#!/usr/bin/env python import sys from setuptools import find_packages, setup import versioneer DISTNAME = 'xarray' LICENSE = 'Apache' AUTHOR = 'xarray Developers' AUTHOR_EMAIL = 'xarray@googlegroups.com' URL = 'https://github.com/pydata/xarray' CLASSIFIERS = [ 'Development Status :: 4 - Beta', 'License :: OSI Approved :: Apache Software License', 'Operating System :: OS Independent', 'Intended Audience :: Science/Research', 'Programming Language :: Python', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Topic :: Scientific/Engineering', ] INSTALL_REQUIRES = ['numpy >= 1.12', 'pandas >= 0.19.2'] TESTS_REQUIRE = ['pytest >= 2.7.1'] if sys.version_info[0] < 3: TESTS_REQUIRE.append('mock') DESCRIPTION = "N-D labeled arrays and datasets in Python" LONG_DESCRIPTION = """ **xarray** (formerly **xray**) is an open source project and Python package that aims to bring the labeled data power of pandas_ to the physical sciences, by providing N-dimensional variants of the core pandas data structures. Our goal is to provide a pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays, rather than the tabular data for which pandas excels. Our approach adopts the `Common Data Model`_ for self- describing scientific data in widespread use in the Earth sciences: ``xarray.Dataset`` is an in-memory representation of a netCDF file. .. _pandas: http://pandas.pydata.org .. _Common Data Model: http://www.unidata.ucar.edu/software/thredds/current/netcdf-java/CDM .. _netCDF: http://www.unidata.ucar.edu/software/netcdf .. _OPeNDAP: http://www.opendap.org/ Important links --------------- - HTML documentation: http://xarray.pydata.org - Issue tracker: http://github.com/pydata/xarray/issues - Source code: http://github.com/pydata/xarray - SciPy2015 talk: https://www.youtube.com/watch?v=X0pAhJgySxk """ # noqa setup(name=DISTNAME, version=versioneer.get_version(), cmdclass=versioneer.get_cmdclass(), license=LICENSE, author=AUTHOR, author_email=AUTHOR_EMAIL, classifiers=CLASSIFIERS, description=DESCRIPTION, long_description=LONG_DESCRIPTION, install_requires=INSTALL_REQUIRES, tests_require=TESTS_REQUIRE, url=URL, python_requires='>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*', packages=find_packages(), package_data={'xarray': ['tests/data/*']})