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support ome-ngff on s3 #209
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Hi @d-v-b and thanks for your suggestions!
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Perfect! I actually forgot that As for testing against cloud storage, I think you can look at the zarr tests for an example. Personally I don't have experience with this part of the test suite, so I can't be more concrete about how to mock the s3 resources (i'm guessing it's via moto? but I don't know for sure). And thank your for reminding me about this zarr issue: zarr-developers/zarr-python#1533, I will look into whether I can figure out a solution for that. I will hold off on a PR here until your refactor lands. With that being said, should I leave this open until |
I fixed that in zarr-developers/zarr-python#1540. You reviewed and merged it (Thanks!). (edit: it is still broken for iohub because there has been no zarr release after that.)
👍 |
Lol, I totally forgot about this. 😆 I'm not sure when the next Zarr release will be, but if you make some noise over in the zarr issue tracker you might get an answer / motivate people to prepare a release. |
New Zarr release is out! Will bump soon. |
It would be great if this library could access ome-ngff data stored on AWS S3, google GCS, etc. Since you have
fsspec
in your dependencies, I think this would be doable without drastic changes.os.path
, so you would need to use something that's agnostic to the storage backend. But it's not clear why you even need to check if the path exists -- Zarr will do that for you, once you choose astore
class.DirectoryStore
is not recommended for anything because it puts all the chunks in a single directory and, with too many chunks, that directory becomes unwieldy. Consider usingNestedDirectoryStore
as a replacement. Second, if you havefsspec
installed along with zarr, then zarr can transparently store stuff on cloud backends withFSStore
.FSStore
will even automatically parse a string likes3://bucket-name/foo.zarr
and pick the correct backend (s3, in this case).If there's appetite, I could submit a PR (I didn't see a pre-existing one, but maybe I didn't look too closely).
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