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>=7.0',
 'cloudpickle',
 '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',
 'docker>=3.6.0',
 'entrypoints',
 'sqlparse',
 ],
 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/'
)