Sebastian Wagner
ed0f425347
* This release rolls back the default engine for HTTP urls, adds
support for DataTree objects in combine_nested and contains
numerous bug fixes.
- Release 2025.11.0
* This release changes the default for keep_attrs such that
attributes are preserved by default, adds support for DataTree
in top-level functions, and contains several memory and
performance improvements as well as a number of bug fixes.
- Release 2025.10.0 and 2025.10.1
* These releases revert a breaking change to Xarray's preferred
netCDF backend.
- Release 2025.09.1
* This release contains improvements to netCDF IO and the
DataTree.from_dict() constructor, as well as a variety of bug
fixes. In particular, the default netCDF backend has switched
from netCDF4 to h5netcdf, which is typically faster.
- Release 2025.09.0
* This release brings a number of small improvements and fixes,
especially related to writing DataTree objects and netCDF files
to disk.
## New Features
* Support rechunking by SeasonResampler for seasonal data
analysis (GH10425, PR10519). By Dhruva Kumar Kaushal.
* Add convenience methods to Coordinates (PR10318) By Justus
Magin.
* Added load_datatree() for loading DataTree objects into memory
from disk. It has the same relationship to open_datatree(), as
load_dataset() has to open_dataset(). By Stephan Hoyer.
* compute=False is now supported by DataTree.to_netcdf() and
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-xarray?expand=0&rev=114
207 lines
6.5 KiB
RPMSpec
207 lines
6.5 KiB
RPMSpec
#
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# spec file for package python-xarray
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#
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# Copyright (c) 2025 SUSE LLC and contributors
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#
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# All modifications and additions to the file contributed by third parties
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# remain the property of their copyright owners, unless otherwise agreed
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# upon. The license for this file, and modifications and additions to the
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# file, is the same license as for the pristine package itself (unless the
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# license for the pristine package is not an Open Source License, in which
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# case the license is the MIT License). An "Open Source License" is a
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# license that conforms to the Open Source Definition (Version 1.9)
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# published by the Open Source Initiative.
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# Please submit bugfixes or comments via https://bugs.opensuse.org/
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#
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%global flavor @BUILD_FLAVOR@%{nil}
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%if "%{flavor}" == "test"
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%bcond_without test
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%define psuffix -test
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%else
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%bcond_with test
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%define psuffix %{nil}
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%endif
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%{?sle15_python_module_pythons}
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Name: python-xarray%{psuffix}
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Version: 2025.12.0
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Release: 0
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Summary: N-D labeled arrays and datasets in Python
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License: Apache-2.0
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URL: https://github.com/pydata/xarray
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Source: https://github.com/pydata/xarray/archive/refs/tags/v%{version}.tar.gz#/xarray-%{version}-gh.tar.gz
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# PATCH-FEATURE-UPSTREAM local_dataset.patch gh#pydata/xarray#5377 mcepl@suse.com
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# fix xr.tutorial.open_dataset to work with the preloaded cache.
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Patch0: local_dataset.patch
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# PATCH-FIX-OPENSUSE: skip dependency on pytest-mypy
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Patch1: no-mypy-test-plugin.patch
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BuildRequires: %{python_module base >= 3.11}
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BuildRequires: %{python_module pip}
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BuildRequires: %{python_module setuptools_scm}
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BuildRequires: %{python_module setuptools}
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BuildRequires: %{python_module wheel}
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BuildRequires: fdupes
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BuildRequires: python-rpm-macros
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Requires: python-numpy >= 1.26
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Requires: python-packaging >= 24.1
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Requires: python-pandas >= 2.2
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Obsoletes: python-xray <= 0.7
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BuildArch: noarch
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%if %{with test}
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BuildRequires: %{python_module hypothesis}
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BuildRequires: %{python_module pytest-asyncio}
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BuildRequires: %{python_module pytest-env}
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BuildRequires: %{python_module pytest-timeout}
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BuildRequires: %{python_module pytest-xdist}
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BuildRequires: %{python_module pytest}
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BuildRequires: %{python_module ruff >= 0.8.0}
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BuildRequires: %{python_module xarray-complete = %{version}}
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%endif
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# /SECTION
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%python_subpackages
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%description
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xarray (formerly xray) is a python-pandas-like and pandas-compatible
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toolkit for analytics on multi-dimensional arrays. It provides
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N-dimensional variants of the python-pandas labeled data structures,
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rather than the tabular data that pandas uses.
