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openSUSE:Backports:SLE-15-SP6:Update
python-xarray
python-xarray.spec
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File python-xarray.spec of Package python-xarray
# # spec file for package python-xarray # # Copyright (c) 2019 SUSE LINUX GmbH, Nuernberg, Germany. # # All modifications and additions to the file contributed by third parties # remain the property of their copyright owners, unless otherwise agreed # upon. The license for this file, and modifications and additions to the # file, is the same license as for the pristine package itself (unless the # license for the pristine package is not an Open Source License, in which # case the license is the MIT License). An "Open Source License" is a # license that conforms to the Open Source Definition (Version 1.9) # published by the Open Source Initiative. # Please submit bugfixes or comments via https://bugs.opensuse.org/ # %{?!python_module:%define python_module() python-%{**} python3-%{**}} %define skip_python2 1 Name: python-xarray Version: 0.13.0 Release: 0 Summary: N-D labeled arrays and datasets in Python License: Apache-2.0 Group: Development/Languages/Python URL: https://github.com/pydata/xarray Source: https://files.pythonhosted.org/packages/source/x/xarray/xarray-%{version}.tar.gz BuildRequires: %{python_module numpy-devel >= 1.12} BuildRequires: %{python_module pandas >= 0.19.2} BuildRequires: %{python_module setuptools} BuildRequires: fdupes BuildRequires: python-rpm-macros Requires: python-numpy >= 1.12 Requires: python-pandas >= 0.19.2 Recommends: python-scipy Provides: python-xray = %{version} Obsoletes: python-xray < %{version} BuildArch: noarch # SECTION tests # dask tests currently failing # BuildRequires: %%{python_module dask-dataframe} BuildRequires: %{python_module pytest >= 2.7.1} BuildRequires: %{python_module scipy} BuildRequires: python2-mock # /SECTION %python_subpackages %description xarray (formerly xray) is a python-pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays. It provides N-dimensional variants of the python-pandas labeled data structures, rather than the tabular data that pandas uses. The Common Data Model for self-describing scientific data is used. The dataset is an in-memory representation of a netCDF file. %prep %setup -q -n xarray-%{version} %build %python_build %install %python_install %python_expand %fdupes %{buildroot}%{$python_sitelib} %check # Tests are xfail on aarch64: gh#pydata/xarray#2334 %pytest -k "not test_datetime_reduce and not test_roundtrip_numpy_datetime_data and not test_download_from_github" %files %{python_files} %doc README.rst %license LICENSE licenses/ %{python_sitelib}/xarray* %changelog
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