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Python client library for NDP EP API

Project description

ndp-ep

CI codecov PyPI version Python versions

A Python client library for interacting with the NDP EP API. This library provides a simple and intuitive interface for managing datasets, organizations, resources, and services through the API.

Features

  • Complete API Coverage: Support for all API endpoints including Kafka topics, S3 resources, URL resources, organizations, and services
  • Authentication: Token-based and username/password authentication
  • Search Functionality: Advanced search capabilities across datasets and resources
  • Error Handling: Comprehensive error handling with meaningful error messages
  • Type Hints: Full type hint support for better IDE integration
  • Testing: Extensive test coverage (>70%) with unit and integration tests

Installation

pip install ndp-ep

Quick Start

from ndp_ep import APIClient

# Initialize client with token
client = APIClient(
    base_url="https://your-api-endpoint.com",
    token="your-access-token"
)

# Or with username/password
client = APIClient(
    base_url="https://your-api-endpoint.com",
    username="your-username",
    password="your-password"
)

# List organizations
organizations = client.list_organizations()
print(organizations)

# Search datasets
results = client.search_datasets(
    terms=["climate", "temperature"],
    server="global"
)

# Register a new organization
org_data = {
    "name": "my_organization",
    "title": "My Organization",
    "description": "A sample organization"
}
response = client.register_organization(org_data)

# Register a service
service_data = {
    "service_name": "user_auth_api",
    "service_title": "User Authentication API",
    "owner_org": "services",
    "service_url": "https://api.example.com/auth",
    "service_type": "API",
    "notes": "RESTful API for user authentication"
}
response = client.register_service(service_data)

API Coverage

Authentication

  • Token-based authentication
  • Username/password authentication

Organizations

  • list_organizations() - List all organizations
  • register_organization() - Create new organization
  • delete_organization() - Delete organization

Datasets and Resources

  • search_datasets() - Search datasets with advanced filters
  • advanced_search() - Advanced search with POST method
  • register_url() - Register URL resources
  • register_s3_link() - Register S3 resources
  • register_kafka_topic() - Register Kafka topics
  • register_general_dataset() - Register general datasets
  • update_url_resource() - Update URL resources
  • update_s3_resource() - Update S3 resources
  • update_kafka_topic() - Update Kafka topics
  • update_general_dataset() - Update general datasets (PUT)
  • patch_general_dataset() - Partially update general datasets (PATCH)
  • delete_resource_by_id() - Delete resource by ID
  • delete_resource_by_name() - Delete resource by name

Services

  • register_service() - Register new services

System Information

  • get_kafka_details() - Get Kafka connection details
  • get_system_status() - Check system status
  • get_system_metrics() - Get system metrics
  • get_jupyter_details() - Get Jupyter connection details

Development

Setting up development environment

# Clone the repository
git clone https://github.com/sci-ndp/ndp-ep-py.git
cd ndp-ep-py

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

# Install development dependencies
pip install -e .
pip install -r requirements-dev.txt

Running tests

# Run all tests
pytest

# Run with coverage
pytest --cov=ndp_ep --cov-report=html

# Run specific test categories
pytest -m unit          # Unit tests only
pytest -m integration   # Integration tests only

Code formatting and linting

# Format code
black ndp_ep tests

# Lint code
flake8 ndp_ep

# Type checking
mypy ndp_ep

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Make your changes
  4. Add tests for your changes
  5. Ensure all tests pass and coverage is maintained
  6. Commit your changes (git commit -m 'Add amazing feature')
  7. Push to the branch (git push origin feature/amazing-feature)
  8. Open a Pull Request

License

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

Changelog

v0.1.0

  • Initial release
  • Complete API coverage for all endpoints
  • Authentication support (token and username/password)
  • Search functionality
  • Resource management (URL, S3, Kafka)
  • Organization management
  • Comprehensive testing suite

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