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/4285#issuecomment-1252772587,https://api.github.com/repos/pydata/xarray/issues/4285,1252772587,IC_kwDOAMm_X85Kq8rr,3019665,2022-09-20T18:48:47Z,2022-09-20T18:48:47Z,NONE,cc @ivirshup @joshmoore (who may be interested in this as well),"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,667864088
https://github.com/pydata/xarray/issues/4242#issuecomment-1232159535,https://api.github.com/repos/pydata/xarray/issues/4242,1232159535,IC_kwDOAMm_X85JcUMv,3019665,2022-08-30T20:56:42Z,2022-08-30T20:56:42Z,NONE,FWIW this sounds similar to what [h5pickle]( https://github.com/DaanVanVugt/h5pickle ) does. Maybe it is worth improving that package with whatever logic Xarray has?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,663148659
https://github.com/pydata/xarray/issues/4118#issuecomment-1198743015,https://api.github.com/repos/pydata/xarray/issues/4118,1198743015,IC_kwDOAMm_X85Hc13n,3019665,2022-07-29T00:14:46Z,2022-07-29T00:14:46Z,NONE,"Wanted to note issue ( https://github.com/carbonplan/ndpyramid/issues/10 ) here, which may be of interest to people here.
Also we are thinking about a Dask blogpost in this space if people have thoughts on what we should include and/or are interested in being involved. Details in issue ( https://github.com/dask/dask-blog/issues/141 ).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,628719058
https://github.com/pydata/xarray/issues/6845#issuecomment-1198655444,https://api.github.com/repos/pydata/xarray/issues/6845,1198655444,IC_kwDOAMm_X85HcgfU,3019665,2022-07-28T21:33:03Z,2022-07-28T21:33:03Z,NONE,"Probably out of my depth here (so please forgive me), but one thing that might be worth looking at is [Array API]( https://data-apis.org/array-api/latest/ ) support, which [CuPy 10+ supports]( https://medium.com/cupy-team/announcing-cupy-v10-b4b0ed6f470a ) and Dask is working on support for ( https://github.com/dask/dask/pull/8750 ). Believe XArray is taking some initial steps in this direction recently ( https://github.com/pydata/xarray/pull/6804 ), but could easily be misunderstanding the scope/intended usage of the changes there.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1321228754
https://github.com/pydata/xarray/pull/6804#issuecomment-1191765132,https://api.github.com/repos/pydata/xarray/issues/6804,1191765132,IC_kwDOAMm_X85HCOSM,3019665,2022-07-21T17:43:20Z,2022-07-21T17:43:20Z,NONE,cc @rgommers (for awareness),"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1307709199
https://github.com/pydata/xarray/issues/3232#issuecomment-1190589331,https://api.github.com/repos/pydata/xarray/issues/3232,1190589331,IC_kwDOAMm_X85G9vOT,3019665,2022-07-20T18:01:56Z,2022-07-20T18:01:56Z,NONE,"While it is true to use PyTorch Tensors directly, one would need the Array API implemented in PyTorch. One could use them indirectly by converting them zero-copy to CuPy arrays, which do have Array API support","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,482543307
https://github.com/pydata/xarray/pull/6542#issuecomment-1122811102,https://api.github.com/repos/pydata/xarray/issues/6542,1122811102,IC_kwDOAMm_X85C7Lze,3019665,2022-05-10T20:06:06Z,2022-05-10T20:06:06Z,NONE,"> @jakirkham were you thinking a reference to the dask docs for more info on optimal chunk sizing and aligning with storage?
It could make sense to refer to or if similar ideas come up here it may be worth mentioning in this change
> or are you suggesting the proposed docs change is too complex?
Not at all.
