text: # -------------------------------------------------------------------------
  # Copyright (c) Microsoft Corporation. All rights reserved.
  # Licensed under the MIT License.
  # -------------------------------------------------------------------------
  """A setuptools based setup module.
  
  See:
  https://packaging.python.org/en/latest/distributing.html
  https://github.com/pypa/sampleproject
  """
  
  # To use a consistent encoding
  from codecs import open
  from os import path
  import sys
  
  # Always prefer setuptools over distutils
  from setuptools import setup, find_packages
  
  here = path.abspath(path.dirname(__file__))
  
  # Get the long description from the README file
  with open(path.join(here, 'README.md')) as f:
      long_description = f.read()
  
  _install_requires = [
          'numpy>=1.14.0',
          'pandas>=0.22',
          'scipy>=0.18',
          'scikit-learn>0.19.0',
      ]
  
  # dotnetcore2 package is available only for python 3.x
  if sys.version_info.major == 3:
      _install_requires.append('dotnetcore2>=2.1.2')
  
  if sys.version_info[0:2] == (2,7):
      _install_requires.append('decorator')
      _install_requires.append('enum')
      _install_requires.append('funcsigs>=1.0.2')
  
  setup(
      name='nimbusml',
  
      # Versions should comply with PEP440.  For a discussion on
      # single-sourcing the version across setup.py and the project code, see
      # https://packaging.python.org/en/latest/single_source_version.html
      version='1.1.0',
  
      description='NimbusML',
      long_description=long_description,
      long_description_content_type='text/markdown',
  
      # The project's main homepage.
      url='https://docs.microsoft.com/en-us/nimbusml',
  
      # Author details
      author='Microsoft',
      author_email='nimbusml@microsoft.com',
  
      # Choose your license
      license='All rights reserved',
  
      # See https://pypi.python.org/pypi?%3Aaction=list_classifiers
      classifiers=[
          # How mature is this project? Common values are
          #   3 - Alpha
          #   4 - Beta
          #   5 - Production/Stable
          'Development Status :: 3 - Alpha',
  
          # Indicate who your project is intended for
          'Intended Audience :: Developers',
  
          # Specify the Python versions you support here. In particular,
          # ensure that you indicate whether you support Python 2, Python
          # 3 or both.
          'Programming Language :: Python :: 2.7',
          'Programming Language :: Python :: 3.5',
          'Programming Language :: Python :: 3.6',
          'Programming Language :: Python :: 3.7',
      ],
  
      # What does your project relate to?
      keywords='microsoft ml ML.NET machine learning nimbusml',
  
      # You can just specify the packages manually here if your project is
      # simple. Or you can use find_packages().
      packages=find_packages(exclude=['contrib', 'docs', 'tests']),
  
      # Alternatively, if you want to distribute just a my_module.py,
      # uncomment this:
      #   py_modules=["my_module"],
  
      # List run-time dependencies here.  These will be installed by pip when
      # your project is installed. For an analysis of "install_requires"
      # vs pip's requirements files see:
      # https://packaging.python.org/en/latest/requirements.html
      install_requires=_install_requires,
      # Recommended format for setuptools>=36.0 follows, however we use an older
      # version so we have to use a workaroud.
      # 'decorator ; python_version=="2.7"'
      # 'enum ; python_version=="2.7"'
      # 'numpy>=1.14.0',
      # 'pandas>=0.22',
      # 'scipy>=0.18',
      # 'scikit-learn>0.19.0'
  
      # List additional groups of dependencies here (e.g. development
      # dependencies). You can install these using the following syntax,
      # for example:
      # $ pip install -e .[dev,test]
      extras_require={
          'tests': [
              'nose>=1.3', 'pytest>=4.4.0',
              'graphviz', 'imageio',
          ],
          'utils': ['graphviz', 'imageio'],
      },
  
      # If your project's tests need one or more additional packages
      # besides those needed to install it, you can use this option to
      # specify them. It should be a string or list of strings specifying
      # what other distributions need to be present for the package's
      # tests to run. When you run the test command, setuptools will
      # attempt to obtain these (even going so far as to download them
      # using EasyInstall).
      # Note that these required projects will not be installed on the
      # system where the tests are run, but only downloaded to the
      # project's setup directory if they're not already installed locally.
      tests_require=[
          'jupyter_client>=4.4.0',
          'nbconvert>=4.2.0',
          'nose>=1.3',
          'pytest>=4.4.0',
      ],
  
      python_requires='>=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <3.8.*',
  
      # If there are data files included in your packages that need to be
      # installed, specify them here.  If using Python 2.6 or less,
      # then these have to be included in MANIFEST.in as well.
      include_package_data=True,
  
      package_data={
      },
  
      # Although 'package_data' is the preferred approach, in some case
      # you may need to place data files outside of your packages. See:
      # http://docs.python.org/3.4/distutils/setupscript.html#installing
      # -additional-files # noqa
      # In this case, 'data_file' will be installed into
      # '<sys.prefix>/my_data'
      data_files=[],
  
      # To provide executable scripts, use entry points in preference to the
      # "scripts" keyword. Entry points provide cross-platform support and
      #  allow pip to create the appropriate form of executable for the
      # target platform.
      entry_points={
      },
  )
  