setup.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Author: David Corre, IAP, corre@iap.fr

The setup script.
"""

from setuptools import setup, find_packages

with open("README.md") as readme_file:
    readme = readme_file.read()

with open("HISTORY.rst") as history_file:
    history = history_file.read()

requirements = [
    "numpy",
    "astropy",
    "matplotlib",
    "Sphinx",
    "twine",
    "h5py",
    "keras",
    "tensorflow",
    "opencv-python-headless",
    "multidict",
    "async-timeout",
    "attrs",
    "chardet",
]
setup_requirements = ["pytest-runner", "flake8", "bumpversion", "wheel", "twine"]

test_requirements = [
    "pytest",
    "pytest-cov",
    "pytest-console-scripts",
    "pytest-html",
    "watchdog",
]

setup(
    author="David Corre",
    author_email="david.corre.fr@gmail.com",
    classifiers=[
        "Development Status :: 4 - Beta",
        "Topic :: Scientific/Engineering :: Astronomy",
        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: MIT License",
        "Natural Language :: English",
        "Programming Language :: Python :: 3",
        "Programming Language :: Python :: 3.5",
        "Programming Language :: Python :: 3.6",
        "Programming Language :: Python :: 3.7",
        "Programming Language :: Python :: 3.8",
    ],
    description="CNN based tools to help identification of astronomical transients.",
    entry_points={
        "console_scripts": [
            "otrain-convert = otrain.cli.convert:main",
            "otrain-train = otrain.cli.train:main",
            "otrain-infer = otrain.cli.infer:main",
            "otrain-checkinfer = otrain.cli.checkinfer:main",
            "otrain-diagnostics = otrain.cli.diagnostic:main",
            "otrain-plot-results = otrain.cli.plot_results:main",
            "otrain-optimise-dataset-size = otrain.cli.optimise_dataset_size:main",
	    "otrain-grad-cam = otrain.cli.grad_cam:main",
        ],
    },
    install_requires=requirements,
    license="MIT license",
    long_description=readme,
    long_description_content_type="text/markdown",
    include_package_data=True,
    keywords=["transients", "detection pipeline", "astronomy", "CNN"],
    name="otrain",
    packages=find_packages(),
    setup_requires=setup_requirements,
    test_suite="tests",
    tests_require=test_requirements,
    # url='https://github.com/dcorre/otrain',
    version="0.1.0",
    zip_safe=False,
)