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setup.py
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setup.py
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# Copyright 2017-2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Placeholder docstring"""
from __future__ import absolute_import
import os
from glob import glob
import sys
from setuptools import setup, find_packages
def read(fname):
"""
Args:
fname:
"""
return open(os.path.join(os.path.dirname(__file__), fname)).read()
def read_version():
return read("VERSION").strip()
# Declare minimal set for installation
required_packages = [
"boto3>=1.10.44",
"numpy>=1.9.0",
"protobuf>=3.1",
"scipy>=0.19.0",
"protobuf3-to-dict>=0.1.5",
"smdebug-rulesconfig==0.1.2",
"importlib-metadata>=1.4.0",
"packaging>=20.0",
]
# Specific use case dependencies
extras = {
"analytics": ["pandas"],
"local": [
"urllib3>=1.21.1,<1.26,!=1.25.0,!=1.25.1",
"docker-compose>=1.25.2",
"PyYAML>=5.3, <6", # PyYAML version has to match docker-compose requirements
],
"tensorflow": ["tensorflow>=1.3.0"],
}
# Meta dependency groups
extras["all"] = [item for group in extras.values() for item in group]
# Tests specific dependencies (do not need to be included in 'all')
extras["test"] = (
[
extras["all"],
"tox==3.13.1",
"flake8",
"pytest==4.4.1",
"pytest-cov",
"pytest-rerunfailures",
"pytest-xdist",
"mock",
"contextlib2",
"awslogs",
"black==19.3b0 ; python_version >= '3.6'",
"stopit==1.1.2",
"apache-airflow==1.10.5",
"fabric>=2.0",
"requests>=2.20.0, <3",
],
)
# enum is introduced in Python 3.4. Installing enum back port
if sys.version_info < (3, 4):
required_packages.append("enum34>=1.1.6")
setup(
name="sagemaker",
version=read_version(),
description="Open source library for training and deploying models on Amazon SageMaker.",
packages=find_packages("src"),
package_dir={"": "src"},
py_modules=[os.path.splitext(os.path.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 :: 3.6",
],
install_requires=required_packages,
extras_require=extras,
entry_points={"console_scripts": ["sagemaker=sagemaker.cli.main:main"]},
include_package_data=True, # TODO-reinvent-2019 [knakad]: Remove after rule_configs is in PyPI
)