issues

Table actions

2 rows where repo = 13221727, type = "pull" and user = 1634164 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

state 2

type 1

  • pull · 2 ✖

repo 1

  • xarray · 2 ✖
id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
606846911 MDExOlB1bGxSZXF1ZXN0NDA4OTY0MTM3 4007 Allow DataArray.to_series() without invoking sparse.COO.todense() khaeru 1634164 open 0     1 2020-04-25T20:15:16Z 2022-06-09T14:50:17Z   FIRST_TIME_CONTRIBUTOR   0 pydata/xarray/pulls/4007

This adds some code (from iiasa/ixmp#317) that allows DataArray.to_series() to be called without invoking sparse.COO.todense() when that is the backing data type.

I'm aware this needs some improvement to meet the standard of the existing codebase, so I hope I could ask for some guidance on how to address the following points (including whom to ask about them): - [ ] Make the same improvement in {DataArray,Dataset}.to_dataframe(). - [ ] Possibly move the code out of dataarray.py to a more appropriate location (where?). - [ ] Possibly check for sparse.COO explicitly instead of xarray.core.pycompat.sparse_array_type. Other SparseArray subclasses, e.g. DOK, may not have the same attributes.

Standard items: - [ ] Tests added. - [x] Passes isort -rc . && black . && mypy . && flake8 (Sort of: these wanted to modify 7 files beyond the one I touched; didn't commit these changes.) - [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/4007/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
70805273 MDExOlB1bGxSZXF1ZXN0MzQwODk5MDk= 401 Handle bool in NetCDF4 conversion khaeru 1634164 closed 0     9 2015-04-24T21:59:08Z 2016-05-26T18:51:06Z 2016-05-23T04:54:40Z FIRST_TIME_CONTRIBUTOR   0 pydata/xarray/pulls/401

I am working on some code that creates xray.Datasets with a 'bool' dtype.

Trying to call Dataset.to_netcdf() on this code causes _nc4_values_and_dtype() to raise a ValueError, so I added these few lines to force the storage of these variables as 1-byte integers.

Perhaps it should be 'u1' instead; I can change that if need be.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/401/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull

Advanced export

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

CSV options: 

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [active_lock_reason] TEXT,
   [draft] INTEGER,
   [pull_request] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [state_reason] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
);
CREATE INDEX [idx_issues_repo]
    ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
    ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
    ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
    ON [issues] ([user]);