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Accepting request 1152304 from home:bnavigator:branches:devel:languages:python:numeric

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- Update to 2024.2.0
  * This release brings size information to the text repr, changes
    to the accepted frequency strings, and various bug fixes.
  ## New Features
  * Added a simple nbytes representation in DataArrays and Dataset
    repr. (GH8690, PR8702). By Etienne Schalk.
  * Allow negative frequency strings (e.g. "-1YE"). These strings
    are for example used in date_range(), and cftime_range()
    (PR8651). By Mathias Hauser.
  * Add NamedArray.expand_dims(), NamedArray.permute_dims() and
    NamedArray.broadcast_to() (PR8380) By Anderson Banihirwe.
  * Xarray now defers to flox’s heuristics to set the default
    method for groupby problems. This only applies to flox>=0.9. By
    Deepak Cherian.
  * All quantile methods (e.g. DataArray.quantile()) now use
    numbagg for the calculation of nanquantiles (i.e., skipna=True)
    if it is installed. This is currently limited to the linear
    interpolation method (method=’linear’). (GH7377, PR8684) By
    Marco Wolsza.
  ## Breaking changes
  * infer_freq() always returns the frequency strings as defined in
    pandas 2.2 (GH8612, PR8627). By Mathias Hauser.
  * Deprecations
  * The dt.weekday_name parameter wasn’t functional on modern
    pandas versions and has been removed. (GH8610, PR8664) By Sam
    Coleman.
  ## Bug fixes
  * Fixed a regression that prevented multi-index level coordinates
    being serialized after resetting or dropping the multi-index
    (GH8628, PR8672). By Benoit Bovy.

OBS-URL: https://build.opensuse.org/request/show/1152304
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-xarray?expand=0&rev=90
This commit is contained in:
Matej Cepl 2024-02-29 08:58:33 +00:00 committed by Git OBS Bridge
parent 531768215c
commit 7b4792ad94
5 changed files with 255 additions and 51 deletions
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_multibuild Normal file
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<multibuild>
<package>test</package>
</multibuild>

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python-xarray.changes
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-------------------------------------------------------------------
Tue Feb 27 10:56:32 UTC 2024 - Ben Greiner <code@bnavigator.de>
- Update to 2024.2.0
* This release brings size information to the text repr, changes
to the accepted frequency strings, and various bug fixes.
## New Features
* Added a simple nbytes representation in DataArrays and Dataset
repr. (GH8690, PR8702). By Etienne Schalk.
* Allow negative frequency strings (e.g. "-1YE"). These strings
are for example used in date_range(), and cftime_range()
(PR8651). By Mathias Hauser.
* Add NamedArray.expand_dims(), NamedArray.permute_dims() and
NamedArray.broadcast_to() (PR8380) By Anderson Banihirwe.
* Xarray now defers to flox’s heuristics to set the default
method for groupby problems. This only applies to flox>=0.9. By
Deepak Cherian.
* All quantile methods (e.g. DataArray.quantile()) now use
numbagg for the calculation of nanquantiles (i.e., skipna=True)
if it is installed. This is currently limited to the linear
interpolation method (method=’linear’). (GH7377, PR8684) By
Marco Wolsza.
## Breaking changes
* infer_freq() always returns the frequency strings as defined in
pandas 2.2 (GH8612, PR8627). By Mathias Hauser.
* Deprecations
* The dt.weekday_name parameter wasn’t functional on modern
pandas versions and has been removed. (GH8610, PR8664) By Sam
Coleman.
## Bug fixes
* Fixed a regression that prevented multi-index level coordinates
being serialized after resetting or dropping the multi-index
(GH8628, PR8672). By Benoit Bovy.
* Fix bug with broadcasting when wrapping array API-compliant
classes. (GH8665, PR8669) By Tom Nicholas.
* Ensure DataArray.unstack() works when wrapping array
API-compliant classes. (GH8666, PR8668) By Tom Nicholas.
* Fix negative slicing of Zarr arrays without dask installed.
(GH8252) By Deepak Cherian.
* Preserve chunks when writing time-like variables to zarr by
enabling lazy CF encoding of time-like variables (GH7132,
GH8230, GH8432, PR8575). By Spencer Clark and Mattia Almansi.
* Preserve chunks when writing time-like variables to zarr by
enabling their lazy encoding (GH7132, GH8230, GH8432, PR8253,
PR8575; see also discussion in PR8253). By Spencer Clark and
Mattia Almansi.
* Raise an informative error if dtype encoding of time-like
variables would lead to integer overflow or unsafe conversion
from floating point to integer values (GH8542, PR8575). By
Spencer Clark.
* Raise an error when unstacking a MultiIndex that has duplicates
as this would lead to silent data loss (GH7104, PR8737). By
Mathias Hauser.
- Release 2024.1.1
## Breaking changes
* Following pandas, infer_freq() will return "YE", instead of "Y"
(formerly "A"). This is to be consistent with the deprecation
of the latter frequency string in pandas 2.2. This is a follow
up to PR8415 (GH8612, PR8642). By Mathias Hauser.
## Deprecations
* Following pandas, the frequency string "Y" (formerly "A") is
deprecated in favor of "YE". These strings are used, for
example, in date_range(), cftime_range(), DataArray.resample(),
and Dataset.resample() among others (GH8612, PR8629). By
Mathias Hauser.
- Release 2024.1.0
* This release brings support for weights in correlation and
covariance functions, a new DataArray.cumulative aggregation,
improvements to xr.map_blocks, an update to our minimum
dependencies, and various bugfixes.
## New Features
* xr.cov() and xr.corr() now support using weights (GH8527,
PR7392). By Llorenç Lledó.
* Accept the compression arguments new in netCDF 1.6.0 in the
netCDF4 backend. See netCDF4 documentation for details. Note
that some new compression filters needs plugins to be installed
which may not be available in all netCDF distributions. By
Markel García-Díez. (GH6929, PR7551)
* Add DataArray.cumulative() & Dataset.cumulative() to compute
cumulative aggregations, such as sum, along a dimension — for
example da.cumulative('time').sum(). This is similar to pandas’
.expanding, and mostly equivalent to .cumsum methods, or to
DataArray.rolling() with a window length equal to the dimension
size. By Maximilian Roos. (PR8512)
* Decode/Encode netCDF4 enums and store the enum definition in
dataarrays’ dtype metadata. If multiple variables share the
same enum in netCDF4, each dataarray will have its own enum
definition in their respective dtype metadata. By Abel Aoun.
(GH8144, PR8147)
## Deprecations
* The squeeze kwarg to GroupBy is now deprecated. (GH2157,
PR8507) By Deepak Cherian.
## Bug fixes
* Support non-string hashable dimensions in xarray.DataArray
(GH8546, PR8559). By Michael Niklas.
* Reverse index output of bottleneck’s rolling
move_argmax/move_argmin functions (GH8541, PR8552). By Kai
Mühlbauer.
* Vendor SerializableLock from dask and use as default lock for
netcdf4 backends (GH8442, PR8571). By Kai Mühlbauer.
* Add tests and fixes for empty CFTimeIndex, including broken
html repr (GH7298, PR8600). By Mathias Hauser.
- Create subpackages for the python [extras], test dependencies
with _multibuild
-------------------------------------------------------------------
Thu Jan 4 11:16:58 UTC 2024 - Sebastian Wagner <sebix@sebix.at>

