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Additional details and impacted files@@ Coverage Diff @@
## master #73 +/- ##
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+ Coverage 52.04% 60.11% +8.07%
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Files 12 13 +1
Lines 490 514 +24
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+ Hits 255 309 +54
+ Misses 235 205 -30 ☔ View full report in Codecov by Harness. 🚀 New features to boost your workflow:
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…ressed create_dataset now forwards `compressor` (Zarr) and `compress` (NetCDF) to the coordinate arrays, not only to the data variables. Other keyword arguments such as filters stay data-variable only, since they can be type specific. NetCDF iscompressed always returned false because NetCDF.jl does not read the deflate level back when opening a variable. Query it with nc_inq_var_deflate instead.
Zarr v3 allows omitting dimension_names, which zarr-python does for 0-dimensional arrays. get_var_dims threw for such arrays because neither dimension_names nor _ARRAY_DIMENSIONS was present. Return an empty list for arrays without dimensions instead.
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I changed to using the zarr_format function from ZarrCore and renamed the corresponding keyword to format. Why is this breaking? |
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| function __init__() | ||
| @debug "new driver key :zarr, updating backendlist." | ||
| YAB.backendlist[:zarr] = ZarrDataset |
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as for the breaking thing, I'm not sure about this backend list, since now the dependency is in ZarrCore and not Zarr, do we still use the key :zarr here?
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We still use the key zarr here, because this is about the format and I would say the existence of ZarrCore is an implementation detail.
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2 participants
as hinted in #72
Plus is needed to properly implement the multi scales work on PyramidSchemes.jl