issue_comments

Table actions

3 rows where issue = 1319621859 and user = 14808389 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: reactions

user 1

  • keewis · 3 ✖

issue 1

  • Clarify difference between `.load()` and `.compute()` · 3 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1197439408 https://github.com/pydata/xarray/issues/6837#issuecomment-1197439408 https://api.github.com/repos/pydata/xarray/issues/6837 IC_kwDOAMm_X85HX3mw keewis 14808389 2022-07-27T22:30:22Z 2022-07-27T22:30:22Z MEMBER

note that the implementation of compute is currently: python def compute(self, **kwargs): new = self.copy(deep=False) return new.load(**kwargs) which means that the inplace vs. "pure function" is literally the only difference (though I don't know whether doing a shallow copy has other implications).

 
{
    "total_count": 2,
    "+1": 2,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Clarify difference between `.load()` and `.compute()` 1319621859
1196891233 https://github.com/pydata/xarray/issues/6837#issuecomment-1196891233 https://api.github.com/repos/pydata/xarray/issues/6837 IC_kwDOAMm_X85HVxxh keewis 14808389 2022-07-27T15:13:45Z 2022-07-27T15:15:46Z MEMBER

Are there lazy array implementations other than dask in xarray?

No, sorry, I mistyped. What I was referring to is the lazy loading mechanism that will load the data into memory once you try to actually do something with it.

However, it might be possible to wrap other lazy array implementations if they implement either __array_ufunc__ and __array_function__, or __array_namespace__ (see #6807).

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Clarify difference between `.load()` and `.compute()` 1319621859
1196850508 https://github.com/pydata/xarray/issues/6837#issuecomment-1196850508 https://api.github.com/repos/pydata/xarray/issues/6837 IC_kwDOAMm_X85HVn1M keewis 14808389 2022-07-27T14:40:54Z 2022-07-27T14:43:31Z MEMBER

Yeah, deprecating return values is not fun. We somewhat recently did that for Dataset.update and found that we could only mention this in the documentation / release notes, which is not great for visibility.

Interestingly, the docstring of Dataset.compute and Dataset.load compare with each other, while for the methods on DataArray and Variable that comparison is missing. None of them actually link to the other method, though.

Given that we have been removing inplace operations as much as possible, I'd vote to remove load entirely or make it an alias of compute.

Edit: up until I read this issue, I somehow assumed compute would only work with dask while load would also load our lazy array implementation into memory. Not sure how I got that impression, but maybe that's another argument to remove / align load?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Clarify difference between `.load()` and `.compute()` 1319621859

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]);