Merge branch 'main' into fix/dask_indexing

* main: (34 commits)
  Explicit indexes (pydata#5692)
  Remove test_rasterio_vrt_network (pydata#6371)
  Allow write_empty_chunks to be set in Zarr encoding (pydata#6348)
  Add new tutorial video (pydata#6353)
  Revert "explicitly install `ipython_genutils` (pydata#6350)" (pydata#6361)
  [pre-commit.ci] pre-commit autoupdate (pydata#6357)
  Run pyupgrade on core/groupby (pydata#6351)
  Generate reductions for DataArray, Dataset, GroupBy and Resample (pydata#5950)
  explicitly install `ipython_genutils` (pydata#6350)
  Bump actions/setup-python from 2 to 3 (pydata#6338)
  Bump actions/checkout from 2 to 3 (pydata#6337)
  In documentation on adding a new backend, add missing import and tweak headings (pydata#6330)
  Lengthen underline, correct spelling, and reword (pydata#6326)
  quantile: use skipna=None (pydata#6303)
  New whatsnew section
  v2022.03.0 release notes (pydata#6319)
  fix typos (using codespell) (pydata#6316)
  Add General issue template (pydata#6314)
  Disable CI runs on forks (pydata#6315)
  Enable running sphinx-build on Windows (pydata#6237)
  ...

Author: dcherian

.github/ISSUE_TEMPLATE/bugreport.yml

@@ -33,14 +33,14 @@ body:
 
         Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
         This will be automatically formatted into code, so no need for markdown backticks.
-      render: python
+      render: Python
 
   - type: textarea
     id: log-output
     attributes:
       label: Relevant log output
       description: Please copy and paste any relevant output. This will be automatically formatted into code, so no need for markdown backticks.
-      render: python
+      render: Python
 
   - type: textarea
     id: extra

.github/ISSUE_TEMPLATE/misc.yml

@@ -0,0 +1,17 @@
+name: Issue
+description: General Issue or discussion topic. For usage questions, please follow the "Usage question" link
+labels: ["needs triage"]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Please describe your issue here.
+  - type: textarea
+    id: issue-description
+    attributes:
+      label: What is your issue?
+      description: |
+        Thank you for filing an issue! Please give us further information on how we can help you.
+      placeholder: Please describe your issue.
+    validations:
+      required: true

.github/workflows/benchmarks.yml

@@ -16,7 +16,7 @@ jobs:
     steps:
       # We need the full repo to avoid this issue
       # https://github.com/actions/checkout/issues/23
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
 

.github/workflows/ci-additional.yaml

@@ -22,7 +22,7 @@ jobs:
     outputs:
       triggered: ${{ steps.detect-trigger.outputs.trigger-found }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 2
       - uses: xarray-contrib/[email protected]
@@ -53,7 +53,7 @@ jobs:
             "py39-flaky",
           ]
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0 # Fetch all history for all branches and tags.
 
@@ -119,12 +119,13 @@ jobs:
   doctest:
     name: Doctests
     runs-on: "ubuntu-latest"
+    if: needs.detect-ci-trigger.outputs.triggered == 'false'
     defaults:
       run:
         shell: bash -l {0}
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0 # Fetch all history for all branches and tags.
       - uses: conda-incubator/setup-miniconda@v2
@@ -161,7 +162,7 @@ jobs:
         shell: bash -l {0}
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0 # Fetch all history for all branches and tags.
       - uses: conda-incubator/setup-miniconda@v2

.github/workflows/ci.yaml

@@ -22,7 +22,7 @@ jobs:
     outputs:
       triggered: ${{ steps.detect-trigger.outputs.trigger-found }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 2
       - uses: xarray-contrib/[email protected]
@@ -44,7 +44,7 @@ jobs:
         # Bookend python versions
         python-version: ["3.8", "3.9", "3.10"]
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0 # Fetch all history for all branches and tags.
       - name: Set environment variables
@@ -115,6 +115,7 @@ jobs:
   event_file:
     name: "Event File"
     runs-on: ubuntu-latest
+    if: github.repository == 'pydata/xarray'
     steps:
       - name: Upload
         uses: actions/upload-artifact@v2

.github/workflows/pypi-release.yaml

@@ -12,10 +12,10 @@ jobs:
     runs-on: ubuntu-latest
     if: github.repository == 'pydata/xarray'
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v3
         name: Install Python
         with:
           python-version: 3.8
@@ -50,7 +50,7 @@ jobs:
     needs: build-artifacts
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v3
         name: Install Python
         with:
           python-version: 3.8

.github/workflows/upstream-dev-ci.yaml

@@ -24,7 +24,7 @@ jobs:
     outputs:
       triggered: ${{ steps.detect-trigger.outputs.trigger-found }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 2
       - uses: xarray-contrib/[email protected]
@@ -52,7 +52,7 @@ jobs:
     outputs:
       artifacts_availability: ${{ steps.status.outputs.ARTIFACTS_AVAILABLE }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0 # Fetch all history for all branches and tags.
       - uses: conda-incubator/setup-miniconda@v2
@@ -110,8 +110,8 @@ jobs:
       run:
         shell: bash
     steps:
-      - uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
+      - uses: actions/checkout@v3
+      - uses: actions/setup-python@v3
         with:
           python-version: "3.x"
       - uses: actions/download-artifact@v2

