issue_comments
14 rows where author_association = "NONE" and issue = 631085856 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: reactions, created_at (date), updated_at (date)
issue 1
- Document writing netcdf from xarray directly to S3 · 14 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
1453906696 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453906696 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85WqNsI | zoj613 44142765 | 2023-03-03T18:08:07Z | 2023-03-03T18:08:07Z | NONE | Based on the docs
It appears scipy engine is safe is one does not need to be bothered with specifying engines.By the way, what are the limitations of the |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1453901550 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453901550 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85WqMbu | peterdudfield 34686298 | 2023-03-03T18:03:49Z | 2023-03-03T18:03:49Z | NONE |
using |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1453899322 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453899322 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85WqL46 | peterdudfield 34686298 | 2023-03-03T18:02:04Z | 2023-03-03T18:02:04Z | NONE |
What do you mean this is |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1453897364 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453897364 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85WqLaU | zoj613 44142765 | 2023-03-03T18:00:33Z | 2023-03-03T18:00:33Z | NONE | I never needed to specify an engine when writing, you only need it when reading the file. I use the |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1453562756 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453562756 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85Wo5uE | peterdudfield 34686298 | 2023-03-03T13:52:08Z | 2023-03-03T17:48:15Z | NONE |
Thanks, i tried to make sure it was |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1453883439 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453883439 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85WqIAv | peterdudfield 34686298 | 2023-03-03T17:47:43Z | 2023-03-03T17:47:43Z | NONE | It could be here's some running notes of mine - https://github.com/openclimatefix/MetOfficeDataHub/issues/65 The same method is
|
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1453873364 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453873364 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85WqFjU | alaws-USGS 108412194 | 2023-03-03T17:38:11Z | 2023-03-03T17:38:33Z | NONE | @peterdudfield Could this be an issue with how you wrote out your NetCDF file? When I write to requester pays buckets, my approach using your variables would look like this and incorporates instructions from fsspec for remote write caching:
I haven't had any read issues with files saved this way. |
{ "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1453553088 | https://github.com/pydata/xarray/issues/4122#issuecomment-1453553088 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85Wo3XA | peterdudfield 34686298 | 2023-03-03T13:43:58Z | 2023-03-03T13:45:59Z | NONE |
How would you go about reading this file? Once it is saved in s3 Im currently getting an error
|
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1401040677 | https://github.com/pydata/xarray/issues/4122#issuecomment-1401040677 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85Tgi8l | zoj613 44142765 | 2023-01-23T21:49:46Z | 2023-01-23T21:52:29Z | NONE | What didn't work:
Changing the above to
|
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1400564474 | https://github.com/pydata/xarray/issues/4122#issuecomment-1400564474 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85Teur6 | zoj613 44142765 | 2023-01-23T15:44:20Z | 2023-01-23T15:44:20Z | NONE |
Thanks, this actually worked for me. It seems as though initializing an s3 store using |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
1400519887 | https://github.com/pydata/xarray/issues/4122#issuecomment-1400519887 | https://api.github.com/repos/pydata/xarray/issues/4122 | IC_kwDOAMm_X85TejzP | zoj613 44142765 | 2023-01-23T15:16:21Z | 2023-01-23T15:16:21Z | NONE | Is there any reliable to use to write a xr.Dataset object as a netcdf file in 2023? I tried using the above approach with |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
745520766 | https://github.com/pydata/xarray/issues/4122#issuecomment-745520766 | https://api.github.com/repos/pydata/xarray/issues/4122 | MDEyOklzc3VlQ29tbWVudDc0NTUyMDc2Ng== | rsignell-usgs 1872600 | 2020-12-15T19:39:16Z | 2020-12-15T19:39:16Z | NONE | I'm closing this the recommended approach for writing NetCDF to object stroage is to write locally, then push. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
640548620 | https://github.com/pydata/xarray/issues/4122#issuecomment-640548620 | https://api.github.com/repos/pydata/xarray/issues/4122 | MDEyOklzc3VlQ29tbWVudDY0MDU0ODYyMA== | rsignell-usgs 1872600 | 2020-06-08T11:36:14Z | 2020-06-08T11:37:21Z | NONE | @martindurant, I asked @ajelenak offline and he reminded me that:
Looking forward to |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 | |
639771646 | https://github.com/pydata/xarray/issues/4122#issuecomment-639771646 | https://api.github.com/repos/pydata/xarray/issues/4122 | MDEyOklzc3VlQ29tbWVudDYzOTc3MTY0Ng== | rsignell-usgs 1872600 | 2020-06-05T20:08:37Z | 2020-06-05T20:54:36Z | NONE | Okay @scottyhq, I tried setting I asked @martindurant about supporting seek for writing in So maybe it's best just to write netcdf files locally and then push them to S3. And to facilitate that, @martindurant merged a PR yesterday to enable ds = xr.open_dataset('http://geoport.usgs.esipfed.org/thredds/dodsC' '/silt/usgs/Projects/stellwagen/CF-1.6/BUZZ_BAY/2651-A.cdf') outfile = fsspec.open('simplecache::s3://chs-pangeo-data-bucket/rsignell/foo2.nc',
mode='wb', s3=dict(profile='default'))
with outfile as f:
ds.to_netcdf(f)
Thanks Martin!!! |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
Document writing netcdf from xarray directly to S3 631085856 |
Advanced export
JSON shape: default, array, newline-delimited, object
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]);
user 4