Merge remote-tracking branch 'upstream/main' into feature/rolling-pad

* upstream/main:
  Save groupby codes after factorizing, pass to flox (pydata#7206)
  [skip-ci] Add compute to groupby benchmarks (pydata#7690)
  Delete built-in cfgrib backend (pydata#7670)
  Added a pronunciation guide to the word Xarray in the README.MD fil… (pydata#7677)
  boundarynorm fix (pydata#7553)
  Fix lazy negative slice rewriting. (pydata#7586)
  [pre-commit.ci] pre-commit autoupdate (pydata#7687)
  Adjust sidebar font colors (pydata#7674)
  Bump pypa/gh-action-pypi-publish from 1.8.1 to 1.8.3 (pydata#7682)
  Raise PermissionError when insufficient permissions (pydata#7629)

.github/workflows/pypi-release.yaml

@@ -72,7 +72,7 @@ jobs:
 
       - name: Publish package to TestPyPI
         if: github.event_name == 'push'
-        uses: pypa/[email protected].1
+        uses: pypa/[email protected].3
         with:
           user: __token__
           password: ${{ secrets.TESTPYPI_TOKEN }}
@@ -90,7 +90,7 @@ jobs:
           name: releases
           path: dist
       - name: Publish package to PyPI
-        uses: pypa/[email protected].1
+        uses: pypa/[email protected].3
         with:
           user: __token__
           password: ${{ secrets.PYPI_TOKEN }}

.github/workflows/testpypi-release.yaml

@@ -78,7 +78,7 @@ jobs:
 
       - name: Publish package to TestPyPI
         if: github.event_name == 'push'
-        uses: pypa/[email protected].1
+        uses: pypa/[email protected].3
         with:
           user: __token__
           password: ${{ secrets.TESTPYPI_TOKEN }}

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
         files: ^xarray/
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.0.257'
+    rev: 'v0.0.259'
     hooks:
       - id: ruff
         args: ["--fix"]

README.md

@@ -11,7 +11,7 @@
 [![Examples on binder](https://img.shields.io/badge/launch-binder-579ACA.svg?logo=data:image/png;base64,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)](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/weather-data.ipynb)
 [![Twitter](https://img.shields.io/twitter/follow/xarray_dev?style=social)](https://twitter.com/xarray_dev)
 
-**xarray** (formerly **xray**) is an open source project and Python
+**xarray** (pronounced "ex-array", formerly known as **xray**) is an open source project and Python
 package that makes working with labelled multi-dimensional arrays
 simple, efficient, and fun!
 

asv_bench/benchmarks/groupby.py

@@ -1,3 +1,5 @@
+# import flox to avoid the cost of first import
+import flox.xarray  # noqa
 import numpy as np
 import pandas as pd
 
@@ -27,24 +29,24 @@ def time_init(self, ndim):
     @parameterized(["method", "ndim"], [("sum", "mean"), (1, 2)])
     def time_agg_small_num_groups(self, method, ndim):
         ds = getattr(self, f"ds{ndim}d")
-        getattr(ds.groupby("a"), method)()
+        getattr(ds.groupby("a"), method)().compute()
 
     @parameterized(["method", "ndim"], [("sum", "mean"), (1, 2)])
     def time_agg_large_num_groups(self, method, ndim):
         ds = getattr(self, f"ds{ndim}d")
-        getattr(ds.groupby("b"), method)()
+        getattr(ds.groupby("b"), method)().compute()
 
     def time_binary_op_1d(self):
-        self.ds1d.groupby("b") - self.ds1d_mean
+        (self.ds1d.groupby("b") - self.ds1d_mean).compute()
 
     def time_binary_op_2d(self):
-        self.ds2d.groupby("b") - self.ds2d_mean
+        (self.ds2d.groupby("b") - self.ds2d_mean).compute()
 
     def peakmem_binary_op_1d(self):
-        self.ds1d.groupby("b") - self.ds1d_mean
+        (self.ds1d.groupby("b") - self.ds1d_mean).compute()
 