.gitignore

@@ -5,8 +5,9 @@ __pycache__
 .hypothesis/
 
 # temp files from docs build
+doc/*.nc
 doc/auto_gallery
-doc/example.nc
+doc/rasm.zarr
 doc/savefig
 
 # C extensions
@@ -72,4 +73,3 @@ xarray/tests/data/*.grib.*.idx
 Icon*
 
 .ipynb_checkpoints
-doc/rasm.zarr

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ repos:
     hooks:
       - id: isort
   - repo: https://github.com/asottile/pyupgrade
-    rev: v2.31.0
+    rev: v2.31.1
     hooks:
       - id: pyupgrade
         args:
@@ -45,7 +45,7 @@ repos:
   #     - id: velin
   #       args: ["--write", "--compact"]
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v0.931
+    rev: v0.940
     hooks:
       - id: mypy
         # Copied from setup.cfg

HOW_TO_RELEASE.md

@@ -109,6 +109,6 @@ upstream        https://github.com/pydata/xarray (push)
 
 ## Note on version numbering
 
-As of 2022.02.0, we utilize the [CALVER](https://calver.org/) version system.
+As of 2022.03.0, we utilize the [CALVER](https://calver.org/) version system.
 Specifically, we have adopted the pattern `YYYY.MM.X`, where `YYYY` is a 4-digit
 year (e.g. `2022`), `MM` is a 2-digit zero-padded month (e.g. `01` for January), and `X` is the release number (starting at zero at the start of each month and incremented once for each additional release).

ci/requirements/environment.yml

@@ -37,6 +37,7 @@ dependencies:
   - pytest
   - pytest-cov
   - pytest-env
+  - pytest-github-actions-annotate-failures
   - pytest-xdist
   - rasterio
   - scipy

doc/api.rst

@@ -106,6 +106,7 @@ Dataset contents
    Dataset.swap_dims
    Dataset.expand_dims
    Dataset.drop_vars
+   Dataset.drop_duplicates
    Dataset.drop_dims
    Dataset.set_coords
    Dataset.reset_coords

doc/conf.py

@@ -28,9 +28,9 @@
 print("python exec:", sys.executable)
 print("sys.path:", sys.path)
 
-if "conda" in sys.executable:
+if "CONDA_DEFAULT_ENV" in os.environ or "conda" in sys.executable:
     print("conda environment:")
-    subprocess.run(["conda", "list"])
+    subprocess.run([os.environ.get("CONDA_EXE", "conda"), "list"])
 else:
     print("pip environment:")
     subprocess.run([sys.executable, "-m", "pip", "list"])

doc/contributing.rst

@@ -274,13 +274,13 @@ Some other important things to know about the docs:
       .. ipython:: python
 
           x = 2
-          x ** 3
+          x**3
 
   will be rendered as::
 
       In [1]: x = 2
 
-      In [2]: x ** 3
+      In [2]: x**3
       Out[2]: 8
 
   Almost all code examples in the docs are run (and the output saved) during the

doc/ecosystem.rst

@@ -17,6 +17,7 @@ Geosciences
 - `climpred <https://climpred.readthedocs.io>`_: Analysis of ensemble forecast models for climate prediction.
 - `geocube <https://corteva.github.io/geocube>`_: Tool to convert geopandas vector data into rasterized xarray data.
 - `GeoWombat <https://github.com/jgrss/geowombat>`_: Utilities for analysis of remotely sensed and gridded raster data at scale (easily tame Landsat, Sentinel, Quickbird, and PlanetScope).
+- `gsw-xarray <https://github.com/DocOtak/gsw-xarray>`_: a wrapper around `gsw <https://teos-10.github.io/GSW-Python>`_ that adds CF compliant attributes when possible, units, name.
 - `infinite-diff <https://github.com/spencerahill/infinite-diff>`_: xarray-based finite-differencing, focused on gridded climate/meteorology data
 - `marc_analysis <https://github.com/darothen/marc_analysis>`_: Analysis package for CESM/MARC experiments and output.
 - `MetPy <https://unidata.github.io/MetPy/dev/index.html>`_: A collection of tools in Python for reading, visualizing, and performing calculations with weather data.

doc/examples/ROMS_ocean_model.ipynb

@@ -77,7 +77,7 @@
     "ds = xr.tutorial.open_dataset(\"ROMS_example.nc\", chunks={\"ocean_time\": 1})\n",
     "\n",
     "# This is a way to turn on chunking and lazy evaluation. Opening with mfdataset, or\n",
-    "# setting the chunking in the open_dataset would also achive this.\n",
+    "# setting the chunking in the open_dataset would also achieve this.\n",
     "ds"
    ]
   },

doc/gallery/plot_colorbar_center.py

@@ -38,6 +38,6 @@
 ax4.set_title("Celsius: center=False")
 ax4.set_ylabel("")
 
