Metadata-Version: 2.1
Name: slsdm
Version: 0.1.0
Summary: A set of SIMD-accelerated DistanceMetric implementations
Maintainer: Meekail Zain
Maintainer-email: zainmeekail@gmail.com
License: new BSD
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: C
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.8
Description-Content-Type: markdown
License-File: LICENSE
Requires-Dist: scikit-learn (>=1.3.dev0)
Provides-Extra: benchmark
Provides-Extra: docs
Provides-Extra: examples
Provides-Extra: tests
Requires-Dist: pytest (>=5.4.3) ; extra == 'tests'
Requires-Dist: pytest-cov (>=2.9.0) ; extra == 'tests'
Requires-Dist: flake8 (>=3.8.2) ; extra == 'tests'
Requires-Dist: black (>=23.3.0) ; extra == 'tests'
Requires-Dist: mypy (>=0.961) ; extra == 'tests'

# Scikit-Learn SIMD DistanceMetrics (SLSDM)

## Install from pip
Run `pip install slsdm`.
## Install From Source:

1. Create a new environment with `xsimd`: `conda create -n <env_name> -c conda-forge python~=3.10.0 compilers`
2. Activate the environment: `conda activate <env_name>`
3. Run `pip install -e .`

Note: if you are building with a custom development installation of scikit-learn then use the `--no-build-isolation`
flag to ensure it is not superceded by the published version.

## Specify SIMD Target Architectures

Coming soon.
