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- Remote writing NETCDF4 files to Amazon S3 · 5 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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1516635334 | https://github.com/pydata/xarray/issues/2995#issuecomment-1516635334 | https://api.github.com/repos/pydata/xarray/issues/2995 | IC_kwDOAMm_X85aZgTG | rebeccaringuette 49281118 | 2023-04-20T16:38:46Z | 2023-04-20T16:38:46Z | NONE | Related issue: https://github.com/pydata/xarray/issues/4122 |
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Remote writing NETCDF4 files to Amazon S3 449706080 | |
723528226 | https://github.com/pydata/xarray/issues/2995#issuecomment-723528226 | https://api.github.com/repos/pydata/xarray/issues/2995 | MDEyOklzc3VlQ29tbWVudDcyMzUyODIyNg== | mullenkamp 2656596 | 2020-11-08T04:13:39Z | 2020-11-08T04:13:39Z | NONE | Hi all, I'd love to have an effective method to save a netcdf4 Dataset to a bytes object (for the S3 purpose specifically). I'm currently using netcdf3 through scipy as described earlier which works fine, but I'm just missing out on some newer netcdf4 options as a consequence. Thanks! |
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Remote writing NETCDF4 files to Amazon S3 449706080 | |
659441282 | https://github.com/pydata/xarray/issues/2995#issuecomment-659441282 | https://api.github.com/repos/pydata/xarray/issues/2995 | MDEyOklzc3VlQ29tbWVudDY1OTQ0MTI4Mg== | euyuil 1539596 | 2020-07-16T14:15:28Z | 2020-07-16T14:15:28Z | NONE | It looks like #23 is related. Do we have a plan about this? |
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Remote writing NETCDF4 files to Amazon S3 449706080 | |
657798184 | https://github.com/pydata/xarray/issues/2995#issuecomment-657798184 | https://api.github.com/repos/pydata/xarray/issues/2995 | MDEyOklzc3VlQ29tbWVudDY1Nzc5ODE4NA== | NowanIlfideme 2067093 | 2020-07-13T21:17:06Z | 2020-07-13T21:17:06Z | NONE | I ran into this issue, here's a simple workaround that seems to work: ```python def dataset_to_bytes(ds: xr.Dataset, name: str = "my-dataset") -> bytes: """Converts datset to bytes."""
``` I tested this using the following: ```python import BytesIO fname = "REDACTED.nc" ds = xr.load_dataset(fname) ds_bytes = dataset_to_bytes(ds) ds2 = xr.load_dataset(BytesIO(ds_bytes)) assert ds2.equals(ds) and all(ds2.attrs[k]==ds.attrs[k] for k in set(ds2.attrs).union(ds.attrs)) ``` The assertion holds true, however the file size on disk is different. It's possible they were saved using different netCDF4 versions, I haven't had time to test that. I tried using just
That's because it falls back to the |
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Remote writing NETCDF4 files to Amazon S3 449706080 | |
518869785 | https://github.com/pydata/xarray/issues/2995#issuecomment-518869785 | https://api.github.com/repos/pydata/xarray/issues/2995 | MDEyOklzc3VlQ29tbWVudDUxODg2OTc4NQ== | NicWayand 1117224 | 2019-08-06T22:39:07Z | 2019-08-06T22:39:07Z | NONE | Is it possible to read mulitple netcdf files on s3 using open_mfdataset? |
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Remote writing NETCDF4 files to Amazon S3 449706080 |
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