1
0
forked from pool/python-xarray
python-xarray/python-xarray.spec
Sebastian Wagner 05745a2f96 - update to version 0.12.2:
- New functions/methods:
  - Two new functions, :py:func:`~xarray.combine_nested` and
    :py:func:`~xarray.combine_by_coords`, allow for combining datasets along any
    number of dimensions, instead of the one-dimensional list of datasets
    supported by :py:func:`~xarray.concat`.
    The new ``combine_nested`` will accept the datasets as a nested
    list-of-lists, and combine by applying a series of concat and merge
    operations. The new ``combine_by_coords`` instead uses the dimension
    coordinates of datasets to order them.
    :py:func:`~xarray.open_mfdataset` can use either ``combine_nested`` or
    ``combine_by_coords`` to combine datasets along multiple dimensions, by
    specifying the argument ``combine='nested'`` or ``combine='by_coords'``.
    The older function :py:func:`~xarray.auto_combine` has been deprecated,
    because its functionality has been subsumed by the new functions.
    To avoid FutureWarnings switch to using ``combine_nested`` or
    ``combine_by_coords``, (or set the ``combine`` argument in
    ``open_mfdataset``). (:issue:`2159`)
    By `Tom Nicholas <http://github.com/TomNicholas>`_.
  - :py:meth:`~xarray.DataArray.rolling_exp` and
    :py:meth:`~xarray.Dataset.rolling_exp` added, similar to pandas'
    ``pd.DataFrame.ewm`` method. Calling ``.mean`` on the resulting object
    will return an exponentially weighted moving average.
    By `Maximilian Roos <https://github.com/max-sixty>`_.
  - New :py:func:`DataArray.str <core.accessor_str.StringAccessor>` for string
    related manipulations, based on ``pandas.Series.str``.
    By `0x0L <https://github.com/0x0L>`_.
  - Added ``strftime`` method to ``.dt`` accessor, making it simpler to hand a
    datetime ``DataArray`` to other code expecting formatted dates and times.
    (:issue:`2090`). :py:meth:`~xarray.CFTimeIndex.strftime` is also now

OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-xarray?expand=0&rev=18
2019-06-30 09:30:45 +00:00

77 lines
2.5 KiB
RPMSpec

#
# 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: 0.12.2
Release: 0
Summary: N-D labeled arrays and datasets in Python
License: Apache-2.0
Group: Development/Languages/Python
URL: http://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
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"
%files %{python_files}
%doc README.rst
%license LICENSE licenses/
%{python_sitelib}/xarray*
%changelog