Merge branch 'main' into get_slice_bound-kind

Author: spencerkclark

.git-blame-ignore-revs

@@ -0,0 +1,5 @@
+# black PR 3142
+d089df385e737f71067309ff7abae15994d581ec
+
+# isort PR 1924
+0e73e240107caee3ffd1a1149f0150c390d43251

.github/workflows/ci-additional.yaml

@@ -42,7 +42,6 @@ jobs:
           [
             "py37-bare-minimum",
             "py37-min-all-deps",
-            "py37-min-nep18",
             "py38-all-but-dask",
             "py38-flaky",
           ]
@@ -103,7 +102,7 @@ jobs:
              $PYTEST_EXTRA_FLAGS
 
       - name: Upload code coverage to Codecov
-        uses: codecov/[email protected].2
+        uses: codecov/[email protected].3
         with:
           file: ./coverage.xml
           flags: unittests,${{ matrix.env }}

.github/workflows/ci.yaml

@@ -100,7 +100,7 @@ jobs:
           path: pytest.xml
 
       - name: Upload code coverage to Codecov
-        uses: codecov/[email protected].2
+        uses: codecov/[email protected].3
         with:
           file: ./coverage.xml
           flags: unittests

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

@@ -122,7 +122,7 @@ jobs:
           shopt -s globstar
           python .github/workflows/parse_logs.py logs/**/*-log
       - name: Report failures
-        uses: actions/github-script@v4.0.2
+        uses: actions/github-script@v4.1
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           script: |

ci/install-upstream-wheels.sh

@@ -42,4 +42,5 @@ python -m pip install \
     git+https://github.com/hgrecco/pint \
     git+https://github.com/pydata/bottleneck \
     git+https://github.com/pydata/sparse \
-    git+https://github.com/intake/filesystem_spec
+    git+https://github.com/intake/filesystem_spec \
+    git+https://github.com/SciTools/nc-time-axis

ci/requirements/py37-min-all-deps.yml

@@ -15,8 +15,8 @@ dependencies:
   - cfgrib=0.9
   - cftime=1.1
   - coveralls
-  - dask=2.15
-  - distributed=2.15
+  - dask=2.24
+  - distributed=2.24
   - h5netcdf=0.8
   - h5py=2.10
   - hdf5=1.10
@@ -25,13 +25,14 @@ dependencies:
   - lxml=4.5  # Optional dep of pydap
   - matplotlib-base=3.2
   - nc-time-axis=1.2
-# netcdf follows a 1.major.minor[.patch] convention (see https://github.com/Unidata/netcdf4-python/issues/1090)
-# bumping the netCDF4 version is currently blocked by #4491
+  # netcdf follows a 1.major.minor[.patch] convention
+  # (see https://github.com/Unidata/netcdf4-python/issues/1090)
+  # bumping the netCDF4 version is currently blocked by #4491
   - netcdf4=1.5.3
   - numba=0.49
   - numpy=1.17
   - pandas=1.0
-  # - pint  # See py37-min-nep18.yml
+  - pint=0.15
   - pip
   - pseudonetcdf=3.1
   - pydap=3.2
@@ -44,7 +45,7 @@ dependencies:
   - scipy=1.4
   - seaborn=0.10
   - setuptools=40.4
-  # - sparse  # See py37-min-nep18.yml
+  - sparse=0.8
   - toolz=0.10
   - zarr=2.4
   - pip:

