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DOC: update whatsnew for xarray 0.11 release (pydata#2548)
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doc/whats-new.rst

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@@ -33,23 +33,8 @@ v0.11.0 (unreleased)
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Breaking changes
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~~~~~~~~~~~~~~~~
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- For non-standard calendars commonly used in climate science, xarray will now
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always use :py:class:`cftime.datetime` objects, rather than by default try to
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coerce them to ``np.datetime64[ns]`` objects. A
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:py:class:`~xarray.CFTimeIndex` will be used for indexing along time
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coordinates in these cases. A new method,
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:py:meth:`~xarray.CFTimeIndex.to_datetimeindex`, has been added
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to aid in converting from a :py:class:`~xarray.CFTimeIndex` to a
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:py:class:`pandas.DatetimeIndex` for the remaining use-cases where
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using a :py:class:`~xarray.CFTimeIndex` is still a limitation (e.g. for
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resample or plotting). Setting the ``enable_cftimeindex`` option is now a
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no-op and emits a ``FutureWarning``.
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- ``Dataset.T`` has been removed as a shortcut for :py:meth:`Dataset.transpose`.
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Call :py:meth:`Dataset.transpose` directly instead.
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- Iterating over a ``Dataset`` now includes only data variables, not coordinates.
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Similarily, calling ``len`` and ``bool`` on a ``Dataset`` now
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includes only data variables
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- Finished deprecation cycles:
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- Finished deprecations (changed behavior with this release):
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- ``Dataset.T`` has been removed as a shortcut for :py:meth:`Dataset.transpose`.
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Call :py:meth:`Dataset.transpose` directly instead.
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- Iterating over a ``Dataset`` now includes only data variables, not coordinates.
@@ -62,34 +47,49 @@ Breaking changes
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raise an error in most cases. You need to use the new resample syntax
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instead, e.g., ``data.resample(time='1D').mean()`` or
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``data.resample({'time': '1D'}).mean()``.
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- Xarray's storage backends now automatically open and close files when
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necessary, rather than requiring opening a file with ``autoclose=True``. A
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global least-recently-used cache is used to store open files; the default
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limit of 128 open files should suffice in most cases, but can be adjusted if
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necessary with
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``xarray.set_options(file_cache_maxsize=...)``. The ``autoclose`` argument
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to ``open_dataset`` and related functions has been deprecated and is now a
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no-op.
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This change, along with an internal refactor of xarray's storage backends,
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should significantly improve performance when reading and writing
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netCDF files with Dask, especially when working with many files or using
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Dask Distributed. By `Stephan Hoyer <https://github.com/shoyer>`_
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- Tutorial data is now loaded lazily. Previous behavior of
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:py:meth:`xarray.tutorial.load_dataset` would call `Dataset.load()` prior
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to returning. This was changed in order to facilitate using this data with
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dask.
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By `Joe Hamman <https://github.com/jhamman>`_.
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Documentation
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~~~~~~~~~~~~~
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- Reduction of :py:meth:`DataArray.groupby` and :py:meth:`DataArray.resample`
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without dimension argument will change in the next release.
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Now we warn a FutureWarning.
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By `Keisuke Fujii <https://github.com/fujiisoup>`_.
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- The ``inplace`` kwarg of a number of `DataArray` and `Dataset` methods is being
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deprecated and will be removed in the next release.
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By `Deepak Cherian <https://github.com/dcherian>`_.
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- New deprecations (behavior will be changed in xarray 0.12):
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- Reduction of :py:meth:`DataArray.groupby` and :py:meth:`DataArray.resample`
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without dimension argument will change in the next release.
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Now we warn a FutureWarning.
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By `Keisuke Fujii <https://github.com/fujiisoup>`_.
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- The ``inplace`` kwarg of a number of `DataArray` and `Dataset` methods is being
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deprecated and will be removed in the next release.
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By `Deepak Cherian <https://github.com/dcherian>`_.
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- Refactored storage backends:
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- Xarray's storage backends now automatically open and close files when
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necessary, rather than requiring opening a file with ``autoclose=True``. A
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global least-recently-used cache is used to store open files; the default
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limit of 128 open files should suffice in most cases, but can be adjusted if
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necessary with
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``xarray.set_options(file_cache_maxsize=...)``. The ``autoclose`` argument
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to ``open_dataset`` and related functions has been deprecated and is now a
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no-op.
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This change, along with an internal refactor of xarray's storage backends,
75+
should significantly improve performance when reading and writing
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netCDF files with Dask, especially when working with many files or using
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Dask Distributed. By `Stephan Hoyer <https://github.com/shoyer>`_
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- Support for non-standard calendars used in climate science:
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- Xarray will now always use :py:class:`cftime.datetime` objects, rather
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than by default trying to coerce them into ``np.datetime64[ns]`` objects.
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A :py:class:`~xarray.CFTimeIndex` will be used for indexing along time
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coordinates in these cases.
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- A new method :py:meth:`~xarray.CFTimeIndex.to_datetimeindex` has been added
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to aid in converting from a :py:class:`~xarray.CFTimeIndex` to a
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:py:class:`pandas.DatetimeIndex` for the remaining use-cases where
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using a :py:class:`~xarray.CFTimeIndex` is still a limitation (e.g. for
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resample or plotting).
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- Setting the ``enable_cftimeindex`` option is now a no-op and emits a
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``FutureWarning``.
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Enhancements
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~~~~~~~~~~~~
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consistent with other xarray functions that accept either dictionaries or
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keyword arguments. By `Stephan Hoyer <https://github.com/shoyer>`_.
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- The preferred way to access tutorial data is now to load it lazily with
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:py:meth:`xarray.tutorial.open_dataset`.
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:py:meth:`xarray.tutorial.load_dataset` calls `Dataset.load()` prior
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to returning (and is now deprecated). This was changed in order to facilitate
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using tutorial datasets with dask.
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By `Joe Hamman <https://github.com/jhamman>`_.
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Bug fixes
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~~~~~~~~~
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setup.py

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2020
'Programming Language :: Python :: 3',
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'Programming Language :: Python :: 3.5',
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'Programming Language :: Python :: 3.6',
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'Programming Language :: Python :: 3.7',
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'Topic :: Scientific/Engineering',
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]
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