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Release Notes

v0.1.3 July 30, 2025

Changed
  • Updated the lower bound variable definition in pulp_engine to set it to None when -inf is specified as the lower bound.
  • Upgraded the download-artifact and cache actions to v4 in the publish-to-pypi.yml workflow.
Fixed
  • Updated deprecated _pytest.python_api.raises imports in several tests.

v0.1.2 April 9, 2024

Changed
  • Upgraded the Setup-Python GitHub Action from version 4 to version 5 in all workflows.
  • Updated the index.md page with a welcome title.
  • Updated the mkdocs.yml config file with the mkdocs social cards plugin.
  • Updated the pyproject.toml config file with the necessary dependencies for the mkdocs social cards plugin.
Fixed
  • Resolved the mathjax.js config file path error in the documentation.

v0.1.1 March 2, 2024

Changed
  • The print_info and print_solution methods in the Model class have been enhanced to improve visibility and provide deeper insights.
  • The get_pretty_string method in the Term class has been refactored as an @abstractmethod for subclass customization.
  • Badges on the main page of the documentation and the readme file have been updated to improve visibility and align with the package's color palette.
  • The git-committers plugin in the mkdocs.yml file has been updated to exclude the index.md, examples/index.md, and api/index.md files for consistency in the current configuration with the git-revision-date-localized plugin.

v0.1.0 March 2, 2024

Initial Implementation

  This release introduces the initial version 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.