192
python-xarray.spec
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@ -16,9 +16,18 @@
#
%global flavor @BUILD_FLAVOR@%{nil}
%if "%{flavor}" == "test"
%bcond_without test
%define psuffix -test
%else
%bcond_with test
%define psuffix %{nil}
%endif
%{?sle15_python_module_pythons}
Name: python-xarray
Version: 2023.12.0
Name: python-xarray%{psuffix}
Version: 2024.2.0
Release: 0
Summary: N-D labeled arrays and datasets in Python
License: Apache-2.0
@ -28,58 +37,20 @@ Source: https://files.pythonhosted.org/packages/source/x/xarray/xarray-%
# fix xr.tutorial.open_dataset to work with the preloaded cache.
Patch0: local_dataset.patch
BuildRequires: %{python_module base >= 3.9}
BuildRequires: %{python_module numpy-devel >= 1.22}
BuildRequires: %{python_module packaging >= 21.3}
BuildRequires: %{python_module pandas >= 1.4}
BuildRequires: %{python_module pip}
BuildRequires: %{python_module setuptools_scm}
BuildRequires: %{python_module setuptools}
BuildRequires: %{python_module wheel}
BuildRequires: fdupes
BuildRequires: python-rpm-macros
Requires: python-numpy >= 1.22
Requires: python-packaging >= 21.3
Requires: python-pandas >= 1.4
Provides: python-xray = %{version}
Obsoletes: python-xray < %{version}
Requires: python-numpy >= 1.23
Requires: python-packaging >= 22
Requires: python-pandas >= 1.5
Obsoletes: python-xray <= 0.7
BuildArch: noarch
# SECTION extras accel
Recommends: python-scipy
Recommends: python-bottleneck
Recommends: python-flox
Recommends: python-numbagg
# /SECTION
# SECTION extras parallalel
Suggests: python-dask-complete
# /SECTION
# SECTION extras viz
Suggests: python-matplotlib
Suggests: python-seaborn
Suggests: python-nc-time-axis
#/SECTION
# SECTION extras io
Suggests: python-netCDF4
Suggests: python-h5netcdf
Suggests: (python-pydap if python-base < 3.10)
Suggests: python-zarr
Suggests: python-fsspec
Suggests: python-cftime
Suggests: python-rasterio
Suggests: python-cfgrib
Suggests: python-pooch
#/SECTION
# SECTION tests
BuildRequires: %{python_module Bottleneck}
BuildRequires: %{python_module dask-dataframe}
BuildRequires: %{python_module dask-diagnostics}
BuildRequires: %{python_module h5netcdf}
BuildRequires: %{python_module matplotlib}
BuildRequires: %{python_module netCDF4}
BuildRequires: %{python_module pooch}
BuildRequires: %{python_module pytest-xdist}
BuildRequires: %{python_module pytest}
BuildRequires: %{python_module scipy}
BuildRequires: %{python_module zarr}
%if %{with test}
BuildRequires: %{python_module xarray-complete = %{version}}
%endif
# /SECTION
%python_subpackages
@ -92,18 +63,113 @@ 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.
%package accel
# for minimum versions, check ci/requirements/min-all-deps.yml
Summary: The python xarray[accel] extra
Requires: python-Bottleneck >= 1.3
Requires: python-opt-einsum
Requires: python-scipy
Requires: python-xarray = %{version}
# not available yet
Recommends: python-flox >= 0.7
Recommends: python-numbagg
%description accel
The [accel] extra for xarray, N-D labeled arrays and datasets in Python
Except flox and numbagg, because they are not packaged yet.
Use `pip-%{python_bin_suffix} --user install flox numbagg` to install from PyPI, if needed.
%package complete
Summary: The python xarray[complete] extra
Requires: python-xarray = %{version}
Requires: python-xarray-accel = %{version}
Requires: python-xarray-dev = %{version}
Requires: python-xarray-io = %{version}
