setup.py

import os
from glob import glob
from os.path import basename
from os.path import splitext

from setuptools import setup, find_packages


def read(fname):
    return open(os.path.join(os.path.dirname(__file__), fname)).read()


setup(name="sagemaker",
      version="1.0.3",
      description="Open source library for training and deploying models on Amazon SageMaker.",
      packages=find_packages('src'),
      package_dir={'': 'src'},
      py_modules=[splitext(basename(path))[0] for path in glob('src/*.py')],
      long_description=read('README.rst'),
      author="Amazon Web Services",
      url='https://github.com/aws/sagemaker-python-sdk/',
      license="Apache License 2.0",
      keywords="ML Amazon AWS AI Tensorflow MXNet",
      classifiers=[
          "Development Status :: 5 - Production/Stable",
          "Intended Audience :: Developers",
          "Natural Language :: English",
          "License :: OSI Approved :: Apache Software License",
          "Programming Language :: Python",
          "Programming Language :: Python :: 2.7",
          "Programming Language :: Python :: 3.5",
      ],

      # Declare minimal set for installation
      install_requires=['boto3>=1.4.8', 'numpy>=1.9.0', 'protobuf>=3.1', 'scipy>=1.0.0'],

      extras_require={
          'test': ['tox', 'flake8', 'pytest', 'pytest-cov', 'pytest-xdist',
                   'mock', 'tensorflow>=1.3.0', 'contextlib2']},

      entry_points={
          'console_scripts': ['sagemaker=sagemaker.cli.main:main'],
      }
      )