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The Common Data Model for self-describing scientific data is used.
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The dataset is an in-memory representation of a netCDF file.
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%package accel
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Summary: The python xarray[accel] extra
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Requires: python-Bottleneck
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Requires: python-numba >= 0.62
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Requires: python-opt-einsum
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Requires: python-scipy >= 1.13
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Requires: python-xarray = %{version}
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# not available yet
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Recommends: python-flox
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Recommends: python-numbagg >= 0.8
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%description accel
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The [accel] extra for xarray, N-D labeled arrays and datasets in Python
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Except flox and numbagg, because they are not packaged yet.
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Use `pip --user install flox numbagg` to install from PyPI, if needed.
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%package complete
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Summary: The python xarray[complete] extra
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Requires: python-xarray = %{version}
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Requires: python-xarray-accel = %{version}
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Requires: python-xarray-io = %{version}
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Requires: python-xarray-parallel = %{version}
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Requires: python-xarray-viz = %{version}
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%description complete
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The [complete] extra for xarray, N-D labeled arrays and datasets in Python
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%package io
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Summary: The python xarray[io] extra
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Requires: python-cftime
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Requires: python-fsspec
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Requires: python-h5netcdf
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Requires: python-netCDF4 >= 1.6
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Requires: python-pooch
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Requires: python-scipy >= 1.13
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Requires: python-xarray = %{version}
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Requires: python-zarr >= 2.18
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# Not available yet
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Recommends: python-pydap
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%description io
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The [io] extra for xarray, N-D labeled arrays and datasets in Python
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%package parallel
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Summary: The python xarray[parallel] extra
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Requires: python-dask-complete
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Requires: python-xarray = %{version}
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%description parallel
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The [parallel] extra for xarray, N-D labeled arrays and datasets in Python
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%package viz
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Summary: The python xarray[viz] extra
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Requires: python-matplotlib >= 3.8
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Requires: python-seaborn
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Requires: python-xarray = %{version}
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# Not available yet
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Recommends: python-cartopy >= 0.23
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Recommends: python-nc-time-axis
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%description viz
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The [viz] extra for xarray, N-D labeled arrays and datasets in Python
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Except nc-time-axis and cartopy, because they're not packaged yet.
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Use `pip --user install nc-time-axis cartopy` to install from PyPI, if needed.
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%prep
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%autosetup -p1 -n xarray-%{version}
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chmod -x xarray/util/print_versions.py
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%build
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%if !%{with test}
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%pyproject_wheel
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%endif
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%install
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%if !%{with test}
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%pyproject_install
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%python_expand %fdupes %{buildroot}%{$python_sitelib}
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%endif
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%if %{with test}
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%check
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# obs file open race conditions?
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donttest="(test_open_mfdataset_manyfiles and (h5netcdf or netCDF4))"
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if [ $(getconf LONG_BIT) -eq 32 ]; then
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# https://github.com/pydata/xarray/issues/5341
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# https://github.com/pydata/xarray/issues/5375
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# still precision problems in 2022.11.0
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donttest="$donttest or (test_interpolate_chunk_advanced and linear)"
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# tests for 64bit types
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donttest="$donttest or TestZarrDictStore or TestZarrDirectoryStore or TestZarrWriteEmpty"
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donttest="$donttest or test_repr_multiindex or test_array_repr_dtypes_unix or test_asi8"
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donttest="$donttest or (test_datatree and TestRepr and test_doc_example)"
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fi
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# h5py was built without ROS3 support, can't use ros3 driver
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donttest="$donttest or TestH5NetCDFDataRos3Driver"
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# NetCDF4 fails with these unsupported drivers
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donttest="$donttest or (TestNetCDF4 and test_compression_encoding and (szip or zstd or blosc_lz or blosc_zlib))"
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%pytest -n auto -rsEf -k "not ($donttest)" xarray
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%endif
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%if !%{with test}
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%files %{python_files}
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%doc README.md
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%license LICENSE licenses/
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%{python_sitelib}/xarray
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%{python_sitelib}/xarray-*.dist-info
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%files %{python_files accel}
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%doc README.md
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%license LICENSE
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%files %{python_files complete}
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%doc README.md
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%license LICENSE
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%files %{python_files io}
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%doc README.md
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%license LICENSE
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%files %{python_files parallel}
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%doc README.md
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%license LICENSE
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%files %{python_files viz}
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%doc README.md
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%license LICENSE
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%endif
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%changelog
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