     def peakmem_binary_op_2d(self):
-        self.ds2d.groupby("b") - self.ds2d_mean
+        (self.ds2d.groupby("b") - self.ds2d_mean).compute()
 
 
 class GroupByDask(GroupBy):
@@ -56,8 +58,8 @@ def setup(self, *args, **kwargs):
         self.ds1d["c"] = self.ds1d["c"].chunk({"dim_0": 50})
         self.ds2d = self.ds2d.sel(dim_0=slice(None, None, 2))
         self.ds2d["c"] = self.ds2d["c"].chunk({"dim_0": 50, "z": 5})
-        self.ds1d_mean = self.ds1d.groupby("b").mean()
-        self.ds2d_mean = self.ds2d.groupby("b").mean()
+        self.ds1d_mean = self.ds1d.groupby("b").mean().compute()
+        self.ds2d_mean = self.ds2d.groupby("b").mean().compute()
 
 
 class GroupByPandasDataFrame(GroupBy):
@@ -88,7 +90,7 @@ def setup(self, *args, **kwargs):
         requires_dask()
         super().setup(**kwargs)
         self.ds1d = self.ds1d.chunk({"dim_0": 50}).to_dataframe()
-        self.ds1d_mean = self.ds1d.groupby("b").mean()
+        self.ds1d_mean = self.ds1d.groupby("b").mean().compute()
 
     def time_binary_op_2d(self):
         raise NotImplementedError
@@ -116,12 +118,12 @@ def time_init(self, ndim):
     @parameterized(["method", "ndim"], [("sum", "mean"), (1, 2)])
     def time_agg_small_num_groups(self, method, ndim):
         ds = getattr(self, f"ds{ndim}d")
-        getattr(ds.resample(time="3M"), method)()
+        getattr(ds.resample(time="3M"), method)().compute()
 
     @parameterized(["method", "ndim"], [("sum", "mean"), (1, 2)])
     def time_agg_large_num_groups(self, method, ndim):
         ds = getattr(self, f"ds{ndim}d")
-        getattr(ds.resample(time="48H"), method)()
+        getattr(ds.resample(time="48H"), method)().compute()
 
 
 class ResampleDask(Resample):

ci/requirements/all-but-dask.yml

@@ -10,7 +10,6 @@ dependencies:
   - bottleneck
   - cartopy
   - cdms2
-  - cfgrib
   - cftime
   - coveralls
   - flox

ci/requirements/doc.yml

@@ -7,7 +7,6 @@ dependencies:
   - python=3.10
   - bottleneck
   - cartopy
-  - cfgrib>=0.9
   - dask-core>=2022.1
   - h5netcdf>=0.13
   - ipykernel

ci/requirements/environment-py311.yml

@@ -8,7 +8,6 @@ dependencies:
   - bottleneck
   - cartopy
   # - cdms2
-  - cfgrib
   - cftime
   - dask-core
   - distributed

ci/requirements/environment-windows-py311.yml

@@ -6,7 +6,6 @@ dependencies:
   - bottleneck
   - cartopy
   # - cdms2  # Not available on Windows
-  # - cfgrib  # Causes Python interpreter crash on Windows: https://github.com/pydata/xarray/pull/3340
   - cftime
   - dask-core
   - distributed

ci/requirements/environment-windows.yml

@@ -6,7 +6,6 @@ dependencies:
   - bottleneck
   - cartopy
   # - cdms2  # Not available on Windows
-  # - cfgrib  # Causes Python interpreter crash on Windows: https://github.com/pydata/xarray/pull/3340
   - cftime
   - dask-core
   - distributed

ci/requirements/environment.yml

@@ -8,7 +8,6 @@ dependencies:
   - bottleneck
   - cartopy
   - cdms2
-  - cfgrib
   - cftime
   - dask-core
   - distributed

ci/requirements/min-all-deps.yml

@@ -12,7 +12,6 @@ dependencies:
   - bottleneck=1.3
   - cartopy=0.20
   - cdms2=3.1
-  - cfgrib=0.9
   - cftime=1.5
   - coveralls
   - dask-core=2022.1

doc/_static/style.css

@@ -172,19 +172,16 @@ https://github.com/bokeh/bokeh/blob/branch-2.4/sphinx/source/bokeh/static/custom
   display: block;
   padding: 0.25rem 1.5rem;
   font-size: 90%;
-  color: rgba(0, 0, 0, 0.65);
 }
 