Requires: python-xarray-parallel = %{version}
Requires: python-xarray-viz = %{version}
%description complete
The [complete] extra for xarray, N-D labeled arrays and datasets in Python
%package dev
Summary: The python xarray[dev] extra
Requires: python-hypothesis
Requires: python-pytest
Requires: python-pytest-cov
Requires: python-pytest-env
Requires: python-pytest-timeout
Requires: python-pytest-xdist
Requires: python-ruff
Requires: python-xarray = %{version}
Requires: python-xarray-complete = %{version}
# Not available and not really useful for us
Recommends: python-pre-commit
%description dev
The [dev] extra for xarray, N-D labeled arrays and datasets in Python
Except pre-commit, Use `pip-%{python_bin_suffix} --user install pre-commit` to install, if needed.
%package io
Summary: The python xarray[io] extra
Requires: python-cftime >= 1.6
Requires: python-fsspec
Requires: python-h5netcdf >= 1.1
Requires: python-netCDF4 >= 1.6
Requires: python-pooch
Requires: python-scipy >= 1.10
Requires: python-xarray = %{version}
Requires: python-zarr >= 2.13
Requires: (python-pydap >= 3.3 if python-base < 3.10)
%description io
The [io] extra for xarray, N-D labeled arrays and datasets in Python
%package parallel
Summary: The python xarray[parallel] extra
Requires: python-dask-complete >= 2022.12
Requires: python-xarray = %{version}
%description parallel
The [parallel] extra for xarray, N-D labeled arrays and datasets in Python
%package viz
Summary: The python xarray[viz] extra
Requires: python-matplotlib >= 3.6
Requires: python-seaborn >= 0.12
Requires: python-xarray = %{version}
# Not available yet
Recommends: python-nc-time-axis
%description viz
The [viz] extra for xarray, N-D labeled arrays and datasets in Python
Except nc-time-axis, because it's not packaged yet.
Use `pip-%{python_bin_suffix} --user install nc-time-axis` to install from PyPI, if needed.
%prep
%autosetup -p1 -n xarray-%{version}
%if "%{version}" == "2024.2.0"
# gh#pydata/xarray#8768, remove this after the next update!
rm -r xarray/tests/datatree
%else
echo "You failed to update the specfile"
exit 1
%endif
chmod -x xarray/util/print_versions.py
%build
%if !%{with test}
%pyproject_wheel
%endif
%install
%if !%{with test}
%pyproject_install
%python_expand %fdupes %{buildroot}%{$python_sitelib}
%endif
%if %{with test}
%check
# obs file open race conditions?
donttest="(test_open_mfdataset_manyfiles and (h5netcdf or netCDF4))"
@ -117,12 +183,42 @@ if [ $(getconf LONG_BIT) -eq 32 ]; then
fi
# h5py was built without ROS3 support, can't use ros3 driver
donttest="$donttest or TestH5NetCDFDataRos3Driver"
%pytest -n auto -rsEf -k "not ($donttest)" xarray
# NetCDF4 fails with these unsupported drivers
donttest="$donttest or (TestNetCDF4 and test_compression_encoding and (szip or zstd or blosc_lz or blosc_zlib))"
%pytest -n auto -rsEf -k "not ($donttest)" xarray
%endif
%if !%{with test}
%files %{python_files}
%doc README.md
%license LICENSE licenses/
%{python_sitelib}/xarray
%{python_sitelib}/xarray-%{version}.dist-info
%files %{python_files accel}
%doc README.md
%license LICENSE
%files %{python_files complete}
%doc README.md
%license LICENSE
%files %{python_files dev}
%doc README.md
%license LICENSE
%files %{python_files io}
%doc README.md
%license LICENSE
%files %{python_files parallel}
%doc README.md
%license LICENSE
%files %{python_files viz}
%doc README.md
%license LICENSE
%endif
%changelog

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