domolibrary2 2.3.1

A Python library for interacting with Domo APIs

Last updated: 2025-11-17

Domolibrary

A Python library for interacting with Domo APIs.

This project includes GitHub Copilot custom prompts for enhanced development workflows. See the Copilot Kit section below.

Installation

pip install domolibrary

Usage

from domolibrary import DomoUser
# Your code here

Project Structure

src/                      # Main package source code
├── classes/              # Domain model classes
├── client/               # API client utilities
├── integrations/         # Integration modules
├── routes/               # API route implementations
├── utils/                # Utility functions
├── __init__.py           # Package initialization
└── _modidx.py           # Module index
scripts/                  # Development scripts
tests/                    # Test files
.vscode/                  # VS Code configuration
.github/workflows/        # CI/CD workflows

Development

This project uses uv for dependency management and development.

Setup Development Environment

# Initial setup (run once)
.\scripts\setup-dev.ps1

This will:

• Install all dependencies (including dev dependencies)
• Set up pre-commit hooks for automatic code quality checks

Development Scripts

All development scripts are located in the scripts/ folder. See scripts/README.md for detailed documentation.

Quick reference:

• .\scripts\setup-dev.ps1 - Setup development environment
• .\scripts\format-code.ps1 - Manual code formatting (fallback)
• .\scripts\lint.ps1 - Run linting and type checking
• .\scripts\test.ps1 - Run tests with coverage
• .\scripts\build.ps1 - Build the package
• .\scripts\publish.ps1 - Publish to PyPI (with validation)

Manual Development Commands

If you prefer to run commands manually:

# Install dependencies
uv sync --dev

# Run linting
uv run ruff check src --fix
uv run black src
uv run isort src
uv run pylint src
uv run mypy src

# Run tests
uv run pytest tests/ --cov=src

# Build package
uv build

# Publish (after all checks pass)
uv publish

Pre-commit Hooks

This project uses pre-commit hooks to automatically check code quality before commits:

• Ruff - Fast Python linter
• Black - Code formatter
• isort - Import sorter

Hooks are installed automatically by setup-dev.ps1. If they cause issues, you can use .\scripts\format-code.ps1 as a fallback.

GitHub Copilot Integration

This project includes a curated collection of GitHub Copilot custom prompts and MCP (Model Context Protocol) server configurations to enhance your development workflow.

🎨 Custom Prompts

Ready-to-use prompts for common development tasks:

Prompt	Description	Usage
architecture-review	Focused architectural review with actionable feedback	/architecture-review
code-review	High-rigor, tech-agnostic code review	/code-review
pragmatic-code-review	Production-focused code review balancing rigor with constraints	/pragmatic-code-review
refactor	Intelligent refactoring with best practices	/refactor
optimize-performance	Identify and fix performance anti-patterns	/optimize-performance
document	Generate exceptional documentation with diagrams	/document
create-prompt	Meta-prompt to generate new custom prompts	/create-prompt

🤖 MCP Server Configuration

Model Context Protocol (MCP) lets Copilot connect to external tool servers for enhanced capabilities:

• Sequential Thinking - Structured thinking process for complex tasks
• Memory - Remember context between conversations
• Context7 - Access to up-to-date framework documentation
• Shadcn UI - Shadcn UI component knowledge (if using React)
• Chrome DevTools - Browser debugging capabilities

Quick MCP Setup

1. Copy memory template:

   cp .mcp/memory.json.dist .mcp/memory.json
   

   ⚠️ Never commit .mcp/memory.json - add to .gitignore

2. Configure servers: The .vscode/mcp.json file is already set up with recommended servers. Copilot will prompt for any required API keys on first use.

3. Enable MCP in VS Code: Ensure GitHub Copilot Chat has MCP enabled in settings.

📚 Documentation

• Custom Prompts Guide - Comprehensive guide on using and creating prompts
• Testing Guide - How to verify your setup is working correctly
• Fork Sync Guide - Information about keeping copilot-kit files updated

Using Prompts

Invoke prompts in GitHub Copilot Chat using the slash command:

/code-review
/refactor
/document

With optional arguments:

/code-review focus=security
/pragmatic-code-review maintainability
/optimize-performance

See the Custom Prompts Guide for detailed usage instructions.

Contributing

See CONTRIBUTING.md for guidelines on contributing to this project, including information about custom prompts and code review standards.