> I was trying to address the lack of documentation on specifying chunks within a zarr array for _non-dask_ arrays/coordinates, but also covering the weedsy (but common) case of datasets with a mix of dask & in-memory arrays/coords like in my example. I have been frustrated by zarr stores I've written with a couple dozen array chunks and thousands of coordinate chunks for this reason, but it's definitely a gnarly topic to cover concisely :P
If there's anything you need help with or would like to discuss, please don't hesitate to raise [a Zarr issue]( https://github.com/zarr-developers/zarr-python/issues ). We also enabled GH discussions over there so if that fits better feel free to use that π","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1221393104
https://github.com/pydata/xarray/pull/6542#issuecomment-1121430268,https://api.github.com/repos/pydata/xarray/issues/6542,1121430268,IC_kwDOAMm_X85C16r8,3019665,2022-05-09T18:23:03Z,2022-05-09T18:23:03Z,NONE,FWIW there's a similar [doc page about chunk size in Dask]( https://docs.dask.org/en/stable/array-best-practices.html#select-a-good-chunk-size ) that may be worth borrowing from,"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 1}",,1221393104
https://github.com/pydata/xarray/issues/3147#issuecomment-1100938882,https://api.github.com/repos/pydata/xarray/issues/3147,1100938882,IC_kwDOAMm_X85Bnv6C,3019665,2022-04-17T19:44:03Z,2022-04-17T19:44:03Z,NONE,Would be good to keep this open,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,470024896
https://github.com/pydata/xarray/issues/5648#issuecomment-941268682,https://api.github.com/repos/pydata/xarray/issues/5648,941268682,IC_kwDOAMm_X844Gp7K,3019665,2021-10-12T18:26:17Z,2021-10-12T18:26:17Z,NONE,"If you haven't already, would be good if those running into issues here could look over the [Array API]( https://data-apis.org/array-api/latest/ ). This is still something that is being worked on, but the goal is to standardize Array APIs. If there are things missing from that, it would be good to hear about them in [a new issue]( https://github.com/data-apis/array-api/issues/new ).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,956103236
https://github.com/pydata/xarray/issues/5648#issuecomment-924111284,https://api.github.com/repos/pydata/xarray/issues/5648,924111284,IC_kwDOAMm_X843FNG0,3019665,2021-09-21T15:40:28Z,2021-09-21T15:40:28Z,NONE,"Maybe too soon to ask, but do we have a link to the video call?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,956103236
https://github.com/pydata/xarray/pull/5751#issuecomment-908626589,https://api.github.com/repos/pydata/xarray/issues/5751,908626589,IC_kwDOAMm_X842KIqd,3019665,2021-08-30T19:28:37Z,2021-08-30T19:28:37Z,NONE,@Illviljan please let us know if there's anything else needed here π,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,983032639
https://github.com/pydata/xarray/issues/5654#issuecomment-908582707,https://api.github.com/repos/pydata/xarray/issues/5654,908582707,IC_kwDOAMm_X842J98z,3019665,2021-08-30T18:28:27Z,2021-08-30T18:28:27Z,NONE,Thanks Hameer! π,"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,957131705
https://github.com/pydata/xarray/issues/5654#issuecomment-906684668,https://api.github.com/repos/pydata/xarray/issues/5654,906684668,IC_kwDOAMm_X842Cuj8,3019665,2021-08-26T19:30:53Z,2021-08-26T19:30:53Z,NONE,cc @pentschev (just so you are aware),"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,957131705
https://github.com/pydata/xarray/issues/5654#issuecomment-903169462,https://api.github.com/repos/pydata/xarray/issues/5654,903169462,IC_kwDOAMm_X8411UW2,3019665,2021-08-21T19:59:40Z,2021-08-21T19:59:40Z,NONE,Yeah was just mentioning that since we had older version of `sparse` pulled while developing that PR at one point and it caused issues. Sounds like that is not the case here,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,957131705
https://github.com/pydata/xarray/issues/5654#issuecomment-903015237,https://api.github.com/repos/pydata/xarray/issues/5654,903015237,IC_kwDOAMm_X8410utF,3019665,2021-08-21T00:05:35Z,2021-08-21T00:09:08Z,NONE,"Would double check that CI is pulling the latest `sparse`
xref: https://github.com/dask/dask/pull/7939#issuecomment-887122942","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,957131705
https://github.com/pydata/xarray/issues/3147#issuecomment-668263428,https://api.github.com/repos/pydata/xarray/issues/3147,668263428,MDEyOklzc3VlQ29tbWVudDY2ODI2MzQyOA==,3019665,2020-08-03T22:02:22Z,2020-08-03T22:02:22Z,NONE,"Yeah +1 for using `pad` instead. Had tried to get rid of `map_overlap`'s padding and use `da.pad` in Dask as well ( https://github.com/dask/dask/pull/5052 ), but haven't had time to get back to that.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,470024896
