datadog-integration

A production-grade Python library for validating Datadog API and Application keys with comprehensive permission testing.

• 🔑 API Key Validation: Verify Datadog API keys are valid and active
• 🔐 Application Key Testing: Test application key permissions and scopes
• 📊 Permission Verification: Validate read access to dashboards and metrics
• 🛡️ Type-Safe: Full type annotations with MyPy support
• 🧪 Well-Tested: Comprehensive test coverage
• 📝 Production-Ready: Follows modern Python packaging standards (PEP 621)
• 🔧 CLI Tool: Command-line interface for quick validation
• 🐍 Python 3.9+: Supports Python 3.9, 3.10, 3.11, and 3.12

pip install datadog-integration

For development:

pip install -e ".[dev]"

The easiest way to validate your Datadog credentials:

# Set environment variables
export DD_API_KEY="your-api-key"
export DD_APP_KEY="your-app-key"
export DD_SITE="datadoghq.com"  # Optional, defaults to datadoghq.com

# Run validation
datadog-key-check

Or use a .env file:

# Create .env file with your credentials
cat > .env << EOF
DD_API_KEY=your-api-key
DD_APP_KEY=your-app-key
DD_SITE=datadoghq.com
EOF

# Run validation (automatically loads .env)
datadog-key-check

Use the library programmatically in your Python code:

from datadog_integration import DatadogValidator

# Initialize validator
validator = DatadogValidator(
    api_key="your-api-key",
    app_key="your-app-key",
    site="datadoghq.com"
)

# Get configuration summary
config = validator.get_config_summary()
print(config)

# Validate API key
api_result = validator.validate_api_key()
if api_result and api_result.ok:
    print("API key is valid!")
else:
    print(f"API key validation failed: {api_result.error}")

# Test dashboard read permissions
dashboard_result = validator.test_dashboards_read()
if dashboard_result and dashboard_result.ok:
    print("Dashboard read access confirmed!")

# Test metrics read permissions
metrics_result = validator.test_metrics_read()
if metrics_result and metrics_result.ok:
    print("Metrics read access confirmed!")

The library supports the following environment variables:

• DD_API_KEY: Your Datadog API key (required for API validation)
• DD_APP_KEY or DD_APPLICATION_KEY: Your Datadog Application key
• DD_SITE: Datadog site (default: datadoghq.com)
• DD_API_KEY_NAME: Optional name/description for the API key
• DD_APP_KEY_NAME: Optional name/description for the Application key
• DD_KEY_ID or DD_APP_ID: Optional Application key identifier

# Clone the repository
git clone https://github.com/lecton-apptio/datadog-integration.git
cd datadog-integration

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install development dependencies
make install-dev

make help          # Show all available commands
make format        # Format code with Black
make lint          # Lint code with Ruff
make type-check    # Type check with MyPy
make test          # Run tests
make test-cov      # Run tests with coverage
make clean         # Remove build artifacts
make build         # Build distribution packages

# Run all tests
make test

# Run with coverage report
make test-cov

# Run specific test file
pytest tests/test_core.py

This project uses several tools to maintain code quality:

• Black: Code formatting (line length: 100)
• Ruff: Fast Python linter
• MyPy: Static type checking
• Pytest: Testing framework

All checks run automatically in CI/CD on Ubuntu, macOS, and Windows for Python 3.9-3.12.

Main class for validating Datadog credentials.

Constructor Parameters:

• api_key (str, optional): Datadog API key
• app_key (str, optional): Datadog Application key
• site (str): Datadog site (default: "datadoghq.com")
• api_key_name (str, optional): Name/description of the API key
• app_key_name (str, optional): Name/description of the Application key
• app_key_id (str, optional): Application key identifier

Methods:

• get_config_summary(): Returns configuration status
• validate_api_key(): Validates the API key
• test_dashboards_read(): Tests dashboard read permissions
• test_metrics_read(): Tests metrics read permissions

Result object returned by validation methods.

Attributes:

• ok (bool): Whether the validation succeeded
• status (int | None): HTTP status code
• curl (str): Redacted curl command for debugging
• data (dict): Response data if successful
• error (dict): Error information if failed

Methods:

• to_dict(): Convert result to dictionary

• load_env_file(path: str = ".env"): Load environment variables from file
• redact_secret(value: str): Redact sensitive values for safe display
• build_curl_command(url: str, headers: dict): Build curl command with redacted secrets

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

This project is licensed under the MIT License - see the LICENSE file for details.

• Issues: GitHub Issues
• Documentation: README.md
• Contributing: CONTRIBUTING.md

This project follows Semantic Versioning:

• MAJOR version for incompatible API changes
• MINOR version for new functionality in a backward compatible manner
• PATCH version for backward compatible bug fixes

Current version: 0.1.0

See CHANGELOG.md for a detailed history of changes.

• Initial release with API key validation
• Application key permission testing
• Dashboard and metrics read verification
• CLI tool with environment variable support
• Full type annotations and comprehensive test coverage

For complete release history, see CHANGELOG.md.