def setup_package():
src_path = os.path.dirname(os.path.abspath(sys.argv[0]))
old_path = os.getcwd()
#os.chdir(src_path)
sys.path.insert(0, src_path)
# Rewrite the version file everytime
#write_version_py(src_path+'/slycot/version.py')
gitrevision = git_version(src_path)
metadata = dict(
name='slycot',
version=VERSION,
maintainer="Slycot developers",
maintainer_email="*****@*****.**",
description=DOCLINES[0],
long_description="\n".join(DOCLINES[2:]),
url='https://github.com/python-control/Slycot',
author='Enrico Avventi et al.',
license='GPLv2',
classifiers=[_f for _f in CLASSIFIERS.split('\n') if _f],
platforms=["Windows", "Linux", "Solaris", "Mac OS-X", "Unix"],
cmdclass={"sdist": sdist_checked},
cmake_args=[ '-DSLYCOT_VERSION:STRING=' + VERSION,
'-DGIT_REVISION:STRING=' + gitrevision,
'-DISRELEASE:STRING=' + str(ISRELEASED),
'-DFULL_VERSION=' + VERSION + '.git' + gitrevision[:7] ],
#cmake_source_dir=src_path,
zip_safe=False,
)
# Windows builds use Flang.
# Flang detection and configuration is not automatic yet; the CMAKE
# settings below are to circumvent that; when scikit-build and cmake
# tools have improved, most of this might be removed?
import platform
if platform.system() == 'Windows':
pbase = r'/'.join(sys.executable.split(os.sep)[:-1])
metadata['cmake_args'].extend([
'-GNMake Makefiles',
'-DF2PY_EXECUTABLE=' + pbase + r'/Scripts/f2py.bat',
'-DCMAKE_Fortran_COMPILER=' + pbase + r'/Library/bin/flang.exe',
'-DCMAKE_Fortran_COMPILER_ID=Flang',
'-DCMAKE_C_COMPILER_ID=MSVC',
'-DCMAKE_C_COMPILER_VERSION=19.0.0',
'-DNumPy_INCLUDE_DIR=' + pbase + r'/Include',
'-DCMAKE_VERBOSE_MAKEFILE:BOOL=ON' ])
try:
setup(**metadata)
finally:
del sys.path[0]
#os.chdir(old_path)
return
def main():
os.chdir(os.path.dirname(os.path.abspath(__file__)))
CI_BUILD = os.environ.get("CI_BUILD", "False")
is_CI_build = True if CI_BUILD == "1" else False
cmake_source_dir = "opencv"
minimum_supported_numpy = "1.13.1"
build_contrib = get_build_env_var_by_name("contrib")
build_headless = get_build_env_var_by_name("headless")
if sys.version_info[:2] >= (3, 6):
minimum_supported_numpy = "1.13.3"
if sys.version_info[:2] >= (3, 7):
minimum_supported_numpy = "1.14.5"
if sys.version_info[:2] >= (3, 8):
minimum_supported_numpy = "1.17.3"
numpy_version = "numpy>=%s" % minimum_supported_numpy
python_version = cmaker.CMaker.get_python_version()
python_lib_path = cmaker.CMaker.get_python_library(python_version).replace(
"\\", "/"
)
python_include_dir = cmaker.CMaker.get_python_include_dir(python_version).replace(
"\\", "/"
)
if os.path.exists(".git"):
import pip._internal.vcs.git as git
g = git.Git() # NOTE: pip API's are internal, this has to be refactored
g.run_command(["submodule", "sync"])
g.run_command(
["submodule", "update", "--init", "--recursive", cmake_source_dir]
)
if build_contrib:
g.run_command(
["submodule", "update", "--init", "--recursive", "opencv_contrib"]
)
package_version, build_contrib, build_headless = get_and_set_info(
build_contrib, build_headless, is_CI_build
)
# https://stackoverflow.com/questions/1405913/python-32bit-or-64bit-mode
x64 = sys.maxsize > 2 ** 32
package_name = "opencv-python"
if build_contrib and not build_headless:
package_name = "opencv-contrib-python"
if build_contrib and build_headless:
package_name = "opencv-contrib-python-headless"
if build_headless and not build_contrib:
package_name = "opencv-python-headless"
long_description = io.open("README.md", encoding="utf-8").read()
packages = ["cv2", "cv2.data"]
package_data = {
"cv2": ["*%s" % sysconfig.get_config_vars().get("SO"), "version.py"]
+ (["*.dll"] if os.name == "nt" else [])
+ ["LICENSE.txt", "LICENSE-3RD-PARTY.txt"],
"cv2.data": ["*.xml"],
}
# Files from CMake output to copy to package.
# Path regexes with forward slashes relative to CMake install dir.
rearrange_cmake_output_data = {
"cv2": (
[r"bin/opencv_videoio_ffmpeg\d{3}%s\.dll" % ("_64" if x64 else "")]
if os.name == "nt"
else []
)
+
# In Windows, in python/X.Y/<arch>/; in Linux, in just python/X.Y/.
# Naming conventions vary so widely between versions and OSes
# had to give up on checking them.
[
"python/cv2[^/]*%(ext)s"
% {"ext": re.escape(sysconfig.get_config_var("EXT_SUFFIX"))}
],
"cv2.data": [ # OPENCV_OTHER_INSTALL_PATH
("etc" if os.name == "nt" else "share/opencv4") + r"/haarcascades/.*\.xml"
],
}
# Files in sourcetree outside package dir that should be copied to package.
# Raw paths relative to sourcetree root.
files_outside_package_dir = {"cv2": ["LICENSE.txt", "LICENSE-3RD-PARTY.txt"]}
ci_cmake_generator = (
["-G", "Visual Studio 14" + (" Win64" if x64 else "")]
if os.name == "nt"
else ["-G", "Unix Makefiles"]
)
cmake_args = (
(ci_cmake_generator if is_CI_build else [])
