect container health
• Manage images, volumes, and networks across projects
• Track projects with a local registry for persistent management
• Rich terminal output with table and JSON formatting options

Requirements

• Python 3.13 or higher
• Docker Engine with Docker Compose v2
• uv (recommended for installation) or pip

Installation

Quick Install (Recommended)

The easiest way to install dokman is using the installation script:

curl -fsSL https://raw.githubusercontent.com/Alg0rix/dokman/main/install.sh | bash

This will automatically install uv if needed and set up dokman.

Upgrade

To upgrade to the latest version, run the install script again or use:

uv tool upgrade dokman

Using uv

If you already have uv installed:

uv tool install --python 3.13 dokman

# Verify installation
dokman --help

Using pip

pip install dokman

From Source

# Clone the repository
git clone https://github.com/Alg0rix/dokman.git
cd dokman

# Install dependencies
uv sync

# Run dokman
uv run dokman --help

Quick Start

Register a Project

Register an existing Docker Compose project for tracking:

# Register from compose file path
dokman register /path/to/docker-compose.yml

# Register with custom name
dokman register /path/to/project --name myapp

Start a Project

Start a project directly (auto-registers if needed):

# Start from current directory
dokman up

# Start from specific path
dokman up -f /path/to/project

# Start with custom name
dokman up -f ./myproject -n myapp

List Projects

# List registered projects
dokman list

# Include unregistered running projects
dokman list --all

# Output as JSON
dokman list --format json

Manage Services

# View project details
dokman info myproject

# Start/stop/restart services
dokman start myproject
dokman stop myproject
dokman restart myproject

# Restart specific service
dokman restart myproject --service web

# Stop and remove containers
dokman down myproject

# Remove with volumes
dokman down myproject --volumes

View Logs

# View all logs
dokman logs myproject

# View specific service logs
dokman logs myproject --service web

# Follow logs in real-time
dokman logs myproject --follow

# Show last N lines
dokman logs myproject --tail 100

Execute Commands

# Run command in container
dokman exec myproject web ls -la

# Interactive shell
dokman exec myproject web sh --interactive

Commands Reference

Project Management

Service Lifecycle

Debugging and Inspection

Resource Management

Command Options

Global Options

• --format, -f: Output format (table or json)
• --help: Show command help

Common Options

• --service, -s: Target specific service
• --all, -a: Include all items (registered and unregistered)
• --volumes, -v: Include volumes in operation

Logs Options

• --follow, -f: Stream logs in real-time
• --tail, -n: Number of lines to show

Redeploy Options

• --no-pull: Skip pulling latest images
• --strict: Fail if any image pull fails

Build Options

• --no-cache: Build without using cache

Stats Options

• --no-stream: Display single snapshot instead of streaming

Environment Options

• --show-secrets: Show sensitive values (masked by default)
• --export: Output in shell export format

Exit Codes

Configuration

Dokman stores its project registry at:

~/.config/dokman/projects.json

This file tracks registered projects and their compose file locations.

Architecture

Dokman follows a layered architecture:

CLI Layer (Typer) -> Service Layer -> Docker Client Layer -> Storage Layer

• CLI Layer: Typer-based commands with Rich output formatting
• Service Layer: Business logic (ProjectManager, ServiceManager, ResourceManager)
• Docker Client Layer: Wraps Docker SDK and compose commands
• Storage Layer: JSON-based project registry

Development

Setup Development Environment

# Install with dev dependencies
uv sync --extra dev

Running Tests

# Run all tests
uv run pytest

# Run specific test file
uv run pytest tests/properties/test_models_properties.py

# Run with verbose output
uv run pytest -v

Code Quality

# Lint code
uvx ruff check

# Type check
uvx ty check

Project Structure

dokman/
  cli/           # CLI commands and output formatting
  clients/       # Docker SDK and compose command wrappers
  models/        # Data models (Project, Service, etc.)
  services/      # Business logic layer
  storage/       # Project registry persistence
tests/
  properties/    # Property-based tests (Hypothesis)

Dependencies

• typer: CLI framework
• docker: Docker SDK for Python
• rich: Terminal output formatting

Development Dependencies

• pytest: Testing framework
• hypothesis: Property-based testing
• pytest-mock: Mocking support

License

MIT License

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests and linting
5. Submit a pull request