text: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  from setuptools import setup
  
  version = "0.4.0"
  setup(name='metric-learn',
        version=version,
        description='Python implementations of metric learning algorithms',
        author=['CJ Carey', 'Yuan Tang'],
        author_email='ccarey@cs.umass.edu',
        url='http://github.com/all-umass/metric-learn',
        license='MIT',
        classifiers=[
            'Development Status :: 4 - Beta',
            'License :: OSI Approved :: MIT License',
            'Programming Language :: Python',
            'Operating System :: OS Independent',
            'Intended Audience :: Science/Research',
            'Topic :: Scientific/Engineering'
        ],
        packages=['metric_learn'],
        install_requires=[
            'numpy',
            'scipy',
            'scikit-learn',
            'six',
            'deap'
        ],
        extras_require=dict(
            docs=['sphinx', 'shinx_rtd_theme', 'numpydoc'],
            demo=['matplotlib'],
        ),
        test_suite='test',
        keywords=[
            'Metric Learning',
            'Large Margin Nearest Neighbor',
            'Information Theoretic Metric Learning',
            'Sparse Determinant Metric Learning',
            'Least Squares Metric Learning',
            'Neighborhood Components Analysis'
        ])
  