+ [
# skbuild inserts PYTHON_* vars. That doesn't satisfy opencv build scripts in case of Py3
"-DPYTHON3_EXECUTABLE=%s" % sys.executable,
"-DPYTHON3_INCLUDE_DIR=%s" % python_include_dir,
"-DPYTHON3_LIBRARY=%s" % python_lib_path,
"-DBUILD_opencv_python3=ON",
"-DBUILD_opencv_python2=OFF",
# When off, adds __init__.py and a few more helper .py's. We use our own helper files with a different structure.
"-DOPENCV_SKIP_PYTHON_LOADER=ON",
# Relative dir to install the built module to in the build tree.
# The default is generated from sysconfig, we'd rather have a constant for simplicity
"-DOPENCV_PYTHON3_INSTALL_PATH=python",
# Otherwise, opencv scripts would want to install `.pyd' right into site-packages,
# and skbuild bails out on seeing that
"-DINSTALL_CREATE_DISTRIB=ON",
# See opencv/CMakeLists.txt for options and defaults
"-DBUILD_opencv_apps=OFF",
"-DBUILD_SHARED_LIBS=OFF",
"-DBUILD_TESTS=OFF",
"-DBUILD_PERF_TESTS=OFF",
"-DBUILD_DOCS=OFF",
]
+ (
["-DOPENCV_EXTRA_MODULES_PATH=" + os.path.abspath("opencv_contrib/modules")]
if build_contrib
else []
)
)
if build_headless:
# it seems that cocoa cannot be disabled so on macOS the package is not truly headless
cmake_args.append("-DWITH_WIN32UI=OFF")
cmake_args.append("-DWITH_QT=OFF")
cmake_args.append("-DWITH_GTK=OFF")
if is_CI_build:
cmake_args.append(
"-DWITH_MSMF=OFF"
) # see: https://github.com/skvark/opencv-python/issues/263
if sys.platform.startswith("linux") and not x64 and "bdist_wheel" in sys.argv:
subprocess.check_call("patch -p0 < patches/patchOpenEXR", shell=True)
# OS-specific components during CI builds
if is_CI_build:
if sys.platform.startswith("linux") and not build_headless:
cmake_args.append("-DWITH_QT=4")
if sys.platform == "darwin" and not build_headless:
if "bdist_wheel" in sys.argv:
cmake_args.append("-DWITH_QT=5")
rearrange_cmake_output_data["cv2.qt.plugins.platforms"] = [
(r"lib/qt/plugins/platforms/libqcocoa\.dylib")
]
subprocess.check_call("patch -p1 < patches/patchQtPlugins", shell=True)
if sys.platform.startswith("linux"):
cmake_args.append("-DWITH_V4L=ON")
cmake_args.append("-DWITH_LAPACK=ON")
cmake_args.append("-DENABLE_PRECOMPILED_HEADERS=OFF")
# https://github.com/scikit-build/scikit-build/issues/479
if "CMAKE_ARGS" in os.environ:
import shlex
cmake_args.extend(shlex.split(os.environ["CMAKE_ARGS"]))
del shlex
# works via side effect
RearrangeCMakeOutput(
rearrange_cmake_output_data, files_outside_package_dir, package_data.keys()
)
skbuild.setup(
name=package_name,
version=package_version,
url="https://github.com/skvark/opencv-python",
license="MIT",
description="Wrapper package for OpenCV python bindings.",
long_description=long_description,
long_description_content_type="text/markdown",
packages=packages,
package_data=package_data,
maintainer="Olli-Pekka Heinisuo",
ext_modules=EmptyListWithLength(),
install_requires=numpy_version,
classifiers=[
"Development Status :: 5 - Production/Stable",
"Environment :: Console",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Information Technology",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Operating System :: MacOS",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: C++",
"Programming Language :: Python :: Implementation :: CPython",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Image Recognition",
"Topic :: Software Development",
],
cmake_args=cmake_args,
cmake_source_dir=cmake_source_dir,
)
setup(
name='itk-skullstripping',
version='0.0.1',
author='Stefan Bauer',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKSkullStrip',
description=r'Automatic skull-stripping for neuroimage analysis',
long_description='ITKSkullStrip provides a class to perform automatic'
'skull-stripping for neuroimage analysis.\n'
'Please refer to:'
'Bauer S., Fejes T., Reyes M.,'
'“Skull-Stripping Filter for ITK”, '
'Insight Journal, http://hdl.handle.net/10380/3353, 2012.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit neuroimaging neuroimaging-analysis',
url=r'https://github.com/InsightSoftwareConsortium/ITKSkullStrip',
install_requires=[
r'itk'
]
)
from skbuild import setup
setup(
name="hello",
version="1.2.3",
description="a minimal example package (CMakeLists not in top-level dir)",
author='The scikit-build team',
license="MIT",
packages=['hello'],
cmake_source_dir='hello'
)
setup(
name='itk-morphologicalcontourinterpolation',
version='1.0.0',
author='Dženan Zukić',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/KitwareMedical/ITKMorphologicalContourInterpolation',
description=r'Interslice interpolations of label images based on their morphology .',
long_description='ITK is an open-source, cross-platform library that '
'provides developers with an extensive suite of software '
'tools for image analysis. This package implements morphological contour interpolation. '
'For more information, see '
'Zukić D., Vicory J., McCormick M., Wisse L., Gerig G., Yushkevich P., Aylward S. '
'"ND Morphological Contour Interpolation" '
'http://insight-journal.org/browse/publication/977 '
'http://hdl.handle.net/10380/3563 ',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit',
url=r'https://itk.org/',
install_requires=[
r'itk'
]
)
def main():
os.chdir(os.path.dirname(os.path.abspath(__file__)))
# These are neede for source fetching
cmake_source_dir = "opencv"
build_contrib = get_build_env_var_by_name("contrib")
# headless flag to skip GUI deps if needed
build_headless = get_build_env_var_by_name("headless")
# Only import 3rd-party modules after having installed all the build dependencies:
# any of them, or their dependencies, can be updated during that process,
# leading to version conflicts
minimum_supported_numpy = "1.11.1"
if sys.version_info[:2] >= (3, 6):
minimum_supported_numpy = "1.11.3"
if sys.version_info[:2] >= (3, 7):
minimum_supported_numpy = "1.14.5"
numpy_version = get_or_install("numpy", minimum_supported_numpy)
get_or_install("scikit-build")
import skbuild
if os.path.exists('.git'):
import pip._internal.vcs.git as git
g = git.Git() # NOTE: pip API's are internal, this has to be refactored
g.run_command(["submodule", "sync"])
g.run_command(["submodule", "update", "--init", "--recursive", cmake_source_dir])
if build_contrib:
g.run_command(["submodule", "update", "--init", "--recursive", "opencv_contrib"])
# https://stackoverflow.com/questions/1405913/python-32bit-or-64bit-mode
x64 = sys.maxsize > 2**32
package_name = "opencv-python"
if build_contrib and not build_headless:
package_name = "opencv-contrib-python"
if build_contrib and build_headless:
package_name = "opencv-contrib-python-headless"
if build_headless and not build_contrib:
package_name = "opencv-python-headless"
long_description = io.open('README.md', encoding="utf-8").read()
package_version = get_opencv_version()
packages = ['cv2', 'cv2.data']
package_data = {
'cv2':
['*%s' % sysconfig.get_config_var('SO')] +
(['*.dll'] if os.name == 'nt' else []) +
["LICENSE.txt", "LICENSE-3RD-PARTY.txt"],
'cv2.data':
["*.xml"]
}
# Files from CMake output to copy to package.
# Path regexes with forward slashes relative to CMake install dir.
rearrange_cmake_output_data = {
'cv2': ([r'bin/opencv_ffmpeg\d{3}%s\.dll' % ('_64' if x64 else '')] if os.name == 'nt' else []) +
# In Windows, in python/X.Y/<arch>/; in Linux, in just python/X.Y/.
# Naming conventions vary so widely between versions and OSes
# had to give up on checking them.
['python/cv2[^/]*%(ext)s' % {'ext': re.escape(sysconfig.get_config_var('SO'))}],
'cv2.data': [ # OPENCV_OTHER_INSTALL_PATH
('etc' if os.name == 'nt' else 'share/opencv4') +
r'/haarcascades/.*\.xml'
]
}
# Files in sourcetree outside package dir that should be copied to package.
# Raw paths relative to sourcetree root.
files_outside_package_dir = {
'cv2': ['LICENSE.txt', 'LICENSE-3RD-PARTY.txt']
}
cmake_args = ([
"-G", "Visual Studio 14" + (" Win64" if x64 else '')
