issue_comments

Table actions

2 rows where author_association = "CONTRIBUTOR", issue = 1177669703 and user = 38358698 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

user 1

  • stanwest · 2 ✖

issue 1

  • No chunk warning if empty · 2 ✖

author_association 1

  • CONTRIBUTOR · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1094118500 https://github.com/pydata/xarray/pull/6402#issuecomment-1094118500 https://api.github.com/repos/pydata/xarray/issues/6402 IC_kwDOAMm_X85BNuxk stanwest 38358698 2022-04-09T20:19:02Z 2022-04-09T20:19:02Z CONTRIBUTOR

@stanwest how's that?

That looks great to me.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   No chunk warning if empty 1177669703
1093300764 https://github.com/pydata/xarray/pull/6402#issuecomment-1093300764 https://api.github.com/repos/pydata/xarray/issues/6402 IC_kwDOAMm_X85BKnIc stanwest 38358698 2022-04-08T19:51:24Z 2022-04-08T19:51:24Z CONTRIBUTOR

@stanwest Can you suggest how to fix this merge conflict please?

Sure. I recommend the following before the return statement in xarray.core.dataset._get_chunk:

```python

Warn where requested chunks break preferred chunks, provided that the variable

contains data.

if var.size: for dim, size, chunk_sizes in zip(dims, shape, chunk_shape): try: preferred_chunk_sizes = preferred_chunks[dim] except KeyError: continue # Determine the stop indices of the preferred chunks, but omit the last stop # (equal to the dim size). In particular, assume that when a sequence # expresses the preferred chunks, the sequence sums to the size. preferred_stops = ( range(preferred_chunk_sizes, size, preferred_chunk_sizes) if isinstance(preferred_chunk_sizes, Number) else itertools.accumulate(preferred_chunk_sizes[:-1]) ) # Gather any stop indices of the specified chunks that are not a stop index # of a preferred chunk. Again, omit the last stop, assuming that it equals # the dim size. breaks = set(itertools.accumulate(chunk_sizes[:-1])).difference( preferred_stops ) if breaks: warnings.warn( "The specified Dask chunks separate the stored chunks along " f'dimension "{dim}" starting at index {min(breaks)}. This could ' "degrade performance. Instead, consider rechunking after loading." ) ```

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   No chunk warning if empty 1177669703

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]);