 .bd-sidebar .nav > li > a:hover {
-  color: rgba(0, 0, 0, 0.85);
   text-decoration: none;
   background-color: transparent;
 }
 
 .bd-sidebar .nav > .active > a,
 .bd-sidebar .nav > .active:hover > a {
   font-weight: 400;
-  color: #130654;
   /* adjusted from original
   color: rgba(0, 0, 0, 0.85);
   background-color: transparent; */
@@ -199,13 +196,11 @@ https://github.com/bokeh/bokeh/blob/branch-2.4/sphinx/source/bokeh/static/custom
   display: block;
   padding: 0.25rem 1.5rem;
   font-size: 90%;
-  color: rgba(0, 0, 0, 0.65);
 }
 
 .bd-sidebar .nav > li > ul > .active > a,
 .bd-sidebar .nav > li > ul > .active:hover > a {
   font-weight: 400;
-  color: #542437;
 }
 
 dt:target {

doc/getting-started-guide/installing.rst

@@ -45,8 +45,6 @@ For netCDF and IO
   other gridded raster datasets.
 - `iris <https://github.com/scitools/iris>`__: for conversion to and from iris'
   Cube objects
-- `cfgrib <https://github.com/ecmwf/cfgrib>`__: for reading GRIB files via the
-  *ECMWF ecCodes* library.
 