] if os.name == 'nt' else [
"-G", "Unix Makefiles" # don't make CMake try (and fail) Ninja first
]) + [
# skbuild inserts PYTHON_* vars. That doesn't satisfy opencv build scripts in case of Py3
"-DPYTHON%d_EXECUTABLE=%s" % (sys.version_info[0], sys.executable),
"-DBUILD_opencv_python%d=ON" % sys.version_info[0],
# When off, adds __init__.py and a few more helper .py's. We use our own helper files with a different structure.
"-DOPENCV_SKIP_PYTHON_LOADER=ON",
# Relative dir to install the built module to in the build tree.
# The default is generated from sysconfig, we'd rather have a constant for simplicity
"-DOPENCV_PYTHON%d_INSTALL_PATH=python" % sys.version_info[0],
# Otherwise, opencv scripts would want to install `.pyd' right into site-packages,
# and skbuild bails out on seeing that
"-DINSTALL_CREATE_DISTRIB=ON",
# See opencv/CMakeLists.txt for options and defaults
"-DBUILD_opencv_apps=OFF",
"-DBUILD_SHARED_LIBS=OFF",
"-DBUILD_TESTS=OFF",
"-DBUILD_PERF_TESTS=OFF",
"-DBUILD_DOCS=OFF"
] + (["-DOPENCV_EXTRA_MODULES_PATH=" + os.path.abspath("opencv_contrib/modules")] if build_contrib else [])
# OS-specific components
if (sys.platform == 'darwin' or sys.platform.startswith('linux')) and not build_headless:
cmake_args.append("-DWITH_QT=4")
if build_headless:
# it seems that cocoa cannot be disabled so on macOS the package is not truly headless
cmake_args.append("-DWITH_WIN32UI=OFF")
cmake_args.append("-DWITH_QT=OFF")
if sys.platform.startswith('linux'):
cmake_args.append("-DWITH_V4L=ON")
cmake_args.append("-DENABLE_PRECOMPILED_HEADERS=OFF")
if all(v in os.environ for v in ('JPEG_INCLUDE_DIR', 'JPEG_LIBRARY')):
cmake_args += [
"-DBUILD_JPEG=OFF",
"-DJPEG_INCLUDE_DIR=%s" % os.environ['JPEG_INCLUDE_DIR'],
"-DJPEG_LIBRARY=%s" % os.environ['JPEG_LIBRARY']
]
# Fixes for macOS builds
if sys.platform == 'darwin':
cmake_args.append("-DWITH_LAPACK=OFF") # Some OSX LAPACK fns are incompatible, see
# https://github.com/skvark/opencv-python/issues/21
cmake_args.append("-DCMAKE_CXX_FLAGS=-stdlib=libc++")
cmake_args.append("-DCMAKE_OSX_DEPLOYMENT_TARGET:STRING=10.7")
if sys.platform.startswith('linux'):
cmake_args.append("-DWITH_IPP=OFF") # tests fail with IPP compiled with
# devtoolset-2 GCC 4.8.2 or vanilla GCC 4.9.4
# see https://github.com/skvark/opencv-python/issues/138
if sys.platform.startswith('linux') and not x64:
cmake_args.append("-DCMAKE_CXX_FLAGS=-U__STRICT_ANSI__")
# ABI config variables are introduced in PEP 425
if sys.version_info[:2] < (3, 2):
import warnings
warnings.filterwarnings('ignore', r"Config variable '[^']+' is unset, "
r"Python ABI tag may be incorrect",
category=RuntimeWarning)
del warnings
# works via side effect
RearrangeCMakeOutput(rearrange_cmake_output_data,
files_outside_package_dir,
package_data.keys())
skbuild.setup(
name=package_name,
version=package_version,
url='https://github.com/skvark/opencv-python',
license='MIT',
description='Wrapper package for OpenCV python bindings.',
long_description=long_description,
long_description_content_type="text/markdown",
packages=packages,
package_data=package_data,
maintainer="Olli-Pekka Heinisuo",
include_package_data=True,
ext_modules=EmptyListWithLength(),
install_requires="numpy>=%s" % numpy_version,
classifiers=[
'Development Status :: 5 - Production/Stable',
'Environment :: Console',
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Information Technology',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: MIT License',
'Operating System :: MacOS',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Operating System :: Unix',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: C++',
'Programming Language :: Python :: Implementation :: CPython',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Image Recognition',
'Topic :: Software Development',
],
cmake_args=cmake_args,
cmake_source_dir=cmake_source_dir,
)
from skbuild import setup
setup(
name="hello-cython",
version="1.2.3",
description="a minimal example package (cython version)",
author='The scikit-build team',
license="MIT",
packages=['hello_cython'],
# The extra '/' was *only* added to check that scikit-build can handle it.
package_dir={'hello_cython': 'hello/'},
)
setup(
name='SimpleITK',
version='1.1.0',
author='Insight Software Consortium',
author_email='*****@*****.**',
packages=['SimpleITK'],
package_dir={'SimpleITK': 'SimpleITK'},
download_url=
r'https://www.itk.org/SimpleITKDoxygen/html/PyDownloadPage.html',
description=
r'SimpleITK is a simplified interface to the Insight Toolkit (ITK) for image registration and segmentation',
long_description=
r'SimpleITK provides an abstraction layer to ITK that enables developers \
and users to access the powerful features of the InsightToolkit in an easy \
to use manner for biomedical image analysis.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='SimpleITK ITK InsightToolkit segmentation registration',
url=r'https://simpleitk.org/',
install_requires=[],
zip_safe=False)
def main():
os.chdir(os.path.dirname(os.path.abspath(__file__)))
# These are neede for source fetching
cmake_source_dir = "opencv"
build_contrib = get_build_env_var_by_name("contrib")
# headless flag to skip GUI deps if needed
build_headless = get_build_env_var_by_name("headless")
# Only import 3rd-party modules after having installed all the build dependencies:
# any of them, or their dependencies, can be updated during that process,
# leading to version conflicts
numpy_version = get_or_install(
"numpy", "1.11.3" if sys.version_info[:2] >= (3, 6) else "1.11.1")
get_or_install("scikit-build")
import skbuild
if os.path.exists('.git'):
import pip._internal.vcs.git as git
g = git.Git(
) # NOTE: pip API's are internal, this has to be refactored
g.run_command(["submodule", "sync"])
g.run_command(
["submodule", "update", "--init", "--recursive", cmake_source_dir])
if build_contrib:
g.run_command([
"submodule", "update", "--init", "--recursive",
"opencv_contrib"
])
# https://stackoverflow.com/questions/1405913/python-32bit-or-64bit-mode
x64 = sys.maxsize > 2**32
package_name = "opencv-python"
if build_contrib and not build_headless:
package_name = "opencv-contrib-python"
if build_contrib and build_headless:
package_name = "opencv-contrib-python-headless"
if build_headless and not build_contrib:
package_name = "opencv-python-headless"
long_description = io.open('README.md', encoding="utf-8").read()
package_version = get_opencv_version()
packages = ['cv2', 'cv2.data']
package_data = {
'cv2': ['*%s' % sysconfig.get_config_var('SO')] +
(['*.dll'] if os.name == 'nt' else []) +
["LICENSE.txt", "LICENSE-3RD-PARTY.txt"],
'cv2.data': ["*.xml"]
}
# Files from CMake output to copy to package.
# Path regexes with forward slashes relative to CMake install dir.
rearrange_cmake_output_data = {
'cv2': ([r'bin/opencv_ffmpeg\d{3}%s\.dll' %
('_64' if x64 else '')] if os.name == 'nt' else []) +
# In Windows, in python/X.Y/<arch>/; in Linux, in just python/X.Y/.
# Naming conventions vary so widely between versions and OSes
# had to give up on checking them.
[
'python/([^/]+/){1,2}cv2[^/]*%(ext)s' % {
'ext': re.escape(sysconfig.get_config_var('SO'))
}
],
'cv2.data': [ # OPENCV_OTHER_INSTALL_PATH
('etc' if os.name == 'nt' else 'share/OpenCV') +
r'/haarcascades/.*\.xml'
]
