import setuptools import os def readme(): with open("README.md") as f: return f.read() def get_data(field): item = "" file_name = "_version.py" if field == "version" else "__init__.py" with open(os.path.join("benchmark", file_name)) as f: for line in f.readlines(): if line.startswith(f"__{field}__"): delim = '"' if '"' in line else "'" item = line.split(delim)[1] break else: raise RuntimeError(f"Unable to find {field} string.") return item def import_scripts(): result = [] names = os.listdir(os.path.join("benchmark", "scripts")) for name in names: result.append(os.path.join("benchmark", "scripts", name)) return result setuptools.setup( name="benchmark", version=get_data("version"), license=get_data("license"), description="Oblique decision tree with svm nodes", long_description=readme(), long_description_content_type="text/markdown", packages=setuptools.find_packages(), url="https://github.com/Doctorado-ML/benchmark", author=get_data("author"), author_email=get_data("author_email"), keywords="scikit-learn oblique-classifier oblique-decision-tree decision-\ tree svm svc", classifiers=[ "Development Status :: 4 - Beta", "License :: OSI Approved :: " + get_data("license"), "Programming Language :: Python :: 3.8", "Natural Language :: English", "Topic :: Scientific/Engineering :: Artificial Intelligence", "Intended Audience :: Science/Research", ], install_requires=[ "scikit-learn", "odte", "pandas", "mufs", "xlsxwriter", "tqdm", ], zip_safe=False, entry_points={ "console_scripts": [ "be_list=benchmark.scripts.be_list:main", "be_report=benchmark.scripts.be_report:main", "be_main=benchmark.scripts.be_main:main", "be_benchmark=benchmark.scripts.be_benchmark:main", "be_best=benchmark.scripts.be_best:main", "be_build_best=benchmark.scripts.be_build_best:main", "be_grid=benchmark.scripts.be_grid:main", "be_pair_check=benchmark.scripts.be_pair_check:main", "be_print_strees=benchmark.scripts.be_print_strees:main", "be_repara=benchmark.scripts.be_repara:main", "be_summary=benchmark.scripts.be_summary:main", ], }, )