issue_comments

Table actions

4 rows where author_association = "NONE" and issue = 1503046820 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 2

issue 1

  • Xarray does not support full range of netcdf-python compression options · 4 ✖

author_association 1

  • NONE · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1517919313 https://github.com/pydata/xarray/issues/7388#issuecomment-1517919313 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85aeZxR zklaus 1185813 2023-04-21T14:27:48Z 2023-04-21T14:27:48Z NONE

Do you need them in 4.9.1 then, or is updating to 4.9.2 an option?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Xarray does not support full range of netcdf-python compression options 1503046820
1514310318 https://github.com/pydata/xarray/issues/7388#issuecomment-1514310318 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85aQoqu zklaus 1185813 2023-04-19T08:05:46Z 2023-04-19T08:05:46Z NONE

For the moment I prefer not to merge this as netcdf 4.9.2 and dask do not seem to play well together.

@markelg, could you elaborate? Is this about the two issues discussed here, or are there more problems? I am asking because I am wondering whether to back-port the patches to 4.9.1?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Xarray does not support full range of netcdf-python compression options 1503046820
1513191535 https://github.com/pydata/xarray/issues/7388#issuecomment-1513191535 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85aMXhv zklaus 1185813 2023-04-18T13:47:55Z 2023-04-18T13:47:55Z NONE

@markelg, regarding the blosc filters, this may have been a combination of conda-forge building and an upstream netcdf-c quirk. In the conda-forge build, we did not install the necessary hdf5 plugins. I fixed that in conda-forge/libnetcdf-feedstock#172. There we also added blosc as a dependency, which was not present before. The netcdf-c quirk is that, if a compression library is not present at build time, support for it will not be compiled and the call to setting the corresponding compression will silently succeed, but not do anything. If the library is present at build time, but the corresponding plugin is missing at runtime, the attempt to set compression will error out. With the most recent libnetcdf-4.9.2 builds one should get working plugins, including working blosc compression.

Regarding the HDF5-diag errors, the upstream bug has already been mentioned. I am suggesting to back-port it in conda-forge/libnetcdf-feedstock#175 for the conda-forge build, so hopefully that will work in libnetcdf-4.9.2 soon, too.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Xarray does not support full range of netcdf-python compression options 1503046820
1511283077 https://github.com/pydata/xarray/issues/7388#issuecomment-1511283077 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85aFFmF trexfeathers 40734014 2023-04-17T12:54:07Z 2023-04-17T12:54:07Z NONE

Hi. I updated the branch and created a fresh python environment with the idea of writing another, final test for this. However before doing it I run the test suite, and got some bad HDF5 errors in test_backends.py::test_open_mfdataset_manyfiles[netcdf4-20-True-None-5]

7549

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Xarray does not support full range of netcdf-python compression options 1503046820

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);