}
# Files in sourcetree outside package dir that should be copied to package.
# Raw paths relative to sourcetree root.
files_outside_package_dir = {
'cv2': ['LICENSE.txt', 'LICENSE-3RD-PARTY.txt']
}
cmake_args = ([
"-G", "Visual Studio 14" + (" Win64" if x64 else '')
] if os.name == 'nt' else [
"-G",
"Unix Makefiles" # don't make CMake try (and fail) Ninja first
]) + [
# skbuild inserts PYTHON_* vars. That doesn't satisfy opencv build scripts in case of Py3
"-DPYTHON%d_EXECUTABLE=%s" % (sys.version_info[0], sys.executable),
"-DBUILD_opencv_python%d=ON" % sys.version_info[0],
# Otherwise, opencv scripts would want to install `.pyd' right into site-packages,
# and skbuild bails out on seeing that
"-DINSTALL_CREATE_DISTRIB=ON",
# See opencv/CMakeLists.txt for options and defaults
"-DBUILD_opencv_apps=OFF",
"-DBUILD_SHARED_LIBS=OFF",
"-DBUILD_TESTS=OFF",
"-DBUILD_PERF_TESTS=OFF",
"-DBUILD_DOCS=OFF"
] + ([
"-DOPENCV_EXTRA_MODULES_PATH=" +
os.path.abspath("opencv_contrib/modules")
] if build_contrib else [])
# OS-specific components
if (sys.platform == 'darwin'
or sys.platform.startswith('linux')) and not build_headless:
cmake_args.append("-DWITH_QT=4")
if build_headless:
# it seems that cocoa cannot be disabled so on macOS the package is not truly headless
cmake_args.append("-DWITH_WIN32UI=OFF")
cmake_args.append("-DWITH_QT=OFF")
if sys.platform.startswith('linux'):
cmake_args.append("-DWITH_V4L=ON")
cmake_args.append("-DENABLE_PRECOMPILED_HEADERS=OFF")
if all(v in os.environ for v in ('JPEG_INCLUDE_DIR', 'JPEG_LIBRARY')):
cmake_args += [
"-DBUILD_JPEG=OFF",
"-DJPEG_INCLUDE_DIR=%s" % os.environ['JPEG_INCLUDE_DIR'],
"-DJPEG_LIBRARY=%s" % os.environ['JPEG_LIBRARY']
]
# Turn off broken components
if sys.platform == 'darwin':
cmake_args.append(
"-DWITH_LAPACK=OFF") # Some OSX LAPACK fns are incompatible, see
# https://github.com/skvark/opencv-python/issues/21
if sys.platform.startswith('linux'):
cmake_args.append(
"-DWITH_IPP=OFF") # https://github.com/opencv/opencv/issues/10411
# ABI config variables are introduced in PEP 425
if sys.version_info[:2] < (3, 2):
import warnings
warnings.filterwarnings('ignore', r"Config variable '[^']+' is unset, "
r"Python ABI tag may be incorrect",
category=RuntimeWarning)
del warnings
# works via side effect
RearrangeCMakeOutput(rearrange_cmake_output_data,
files_outside_package_dir, package_data.keys())
skbuild.setup(
name=package_name,
version=package_version,
url='https://github.com/skvark/opencv-python',
license='MIT',
description='Wrapper package for OpenCV python bindings.',
long_description=long_description,
long_description_content_type="text/markdown",
packages=packages,
package_data=package_data,
maintainer="Olli-Pekka Heinisuo",
include_package_data=True,
ext_modules=EmptyListWithLength(),
install_requires="numpy>=%s" % numpy_version,
classifiers=[
'Development Status :: 5 - Production/Stable',
'Environment :: Console',
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Information Technology',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: MIT License',
'Operating System :: MacOS',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Operating System :: Unix',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: C++',
'Programming Language :: Python :: Implementation :: CPython',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Image Recognition',
'Topic :: Software Development',
],
cmake_args=cmake_args,
cmake_source_dir=cmake_source_dir,
)
setup(
name='itk-cleaver',
version='1.2.0',
author='SCI Institute',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/SCIInstitute/ITKCleaver',
description=
r'An ITK interface to the Cleaver multi-material tetrahedral meshing library',
long_description=
'Cleaver2 ( https://github.com/SCIInstitute/Cleaver2/releases) is a free multimaterial tetrahedral meshing tool developed by the NIH Center for Integrative Biomedical Computing at the University of Utah Scientific Computing and Imaging (SCI) Institute.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 4 - Beta", "Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit',
url=r'https://itk.org/',
install_requires=[r'itk>=5.3rc4'])
]
python_requires = '>=3.5, <3.10'
setup(name=package_info.__package_name__,
version=package_info.__version__,
description=package_info.__description__,
long_description=open('README.rst').read(),
author=package_info.__contact_names__,
author_email=package_info.__contact_emails__,
maintainer=package_info.__contact_names__,
maintainer_email=package_info.__contact_emails__,
url=package_info.__repository_url__,
download_url=package_info.__download_url__,
license=package_info.__license__,
ext_modules=[CMakeExtension('pyqubo')],
cmdclass=dict(build_ext=CMakeBuild, cpp_test=CppTest),
zip_safe=False,
packages=packages,
keywords=package_info.__keywords__,
install_requires=install_requires,
python_requires=python_requires,
classifiers=[
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'License :: OSI Approved :: Apache Software License',
])
from setuptools_scm import get_version
from skbuild import setup
project_name = "cppcolormap"
setup(
name=project_name,
description="Library with colormaps",
long_description="Library with colormaps",
keywords="colormap, plot, matplotlib",
version=get_version(),
license="MIT",
author="Tom de Geus",
author_email="*****@*****.**",
url=f"https://github.com/tdegeus/{project_name}",
packages=[f"{project_name}"],
package_dir={"": "python"},
cmake_install_dir=f"python/{project_name}",
cmake_minimum_required_version="3.13...3.21",
)
setup(name='itk-labelerodedilate',
version='1.1.1',
author='Richard Beare',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=
r'https://github.com/InsightSoftwareConsortium/ITKLabelErodeDilate',
description=
r'An ITK module for erode and dilate operations on label images',
long_description=
'itk-labelerodedilate provides classes for morphological math '
'erode and dilate operations on label images.\n'
'Please refer to:\n'
'Beare, R. and Jackway, P. '
'"Parallel Algorithms via Scaled Paraboloid Structuring '
'Functions for Spatially-Variant and Label-Set Dilations '
'and Erosions", '
'2011 International Conference on Digital Image Computing '
'Techniques and Applications (DICTA). 180--185. 2011. IEEE.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 4 - Beta", "Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit Math-morphology Label-images',
url=r'https://github.com/InsightSoftwareConsortium/ITKLabelErodeDilate',
install_requires=[r'itk>=5.1.2'])
setup(
name='itk-bonemorphometry',
version='1.1.1',
author='Jean-Baptiste Vimort',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKBoneMorphometry',
description=r'An ITK module to compute bone morphometry features and feature maps',
long_description='ITKBoneMorphometry provides bone analysis filters that '
'compute features from N-dimensional images that '
'represent the internal architecture of bone.\n'
'Please refer to:'
'Vimort J., McCormick M., Paniagua B.,'
'“Computing Bone Morphometric Feature Maps from 3-Dimensional Images”, '
'Insight Journal, January-December 2017, http://hdl.handle.net/10380/3588.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit bones morphometry',
url=r'https://github.com/InsightSoftwareConsortium/ITKBoneMorphometry',
install_requires=[
r'itk>=5.0b01'
]
)
setup(
name='lesionsizingtoolkit',
version='0.0.1',
author='Xiao Xiao Liu',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/LesionSizingToolkit',
description=r'A generic and extensible ITK module for lesion segmentation',
long_description='lesionsizingtoolkit provides a generic, modular, and '
'extensible architecture for lesion sizing algorithms '
'in medical images as well as a reference algorithm for '
'lung solid lesion segmentation in CT images.\n'
'Please refer to:\n'
'Liu X., Helba B., Krishnan K., Reynolds P., McCormick M., Turner W., Ibáñez L., Yankelevitz D., Avila R., '
'"Fostering Open Science in Lung Cancer Lesion Sizing with ITK module LSTK", '
'Insight Journal, January-December 2012, http://hdl.handle.net/10380/3369.',
classifiers=[
"License :: OSI Approved :: BSD 2-Clause \"Simplified\" License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='BSD',
keywords='ITK InsightToolkit',
url=r'https://github.com/InsightSoftwareConsortium/LesionSizingToolkit',
install_requires=[
r'itk'
]
)
setup(
name='itk-ultrasound',
version='0.2.2',
author='Matthew McCormick',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/KitwareMedical/ITKUltrasound',
description=(r'Filters for use with the Insight Toolkit (ITK)'
' that may be particularly useful for the reconstruction and'
' analysis of ultrasound images.'),
long_description=
(r'This package contains filters for use with the Insight Toolkit'
' (ITK) for the reconstruction and analysis of ultrasound images. This includes'
' B-mode image generation, scan conversion, strain imaging, and '
' ultrasound spectroscopy.'),
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 4 - Beta", "Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit ultrasound imaging',
url=r'http://www.insight-journal.org/browse/publication/722',
install_requires=[r'itk>=5.0b01'])
setup(
name='itk-strain',
version='0.1.0',
author='Matthew M. McCormick',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKStrain',
description=r'ITK filters to estimate a strain tensor field from a displacement field or a spatial transformation',
long_description='itk-strain provides N-dimensional computational '
'framework of strain tensor images in the Insight '
'Toolkit. The filters provided can compute a strain '
'tensor image from a displacement field image and a '
'strain tensor image from a general spatial transform. '
'In both cases, infinitesimal, Green-Lagrangian, or '
'Eulerian-Almansi strain can be generated.\n'
'Please refer to:\n'
'M. McCormick, "N-Dimensional Computation of Strain Tensor Images in the Insight Toolkit.", '
'Insight Journal, January-December 2017, http://hdl.handle.net/10380/3573',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK Strain Tensor Displacement Field',
url=r'https://github.com/InsightSoftwareConsortium/ITKStrain',
install_requires=[
r'itk'
]
)
from skbuild import setup
import os, io
this_directory = os.path.abspath(os.path.dirname(__file__))
with io.open(os.path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
if __name__ == '__main__':
setup(
name='py_slvs',
version='1.0.1',
packages=['py_slvs'],
license='Gnu General Public License 3.0',
author='Zheng, Lei',
author_email='*****@*****.**',
cmake_args=['-DENABLE_GUI:BOOL=OFF','-DBUILD_PYTHON:BOOL=ON'],
cmake_source_dir='slvs',
url='https://github.com/realthunder/slvs_py',
description='Python binding of SOLVESPACE geometry constraint solver',
long_description=long_description,
long_description_content_type='text/markdown'
)
from setuptools import Extension
from skbuild import setup
setup(
name="hello",
version="1.2.3",
description="a minimal example package",
author='The scikit-build team',
license="MIT",
packages=['hello'],
ext_modules=[
Extension(
'hello._hello_ext',
sources=['hello/_hello_ext.cxx'],
)
]
)
