issues

Towards the strict goal in #8239.

dask has added py.typed files so now the ignores shouldn't be needed anymore: https://github.com/dask/dask/pull/8854 https://github.com/dask/distributed/pull/5328 As does numpy and pint

pycompat.py doesn't error anymore, so it's good to type check that one as well. Fixed also a python 3.8 related error in it.

Fixes these errors that I've been seeing locally for a while:

python !mypy C:\Users\J.W\Documents\GitHub\xarray\xarray\core\coordinates.py --ignore-missing-imports C:\Users\J.W\Documents\GitHub\xarray\xarray\core\pycompat.py:48: error: Incompatible types in assignment (expression has type "Tuple[]", variable has type "Tuple[Any]") C:\Users\J.W\Documents\GitHub\xarray\xarray\core\pycompat.py:50: error: Incompatible types in assignment (expression has type "Optional[Module]", variable has type "Optional[Literal['dask', 'pint', 'cupy', 'sparse']]") Found 2 errors in 1 file (checked 1 source file)

Not sure why the CI isn't catching these?

Splitting up #5622 as the scope of it has grown too large now.

• Adds support for dataarray scatter plots and replaces the dataset version.
• Scatter now has 3d support with the z argument.
• Scatter now always returns a single pathcollection, earlier it could return a list of pathcollection when using categoricals
• Better legend, handles now categoricals. Making continous/discrete options slightly redundant, still there though.
• Facetgrid generalized slightly to handle 3d plots.

TODO: * sharex sharey test https://github.com/pydata/xarray/pull/7047: len(list(ax.get_shared_x_axes())) != 0

• [x] Tests added
• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
• [ ] New functions/methods are listed in api.rst

Matplotlibs 3d plots appears to not support sharex/sharey. So reset to default values instead. This improves the look of the plot as axis values aren't deleted.

Example: ```python import matplotlib.pyplot as plt

fig = plt.figure() subplot_kws = {"projection":"3d"} ax1 = fig.add_subplot(211, subplot_kws) ax1.plot([0, 1, 2], [5,6,6]) ax2 = fig.add_subplot(212, sharex = ax1, subplot_kws) ax2.plot([0, 1, 2], [5,4,2]) # x axis is not linked. ``` Split up from #6778.

Cache some small properties that are rather slow to calculate but doesn't change that often.

Questions that needs to be resolved:

• [ ] Can these properties change during the lifetime of the class? If so the cache needs to be reset when that happens.

• [ ] Related to #3514
• [ ] Tests added
• [ ] Passes pre-commit run --all-files
• [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
• [ ] New functions/methods are listed in api.rst

Notes * Mixin classes makes it difficult to cache properties. For example ndim in NdimSizeLenMixin cannot be easily be replaced with cache_readonly.

The backend classes are initialized in the build_engine function: https://github.com/pydata/xarray/blob/8b95da8e21a9d31de9f79cb0506720595f49e1dd/xarray/backends/plugins.py#L93

This wasn't the case for custom backends: https://github.com/pydata/xarray/blob/8b95da8e21a9d31de9f79cb0506720595f49e1dd/xarray/backends/plugins.py#L161

This PR initializes the engine, fixes the incorrect signature in the test (#5033) and reverts the doc changes done in #5532.

• [x] Tests added
• [x] Passes pre-commit run --all-files
• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

Attempt to fix these errors found in #5365.

xarray/core/computation.py:1533: error: Argument "variable_dim" to "to_stacked_array" of "Dataset" has incompatible type "Hashable"; expected "str" [arg-type] xarray/core/computation.py:1533: error: Argument "sample_dims" to "to_stacked_array" of "Dataset" has incompatible type "Mapping[Hashable, int]"; expected "Sequence[Hashable]" [arg-type] - [x] Passes pre-commit run --all-files

Removing a commented improvement that required that the minimum version requirement for dask to be increased.

• [x] Requires #5556
• [x] Passes pre-commit run --all-files

Make the transpose faster. * get_axis_num seems slow, avoid triggering it unnecessarily for example when using 1d arrays. * .copy(deep=False) is the bottleneck for 1d arrays. Not sure if it can be dealt with though.

• [ ] Closes #xxxx
• [ ] Tests added
• [ ] Passes pre-commit run --all-files
• [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
• [ ] New functions/methods are listed in api.rst

Found some checks that should always be true nowadays.