setup.py

"""
The build/compilations setup

>> pip install -r requirements.txt
>> python setup.py install
"""
import pip
import logging
import pkg_resources

try:
    from setuptools import setup, find_packages
except ImportError:
    from distutils.core import setup

def _parse_requirements(file_path):
    pip_ver = pkg_resources.get_distribution('pip').version
    pip_version = list(map(int, pip_ver.split('.')[:2]))
    if pip_version >= [6, 0]:
        raw = pip.req.parse_requirements(file_path,
                                         session=pip.download.PipSession())
    else:
        raw = pip.req.parse_requirements(file_path)
    return [str(i.req) for i in raw]

with open("README.md", "r") as fh:
    long_description = fh.read()
    
# parse_requirements() returns generator of pip.req.InstallRequirement objects
try:
    install_reqs = _parse_requirements("requirements.txt")
except Exception:
    logging.warning('Fail load requirements file, so using default ones.')
    install_reqs = []

setup(
    name='deeptetrad',
    version='1.0.1.0',
    url='https://github.com/abysslover/deeptetrad',
    author='Eun-Cheon Lim',
    author_email='abysslover@gmail.com',
    license='GPL3.0',
    description='DeepTetrad: a deep learning model for fluorescent pollen-tetrad image analysis',
    package_dir={'': '.', 'deeptetrad': './src/deeptetrad', 'mrcnn': './src/mrcnn', 'imgaug': './src/imgaug'},
    packages=find_packages(where="./src"),
    package_data={'deeptetrad': ['src/deeptetrad/pollen/*/*', 'src/deeptetrad/tetrad/*/*'], 'imgaug': ['src/imgaug/*.ttf', 'src/imgaug/*.json', 'src/imgaug/*.png', 'src/imgaug/*.jpg']},
    install_requires=install_reqs,
    include_package_data=True,
    python_requires='>=3.4',
    entry_points = {
        'console_scripts': ['deeptetrad=deeptetrad.entry:main'],
    },
    long_description=long_description,
    classifiers=[
        "Development Status :: 5 - Production/Stable",
        "Environment :: Console",
        "Intended Audience :: Developers",
        "Intended Audience :: Information Technology",
        "Intended Audience :: Education",
        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
        "Natural Language :: English",
        "Operating System :: OS Independent",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Scientific/Engineering :: Image Recognition",
        "Topic :: Scientific/Engineering :: Visualization",
#         "Topic :: Scientific/Engineering :: Image Segmentation",
        "Programming Language :: Python :: 3",
    ],
    keywords="tetrad crossover interference tensorflow keras",
)