# Need to export all headers on windows...
cmake_args.append('-DCMAKE_WINDOWS_EXPORT_ALL_SYMBOLS=TRUE')
if os.getenv('USE_PYTHON_IN_PATH'):
python_exe = shutil.which('python')
if python_exe:
# For this program, we use find_package(Python3 ...)
cmake_args.append(f'-DPython3_EXECUTABLE={python_exe}')
with open('requirements.txt') as f:
install_requires = f.read()
setup(
name='stempy',
use_scm_version=True,
description='A package for the ingestion of 4D STEM data.',
long_description='A package for the ingestion of 4D STEM data.',
url='https://github.com/OpenChemistry/stempy',
author='Kitware Inc',
license='BSD 3-Clause',
classifiers=[
'Development Status :: 3 - Alpha',
'License :: OSI Approved :: BSD License',
'Programming Language :: Python :: 3',
],
keywords='',
packages=['stempy'],
install_requires=install_requires,
cmake_args=cmake_args,
)
from skbuild import setup
from os import path
setup(
cmake_args= [
'-DANTLR_JAR_LOCATION='+path.abspath('antlr4/antlr-4.7.2-complete.jar'),
#'-DCMAKE_BUILD_TYPE=Debug'
],
name='hdlConvertor',
version='1.2',
description='VHDL and System Verilog parser written in c++, this module is primary used for hdl manipulation and analysis',
url='https://github.com/Nic30/hdlConvertor',
author='Michal Orsak',
author_email='*****@*****.**',
keywords=['vhdl', 'verilog', 'system verilog', 'parser', 'hdl'],
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'Operating System :: OS Independent',
'Topic :: Software Development :: Build Tools',
'Programming Language :: C++',
'Programming Language :: Python :: 2.7'
'Programming Language :: Python :: 3',
],
packages=['hdlConvertor'],
package_dir={'hdlConvertor':'src/'}
)
import sys
from skbuild import setup
# Require pytest-runner only when running tests
pytest_runner = (['pytest-runner>=2.0,<3dev']
if any(arg in sys.argv for arg in ('pytest', 'test'))
else [])
setup_requires = pytest_runner
setup(
name="hello-cython",
version="1.2.3",
description="a minimal example package (cython version)",
author='The scikit-build team',
license="MIT",
packages=['hello'],
install_requires=['cython'],
tests_require=['pytest'],
setup_requires=setup_requires
)
setup(
name='itk-labelerodedilate',
version='1.1.1',
author='Richard Beare',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKLabelErodeDilate',
description=r'An ITK module for erode and dilate operations on label images',
long_description='itk-labelerodedilate provides classes for morphological math '
'erode and dilate operations on label images.\n'
'Please refer to:\n'
'Beare, R. and Jackway, P. '
'"Parallel Algorithms via Scaled Paraboloid Structuring '
'Functions for Spatially-Variant and Label-Set Dilations '
'and Erosions", '
'2011 International Conference on Digital Image Computing '
'Techniques and Applications (DICTA). 180--185. 2011. IEEE.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit Math-morphology Label-images',
url=r'https://github.com/InsightSoftwareConsortium/ITKLabelErodeDilate',
install_requires=[
r'itk>=5.0b01'
]
)
setup(
name="kaaengine",
author="labuzm, maniek2332",
author_email="[email protected], [email protected]",
version=versioneer.get_version(),
cmdclass=versioneer.get_cmdclass(),
python_requires=">=3.5",
description="Pythonic game engine for humans.",
long_description=readme_content,
long_description_content_type='text/markdown',
url="https://github.com/kaaengine/kaa",
packages=setuptools.find_packages(),
license="MIT",
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: MIT License",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX :: Linux",
"Programming Language :: C++",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3 :: Only",
"Topic :: Games/Entertainment",
"Topic :: Software Development",
],
include_package_data=False,
cmake_source_dir=KAA_SETUP_CMAKE_SOURCE,
cmake_args=[
'-DKAA_INSTALL_KAACORE:BOOL=OFF',
],
)
from skbuild import setup
setup(
name="hello",
version="1.2.3",
description="a minimal example package",
author='The scikit-build team',
license="MIT",
packages=['hello'],
package_dir={'': 'src'},
test_suite='hello_tests'
)
setup(
name='itk-simpleitkfilters',
version='0.1.0',
author='SimpleITK',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/SimpleITK/ITKSimpleITKFilters',
description=r'This module contains a collension of ITK Filters used by SimpleITK. These filter are usefull to SimpleITK in that they may wrap existing ITK filters with an interface expected by SimpleITK, or may add important basic filters needed for completeness.',
long_description='ITK is an open-source, cross-platform library that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and segmenting multidimensional scientific images.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit',
url=r'https://itk.org/',
install_requires=[
r'itk>=5.1.0.post2'
]
)
from skbuild import setup
setup(
name="hello",
version="1.2.3",
description="a minimal example package",
author='The scikit-build team',
license="MIT",
packages=[]
)
ver_path = convert_path('pynegf/version.py')
with open(ver_path) as ver_file:
exec(ver_file.read(), main_ns)
with open("README.md", "r") as fh:
long_description = fh.read()
setup(
name="pynegf",
version=main_ns['__version__'],
author="Gabriele Penazzi",
author_email="*****@*****.**",
description="A wrapper for libnegf, a library for Non Equilibrium Green's Function based charge transport.",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/gpenazzi/pynegf",
packages=['pynegf'],
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
python_requires='>=3.6',
install_requires=['numpy', 'scipy'],
tests_require=['pytest'],
cmake_args=[
'-DBUILD_SHARED_LIBS=ON'],
cmake_source_dir='libnegf',
cmake_install_dir='pynegf'
)
from skbuild import setup
setup(
name='hello',
version='1.2.3',
author='John Doe',
author_email='*****@*****.**',
url='https://example.com',
include_package_data=True,
)
skbuild.setup(
name="lfortran",
version=version,
author="Ondřej Čertík",
author_email="*****@*****.**",
description="Fortran compiler",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://gitlab.com/lfortran/lfortran",
packages=setuptools.find_packages(),
include_package_data=True,
data_files=[
('share/lfortran/nb', ['share/lfortran/nb/Demo.ipynb']),
],
scripts=['lfort'],
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
cmake_languages=('C'),
install_requires=[
"pytest",
"llvmlite",
"prompt_toolkit",
"antlr4-python3-runtime",
"pygments",
],
)
setup(
name='goofit',
version='2.2.2',
description='GooFit fitting package',
author='Henry Schreiner',
author_email='*****@*****.**',
url='https://goofit.github.io',
platforms = ["POSIX"],
provides = ["goofit"],
install_requires = [
'numpy>=1.11.1',
],
classifiers = [
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
"Natural Language :: English",
"Operating System :: Unix",
"Programming Language :: C++",
"Programming Language :: Python",
"Programming Language :: Python :: 2",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.4",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Topic :: Scientific/Engineering :: Physics"
],
cmake_args=ITEMS,
license="LGPL 3.0",
packages=['goofit'],
extras_require={
'dev': [
'pytest',
'matplotlib>=1.5',
'pandas>=0.15.1',
'uncertainties>=3.0.2',
'scipy'
]
},
long_description='''\
GooFit for Python
-----------------
GooFit is a highly parallel fitting framework originally designed for High Energy Physics.