-# Mke it nice
+# Make it nice
 plt.tight_layout()
 plt.show()

doc/getting-started-guide/quick-overview.rst

@@ -215,13 +215,15 @@ You can directly read and write xarray objects to disk using :py:meth:`~xarray.D
 .. ipython:: python
 
     ds.to_netcdf("example.nc")
-    xr.open_dataset("example.nc")
+    reopened = xr.open_dataset("example.nc")
+    reopened
 
 .. ipython:: python
     :suppress:
 
     import os
 
+    reopened.close()
     os.remove("example.nc")
 
 

doc/internals/how-to-add-new-backend.rst

@@ -172,6 +172,7 @@ Xarray :py:meth:`~xarray.open_dataset`, and returns a boolean.
 
 Decoders
 ^^^^^^^^
+
 The decoders implement specific operations to transform data from on-disk
 representation to Xarray representation.
 
@@ -199,6 +200,11 @@ performs the inverse transformation.
 
 In the following an example on how to use the coders ``decode`` method:
 
+.. ipython:: python
+    :suppress:
+
+    import xarray as xr
+
 .. ipython:: python
 
     var = xr.Variable(
@@ -239,7 +245,7 @@ interface only the boolean keywords related to the supported decoders.
 .. _RST backend_registration:
 
 How to register a backend
-+++++++++++++++++++++++++++
++++++++++++++++++++++++++
 
 Define a new entrypoint in your ``setup.py`` (or ``setup.cfg``) with:
 
@@ -273,15 +279,16 @@ If you are using `Poetry <https://python-poetry.org/>`_ for your build system, y
 
 .. code-block:: toml
 
-    [tool.poetry.plugins."xarray_backends"]
+    [tool.poetry.plugins."xarray.backends"]
     "my_engine" = "my_package.my_module:MyBackendEntryClass"
 
 See https://python-poetry.org/docs/pyproject/#plugins for more information on Poetry plugins.
 
 .. _RST lazy_loading:
 
-How to support Lazy Loading
+How to support lazy loading
 +++++++++++++++++++++++++++
+
 If you want to make your backend effective with big datasets, then you should
 support lazy loading.
 Basically, you shall replace the :py:class:`numpy.ndarray` inside the
@@ -317,7 +324,7 @@ grouped in three types of indexes
 :py:class:`~xarray.core.indexing.OuterIndexer` and
 :py:class:`~xarray.core.indexing.VectorizedIndexer`.
 This implies that the implementation of the method ``__getitem__`` can be tricky.
-In oder to simplify this task, Xarray provides a helper function,
+In order to simplify this task, Xarray provides a helper function,
 :py:func:`~xarray.core.indexing.explicit_indexing_adapter`, that transforms
 all the input  ``indexer`` types (`basic`, `outer`, `vectorized`) in a tuple
 which is interpreted correctly by your backend.
@@ -338,8 +345,8 @@ This is an example ``BackendArray`` subclass implementation:
             # other backend specific keyword arguments
         ):
             self.shape = shape
-            self.dtype = lock
-            self.lock = dtype
+            self.dtype = dtype
+            self.lock = lock
 
         def __getitem__(
             self, key: xarray.core.indexing.ExplicitIndexer
@@ -380,8 +387,9 @@ opening files, we therefore suggest to use the helper class provided by Xarray
 
 .. _RST indexing:
 
-Indexing Examples
+Indexing examples
 ^^^^^^^^^^^^^^^^^
+
 **BASIC**
 
 In the ``BASIC`` indexing support, numbers and slices are supported.
@@ -426,7 +434,7 @@ The ``OUTER_1VECTOR`` indexing shall supports number, slices and at most one
 list. The behaviour with the list shall be the same of ``OUTER`` indexing.
 
 If you support more complex indexing as `explicit indexing` or
-`numpy indexing`, you can have a look to the implemetation of Zarr backend and Scipy backend,
+`numpy indexing`, you can have a look to the implementation of Zarr backend and Scipy backend,
 currently available in :py:mod:`~xarray.backends` module.
 
 .. _RST preferred_chunks:

doc/internals/zarr-encoding-spec.rst

@@ -14,7 +14,7 @@ for the storage of the NetCDF data model in Zarr; see
 discussion.
 
 First, Xarray can only read and write Zarr groups. There is currently no support
-for reading / writting individual Zarr arrays. Zarr groups are mapped to
+for reading / writing individual Zarr arrays. Zarr groups are mapped to
 Xarray ``Dataset`` objects.
 
 Second, from Xarray's point of view, the key difference between
@@ -63,3 +63,10 @@ re-open it directly with Zarr:
     print(os.listdir("rasm.zarr"))
     print(zgroup.tree())
     dict(zgroup["Tair"].attrs)
+
+.. ipython:: python
+    :suppress:
+
+    import shutil
+
+    shutil.rmtree("rasm.zarr")