%global srcname xarray

%global data_commit 7d8290e0be9d2a8f4b4381641f20a97db6eaea3d

%bcond_with docs

Name:           python-%{srcname}

Version:        2023.9.0

Release:        %autorelease

Summary:        N-D labeled arrays and datasets in Python

License:        Apache-2.0

URL:            https://github.com/pydata/xarray

Source0:        %pypi_source %{srcname}

# Data for examples only.

Source1:        https://github.com/pydata/xarray-data/archive/%{data_commit}/xarray-data-%{data_commit}.tar.gz

# All Fedora specific.

Patch0001:      0001-DOC-Skip-examples-using-unpackaged-dependencies.patch

Patch0002:      0002-DOC-Don-t-print-out-conda-pip-environment.patch

BuildArch:      noarch

BuildRequires:  python3-devel

BuildRequires:  python3dist(bottleneck)

BuildRequires:  python3dist(cftime) >= 1.2

BuildRequires:  python3dist(dask[array]) >= 2.30

BuildRequires:  python3dist(dask[dataframe]) >= 2.30

BuildRequires:  python3dist(netcdf4) >= 1.5

BuildRequires:  python3dist(pint) >= 0.16

BuildRequires:  python3dist(pytest) >= 2.7.1

BuildRequires:  python3dist(pytest-xdist)

BuildRequires:  python3dist(rasterio) >= 1.1

BuildRequires:  python3dist(seaborn) >= 0.11

BuildRequires:  python3dist(zarr) >= 2.5

%global _description %{expand: \

Xarray (formerly xray) is an open source project and Python package that

makes working with labelled multi-dimensional arrays simple, efficient,

and fun!

Xarray introduces labels in the form of dimensions, coordinates and

attributes on top of raw NumPy-like arrays, which allows for a more

intuitive, more concise, and less error-prone developer experience. The

package includes a large and growing library of domain-agnostic functions

for advanced analytics and visualization with these data structures.

Xarray was inspired by and borrows heavily from pandas, the popular data

analysis package focused on labelled tabular data. It is particularly

tailored to working with netCDF files, which were the source of xarray’s

data model, and integrates tightly with dask for parallel computing.}

%description %{_description}

%package -n     python3-%{srcname}

Summary:        %{summary}

%description -n python3-%{srcname} %{_description}

%if %{with docs}

%package -n python-%{srcname}-doc

Summary:        xarray documentation

BuildRequires:  python3dist(cartopy)

BuildRequires:  natural-earth-map-data-110m

BuildRequires:  natural-earth-map-data-10m

BuildRequires:  python3-ipython-sphinx

BuildRequires:  python3dist(jupyter-client)

BuildRequires:  python3dist(matplotlib) >= 3.3

BuildRequires:  python3dist(sphinx)

BuildRequires:  python3dist(sphinx-gallery)

BuildRequires:  python3dist(sphinx-rtd-theme)

%description -n python-%{srcname}-doc

Documentation for xarray

%endif

%prep

%autosetup -n %{srcname}-%{version} -p1

%if %{with docs}

# Provide example datasets for building docs.

tar xf %SOURCE1 --transform='s~^\(%{srcname}-data-%{data_commit}/\)~\1.xarray_tutorial_data/~'

%endif

%generate_buildrequires

%pyproject_buildrequires -r

%build

%pyproject_wheel

%if %{with docs}

# generate html docs

pushd doc

PYTHONPATH=${PWD}/.. HOME=${PWD}/../%{srcname}-data-%{data_commit} make html

# remove the sphinx-build leftovers

rm -rf _build/html/.{doctrees,buildinfo}

popd

%endif

%install

%pyproject_install

%pyproject_save_files %{srcname}

%check

rm -rf xarray

pytest_args=(

  -n auto

  -m "not network"

  # https://github.com/pydata/xarray/issues/7513

  -k 'not test_open_mfdataset_manyfiles'

)

%{pytest} -ra "${pytest_args[@]}" --pyargs xarray

%files -n python3-%{srcname} -f %{pyproject_files}

%license LICENSE licenses/DASK_LICENSE licenses/NUMPY_LICENSE licenses/PANDAS_LICENSE licenses/PYTHON_LICENSE licenses/SEABORN_LICENSE

%doc README.md

%if %{with docs}

%files -n python-%{srcname}-doc

%doc doc/_build/html

%license LICENSE licenses/DASK_LICENSE licenses/NUMPY_LICENSE licenses/PANDAS_LICENSE licenses/PYTHON_LICENSE licenses/SEABORN_LICENSE

%endif

%changelog

%autochangelog