Installation basics
===================
This package can be installed with pip, but uses SciKit-Build, and is build, fully optimized, on your system. Because of this, there are a few caveats when running a pip install. Make sure you have SciKit-Build (``pip install scikit-build``) before you attempt an install. Also, if you don't have a recent version of CMake (3.8 or better recommended), also run ``pip install cmake``. When you build, you should also use pip's ``-v`` flag, so that you can see it build (and observe the
configuration options). Otherwise, you might wait a very long time without output (especially if CUDA was found).
Installation: pip
=================
Using pip 10+::
pip install -v goofit
Using pip < 10::
pip install scikit-build
pip install -v goofit
GooFit will automatically look for CUDA, and build in GPU mode if it finds CUDA. You can pick a specific version by passing through a CMake option (see below), or by setting an environment variable, `GOOFIT_DEVICE` before building. You may want to build with OpenMP as a backend to avoid using your GPU, or you might want the CPP version if you are using Anaconda on macOS. Here are the three common backends::
GOOFIT_DEVICE=CUDA pip install -v goofit
GOOFIT_DEVICE=OMP pip install -v goofit
GOOFIT_DEVICE=CPP pip install -v goofit
If you want to send arbitrary commands to CMake through PIP, you will need to pass each option through, starting with a ``--`` option. Pip will try to reuse the built version if you do not pass options, but will rebuild if you pass options, so this works for a rebuild, unlike the lines above. This is how you would do this to set OMP as the backend::
pip install -v goofit --install-option="--" --install-option="-DGOOFIT_DEVICE=OMP"
# OR
PIP_INSTALL_OPTION="-- -DGOOFIT_DEVICE=OMP" pip install -v goofit
Installation: local
===================
If you want to add PDFs to GooFit, or use GooFit pacakges, you should be working in a local directory using git. In the following example, I'm assuming you've set up SSH keys with GitHub; you can use https instead if you prefer by changing the URL to ``https://github.com/GooFit/GooFit.git``::
git clone --recursive [email protected]:GooFit/GooFit.git
cd goofit
Pipenv
~~~~~~
You can set up a quick environment using pipenv::
pipenv install --dev
Then activate that environment::
pipenv shell
Local pip
~~~~~~~~~
The normal install here works, though as usual you should include verbose output::
pip install -v .
You can pass through options to the build command, for example::
pip install -v . --install-option="--" --install-option="-DGOOFIT_PACKAGES=OFF"
# OR
PIP_INSTALL_OPTION="-- -DGOOFIT_PACKAGES=OFF" pip install -v .
Building a source package from git
==================================
For developers only:
To make a source package, start with a clean (such as new) git GooFit package with all submodules checked out::
git clone --branch=master --recursive --depth=10 [email protected]:GooFit/GooFit.git
cd goofit
python setup.py sdist
python -m twine upload dist/*
To make a binary package, use instead::
python setup.py bdist_wheel -- -DGOOFIT_OPTI="-march=core2"
'''
)
setup(
name='itk-fixedpointinversedisplacementfield',
version='1.0.0',
author='Insight Software Consortium',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=
r'https://github.com/InsightSoftwareConsortium/ITKFixedPointInverseDisplacementField',
description=
r'Takes a displacement field as input and computes the displacement field that is its inverse.',
long_description='itk-fixedpointinversedisplacementfield takes a '
'displacement field as input and computes the '
'displacement field that is its inverse with a simple '
'fixed-point approach.\n'
'Please refer to:\n'
'M. Luethi, "Inverting deformation fields using a fixed point iteration scheme.", '
'Insight Journal, July-December 2010, http://hdl.handle.net/10380/3222.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 4 - Beta", "Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit Spatial-Transforms',
url=
r'https://github.com/InsightSoftwareConsortium/ITKFixedPointInverseDisplacementField',
install_requires=[r'itk>=5.1.1'])
from skbuild import setup
setup(
name="fail_with_fatal_error_cmakelists",
version="0.0.1",
description=("test project that should always fail to build because it "
"provides a CMakeLists.txt reporting a FATAL_ERROR"),
author="The scikit-build team",
license="MIT",
)
setup(
name='itk-boneenhancement',
version='0.3.1',
author='Bryce A. Besler',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=
r'https://github.com/InsightSoftwareConsortium/ITKBoneEnhancement',
description=
r'Various filters for enhancing cortical bones in quantitative computed tomography.',
long_description=
'ITK is an open-source, cross-platform library that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and segmenting multidimensional scientific images.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 4 - Beta", "Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit',
url=r'https://itk.org/',
install_requires=[r'itk>=5.1.0.post3'])
from skbuild import setup
setup(
name="hello-cython",
version="1.2.3",
description="a minimal example package (cython version)",
author='The scikit-build team',
license="MIT",
packages=['hello_cython'],
package_dir={'hello_cython': 'hello'},
)
{%- set modname = cookiecutter.project_slug.replace('-', '') -%}
from skbuild import setup
{%- if cookiecutter.use_submodules == "No" %}
import os
import pybind11
{%- endif %}
setup(
name='{{ modname }}',
version='0.0.1',
author='{{ cookiecutter.full_name }}',
author_email='*****@*****.**',
description='Add description here',
long_description='',
classifiers=[
"Programming Language :: Python :: 3",
"Operating System :: OS Independent",
{%- if cookiecutter.license == "MIT" %}
"License :: OSI Approved :: MIT License",
{%- elif cookiecutter.license == "BSD-2" %}
"License :: OSI Approved :: BSD License",
{%- elif cookiecutter.license == "GPL-3.0" %}
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
{%- elif cookiecutter.license == "LGPL-3.0" %}
"License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)",
{%- endif %}
],
zip_safe=False,
packages=["{{ modname }}"],
cmake_args=[
setup(
name='itk-higherorderaccurategradient',
version='1.0.2',
author='Matthew M. McCormick',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKHigherOrderAccurateGradient',
description=r'ITK filters to estimate higher order accurate derivative and gradients',
long_description='itk-higherorderaccurategradient provides higher order '
'accurate derivative and gradient image filters.\n'
'Please refer to:\n'
'M. McCormick, "Higher Order Accurate Derivative and Gradient Calculation in ITK.", '
'Insight Journal, July-December 2010, http://hdl.handle.net/10380/3231',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK Higher-order Derivative Gradient',
url=r'https://github.com/InsightSoftwareConsortium/ITKHigherOrderAccurateGradient',
install_requires=[
r'itk>=5.0rc01'
]
)
setup(name='{{ cookiecutter.python_package_name }}',
version='0.1.0',
author='{{ cookiecutter.full_name }}',
author_email='{{ cookiecutter.email }}',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'{{ cookiecutter.download_url }}',
description=r'{{ cookiecutter.project_short_description }}',
long_description='{{ cookiecutter.project_long_description }}',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 4 - Beta", "Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit',
url=r'https://itk.org/',
install_requires=[r'itk>=5.0.0.post1'])
setup(
name='avogadro',
use_scm_version=True,
setup_requires=['setuptools_scm'],
