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setup.py
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setup.py
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"""A setuptools based setup module.
See:
https://packaging.python.org/en/latest/distributing.html
https://github.com/pypa/sampleproject
Built using this blog post as well:
https://hynek.me/articles/sharing-your-labor-of-love-pypi-quick-and-dirty/
https://tom-christie.github.io/articles/pypi/
http://stackoverflow.com/questions/11848030/how-include-static-files-to-setuptools-python-package
"""
# Always prefer setuptools over distutils
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='auto_ml',
# Versions should comply with PEP440. For a discussion on single-sourcing
# the version across setup.py and the project code, see
# https://packaging.python.org/en/latest/single_source_version.html
version='1.2.0',
description='Automated machine learning for production and analytics',
long_description=long_description,
# The project's main homepage.
url='https://github.com/ClimbsRocks/auto_ml',
# Author details
author='Preston Parry',
author_email='[email protected]',
# Choose your license
license='MIT',
# See https://pypi.python.org/pypi?%3Aaction=list_classifiers
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 4 - Beta',
# Indicate who your project is intended for
'Intended Audience :: Developers',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
# Pick your license as you wish (should match "license" above)
'License :: OSI Approved :: MIT License',
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 2',
# 'Programming Language :: Python :: 2.6',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
# 'Programming Language :: Python :: 3.3',
# 'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
],
# What does your project relate to?
keywords=['machine learning', 'data science', 'automated machine learning', 'regressor', 'regressors', 'regression', 'classification', 'classifiers', 'classifier', 'estimators', 'predictors', 'XGBoost', 'Random Forest', 'sklearn', 'scikit-learn', 'analytics', 'analysts', 'coefficients', 'feature importances'],
# You can just specify the packages manually here if your project is
# simple. Or you can use find_packages().
packages=['auto_ml'],
# Alternatively, if you want to distribute just a my_module.py, uncomment
# this:
# py_modules=["my_module"],
# List run-time dependencies here. These will be installed by pip when
# your project is installed. For an analysis of "install_requires" vs pip's
# requirements files see:
# https://packaging.python.org/en/latest/requirements.html
install_requires=['scikit-learn', 'xgboost', 'scipy'],
# List additional groups of dependencies here (e.g. development
# dependencies). You can install these using the following syntax,
# for example:
# $ pip install -e .[dev,test]
# extras_require={
# 'dev': ['check-manifest'],
# 'test': ['coverage'],
# },
# If there are data files included in your packages that need to be
# installed, specify them here. If using Python 2.6 or less, then these
# have to be included in MANIFEST.in as well.
# include_package_data=True,
# package_data={
# 'corpora': ['corpora/aggregatedCorpusCleanedAndFiltered.csv']
# }
# Although 'package_data' is the preferred approach, in some case you may
# need to place data files outside of your packages. See:
# http://docs.python.org/3.4/distutils/setupscript.html#installing-additional-files # noqa
# In this case, 'data_file' will be installed into '<sys.prefix>/my_data'
# data_files=[('my_data', ['data/data_file'])],
# To provide executable scripts, use entry points in preference to the
# "scripts" keyword. Entry points provide cross-platform support and allow
# pip to create the appropriate form of executable for the target platform.
# entry_points={
# 'console_scripts': [
# 'sample=sample:main',
# ],
# },
)