issue_comments: 552619589
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/2799#issuecomment-552619589 | https://api.github.com/repos/pydata/xarray/issues/2799 | 552619589 | MDEyOklzc3VlQ29tbWVudDU1MjYxOTU4OQ== | 90008 | 2019-11-11T21:16:36Z | 2019-11-11T21:16:36Z | CONTRIBUTOR | Hmm, slicing should basically be a no-op. The fact that xarray makes it about 100x slower is a real killer. It seems from this conversation that it might be hard to workaround
```python
import xarray as xr
import numpy as np
n = np.zeros(shape=(1024, 1024))
x = xr.DataArray(n, dims=('y', 'x'))
the_slice = np.s_[256:512, 256:512]
%timeit n[the_slice]
%timeit x[the_slice]
186 ns ± 0.778 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
70.3 µs ± 593 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
```
|
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