description='Avogadro provides analysis and data processing useful in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas.',
author='Kitware',
license='BSD',
url='https://github.com/OpenChemistry/avogadrolibs',
classifiers=[
'License :: OSI Approved :: BSD License',
'Programming Language :: Python',
'Programming Language :: C++',
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Intended Audience :: Education',
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering',
'Topic :: Scientific/Engineering :: Information Analysis',
'Topic :: Software Development :: Libraries',
'Operating System :: Microsoft :: Windows',
'Operating System :: Unix',
'Operating System :: MacOS'
],
packages=['avogadro'],
cmake_args=[
'-DUSE_SPGLIB:BOOL=FALSE',
'-DUSE_OPENGL:BOOL=FALSE',
'-DUSE_QT:BOOL=FALSE',
'-DUSE_MMTF:BOOL=FALSE',
'-DUSE_PYTHON:BOOL=TRUE',
'-DUSE_MOLEQUEUE:BOOL=FALSE',
'-DUSE_HDF5:BOOL=FALSE',
'-DUSE_LIBARCHIVE:BOOL=FALSE',
'-DUSE_LIBMSYM:BOOL=FALSE'
]
)
setup(
name=PACKAGE_NAME,
version=VERSION,
packages=setuptools.find_namespace_packages(include=['qiskit.*']),
cmake_source_dir='.',
description="Qiskit Aer - High performance simulators for Qiskit",
long_description=README,
long_description_content_type='text/markdown',
url="https://github.com/Qiskit/qiskit-aer",
author="AER Development Team",
author_email="*****@*****.**",
license="Apache 2.0",
classifiers=[
"Environment :: Console",
"License :: OSI Approved :: Apache Software License",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"Operating System :: Microsoft :: Windows",
"Operating System :: MacOS",
"Operating System :: POSIX :: Linux",
"Programming Language :: C++",
"Programming Language :: Python :: 3 :: Only",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Topic :: Scientific/Engineering",
],
python_requires=">=3.6",
install_requires=requirements,
setup_requires=setup_requirements,
include_package_data=True,
cmake_args=["-DCMAKE_OSX_DEPLOYMENT_TARGET:STRING=10.9"],
keywords="qiskit aer simulator quantum addon backend",
zip_safe=False
)
setup(
name='itk-variationalregistration',
version='0.0.1',
author='Alexander Schmidt-Richberg',
author_email='',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKVariationalRegistration',
description=r'An ITK module to perform variational image registration',
long_description='itk-variationalregistration provides a fexible framework '
'for deformable registration of two images using '
'PDE-based variational registration.\n'
'Please refer to:\n'
'Schmidt-Richberg A., Werner R., Handels H., Ehrhardt J., '
'"A Flexible Variational Registration Framework", '
'Insight Journal, http://hdl.handle.net/10380/3460, 2014.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit',
url=r'https://itk.org/',
install_requires=[
r'itk'
]
)
setup(
name="pyeoskit",
version="1.1.3",
description="Python Toolkit for EOS",
author='learnforpractice',
license="MIT",
url="https://github.com/learnforpractice/pyeoskit",
packages=['pyeoskit'],
# The extra '/' was *only* added to check that scikit-build can handle it.
package_dir={'pyeoskit': 'pysrc'},
package_data={'pyeoskit': [
'data/*',
'contracts/eosio.bios/*',
'contracts/eosio.msig/*',
'contracts/eosio.system/*',
'contracts/eosio.token/*',
'contracts/eosio.wrap/*',
'contracts/micropython/*',
'test_template.py',
]
},
install_requires=[
'requests_unixsocket>=0.2.0',
'httpx>=0.19.0',
'base58>=2.1.1',
'asn1>=2.4.2',
'ledgerblue>=0.1.41'
],
include_package_data=True
)
setup(
name='itk-splitcomponents',
version='2.0.0',
author='Matthew M. McCormick',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKSplitComponents',
description=r'ITK filters to split a multi-component pixel image into component-wise scalar images',
long_description='itk-splitcomponents provides a class that takes an image '
'with multi-component pixels and outputs a scalar image '
'for each component. This can be useful when examining '
'images of vectors, tensors, etc.\n'
'Please refer to:\n'
'M. McCormick, "An ITK Class that Splits Multi-Component Images.", '
'Insight Journal, July-December 2010, http://hdl.handle.net/10380/3230',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK Higher-order Derivative Gradient',
url=r'https://github.com/InsightSoftwareConsortium/ITKSplitComponents',
install_requires=[
r'itk>=5.0rc01'
]
)
setup(
name='itk',
version=get_versions()['package-version'],
author='Insight Software Consortium',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
py_modules=[
'itkBase',
'itkConfig',
'itkExtras',
'itkLazy',
'itkTemplate',
'itkTypes',
'itkVersion',
'WrapITKBuildOptionsPython'
],
download_url=r'https://itk.org/ITK/resources/software.html',
description=r'ITK is an open-source toolkit for multidimensional image '
r'analysis.',
long_description='ITK is an open-source, cross-platform library that '
'provides developers with an extensive suite of software '
'tools for image analysis. Developed through extreme '
'programming methodologies, ITK employs leading-edge '
'algorithms for registering and segmenting '
'multidimensional scientific images.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit segmentation registration image imaging',
url=r'https://itk.org/',
install_requires=[
]
)
from skbuild import setup
setup(
name="hello",
version="1.2.3",
description=("a minimal example packagze that should always fail to build "
"because it provides a _hello.cxx with a compile error"),
author='The scikit-build team',
license="MIT",
packages=['hello'],
)
setup(name=project_name,
packages=packages,
package_dir={"": package_dir},
version=version,
description='The Taichi Programming Language',
author='Taichi developers',
author_email='*****@*****.**',
url='https://github.com/taichi-dev/taichi',
python_requires=">=3.6,<3.11",
install_requires=[
'numpy', 'sourceinspect>=0.0.4', 'colorama', 'rich',
'astunparse;python_version<"3.9"'
],
data_files=[(os.path.join('_lib', 'runtime'), data_files)],
keywords=['graphics', 'simulation'],
license=
'Apache Software License (http://www.apache.org/licenses/LICENSE-2.0)',
include_package_data=True,
entry_points={
'console_scripts': [
'ti=taichi._main:main',
],
},
classifiers=classifiers,
cmake_args=get_cmake_args(),
cmake_process_manifest_hook=exclude_paths,
cmdclass={
'egg_info': EggInfo,
'clean': Clean
},
has_ext_modules=lambda: True)
from skbuild import setup
setup(
name="manifest-in",
version="1.2.3",
description="a minimal example package with a MANIFEST.in",
author='The scikit-build team',
license="MIT",
packages=['hello'],
)
name.endswith('.cmake') or # cmake files
name.endswith('.pc') or # package-config files
name.endswith('.txt') # text files
)
def cmake_process_manifest_hook(cmake_manifest):
print(cmake_manifest)
print('\n\n')
cmake_manifest = list(filter(accept_file, cmake_manifest))
print(cmake_manifest)
return cmake_manifest
setup(name="xeus-python",
version=xeus_version,
description='A wheel for xeus-python',
author='Sylvain Corlay, Johan Mabille, Martin Renou',
license='',
packages=['xpython'],
py_modules=['xpython_launcher'],
install_requires=[
'pygments>=2.3.1,<3', 'debugpy>=1.1.0', 'ipython>=7.20,<8'
],
setup_requires=setup_requires,
cmake_args=[
'-DCMAKE_INSTALL_LIBDIR=lib',
'-DPYTHON_EXECUTABLE:FILEPATH=' + python_path
],
cmake_process_manifest_hook=cmake_process_manifest_hook)
from skbuild import setup
setup(
name="tower_of_babel",
version="0.0.1",
description="integration test of skbuild's support across various python"
"module types and code generation technologies",
author="The scikit-build team",
license="MIT",
scripts=['scripts/tbabel'],
)
setup(
name='eclipse-sumo',
version=SUMO_VERSION,
url='https://sumo.dlr.de/',
