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%global srcname xarray
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%global data_commit 5fdb22b5613ba8176b9f6fa67be783d7810643eb
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%bcond_with docs
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Name:           python-%{srcname}
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Version:        0.20.1
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Release:        %autorelease
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Summary:        N-D labeled arrays and datasets in Python
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License:        ASL 2.0
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URL:            https://github.com/pydata/xarray
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Source0:        %pypi_source
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# Data for examples only.
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Source1:        https://github.com/pydata/xarray-data/archive/%{data_commit}/xarray-data-%{data_commit}.tar.gz
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Source2:        https://github.com/mapbox/rasterio/raw/1.0.21/tests/data/RGB.byte.tif
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# All Fedora specific.
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Patch0001:      0001-DOC-Don-t-download-RGB.byte.tif-during-build.patch
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Patch0002:      0002-DOC-Skip-examples-using-unpackaged-dependencies.patch
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Patch0003:      0003-DOC-Don-t-print-out-conda-pip-environment.patch
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BuildArch:      noarch
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BuildRequires:  python3-devel
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BuildRequires:  python3dist(cftime) >= 1.2
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BuildRequires:  python3dist(dask[array]) >= 2.30
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BuildRequires:  python3dist(dask[dataframe]) >= 2.30
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BuildRequires:  python3dist(netcdf4) >= 1.5
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BuildRequires:  python3dist(pint) >= 0.16
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BuildRequires:  python3dist(pytest) >= 2.7.1
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BuildRequires:  python3dist(pytest-xdist)
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BuildRequires:  python3dist(rasterio) >= 1.1
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BuildRequires:  python3dist(seaborn) >= 0.11
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BuildRequires:  python3dist(zarr) >= 2.5
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%global _description %{expand: \
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Xarray (formerly xray) is an open source project and Python package that
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makes working with labelled multi-dimensional arrays simple, efficient,
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and fun!
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Xarray introduces labels in the form of dimensions, coordinates and
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attributes on top of raw NumPy-like arrays, which allows for a more
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intuitive, more concise, and less error-prone developer experience. The
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package includes a large and growing library of domain-agnostic functions
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for advanced analytics and visualization with these data structures.
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Xarray was inspired by and borrows heavily from pandas, the popular data
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analysis package focused on labelled tabular data. It is particularly
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tailored to working with netCDF files, which were the source of xarray's
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data model, and integrates tightly with dask for parallel computing.}
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%description %{_description}
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%package -n     python3-%{srcname}
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Summary:        %{summary}
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%description -n python3-%{srcname} %{_description}
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%if %{with docs}
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%package -n python-%{srcname}-doc
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Summary:        xarray documentation
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BuildRequires:  python3dist(cartopy)
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BuildRequires:  natural-earth-map-data-110m
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BuildRequires:  natural-earth-map-data-10m
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BuildRequires:  python3-ipython-sphinx
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BuildRequires:  python3dist(jupyter-client)
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BuildRequires:  python3dist(matplotlib) >= 3.3
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BuildRequires:  python3dist(sphinx)
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BuildRequires:  python3dist(sphinx-gallery)
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BuildRequires:  python3dist(sphinx-rtd-theme)
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%description -n python-%{srcname}-doc
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Documentation for xarray
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%endif
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%prep
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%autosetup -n %{srcname}-%{version} -p1
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%if %{with docs}
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# Provide example datasets for building docs.
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tar xf %SOURCE1 --transform='s~^\(%{srcname}-data-%{data_commit}/\)~\1.xarray_tutorial_data/~'
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cp -p %SOURCE2 ./doc/gallery/
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%endif
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%generate_buildrequires
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%pyproject_buildrequires -r
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%build
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%pyproject_wheel
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%if %{with docs}
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# generate html docs
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pushd doc
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PYTHONPATH=${PWD}/.. HOME=${PWD}/../%{srcname}-data-%{data_commit} make html
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# remove the sphinx-build leftovers
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rm -rf _build/html/.{doctrees,buildinfo}
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popd
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%endif
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%install
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%pyproject_install
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%pyproject_save_files %{srcname}
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%check
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rm -rf xarray
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pytest_args=(
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  -n auto
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  -m "not network"
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)
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%{pytest} -ra "${pytest_args[@]}" --pyargs xarray
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%files -n python3-%{srcname} -f %{pyproject_files}
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%license LICENSE licenses/DASK_LICENSE licenses/NUMPY_LICENSE licenses/PANDAS_LICENSE licenses/PYTHON_LICENSE licenses/SEABORN_LICENSE
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%doc README.rst
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%if %{with docs}
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%files -n python-%{srcname}-doc
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%doc doc/_build/html
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%license LICENSE licenses/DASK_LICENSE licenses/NUMPY_LICENSE licenses/PANDAS_LICENSE licenses/PYTHON_LICENSE licenses/SEABORN_LICENSE
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%endif
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%changelog
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%autochangelog