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setup.py
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setup.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#TODO update this
from setuptools import setup, find_packages
def calculate_version():
initpy = open('tpot2/_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='TPOT2',
python_requires='>=3.10, <3.12', #for configspace compatibility
version=package_version,
author='Pedro Ribeiro',
packages=find_packages(),
url='https://github.com/EpistasisLab/tpot2',
license='GNU/LGPLv3', #TODO
entry_points={'console_scripts': ['tpot2=tpot2:main', ]},
description=('Tree-based Pipeline Optimization Tool'),
long_description='''
A Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.
''',
zip_safe=True,
install_requires=['numpy==1.26.4',
'scipy>=1.3.1',
'scikit-learn>=1.3.0',
'update_checker>=0.16',
'tqdm>=4.36.1',
'stopit>=1.1.1',
'pandas>=2.2.0',
'joblib>=1.1.1',
'xgboost>=1.7.0',
'matplotlib>=3.6.2',
'traitlets>=5.8.0',
'lightgbm>=3.3.3',
'optuna>=3.0.5',
'networkx>=3.0',
'dask>=2024.4.2',
'distributed>=2024.4.2',
'dask-expr>=1.0.12',
'dask-jobqueue>=0.8.5',
'func_timeout>=4.3.5',
'configspace>=1.1.1',
],
extras_require={
'skrebate': ['skrebate>=0.3.4'],
'mdr': ['scikit-mdr>=0.4.4'],
'sklearnex' : ['scikit-learn-intelex>=2023.2.1'],
'amltk' : ['amltk>=1.12.1'],
},
classifiers=[
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)',
'Programming Language :: Python :: 3.10',
'Topic :: Scientific/Engineering :: Artificial Intelligence'
],
keywords=['pipeline optimization', 'hyperparameter optimization', 'data science', 'machine learning', 'genetic programming', 'evolutionary computation'],
)