Initial implementation of PyORlib

[idapena]

Initial Checks

• The code compiles successfully without any errors or warnings.
• The terminology used in the code aligns with approved standards.
• I have personally tested these changes on my local environment.
• I have ensured that relevant documentation has been added or updated.
• My code follows the established coding style guidelines.
• I have added tests for the new code (if applicable).
• All existing tests have passed successfully.

Description

This pull request introduces the initial implementation of PyORlib, a powerful Python library for operations research and optimization. PyORlib provides a set of abstractions to easily define, solve, and interact with mathematical models in a standardized manner across different optimization packages. It serves as a user-friendly and powerful platform for students, researchers, and practitioners to explore optimization concepts, experiment with algorithms, and expand their knowledge.

Implementation Details

The first implementation includes all the core functionalities of the package, encompassing built-in optimization package integrations, algebraic modeling, validators, and more.

Testing and Coverage

This release includes a test suite that verifies the correctness of the package implementation. It also integrates code coverage, achieving 100% test coverage. The tests are configured to run automatically via GitHub Actions on both push and pull requests to the master branch.

Formatter and Lint Configuration

A formatter and lint configuration have been added to the project. This ensures consistent code style, maintainability, and adherence to the established coding standards defined in the project documentation.

Documentation

Additionally, this release includes comprehensive documentation for the package. The documentation covers the main page, a detailed getting started guide, examples, API reference, and release notes.