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setup.py
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setup.py
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"""
# Min version : pip3 install -e .
# Full version (to be reduced) : pip3 install -e .["full"]
# Document version : pip3 install -e .["doc"]
"""
from setuptools import setup, find_packages
import re
with open('README.md', 'r') as fh:
long_description = fh.read()
_deps = [
"matplotlib>=3.3.4",
"scikit-learn>=1.4.1",
"owlready2>=0.40",
"torch>=1.7.1,<2.2.0",
"rdflib>=6.0.2",
"pandas>=1.5.0",
"sortedcontainers>=2.4.0", # AB: This is required
"deap>=1.3.1",
"flask>=1.1.2",
"httpx>=0.25.2",
"gradio>=4.11.0",
"tqdm>=4.64.0",
"transformers>=4.38.1",
"pytest>=7.2.2",
"owlapy==1.0.2",
"dicee>=0.1.2",
"ontosample>=0.2.2",
"sphinx>=7.2.6",
"sphinx-autoapi>=3.0.0",
"sphinx_rtd_theme>=2.0.0",
"sphinx-theme>=1.0",
"sphinxcontrib-plantuml>=0.27",
"plantuml-local-client>=1.2022.6",
"myst-parser>=2.0.0",
"flake8>=6.0.0",
"fastapi>=0.110.1",
"uvicorn>=0.29.0"]
deps = {b: a for a, b in (re.findall(r"^(([^!=<>~ ]+)(?:[!=<>~ ].*)?$)", x)[0] for x in _deps)}
def deps_list(*pkgs):
return [deps[pkg] for pkg in pkgs]
extras = dict()
extras["min"] = deps_list(
"matplotlib",
"torch",
"rdflib",
"pandas",
"sortedcontainers",
"owlready2",
"owlapy",
"flask", # Drill, NCES
"tqdm", "transformers", # NCES
"dicee", # Drill
"deap", # Evolearner
"fastapi",
"uvicorn")
extras["doc"] = (deps_list("sphinx",
"sphinx-autoapi",
"sphinx-theme",
"sphinx_rtd_theme",
"sphinxcontrib-plantuml",
"plantuml-local-client", "myst-parser"))
extras["full"] = (extras["min"] + deps_list("httpx", "pytest", "gradio", "ontosample"))
setup(
name="ontolearn",
description="Ontolearn is an open-source software library for structured machine learning in Python. Ontolearn includes modules for processing knowledge bases, inductive logic programming and ontology engineering.",
version="0.7.1",
packages=find_packages(),
install_requires=extras["min"],
extras_require=extras,
author='Caglar Demir',
author_email='caglardemir8@gmail.com',
url='https://github.com/dice-group/Ontolearn',
classifiers=[
"Programming Language :: Python :: 3.10",
"License :: OSI Approved :: MIT License",
"Topic :: Scientific/Engineering :: Artificial Intelligence"],
python_requires='>=3.10.13',
entry_points={"console_scripts": ["ontolearn-webservice=ontolearn.scripts.run:main"]},
long_description=long_description,
long_description_content_type="text/markdown",
)