forked from pool/python-xarray
b82feb2bc8
- This patch release fixes an incompatability with a recent pandas change, which:
- was causing an issue indexing with a ``datetime64``. It also includes:
- improvements to ``rolling``, ``to_dataframe``, ``cov`` & ``corr`` methods and:
- bug fixes. Our documentation has a number of improvements, including fixing all :
- doctests and confirming their accuracy on every commit.:
- Many thanks to the 36 contributors who contributed to this release:
- Aaron Spring, Akio Taniguchi, Aleksandar Jelenak, Alexandre Poux,:
- Caleb, Dan Nowacki, Deepak Cherian, Gerardo Rivera, Jacob Tomlinson, James A.:
- Bednar, Joe Hamman, Julia Kent, Kai Mühlbauer, Keisuke Fujii, Mathias Hauser,:
- Maximilian Roos, Nick R. Papior, Pascal Bourgault, Peter Hausamann, Romain:
- Martinez, Russell Manser, Samnan Rahee, Sander, Spencer Clark, Stephan Hoyer,:
- Thomas Zilio, Tobias Kölling, Tom Augspurger, alexamici, crusaderky, darikg,:
- inakleinbottle, jenssss, johnomotani, keewis, and rpgoldman.:
- Breaking changes:
- :py:meth:`DataArray.astype` and :py:meth:`Dataset.astype` now preserve attributes. Keep the
old behavior by passing `keep_attrs=False` (:issue:`2049`, :pull:`4314`).
By `Dan Nowacki <https://github.com/dnowacki-usgs>`_ and `Gabriel Joel Mitchell <https://github.com/gajomi>`_.
- New Features:
- :py:meth:`~xarray.DataArray.rolling` and :py:meth:`~xarray.Dataset.rolling`
now accept more than 1 dimension. (:pull:`4219`)
By `Keisuke Fujii <https://github.com/fujiisoup>`_.
- :py:meth:`~xarray.DataArray.to_dataframe` and :py:meth:`~xarray.Dataset.to_dataframe`
now accept a ``dim_order`` parameter allowing to specify the resulting dataframe's
dimensions order (:issue:`4331`, :pull:`4333`).
By `Thomas Zilio <https://github.com/thomas-z>`_.
- Support multiple outputs in :py:func:`xarray.apply_ufunc` when using
``dask='parallelized'``. (:issue:`1815`, :pull:`4060`).
By `Kai Mühlbauer <https://github.com/kmuehlbauer>`_.
- ``min_count`` can be supplied to reductions such as ``.sum`` when specifying
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-xarray?expand=0&rev=39
80 lines
2.7 KiB
RPMSpec
80 lines
2.7 KiB
RPMSpec
#
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# spec file for package python-xarray
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#
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# Copyright (c) 2020 SUSE LLC
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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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%{?!python_module:%define python_module() python-%{**} python3-%{**}}
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%define skip_python2 1
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Name: python-xarray
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Version: 0.16.1
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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://files.pythonhosted.org/packages/source/x/xarray/xarray-%{version}.tar.gz
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BuildRequires: %{python_module numpy >= 1.15}
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BuildRequires: %{python_module numpy-devel >= 1.14}
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BuildRequires: %{python_module pandas >= 0.25}
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BuildRequires: %{python_module setuptools_scm}
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BuildRequires: %{python_module setuptools}
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BuildRequires: fdupes
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BuildRequires: python-rpm-macros
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Requires: python-numpy >= 1.15
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Requires: python-pandas >= 0.25
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Recommends: python-scipy >= 1.3
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Suggests: python-dask >= 2.2
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Provides: python-xray = %{version}
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Obsoletes: python-xray < %{version}
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BuildArch: noarch
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# SECTION tests
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# dask tests currently failing
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# BuildRequires: %%{python_module dask-dataframe}
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BuildRequires: %{python_module pytest >= 2.7.1}
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BuildRequires: %{python_module scipy}
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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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%prep
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%setup -q -n xarray-%{version}
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chmod -x xarray/util/print_versions.py
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%build
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%python_build
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%install
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%python_install
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%python_expand %fdupes %{buildroot}%{$python_sitelib}
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%check
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# test_no_warning_from_dask_effective_get fails due to upstream scipy warning
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%pytest -k "not test_download_from_github and not test_no_warning_from_dask_effective_get" xarray
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%files %{python_files}
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%doc README.rst
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%license LICENSE licenses/
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%{python_sitelib}/xarray*
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%changelog
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