lnpi-gridapi 1.0.7.1

Python client library for LNPI Grid API

LNPI GridAPI Python Client

A comprehensive Python client library for interacting with the LNPI Grid API, providing type-safe, intuitive access to research studies, medical imaging data, and workflow management.

Features

• 🚀 Type-safe interactions with all Grid API endpoints
• 🏗️ Intuitive resource management with proper abstractions
• 📊 Comprehensive CRUD operations for all data models
• 🔍 Advanced querying and filtering capabilities
• 🔐 Robust authentication handling
• ⚡ Async support for high-performance applications
• 📚 Excellent developer experience with proper error handling

Installation

From PyPI

pip install lnpi_gridapi

From Source

git clone https://github.com/kelvinlim/gridapi.git
cd gridapi
pip install -e .

With Optional Dependencies

# For CLI functionality
pip install lnpi_gridapi[cli]

# For async support
pip install lnpi_gridapi[async]

# For development
pip install lnpi_gridapi[dev]

# All features
pip install lnpi_gridapi[all]

Windows Standalone Executable

For users who don't want to install Python:

1. Download: Get the pre-built executable from releases
   • Windows: gridapi-windows.exe
   • macOS: gridapi-macos
   • Linux: gridapi-linux
2. Configure: Create a grid_token file with your API credentials
3. Run: Execute the executable directly from command line

See WINDOWS_BUILD.md for detailed instructions on building cross-platform executables. See DEPLOYMENT.md for information about automated releases and deployment.

Releases

Latest Release

Download the latest release from GitHub Releases:

• Windows: gridapi-windows.exe
• macOS: gridapi-macos
• Linux: gridapi-linux

Release Process

Releases are automatically created when version tags are pushed:

git tag v1.0.0
git push origin v1.0.0

This triggers GitHub Actions to:

1. Build executables for all platforms
2. Create a GitHub release with downloadable assets
3. Generate checksums for verification

Quick Start

Using grid_token file (Recommended)

Create a grid_token file in your project directory:

grid_token=your-api-token-here
base_url=https://api.grid.example.com

Then use it in your code:

from pathlib import Path
from gridapi import GridAPIClient

# Load config from grid_token file
config_path = Path("grid_token")
config = {}
if config_path.exists():
    with open(config_path, 'r') as f:
        for line in f:
            if '=' in line:
                key, value = line.strip().split('=', 1)
                config[key] = value

# Initialize client
client = GridAPIClient(
    base_url=config.get('base_url', 'https://api.grid.example.com'),
    token=config.get('grid_token')
)

# Create a study
study = client.grid.studies.create({
    "description": "Clinical Trial Study",
    "investigator": "Dr. Jane Smith",
    "status": 1
})

# List studies with filtering
studies = client.grid.studies.list(
    investigator="Dr. Smith",
    status=1
)

# Access nested resources
events = client.grid.studies(study.id).events.list()

API Categories

Grid API

• Studies: Research study management
• Datatypes: Data type definitions
• Subjects: Study participants
• Events: Study events and details
• Procedures: Study procedures

Image API

• Acquisitions: Image acquisition data
• Actions: Image processing actions
• Scanner Types: Scanner configurations
• Raw Data: Raw image data management

Taskflow API

• Measures: Study measures
• Participants: Workflow participants

Advanced Usage

Complex Filtering

# Advanced querying
studies = client.grid.studies.list(
    search="clinical trial",
    ordering="-created_at",
    status__gte=1
)

# Nested resource operations
subject = client.grid.studies(123).subjects(456).get()
contacts = client.grid.studies(123).subjects(456).contacts.list()

Async Support

import asyncio
from gridapi import AsyncGridAPIClient

async def main():
    client = AsyncGridAPIClient(
        base_url="https://api.grid.example.com",
        token="your-api-token"
    )
    
    studies = await client.grid.studies.list()
    return studies

# Run async code
studies = asyncio.run(main())

Examples

Check out the examples directory for comprehensive usage examples:

• examples/simple_example.py - Basic usage with grid_token file
• examples/basic_usage.py - Common operations and patterns
• examples/advanced_usage.py - Complex queries and advanced features
• examples/cli_usage.py - Command-line interface examples
• examples/event_details_example.py - Event details functionality examples

All examples use the grid_token file for configuration, making them easy to run.

CLI Usage

The CLI automatically reads configuration from a grid_token file and provides comprehensive access to all GridAPI resources:

# Create configuration file
echo "grid_token=your-api-token-here" > grid_token
echo "base_url=https://your-api-url.com" >> grid_token

# Study management
gridapi studies list                                    # List all studies
gridapi studies get 100                               # Get study details
gridapi studies create --description "Test Study" --investigator "Dr. Test"

# Study resources
gridapi studies subjects 100                          # List subjects for study 100
gridapi studies procedures 100                         # List procedures for study 100
gridapi studies events 100                            # List events for study 100
gridapi studies event-details 100 10000               # List details for event 10000
gridapi studies subject-contacts 100 1000             # List contacts for subject 1000

# Image management
gridapi actions list                                   # List all image actions
gridapi actions list --status completed               # List completed actions

# Output formats
gridapi studies subjects 100 --format json            # JSON output
gridapi studies subjects 100 --format table           # Table output (default)

# Configuration
gridapi config                                         # Show current configuration
gridapi --help                                         # Show help

CLI Features

• Automatic Configuration: Reads from grid_token file by default
• Multiple Output Formats: Table (default) and JSON output
• Comprehensive Coverage: Access to all study resources and nested data
• Command Overrides: Override config file with command-line options
• Rich Output: Beautiful tables with colors and formatting
• Error Handling: Clear error messages and validation

Authentication

The GridAPI client supports multiple authentication methods:

# Token authentication
client = GridAPIClient(
    base_url="https://api.grid.example.com",
    token="your-api-token"
)

# Cookie authentication
client = GridAPIClient(
    base_url="https://api.grid.example.com",
    session_id="your-session-id"
)

Error Handling

from gridapi.exceptions import GridAPIError, ValidationError

try:
    study = client.grid.studies.create(invalid_data)
except ValidationError as e:
    print(f"Validation error: {e}")
except GridAPIError as e:
    print(f"API error: {e}")

Contributing

Contributions are welcome! Please read our contributing guidelines and submit pull requests to our GitHub repository.

License

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