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setup.py
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setup.py
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"""Setup for the spectromer package."""
import os
import re
from setuptools import find_packages, setup
here = os.path.abspath(os.path.dirname(__file__))
# Get the long description from the relevant file
with open(os.path.join(here, "README.md"), encoding="utf8") as f:
long_description = f.read()
def read(*parts):
with open(os.path.join(here, *parts), "r", encoding="utf8") as fp:
return fp.read()
def find_version(*file_paths):
version_file = read(*file_paths)
version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M)
if version_match:
return version_match.group(1)
raise RuntimeError("Unable to find version string.")
__version__ = find_version("spectromer", "__version__.py")
test_deps = [
"pytest",
"pytest-cov",
"pytest-readme",
"scipy-stubs",
"pandas-stubs",
"types-tqdm",
"validate_version_code",
]
extras = {
"test": test_deps,
}
setup(
name="spectromer",
version=__version__,
description="ML utilities for natural products classification",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/LucaCappelletti94/spectromer",
author="LucaCappelletti94",
license="MIT",
include_package_data=True,
classifiers=[
"Development Status :: 3 - Alpha",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
],
packages=find_packages(exclude=["contrib", "docs", "tests*"]),
tests_require=test_deps,
python_requires=">=3.9",
install_requires=[
"downloaders",
"compress_json",
"numpy",
"scikit-learn",
"plot-keras-history",
"cache_decorator",
"pydot",
"keras",
"barplots>=1.2.0",
"silence_tensorflow",
"environments_utils>=1.0.14",
"scikit-fingerprints",
"extra-keras-metrics>=2.0.12",
"compress_pickle",
"typeguard",
"matchms",
"anytree",
],
extras_require=extras,
entry_points={
"console_scripts": [
"spectromer=spectromer.cli:main",
],
},
)