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from codecs import open |
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from os import path |
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import re |
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# Always prefer setuptools over distutils |
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from setuptools import find_packages, setup |
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name = "sciapy" |
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meta_path = path.join(name, "__init__.py") |
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here = path.abspath(path.dirname(__file__)) |
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extras_require = { |
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"msis": ["nrlmsise00"], |
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"tests": ["nrlmsise00", "pytest"], |
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} |
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extras_require["all"] = sorted( |
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{v for req in extras_require.values() for v in req}, |
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) |
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# Approach taken from |
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# https://packaging.python.org/guides/single-sourcing-package-version/ |
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# and the `attrs` package https://www.attrs.org/ |
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# https://github.com/python-attrs/attrs |
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def read(*parts): |
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""" |
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Builds an absolute path from *parts* and and return the contents of the |
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resulting file. Assumes UTF-8 encoding. |
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""" |
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with open(path.join(here, *parts), "rb", "utf-8") as f: |
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return f.read() |
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def find_meta(meta, *path): |
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""" |
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Extracts __*meta*__ from *path* (can have multiple components) |
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""" |
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meta_file = read(*path) |
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meta_match = re.search( |
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r"^__{meta}__ = ['\"]([^'\"]*)['\"]".format(meta=meta), meta_file, re.M, |
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) |
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if not meta_match: |
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raise RuntimeError("__{meta}__ string not found.".format(meta=meta)) |
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return meta_match.group(1) |
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# Get the long description from the README file |
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long_description = read("README.md") |
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version = find_meta("version", meta_path) |
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if __name__ == "__main__": |
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setup( |
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name=name, |
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version=version, |
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description='Python tools for (some) SCIAMACHY data', |
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long_description=long_description, |
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long_description_content_type="text/markdown", |
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url='http://github.com/st-bender/sciapy', |
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author='Stefan Bender', |
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author_email='[email protected]', |
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packages=find_packages(), |
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scripts=['scripts/scia_binary_util.py', |
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'scripts/scia_conv_hdf5_limb.py', |
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'scripts/scia_daily_zonal_mean.py', |
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'scripts/scia_post_process_l2.py'], |
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package_data={ |
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'sciapy.level2': ['IGRF.tab', 'AACGM2005_80km_grid.nc'], |
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'sciapy': ['data/indices/*.dat', 'data/indices/*.txt'], |
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}, |
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install_requires=[ |
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'numpy>=1.13.0', |
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'scipy>=0.17.0', |
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'matplotlib>=2.2', |
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'netCDF4', |
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'h5py', |
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'dask', |
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'toolz', |
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'astropy', |
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'pandas', |
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'xarray', |
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'parse', |
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'autograd', |
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'celerite>=0.3.0', |
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'corner', |
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'george', |
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'emcee', |
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'regressproxy', |
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], |
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extras_require=extras_require, |
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license='GPLv2', |
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classifiers=[ |
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"Development Status :: 3 - Alpha", |
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"Intended Audience :: Science/Research", |
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"License :: OSI Approved :: GNU General Public License v2 (GPLv2)", |
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"Programming Language :: Python", |
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"Programming Language :: Python :: 2", |
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"Programming Language :: Python :: 2.7", |
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"Programming Language :: Python :: 3", |
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"Programming Language :: Python :: 3.4", |
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"Programming Language :: Python :: 3.5", |
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"Programming Language :: Python :: 3.6", |
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"Programming Language :: Python :: 3.7", |
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"Programming Language :: Python :: 3.8", |
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103
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], |
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entry_points={'console_scripts': |
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[ |
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'scia_regress = sciapy.regress.__main__:main', |
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'scia_post_process_l2 = sciapy.level2.post_process:main', |
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] |
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}, |
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options={ |
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"bdist_wheel": {"universal": True}, |
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}, |
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zip_safe=False, |
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) |
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st-bender /
sciapy
