issue_comments: 983925525
This data as json
| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/6036#issuecomment-983925525 | https://api.github.com/repos/pydata/xarray/issues/6036 | 983925525 | IC_kwDOAMm_X846pYMV | 2448579 | 2021-12-01T18:10:07Z | 2021-12-01T18:10:07Z | MEMBER | @DonjetaR Thanks for the very well written issue! and for confirming #6013. Could you please add a minimum reproducible example to #6013? I think that would help greatly The following runs in 1s for me which seems OK. Can you open an issue over at dask about this. Xarray can't do anything about it. ``` python import dask.array dim_size = (10, 15_000, 15_000) chunks = dask.array.empty(dim_size, chunks=(10, 10, 10)).chunks %timeit dask.array.core.slices_from_chunks(chunks) ``` On repeated runs it drops down to 200ms (because of caching I guess), so it was important to restart the kernel to test it out. |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
1068225524 |