download_url='https://sumo.dlr.de/download',
author='DLR and contributors',
author_email='*****@*****.**',
license='EPL-2.0',
description=("A microscopic, multi-modal traffic simulation package"),
long_description=open(os.path.join(os.path.dirname(package_dir), 'README.md')).read(),
long_description_content_type='text/markdown',
classifiers=[
'Development Status :: 5 - Production/Stable',
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: Eclipse Public License 2.0 (EPL-2.0)',
'Programming Language :: C++',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 3',
],
keywords='traffic simulation traci sumo',
packages=['sumo'],
package_dir={'': 'tools/build'},
cmake_install_dir='tools/build/sumo',
entry_points={
'console_scripts': [
'activitygen=sumo:activitygen',
'dfrouter=sumo:dfrouter',
'duarouter=sumo:duarouter',
'emissionsDrivingCycle=sumo:emissionsDrivingCycle',
'emissionsMap=sumo:emissionsMap',
'jtrrouter=sumo:jtrrouter',
'marouter=sumo:marouter',
'netconvert=sumo:netconvert',
'netedit=sumo:netedit',
'netgenerate=sumo:netgenerate',
'od2trips=sumo:od2trips',
'polyconvert=sumo:polyconvert',
'sumo=sumo:sumo',
'sumo-gui=sumo:sumo_gui',
]
},
)
from skbuild import setup
setup(
name="fail_with_syntax_error_cmakelists",
version="0.0.1",
description=("test project that should always fail to build because it "
"provides a CMakeLists.txt with a syntax error"),
author="The scikit-build team",
license="MIT",
)
from skbuild import setup
long_description = open('README.md').read()
setup(name="py_smartreply",
version="0.0.1",
author="Narasimha Prasanna HN",
author_email="*****@*****.**",
description="Python bindings for Tensorflow Lite Smart-Reply Runtime.",
url="https://github.com/Narasimha1997/py_cpu.git",
license="Apache 2.0 License",
has_package_data=False,
package_dir={"": "src"},
packages=["smartreply"],
cmake_install_dir="src/smartreply",
package_data={"smartreply": ['*.tflite']},
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Topic :: System :: Hardware',
'License :: OSI Approved :: Apache Software License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.2',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.9',
],
python_requires='>=3',
long_description=long_description,
long_description_content_type='text/markdown')
setup(
name='itk-bsplinegradient',
version='0.1.0',
author='Matthew McCormick',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKBSplineGradient',
description=r"Approximate an image's gradient from a B-spline fit to its intensity.",
long_description='itk-bsplinegradient provides classes to approximate '
'an image\'s gradient from a B-spline fit to its '
'intensity.\n',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit Image-Gradient B-spline',
url=r'https://github.com/InsightSoftwareConsortium/ITKBSplineGradient',
install_requires=[
r'itk'
]
)
setup(
name='itk-contrastlimitedadaptivehistogramequalization',
version='0.1.0',
author='Andinet Enquobahrie',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=
r'https://github.com/InsightSoftwareConsortium/ITKContrastLimitedAdaptiveHistogramEqualization',
description=
r'This is a template that serves as a starting point for a new module.',
long_description=
'ITK is an open-source, cross-platform library that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and segmenting multidimensional scientific images.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python", "Programming Language :: C++",
"Development Status :: 4 - Beta", "Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX", "Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit',
url=r'https://itk.org/',
install_requires=[r'itk>=5.1.0.post2'])
from skbuild import setup
setup(
name="hello",
version="1.2.3",
description="a minimal example package (cpp version)",
author='The scikit-build team',
license="MIT",
packages=['hello'],
tests_require=[],
setup_requires=[],
cmake_source_dir="../../"
)
'Intended Audience :: Developers',
'Intended Audience :: Science/Research',
'Operating System :: MacOS :: MacOS X',
'Operating System :: Unix',
'Topic :: Software Development :: Libraries :: Python Modules',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Utilities',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3 :: Only',
],
project_urls={ # Optional
'Bug Reports': 'https://github.com/WildbookOrg/wildbook-ia/issues',
'Funding': 'https://www.wildme.org/donate/',
'Say Thanks!': 'https://community.wildbook.org',
'Source': URL,
},
entry_points="""\
[console_scripts]
wbia-init-testdbs = wbia.cli.testdbs:main
""",
)
if __name__ == '__main__':
"""
python -c "import wbia; print(wbia.__file__)"
"""
setup(**KWARGS)
setup(
name='itk-iofdf',
version='1.0.0',
author='Glenn Pierce',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/InsightSoftwareConsortium/ITKIOFDF',
description=r'ITK `ImageIO` class to read or write the FDF image format',
long_description='itk-iofdf provides an `ImageIO` class to read or '
'write the FDF image format.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='ITK InsightToolkit FDF',
url=r'https://github.com/InsightSoftwareConsortium/ITKIOFDF',
install_requires=[
r'itk'
]
)
setup(
name='itk-rtk',
version='2.0.0',
author='RTK Consortium',
author_email='*****@*****.**',
packages=['itk'],
package_dir={'itk': 'itk'},
download_url=r'https://github.com/SimonRit/RTK',
description=r'The Reconstruction Toolkit (RTK) for fast circular cone-beam CT reconstruction.',
long_description='Based on the Insight Toolkit ITK, RTK provides: basic operators for reconstruction (e.g. filtering, forward, projection and backprojection), multithreaded CPU and GPU versions, tools for respiratory motion correction, I/O for several scanners, preprocessing of raw data for scatter correction.',
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: C++",
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Healthcare Industry",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
"Topic :: Scientific/Engineering :: Information Analysis",
"Topic :: Software Development :: Libraries",
"Operating System :: Android",
"Operating System :: Microsoft :: Windows",
"Operating System :: POSIX",
"Operating System :: Unix",
"Operating System :: MacOS"
],
license='Apache',
keywords='RTK Reconstruction Toolkit',
url=r'https://www.openrtk.org/',
install_requires=[
r'itk>=5.0rc1'
]
)
setup(
name='tomopy',
packages=['tomopy'],
package_dir={"": "source"},
setup_requires=['setuptools_scm', 'setuptools_scm_git_archive'],
use_scm_version=True,
include_package_data=True,
zip_safe=False,
author='Doga Gursoy',
author_email='*****@*****.**',
description='Tomographic Reconstruction in Python.',
keywords=['tomography', 'reconstruction', 'imaging'],
url='http://tomopy.readthedocs.org',
download_url='http://github.com/tomopy/tomopy.git',
license='BSD-3',
cmake_args=cmake_args,
cmake_languages=('C'),
platforms='Any',
classifiers=[
'Development Status :: 4 - Beta',
'License :: OSI Approved :: BSD License',
'Intended Audience :: Science/Research',
'Intended Audience :: Education',
'Intended Audience :: Developers',
'Natural Language :: English',
'Operating System :: OS Independent',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: C']
)
#
# DO NOT MODIFY THIS FILE!
# This file is autogenerated by the `dunepackaging.py` script and
# only used for the pypi dune packages. This file will not be included in
# the build directory.
#
import os, sys
here = os.path.dirname(os.path.abspath(__file__))
mods = os.path.join(here, "python", "dune")
sys.path.append(mods)
try:
from dune.packagemetadata import metaData
except ImportError:
from packagemetadata import metaData
from skbuild import setup
setup(**metaData()[1])
