text: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  
  # Note: To use the 'upload' functionality of this file, you must:
  #   $ pip install twine
  
  # Based on https://github.com/catalyst-team/catalyst/blob/master/setup.py
  
  import io
  import os
  import sys
  from glob import glob
  from shutil import rmtree
  
  from setuptools import find_packages, setup, Command
  
  # Package meta-data.
  NAME = 'mlcomp'
  DESCRIPTION = 'Machine learning pipelines. ' \
                'Especially, for competitions, like Kaggle'
  URL = 'https://github.com/catalyst-team/mlcomp'
  EMAIL = 'lightsanweb@gmail.com'
  AUTHOR = 'Evgeny Semyonov'
  REQUIRES_PYTHON = '>=3.6.0'
  
  PROJECT_ROOT = os.path.abspath(os.path.dirname(__file__))
  
  
  def load_requirements():
      with open(os.path.join(PROJECT_ROOT, 'requirements.txt'), 'r') as f:
          return f.read()
  
  
  def load_readme():
      readme_path = os.path.join(PROJECT_ROOT, 'README.md')
      with io.open(readme_path, encoding='utf-8') as f:
          return '\n' + f.read()
  
  
  def load_version():
      context = {}
      with open(os.path.join(PROJECT_ROOT, 'mlcomp', '__version__.py')) as f:
          exec(f.read(), context)
      return context['__version__']
  
  
  def files(directory):
      objs = glob(os.path.join(directory, '**'), recursive=True)
      folders = [o for o in objs if os.path.isdir(o)]
      for folder in folders:
          if '__pycache__' in folder:
              continue
  
          folder_files = [
              os.path.join(folder, f) for f in os.listdir(folder)
              if os.path.isfile(os.path.join(folder, f))
          ]
          yield folder, folder_files
  
  
  def get_data_files():
      res = []
  
      res.extend(files('mlcomp/utils'))
      res.extend(files('mlcomp/bin'))
      res.extend(files('mlcomp/docker'))
      res.extend(files('mlcomp/server/front/dist'))
      res.extend(files('mlcomp/migration'))
      return res
  
  
  class UploadCommand(Command):
      """Support setup.py upload."""
  
      description = 'Build and publish the package.'
      user_options = []
  
      @staticmethod
      def status(s):
          """Prints things in bold."""
          print('\033[1m{0}\033[0m'.format(s))
  
      def initialize_options(self):
          pass
  
      def finalize_options(self):
          pass
  
      def run(self):
          try:
              self.status('Removing previous builds…')
              rmtree(os.path.join(PROJECT_ROOT, 'dist'))
          except OSError:
              pass
  
          self.status('Building Source and Wheel (universal) distribution…')
          os.system(
              '{0} setup.py sdist bdist_wheel --universal'.format(
                  sys.executable
              )
          )
  
          self.status('Uploading the package to PyPI via Twine…')
          os.system('python -m twine upload dist/*')
  
          self.status('Pushing git tags…')
          os.system('git tag v{0}'.format(load_version()))
          os.system('git push --tags')
  
          sys.exit()
  
  
  setup(
      name=NAME,
      version=load_version(),
      description=DESCRIPTION,
      long_description=load_readme(),
      long_description_content_type='text/markdown',
      author=AUTHOR,
      author_email=EMAIL,
      python_requires=REQUIRES_PYTHON,
      url=URL,
      packages=find_packages(exclude=('tests',)),
      install_requires=load_requirements(),
      include_package_data=True,
      data_files=get_data_files(),
      zip_safe=False,
      license='MIT',
      classifiers=[
          'License :: OSI Approved :: MIT License',
          'Intended Audience :: Developers',
          'Intended Audience :: Science/Research',
          'Programming Language :: Python',
          'Programming Language :: Python :: 3.6',
          'Programming Language :: Python :: 3.7',
          'Programming Language :: Python :: Implementation :: CPython',
          'Topic :: Scientific/Engineering :: Artificial Intelligence'
      ],
      # $ setup.py publish support.
      cmdclass={
          'upload': UploadCommand
      },
      entry_points={
          'console_scripts': [
              'mlcomp-server = mlcomp.server.__main__:main',
              'mlcomp-worker = mlcomp.worker.__main__:main',
              'mlcomp-contrib = mlcomp.contrib.__main__:main',
              'mlcomp = mlcomp.__main__:main',
          ],
      }
  )
  