https://github.com/pydata/xarray/issues/3232#issuecomment-606354369,https://api.github.com/repos/pydata/xarray/issues/3232,606354369,MDEyOklzc3VlQ29tbWVudDYwNjM1NDM2OQ==,3019665,2020-03-31T02:07:47Z,2020-03-31T02:07:47Z,NONE,Well here's [a blogpost on using Dask + CuPy]( https://blog.dask.org/2019/03/18/dask-nep18 ). Maybe start there and build up to using Xarray.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,482543307
https://github.com/pydata/xarray/issues/3232#issuecomment-606262540,https://api.github.com/repos/pydata/xarray/issues/3232,606262540,MDEyOklzc3VlQ29tbWVudDYwNjI2MjU0MA==,3019665,2020-03-30T21:31:18Z,2020-03-30T21:31:18Z,NONE,"Yeah Jacob and I played with this a few months back. There were some issues, but my recollection is pretty hazy. If someone gives this another try, it would be interesting to hear how things go.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,482543307
https://github.com/pydata/xarray/issues/3815#issuecomment-604207177,https://api.github.com/repos/pydata/xarray/issues/3815,604207177,MDEyOklzc3VlQ29tbWVudDYwNDIwNzE3Nw==,3019665,2020-03-26T03:26:02Z,2020-03-26T03:26:02Z,NONE,Sure an upstream issue would be welcome. Thanks for unpacking that further Mark π,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,573577844
https://github.com/pydata/xarray/issues/3815#issuecomment-604022035,https://api.github.com/repos/pydata/xarray/issues/3815,604022035,MDEyOklzc3VlQ29tbWVudDYwNDAyMjAzNQ==,3019665,2020-03-25T18:51:51Z,2020-03-25T18:51:51Z,NONE,Sorry I don't know. Maybe @rabernat can advise? π,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,573577844
https://github.com/pydata/xarray/pull/3526#issuecomment-554045517,https://api.github.com/repos/pydata/xarray/issues/3526,554045517,MDEyOklzc3VlQ29tbWVudDU1NDA0NTUxNw==,3019665,2019-11-14T19:37:13Z,2019-11-14T19:37:13Z,NONE,"Yeah this probably works as these are just JSON files. That said, IDK that we are making any attempt to ensure this works. IOW I don't think this is tested or in the spec.
Additionally IDK that we do the same decoding on nested dictionaries as would be done on a flat dictionary. Meaning non-JSON values like `datetime64`/`timedelta64` might not be handled correctly in this case.
Could be wrong about these things. Those are just my immediate thoughts.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,522519084
https://github.com/pydata/xarray/pull/3276#issuecomment-540846421,https://api.github.com/repos/pydata/xarray/issues/3276,540846421,MDEyOklzc3VlQ29tbWVudDU0MDg0NjQyMQ==,3019665,2019-10-11T00:03:25Z,2019-10-11T00:03:25Z,NONE,Congratulations! π,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,488243328
https://github.com/pydata/xarray/issues/3147#issuecomment-513044413,https://api.github.com/repos/pydata/xarray/issues/3147,513044413,MDEyOklzc3VlQ29tbWVudDUxMzA0NDQxMw==,3019665,2019-07-19T00:33:55Z,2019-07-19T00:42:03Z,NONE,"Another approach for the `split_by_chunks` implementation would be...
```python
def split_by_chunks(a):
for sl in da.core.slices_from_chunks(a.chunks):
yield (sl, a[sl])
```
While a little bit more cumbersome to write, this could be implemented with `.blocks` and may be a bit more performant.
```python
def split_by_chunks(a):
for i, sl in zip(np.ndindex(a.numblocks), da.core.slices_from_chunks(a.chunks)):
yield (sl, a.blocks[i])
```
If the slices are not strictly needed, this could be simplified a bit more.
```python
def split_by_chunks(a):
for i in np.ndindex(a.numblocks):
yield a.blocks[i]
```
Admittedly `slices_from_chunks` is an internal utility function. Though it is unlikely to change. We could consider exposing it as part of the API if that is useful.
We could consider other things like making `.blocks` iterable, which could make this more friendly as well. Raised issue ( https://github.com/dask/dask/issues/5117 ) on this point.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,470024896
https://github.com/pydata/xarray/issues/3147#issuecomment-513029753,https://api.github.com/repos/pydata/xarray/issues/3147,513029753,MDEyOklzc3VlQ29tbWVudDUxMzAyOTc1Mw==,3019665,2019-07-18T23:22:11Z,2019-07-18T23:22:11Z,NONE,That sounds somewhat similar to `.blocks` accessor in Dask Array. ( https://github.com/dask/dask/pull/3689 ) Maybe we should align on that as well?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,470024896
https://github.com/pydata/xarray/issues/2586#issuecomment-453807790,https://api.github.com/repos/pydata/xarray/issues/2586,453807790,MDEyOklzc3VlQ29tbWVudDQ1MzgwNzc5MA==,3019665,2019-01-13T07:11:23Z,2019-01-13T07:11:23Z,NONE,"I'm not really familiar with XArray's internals, but issue ( https://github.com/pydata/xarray/issues/2660 ) looks relevant.
