Werpy

Enhancements

- Updated tests to better handle and validate invalid input types.

- Improved code quality by addressing some minor CodeFactor alerts:
- Fixed naming issues and built-in name overrides.
- Updated constants to use proper UPPER_CASE naming style.

- Included 'ZeroDivisionError' in exception handling across source files for better error coverage.

- Adopted REUSE and SDCX specifications for license compliance:
- Removed unnecessary license files for third-party dependencies ('numpy', 'pandas', 'cython') from the 'LICENSES' directory.
- Added 'BSD-3-Clause.txt' license file to the 'LICENSES' directory.
- Added 'SPDX-FileCopyrightText' and 'SPDX-License-Identifier' headers directly in all '.py' and '.pyx' source files.
- Created a 'REUSE.toml' file to centralize license declarations. The benefits of doing this for other files include:
- Centralized license declarations — avoids repetitive SPDX headers in every file (there are lots of other files).
- Cleaner source files — especially for binary or non-comment-friendly formats (e.g., '.png', '.yml', '.toml').
- Scalable and maintainable — simplifies licensing for new files and directories.
- Improved automation — supports tools like 'reuse lint' and CI-based license checks.
- Clarity and compliance — enhances transparency and ensures open source compliance through machine-readable metadata.

- Initial support for static type checking: included py.typed marker file to enable type checkers to recognize the package as typed. Note: full type coverage is not yet guaranteed and will be improved incrementally.


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Enhancements

- Custom exception handling for ZeroDivisionError to catch cases where the reference is blank or both reference and hypothesis are empty. When either of these events occur a clear, descriptive error message is Raised:
"Invalid input: reference must not be blank, and reference and hypothesis cannot both be empty."

- Unit test added to verify that blank reference and hypothesis inputs raise a ZeroDivisionError.

- Publishing process is now automated using GitHub Actions and PyPI Trusted Publishing



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Breaking Changes

- Dropped support for Python 3.8.x and 3.9.x
- These versions have reached or are nearing their end of life
- Users are strongly encouraged to upgrade to Python 3.10 or later
- This change allows us to utilize newer Python features, improve overall package maintenance and security
- Minimum supported Python version is now 3.10

- Dropped support for Pandas 1.x (pandas>=2.0.0 is now required)

- NumPy versions below 1.26.0 are no longer supported for Python 3.10+

- NumPy 2.x is required for Python 3.12+, which may introduce API changes


Enhancements

- Official support for Python 3.13:
- This release ensures full compatibility with Python 3.13, with thorough testing to verify seamless functionality.
- All dependencies have been reviewed and confirmed to be compatible with Python 3.13.

- Updated minimum required versions for NumPy dependencies:
- For Python < 3.12: Increased from 1.21.6 to 1.26.0
- For Python >= 3.12: Increased to 2.2.0 (previously 1.23.2 for Python >= 3.11)

- Updated minimum required versions for Pandas dependencies:
- Increased from 1.3.0 to 2.0.0, ensuring compatibility with the latest NumPy versions.

- Bump sphinx from 7.3.7 to 8.1.3

- Bump sphinx-nefertiti from 0.3.4 to 0.7.4
- The latest version ('0.7.4') is now fully compatible with Sphinx 8.1.

- Updated C standard from C11 ('c_std=c11') to C17 ('c_std=c17') in the Meson build system.
- Improves compatibility with modern compilers.
- Aligns with the latest stable C standard while maintaining backward compatibility.
- No breaking changes expected, as C17 is a bug-fix refinement of C11.

- Updated Cython NumPy Import Convention
- Changed cimport numpy as np to cimport numpy as cnp to align with Cython best practices, improving clarity between Python and Cython NumPy APIs.

- Explicit NumPy C API Initialization
- Added cnp.import_array() to ensure proper initialization of NumPy’s C API, resolving the numpy.core.multiarray failed to import error in NumPy 2.x+.

- Updated Cython Function Type Annotation
- Changed cpdef np.ndarray calculations(...) to cpdef cnp.ndarray calculations(...) to properly reference the Cython-level NumPy API, ensuring type safety and compatibility with compiled C extensions.


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Enhancements

All the following changes were incorporated into the major v3.0.0 rollout

- Bump idna from 3.6 to 3.7 in /docs ([5](https://github.com/analyticsinmotion/werpy/pull/5))
- Bump sphinx from 7.2.6 to 7.3.7 ([6](https://github.com/analyticsinmotion/werpy/pull/6))
- Bump jinja2 from 3.1.3 to 3.1.4 in /docs ([7](https://github.com/analyticsinmotion/werpy/pull/7))
- Bump requests from 2.31.0 to 2.32.2 in /docs ([10](https://github.com/analyticsinmotion/werpy/pull/10))
- Bump urllib3 from 2.1.0 to 2.2.2 in /docs ([11](https://github.com/analyticsinmotion/werpy/pull/11))
- Bump sphinx-nefertiti from 0.3.2 to 0.3.4 ([12](https://github.com/analyticsinmotion/werpy/pull/12))
- Bump certifi from 2023.11.17 to 2024.7.4 in /docs ([13](https://github.com/analyticsinmotion/werpy/pull/13))

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Enhancements

- Full compatibility with Python v3.12:
- The package has been thoroughly tested and verified to work seamlessly with Python v3.12.
- All dependencies have been updated and are also compliant with Python v3.12.

- Added comprehensive package documentation using Sphinx and hosted on Read the Docs. The documentation covers installation instructions, usage guides, and worked examples of all feature functionality. Access the documentation at [https://werpy.readthedocs.io/](https://werpy.readthedocs.io/).

- Updated the circleci config.yml file to support the compilation of Cython .pyx files.

- Integrated codecov into the circleci config.yml file to generate comprehensive coverage reports.

- Enhanced testing procedures to increase code coverage percentage.

- Ensured compliance with the Black code formatting by modifying relevant files.


Changed

- Bump jinja2 from 3.1.2 to 3.1.3 in /docs. ([1](https://github.com/analyticsinmotion/werpy/pull/1))
- For more information please see the Jinja release documentation [https://github.com/pallets/jinja/releases](https://github.com/pallets/jinja/releases).

- Bump sphinx-nefertiti from 0.2.1 to 0.2.3 ([2](https://github.com/analyticsinmotion/werpy/pull/2))

- Bump sphinx-nefertiti from 0.2.3 to 0.3.1 ([3](https://github.com/analyticsinmotion/werpy/pull/3))


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Enhancements

- Updated the meson.build file to align with the recommended approach for integrating Cython into the build process:
- Added Cython to the list of languages utilized by the project.
- Passed the Cython source code directly to the py.extension_module() definition for improved integration.
- Specified the C standard configuration as C11, instructing Meson to use C11 as the designated C standard.


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