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globalMOO SDK Suite v1.0.0 - Official Release

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@moridinamael moridinamael released this 18 Mar 20:35
v1.0.0
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globalMOO SDK Suite v1.0.0 - Official Release

We are thrilled to announce the official 1.0.0 release of the globalMOO SDK Suite! This release provides a comprehensive set of examples demonstrating how to leverage the globalMOO optimization platform API across multiple programming languages.

What is the globalMOO SDK Suite?

The globalMOO SDK Suite showcases how to integrate with the powerful multi-objective optimization platform designed to solve complex inverse problems. The examples demonstrate how to:

  • Find optimal input parameters that achieve desired output targets
  • Work with mixed variable types (continuous, integer, boolean, categorical)
  • Define different types of optimization objectives
  • Solve problems that would be difficult or impossible with traditional methods

Key Features

  • Multi-language Support: Includes example implementations for Python, JavaScript, C#, and PHP
  • Consistent Examples: Each language implements the same set of optimization scenarios
  • Comprehensive API Usage: Demonstrates the full range of globalMOO API capabilities
  • Step-by-Step Guides: Detailed documentation for each example
  • Configuration Templates: Includes environment templates for easy setup

Example Types

All SDK implementations include a consistent set of examples demonstrating key capabilities:

  • Linear - Linear system of equations with 3 inputs and 5 outputs
  • Simple - Basic nonlinear 3-input, 3-output quadratic function example
  • Integer - Example demonstrating integer variable optimization
  • Logical - Example showing boolean variable optimization
  • Categorical - Example with categorical variable handling
  • Exact Objective - High-precision optimization with exact L1-convergence
  • Multiple Objective Types - Mixed objective types in a single model
  • Multiple Outcome - Working with subsets of model outputs
  • Complex - Advanced example with mixed variable types and constraints
  • Convolutional - Finding multiple valid solutions for underdetermined systems
  • Constrained Maximization - Maximizing an objective while respecting constraints

Getting Started

Python Implementation

pip install globalmoo-sdk

The Python examples also include a webhook implementation for setting up a client-side server to handle API events, and an interactive Colab notebook for trying the SDK directly in your browser.

JavaScript Implementation

npm install @globalmoo/globalmoo-sdk

Our JavaScript SDK provides a modern, Promise-based interface with full support for async/await patterns and ES modules.

C# Implementation

Install the NuGet package:

dotnet add package GMOO.SDK

Our C# SDK provides a strongly-typed, async-first interface that follows modern .NET conventions and best practices.

PHP Implementation

composer require globalmoo/gmoo-sdk-php

Requires PHP 8.3+ with curl and json extensions.

Configuration

All examples use a consistent configuration approach:

  • Set GMOO_API_KEY to your globalMOO API key
  • Set GMOO_API_URI to https://app.globalmoo.com/api/

Each language directory includes an .env.dist file with the required environment variables.

Documentation

For comprehensive documentation and API reference, visit our [globalMOO Documentation](https://globalmoo.gitbook.io/globalmoo-documentation).

Support

If you have any questions or need assistance, please contact us at [email protected].

License

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

We're excited to see how you'll use the globalMOO platform to solve your most challenging optimization problems!

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