What happens if you do?
```python
ds.to_zarr(zarr.group(zarr.ZipStore(""test.zarr"")))
print(xr.open_zarr(zarr.group(zarr.ZipStore(""test.zarr""))))
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,386515973
https://github.com/pydata/xarray/pull/2398#issuecomment-422893434,https://api.github.com/repos/pydata/xarray/issues/2398,422893434,MDEyOklzc3VlQ29tbWVudDQyMjg5MzQzNA==,3019665,2018-09-19T17:38:42Z,2018-09-19T17:38:42Z,NONE,"@shoyer, have you seen `da.pad`?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,356698348
https://github.com/pydata/xarray/issues/1770#issuecomment-396828029,https://api.github.com/repos/pydata/xarray/issues/1770,396828029,MDEyOklzc3VlQ29tbWVudDM5NjgyODAyOQ==,3019665,2018-06-13T06:27:36Z,2018-06-13T06:27:36Z,NONE,Is this still an issue?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,280626621
https://github.com/pydata/xarray/issues/2074#issuecomment-383723159,https://api.github.com/repos/pydata/xarray/issues/2074,383723159,MDEyOklzc3VlQ29tbWVudDM4MzcyMzE1OQ==,3019665,2018-04-23T21:06:42Z,2018-04-23T21:06:42Z,NONE,"> from what I understand `da.dot` implements... a limited special case of `da.einsum`?
Basically `dot` is an inner product. Certainly inner products can be formulated using Einstein notation (i.e. calling with `einsum`).
The question is whether the performance keeps up with that formulation. Currently it sounds like chunking causes some problems right now IIUC. However things like `dot` and `tensordot` dispatch through optimized BLAS routines. In theory `einsum` should do the same ( https://github.com/numpy/numpy/pull/9425 ), but the experimental data still shows a few warts. For example, `matmul` is implemented with `einsum`, but is slower than `dot`. ( https://github.com/numpy/numpy/issues/7569 ) ( https://github.com/numpy/numpy/issues/8957 ) Pure `einsum` implementations seem to perform similarly.
> I ran a few more benchmarks...
What are the arrays used as input for this case?
> ...apparently `xarray.dot` on a dask backend is situationally faster than all other implementations when you are not reducing on any dimensions...
Having a little trouble following this. `dot` reduces one dimension from each input. Excepting if one of the inputs is 0-D (i.e. a scalar), then it is just multiplying a single scalar through an array. Is that what you are referring?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,316618290
https://github.com/pydata/xarray/issues/2074#issuecomment-383637379,https://api.github.com/repos/pydata/xarray/issues/2074,383637379,MDEyOklzc3VlQ29tbWVudDM4MzYzNzM3OQ==,3019665,2018-04-23T16:26:51Z,2018-04-23T16:26:51Z,NONE,"Might be worth revisiting how `da.dot` is implemented as well. That would be the least amount of rewriting for you and would generally be nice for Dask users. If you have not already, @crusaderky, it would be nice to raise an issue over at Dask with a straight Dask benchmark comparing Dask Array's `dot` and `einsum`.
cc @mrocklin","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,316618290
https://github.com/pydata/xarray/issues/1784#issuecomment-367164232,https://api.github.com/repos/pydata/xarray/issues/1784,367164232,MDEyOklzc3VlQ29tbWVudDM2NzE2NDIzMg==,3019665,2018-02-20T23:58:47Z,2018-02-20T23:58:47Z,NONE,What is `store` in this case? Sorry not very familiar with how xarray does things.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,282178751
https://github.com/pydata/xarray/pull/1528#issuecomment-364812486,https://api.github.com/repos/pydata/xarray/issues/1528,364812486,MDEyOklzc3VlQ29tbWVudDM2NDgxMjQ4Ng==,3019665,2018-02-12T01:51:40Z,2018-02-12T01:51:40Z,NONE,"So Zarr supports storing structured arrays. Maybe thatβs what you are looking for, @martindurant? Would suggest using the latest 2.2.0 RC though as it fixed a few issues in this regard (particularly with NumPy 1.14).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,253136694
https://github.com/pydata/xarray/pull/1793#issuecomment-360590825,https://api.github.com/repos/pydata/xarray/issues/1793,360590825,MDEyOklzc3VlQ29tbWVudDM2MDU5MDgyNQ==,3019665,2018-01-25T20:29:58Z,2018-01-25T20:29:58Z,NONE,"Yep, using `dask.array.store` regularly with the `distributed` scheduler both on our cluster and in a local Docker image for testing. Am using Zarr Arrays as the targets for `store` to write to. Basically rechunk the data to match the chunking selected for the Zarr Array and then write out in parallel lock-free.
