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@TheGreatAlgo TheGreatAlgo commented May 30, 2025

You can test by pulling the latest kubo node as a docker container

https://github.com/ipfs/kubo?tab=readme-ov-file#-developer-preview-images

Then you need to remove the rpc_base_url and gateway to use local defaults. That way it connects to docker kubo node running 0.36. Its otherwise not officially release.
Screenshot 2025-06-02 at 9 31 17 AM

I do have full test coverage, so if you don't want to do that, you can refer to this image.
Screenshot 2025-06-02 at 9 32 04 AM

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@abidsikder abidsikder left a comment

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I see that this PR is waiting for kubo 0.36. In the meantime, perhaps we can consider using python's native slice() type for the byte range request parameters in KuboCAS?

@abidsikder abidsikder marked this pull request as draft May 30, 2025 15:13
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you mean for InMemoryCAS where i do data[start:end] for example?

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abidsikder commented May 30, 2025

you mean for InMemoryCAS where i do data[start:end] for example?

I meant for the input arguments. I was suggesting they take a python slice() object instead. But I'm no longer sure that makes much sense for just an offset and length, if that's what zarr encrypted store is using and is more compatible with the concept of byte ranges. Perhaps we can disregard this suggestion then.

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Faolain commented Jun 1, 2025

@TheGreatAlgo were you able to test this out? master-latest docker image described here https://github.com/ipfs/kubo?tab=readme-ov-file#-developer-preview-images from https://hub.docker.com/r/ipfs/kubo/tags?name=master-latest should have the new fixed gateway work in it. Could just be a matter of running that docker image locally, pinning a dataset like the cpc one, and then testing if the get partials works against the gateway for the local running docker node.

As a sidenote, nothing important here just referencing the fsspec one which this PR appears to implement pattern wise https://github.com/zarr-developers/zarr-python/blob/d19f3f0a825b5be986fa6e2f797aa4ddec0b90ed/src/zarr/storage/_fsspec.py#L309

ChatGPT o3 Review:
Screenshot 2025-06-05 at 12 20 51 AM

Screenshot 2025-06-05 at 12 21 35 AM Screenshot 2025-06-05 at 12 21 52 AM Screenshot 2025-06-05 at 12 22 05 AM Screenshot 2025-06-05 at 12 22 29 AM Screenshot 2025-06-05 at 12 22 48 AM

@TheGreatAlgo TheGreatAlgo marked this pull request as ready for review June 2, 2025 13:33
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Great tests!

Only thing I would suggest is to refactor the random xarray Dataset generation into a pytest fixture since it's being used across multiple tests now, but this PR seems ready to merge as is.

@Faolain Faolain mentioned this pull request Jun 4, 2025
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being done on sharding

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4 participants