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setup.py
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setup.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from setuptools import setup, find_packages
def calculate_version():
initpy = open('tpot/_version.py').read().split('\n')
version = list(filter(lambda x: '__version__' in x, initpy))[0].split('\'')[1]
return version
package_version = calculate_version()
setup(
name='TPOT',
version=package_version,
author='Randal S. Olson',
author_email='rso@randalolson.com',
packages=find_packages(),
url='https://github.com/EpistasisLab/tpot',
license='GNU/LGPLv3',
entry_points={'console_scripts': ['tpot=tpot:main', ]},
description=('Tree-based Pipeline Optimization Tool'),
long_description='''
A Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.
Contact
=============
If you have any questions or comments about TPOT, please feel free to contact us via:
E-mail: ttle@pennmedicine.upenn.edu or weixuanf@pennmedicine.upenn.edu
or Twitter: https://twitter.com/trang1618 or https://twitter.com/WeixuanFu
This project is hosted at https://github.com/EpistasisLab/tpot
''',
zip_safe=True,
install_requires=['numpy>=1.16.3',
'scipy>=1.3.1',
'scikit-learn>=0.22.0',
'deap>=1.2',
'update_checker>=0.16',
'tqdm>=4.36.1',
'stopit>=1.1.1',
'pandas>=0.24.2',
'joblib>=0.13.2'],
extras_require={
'xgboost': ['xgboost==0.90'],
'skrebate': ['skrebate>=0.3.4'],
'mdr': ['scikit-mdr>=0.4.4'],
'dask': ['dask>=0.18.2',
'distributed>=1.22.1',
'dask-ml>=1.0.0'],
'torch': ['torch==1.3.1'],
},
classifiers=[
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Topic :: Scientific/Engineering :: Artificial Intelligence'
],
keywords=['pipeline optimization', 'hyperparameter optimization', 'data science', 'machine learning', 'genetic programming', 'evolutionary computation'],
)