WIP: Zarr chunks refactor #4550
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Add necessary imports for this function.
# Conflicts: # xarray/backends/api.py
…ad-refactor # Conflicts: # xarray/backends/apiv2.py
- to be used in apiv2 without instantiate the object
- modify signature - move default setting inside backends
…2.dataset_from_backend_dataset`
…lated error message
# Conflicts: # xarray/backends/apiv2.py
# Conflicts: # xarray/backends/apiv2.py
…arr-chunks-refactor � Conflicts: � xarray/backends/apiv2.py � xarray/core/dataset.py
re-add check on chunks type
re-add check on chunks type
…arr-chunks-refactor � Conflicts: � xarray/backends/apiv2.py
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Hello @aurghs! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:
Comment last updated at 2020-11-02 12:07:00 UTC |
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This work aims to harmonize the way zarr deals with chunking to have similar behavior for all other backends and unify the code.
Most of the changes involve the new API, apiv2.py, except for some changes in the code that has been added with the merge of #4187.
main changes:
apiv2.dataset_from_backend_datasetfunction.get_chunksfromzarrtodataset.current status:
apiv2.open_datasetchunks='auto'andchunks={}now has the same beahviuorapiv2.open_datasetfor all the backends now the default chunking is provided by the backend, if it is not available it uses one big chunk.Missing points:
chunksizeschunks)There is one open point to be discussed yet:
dataset.chunksandopen_dataset(..., chunks=...)have different behaviors.dataset.chunks(chunks={})opens the dataset with only one chunk per variable, while inopen_dataset(..., chunks={})it usesencodings['chunks'], when available.Note that also
chunks=Nonehas a different behaviour:open_dataset(..., chunks=None)(oropen_dataset(...), it's the deafult) returns variables without chunks, whiledataset.chunk(chunks=None)(ordataset.chunk(), it's the default) has the same behavior ofdataset.chunk(chunks=None). Probably it's not worth changing it.isort . && black . && mypy . && flake8whats-new.rstapi.rst