ci/requirements/py37-min-nep18.yml

@@ -16,7 +16,7 @@ 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).
-- `infinite-diff <https://github.com/spencerahill/infinite-diff>`_: xarray-based finite-differencing, focused on gridded climate/meterology data
+- `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.
 - `MPAS-Analysis <http://mpas-analysis.readthedocs.io>`_: Analysis for simulations produced with Model for Prediction Across Scales (MPAS) components and the Accelerated Climate Model for Energy (ACME).
@@ -46,7 +46,6 @@ Geosciences
 - `xESMF <https://pangeo-xesmf.readthedocs.io/>`_: Universal regridder for geospatial data.
 - `xgcm <https://xgcm.readthedocs.io/>`_: Extends the xarray data model to understand finite volume grid cells (common in General Circulation Models) and provides interpolation and difference operations for such grids.
 - `xmitgcm <http://xgcm.readthedocs.io/>`_: a python package for reading `MITgcm <http://mitgcm.org/>`_ binary MDS files into xarray data structures.
-- `xshape <https://xshape.readthedocs.io/>`_: Tools for working with shapefiles, topographies, and polygons in xarray.
 
 Machine Learning
 ~~~~~~~~~~~~~~~~
@@ -68,7 +67,7 @@ Extend xarray capabilities
 - `hypothesis-gufunc <https://hypothesis-gufunc.readthedocs.io/en/latest/>`_: Extension to hypothesis. Makes it easy to write unit tests with xarray objects as input.
 - `nxarray <https://github.com/nxarray/nxarray>`_: NeXus input/output capability for xarray.
 - `xarray-compare <https://github.com/astropenguin/xarray-compare>`_: xarray extension for data comparison.
-- `xarray-custom <https://github.com/astropenguin/xarray-custom>`_: Data classes for custom xarray creation.
+- `xarray-dataclasses <https://github.com/astropenguin/xarray-dataclasses>`_: xarray extension for typed DataArray and Dataset creation.
 - `xarray_extras <https://github.com/crusaderky/xarray_extras>`_: Advanced algorithms for xarray objects (e.g. integrations/interpolations).
 - `xpublish <https://xpublish.readthedocs.io/>`_: Publish Xarray Datasets via a Zarr compatible REST API.
 - `xrft <https://github.com/rabernat/xrft>`_: Fourier transforms for xarray data.

doc/ecosystem.rst

@@ -95,12 +95,6 @@ dependencies:
 - **setuptools:** 42 months (but no older than 40.4)
 - **numpy:** 18 months
   (`NEP-29 <https://numpy.org/neps/nep-0029-deprecation_policy.html>`_)
-- **dask and dask.distributed:** 12 months
-- **sparse, pint** and other libraries that rely on
-  `NEP-18 <https://numpy.org/neps/nep-0018-array-function-protocol.html>`_
-  for integration: very latest available versions only, until the technology will have
-  matured. This extends to dask when used in conjunction with any of these libraries.
-  numpy >=1.17.
 - **all other libraries:** 12 months
 
 This means the latest minor (X.Y) version from N months prior. Patch versions (x.y.Z)
@@ -109,10 +103,7 @@ release is guaranteed to work.
 
 You can see the actual minimum tested versions:
 
-- `For NEP-18 libraries
-  <https://github.com/pydata/xarray/blob/main/ci/requirements/py37-min-nep18.yml>`_
-- `For everything else
-  <https://github.com/pydata/xarray/blob/main/ci/requirements/py37-min-all-deps.yml>`_
+`<https://github.com/pydata/xarray/blob/main/ci/requirements/py37-min-all-deps.yml>`_
 
 .. _installation-instructions:
 

doc/getting-started-guide/installing.rst

@@ -37,7 +37,7 @@ Why has xarray been successful? In our opinion:
       labeled multidimensional arrays, rather than solving particular
       problems.
    -  This facilitates collaboration between users with different needs,
-      and helps us attract a broad community of contributers.
+      and helps us attract a broad community of contributors.
    -  Importantly, this retains flexibility, for use cases that don't
       fit particularly well into existing frameworks.
 
@@ -82,7 +82,7 @@ We think the right approach to extending xarray's user community and the
 usefulness of the project is to focus on improving key interfaces that
 can be used externally to meet domain-specific needs.
 
-We can generalize the community's needs into three main catagories:
+We can generalize the community's needs into three main categories:
 
 -  More flexible grids/indexing.
 -  More flexible arrays/computing.