old_contents: import imp
  import os
  from setuptools import setup, find_packages
  
  version = imp.load_source(
      'mlflow.version', os.path.join('mlflow', 'version.py')).VERSION
  
  
  # Get a list of all files in the JS directory to include in our module
  def package_files(directory):
      paths = []
      for (path, directories, filenames) in os.walk(directory):
          for filename in filenames:
              paths.append(os.path.join('..', path, filename))
      return paths
  
  
  # Prints out a set of paths (relative to the mlflow/ directory) of files in mlflow/server/js/build
  # to include in the wheel, e.g. "../mlflow/server/js/build/index.html"
  js_files = package_files('mlflow/server/js/build')
  sagmaker_server_files = package_files("mlflow/sagemaker/container")
  
  setup(
      name='mlflow',
      version=version,
      packages=find_packages(exclude=['tests', 'tests.*']),
      package_data={"mlflow": js_files + sagmaker_server_files},
      install_requires=[
          'click>=6.7',
          'databricks-cli>=0.8.0',
          'requests>=2.17.3',
          'six>=1.10.0',
          'gunicorn',
          'Flask',
          'numpy',
          'pandas',
          'scipy',
          'scikit-learn',
          'python-dateutil',
          'protobuf>=3.6.0',
          'gitpython>=2.1.0',
          'pyyaml',
          'boto3',
          'querystring_parser',
          'simplejson',
          'mleap>=0.8.1',
      ],
      entry_points='''
          [console_scripts]
          mlflow=mlflow.cli:cli
      ''',
      zip_safe=False,
      author='Databricks',
      description='MLflow: An ML Workflow Tool',
      long_description=open('README.rst').read(),
      license='Apache License 2.0',
      classifiers=[
          'Intended Audience :: Developers',
          'Programming Language :: Python :: 2.7',
          'Programming Language :: Python :: 3.6',
      ],
      keywords='ml ai databricks',
      url='https://mlflow.org/'
  )
  
new_contents: import imp
  import os
  from setuptools import setup, find_packages
  
  version = imp.load_source(
      'mlflow.version', os.path.join('mlflow', 'version.py')).VERSION
  
  
  # Get a list of all files in the JS directory to include in our module
  def package_files(directory):
      paths = []
      for (path, directories, filenames) in os.walk(directory):
          for filename in filenames:
              paths.append(os.path.join('..', path, filename))
      return paths
  
  
  # Prints out a set of paths (relative to the mlflow/ directory) of files in mlflow/server/js/build
  # to include in the wheel, e.g. "../mlflow/server/js/build/index.html"
  js_files = package_files('mlflow/server/js/build')
  sagmaker_server_files = package_files("mlflow/sagemaker/container")
  
  setup(
      name='mlflow',
      version=version,
      packages=find_packages(exclude=['tests', 'tests.*']),
      package_data={"mlflow": js_files + sagmaker_server_files},
      install_requires=[
          'click>=6.7',
          'databricks-cli>=0.8.0',
          'requests>=2.17.3',
          'six>=1.10.0',
          'gunicorn',
          'Flask',
          'numpy',
          'pandas',
          'scipy',
          'scikit-learn',
          'python-dateutil',
          'protobuf>=3.6.0',
          'gitpython>=2.1.0',
          'pyyaml',
          'boto3>=1.7.12',
          'querystring_parser',
          'simplejson',
          'mleap>=0.8.1',
      ],
      entry_points='''
          [console_scripts]
          mlflow=mlflow.cli:cli
      ''',
      zip_safe=False,
      author='Databricks',
      description='MLflow: An ML Workflow Tool',
      long_description=open('README.rst').read(),
      license='Apache License 2.0',
      classifiers=[
          'Intended Audience :: Developers',
          'Programming Language :: Python :: 2.7',
          'Programming Language :: Python :: 3.6',
      ],
      keywords='ml ai databricks',
      url='https://mlflow.org/'
  )
  
subject: Add boto3 version dependency (#470)