setup.py

from setuptools import setup, Extension
import numpy
import os

inc_dirs = []
inc_dirs.append(numpy.get_include())
lib_dirs = []
libs = []

# set commands to build the c assistance modules
extensions = [
    Extension(
        "fastkde.floodFillSearch",
        ["src/fastkde/floodFillSearch.pyx"],
        libraries=libs,
        library_dirs=lib_dirs,
        include_dirs=inc_dirs,
        runtime_library_dirs=lib_dirs,
    ),
    Extension(
        "fastkde.nufft",
        ["src/fastkde/nufft.pyx"],
        libraries=libs,
        library_dirs=lib_dirs,
        include_dirs=inc_dirs,
        runtime_library_dirs=lib_dirs,
    ),
]

# get revision information
with open("REVISION", "r") as fin:
    revision = fin.read().rstrip()

# read the long description
with open("README.md", "r") as fin:
    long_description = fin.read()

with open("requirements.txt", "r") as fin:
    install_requires = fin.read().split()

extras = {
    "test": ["pytest"],
    "dev": [],
}
extras["all"] = sum(extras.values(), [])
extras["dev"] += extras["test"]

setup(
    name="fastkde",
    packages=["fastkde"],
    version=revision,
    description="Tools for fast and robust univariate and multivariate kernel density estimation",
    long_description=long_description,
    long_description_content_type="text/markdown",
    author="Travis A. O'Brien",
    author_email="obrienta@iu.edu",
    url="https://github.com/LBL-EESA/fastkde",
    download_url="https://github.com/LBL-EESA/fastkde/archive/v{}.tar.gz".format(
        revision
    ),
    keywords=["statistics", "probability", "KDE", "kernel density estimation"],
    py_modules=[
        "fastkde.fastKDE",
        "fastkde.empiricalCharacteristicFunction",
        "fastkde.plot",
    ],
    classifiers=[],
    ext_modules=extensions,
    install_requires=install_requires,
    extras_require=extras,
    where="src",
)