Our cluster uses NFS for things like one's home directory. So these are accessible across nodes. Also there are other types of storage available that are a bit faster and still remain accessible across nodes. So these work pretty well.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,283388962
https://github.com/pydata/xarray/issues/1784#issuecomment-352036122,https://api.github.com/repos/pydata/xarray/issues/1784,352036122,MDEyOklzc3VlQ29tbWVudDM1MjAzNjEyMg==,3019665,2017-12-15T15:38:14Z,2017-12-15T15:38:14Z,NONE,"In case anyone is curious, PR ( https://github.com/dask/dask/pull/2980 ) contains this work. Feedback welcome.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,282178751
https://github.com/pydata/xarray/issues/1784#issuecomment-351837521,https://api.github.com/repos/pydata/xarray/issues/1784,351837521,MDEyOklzc3VlQ29tbWVudDM1MTgzNzUyMQ==,3019665,2017-12-14T21:13:30Z,2017-12-14T21:13:30Z,NONE,"Just to give a brief synopsis of what we are working in Dask in case it is valuable for this or other contexts, have given an overview of the relevant work below.
With Matthew's help am trying to add a `keep` argument to `da.store`. By default `keep=False`, which is the current behavior of `da.store`. If `keep=True` however, it returns Dask Arrays that can lazily load data written by `da.store`. Thus allowing the stored result to be linked to later computations before it is fully written. The `compute` argument of `da.store` affects whether to submit the storage tasks immediately (adding `Future`s into the resultant Dask Array) or whether to hold off until a later computation step triggers it.
This sort of functionality could be useful for a variety of situations including the one Matthew has described above. Also this could be useful for viewing partially computed results before they are totally done. Another use case could be more rapid batching of computations with many intermediate values. There is also an opportunity to re-explore caching in this context; thus, revisiting an area that many people have previously shown interest in.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,282178751
https://github.com/pydata/xarray/pull/1528#issuecomment-350504017,https://api.github.com/repos/pydata/xarray/issues/1528,350504017,MDEyOklzc3VlQ29tbWVudDM1MDUwNDAxNw==,3019665,2017-12-09T20:38:58Z,2017-12-09T20:38:58Z,NONE,"> Just to confirm, if writes are aligned with chunk boundaries in the destination array then no locking is required.
As a minor point to complement what Matthew and Alistair have already said, one can pretty easily `rechunk` beforehand so that the chunks will have a nice 1-to-1 non-overlapping mapping on disk. Not sure whether this strategy is good enough to make default. However have had no issues doing this myself. Also would expect it is better than holding one lock over the whole Zarr Array. Though there may be some strange edge cases that I have not encountered.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,253136694
https://github.com/pydata/xarray/issues/1759#issuecomment-349772394,https://api.github.com/repos/pydata/xarray/issues/1759,349772394,MDEyOklzc3VlQ29tbWVudDM0OTc3MjM5NA==,3019665,2017-12-06T20:57:51Z,2017-12-06T20:57:51Z,NONE,"Given the recent turn in discussion here, might be worthwhile to share some thoughts on issue ( https://github.com/dask/dask/issues/2694 ).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,279161550
https://github.com/pydata/xarray/pull/860#issuecomment-221893997,https://api.github.com/repos/pydata/xarray/issues/860,221893997,MDEyOklzc3VlQ29tbWVudDIyMTg5Mzk5Nw==,3019665,2016-05-26T14:51:14Z,2016-05-26T14:51:14Z,NONE,"Also, FYI we have `python-coveralls` currently. Though we don't have `coveralls` yet.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,156793282
https://github.com/pydata/xarray/pull/860#issuecomment-221758918,https://api.github.com/repos/pydata/xarray/issues/860,221758918,MDEyOklzc3VlQ29tbWVudDIyMTc1ODkxOA==,3019665,2016-05-26T02:04:59Z,2016-05-26T02:04:59Z,NONE,"Please let me know if there is something actionable for me here. Looks like that is not the case. If that changes, please let me know.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,156793282