 For accelerating xarray
 ~~~~~~~~~~~~~~~~~~~~~~~

doc/user-guide/io.rst

@@ -1257,7 +1257,7 @@ GRIB format via cfgrib
 
 Xarray supports reading GRIB files via ECMWF cfgrib_ python driver,
 if it is installed. To open a GRIB file supply ``engine='cfgrib'``
-to :py:func:`open_dataset`:
+to :py:func:`open_dataset` after installing cfgrib_:
 
 .. ipython::
     :verbatim:

doc/whats-new.rst

@@ -39,6 +39,10 @@ Bug fixes
 
 - Fix :py:meth:`xr.polyval` with non-system standard integer coeffs (:pull:`7619`).
   By `Shreyal Gupta <https://github.com/Ravenin7>`_ and `Michael Niklas <https://github.com/headtr1ck>`_.
+- Improve error message when trying to open a file which you do not have permission to read (:issue:`6523`, :pull:`7629`).
+  By `Thomas Coleman <https://github.com/ColemanTom>`_.
+- Proper plotting when passing :py:class:`~matplotlib.colors.BoundaryNorm` type argument in :py:meth:`DataArray.plot`. (:issue:`4061`, :issue:`7014`,:pull:`7553`)
+  By `Jelmer Veenstra <https://github.com/veenstrajelmer>`_.
 
 Documentation
 ~~~~~~~~~~~~~
@@ -49,6 +53,10 @@ Documentation
 Internal Changes
 ~~~~~~~~~~~~~~~~
 
+- Remove internal support for reading GRIB files through the ``cfgrib`` backend. ``cfgrib`` now uses the external
+  backend interface, so no existing code should break.
+  By `Deepak Cherian <https://github.com/dcherian>`_.
+
 .. _whats-new.2023.03.0:
 
 v2023.03.0 (March 22, 2023)

setup.cfg

@@ -89,7 +89,6 @@ io =
     fsspec
     cftime
     rasterio
-    cfgrib
     pooch
     ## Scitools packages & dependencies (e.g: cartopy, cf-units) can be hard to install
     # scitools-iris

xarray/backends/__init__.py

@@ -3,7 +3,6 @@
 DataStores provide a uniform interface for saving and loading data in different
 formats. They should not be used directly, but rather through Dataset objects.
 """
-from xarray.backends.cfgrib_ import CfGribDataStore
 from xarray.backends.common import AbstractDataStore, BackendArray, BackendEntrypoint
 from xarray.backends.file_manager import (
     CachingFileManager,
@@ -30,7 +29,6 @@
     "BackendEntrypoint",
     "FileManager",
     "CachingFileManager",
-    "CfGribDataStore",
     "DummyFileManager",
     "InMemoryDataStore",
     "NetCDF4DataStore",

xarray/backends/api.py

@@ -43,7 +43,7 @@
     T_NetcdfEngine = Literal["netcdf4", "scipy", "h5netcdf"]
     T_Engine = Union[
         T_NetcdfEngine,
-        Literal["pydap", "pynio", "pseudonetcdf", "cfgrib", "zarr"],
+        Literal["pydap", "pynio", "pseudonetcdf", "zarr"],
         type[BackendEntrypoint],
         str,  # no nice typing support for custom backends
         None,
@@ -64,7 +64,6 @@
     "h5netcdf": backends.H5NetCDFStore.open,
     "pynio": backends.NioDataStore,
     "pseudonetcdf": backends.PseudoNetCDFDataStore.open,
-    "cfgrib": backends.CfGribDataStore,
     "zarr": backends.ZarrStore.open_group,
 }
 
@@ -387,7 +386,7 @@ def open_dataset(
         ends with .gz, in which case the file is gunzipped and opened with
         scipy.io.netcdf (only netCDF3 supported). Byte-strings or file-like
         objects are opened by scipy.io.netcdf (netCDF3) or h5py (netCDF4/HDF).
-    engine : {"netcdf4", "scipy", "pydap", "h5netcdf", "pynio", "cfgrib", \
+    engine : {"netcdf4", "scipy", "pydap", "h5netcdf", "pynio", \
         "pseudonetcdf", "zarr", None}, installed backend \
         or subclass of xarray.backends.BackendEntrypoint, optional
         Engine to use when reading files. If not provided, the default engine
@@ -479,7 +478,7 @@ def open_dataset(
           relevant when using dask or another form of parallelism. By default,
           appropriate locks are chosen to safely read and write files with the
           currently active dask scheduler. Supported by "netcdf4", "h5netcdf",
-          "scipy", "pynio", "pseudonetcdf", "cfgrib".
+          "scipy", "pynio", "pseudonetcdf".
 
         See engine open function for kwargs accepted by each specific engine.
 
@@ -576,7 +575,7 @@ def open_dataarray(
         ends with .gz, in which case the file is gunzipped and opened with
         scipy.io.netcdf (only netCDF3 supported). Byte-strings or file-like
         objects are opened by scipy.io.netcdf (netCDF3) or h5py (netCDF4/HDF).
-    engine : {"netcdf4", "scipy", "pydap", "h5netcdf", "pynio", "cfgrib", \
+    engine : {"netcdf4", "scipy", "pydap", "h5netcdf", "pynio", \
         "pseudonetcdf", "zarr", None}, installed backend \
         or subclass of xarray.backends.BackendEntrypoint, optional
         Engine to use when reading files. If not provided, the default engine
@@ -666,7 +665,7 @@ def open_dataarray(
           relevant when using dask or another form of parallelism. By default,
           appropriate locks are chosen to safely read and write files with the
           currently active dask scheduler. Supported by "netcdf4", "h5netcdf",
-          "scipy", "pynio", "pseudonetcdf", "cfgrib".
+          "scipy", "pynio", "pseudonetcdf".
 
         See engine open function for kwargs accepted by each specific engine.
 
@@ -803,7 +802,7 @@ def open_mfdataset(
         If provided, call this function on each dataset prior to concatenation.
         You can find the file-name from which each dataset was loaded in
         ``ds.encoding["source"]``.
-    engine : {"netcdf4", "scipy", "pydap", "h5netcdf", "pynio", "cfgrib", \
+    engine : {"netcdf4", "scipy", "pydap", "h5netcdf", "pynio", \
         "pseudonetcdf", "zarr", None}, installed backend \
         or subclass of xarray.backends.BackendEntrypoint, optional
         Engine to use when reading files. If not provided, the default engine