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- docs on specifying chunks in to_zarr encoding arg · 17 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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1165862649 | https://github.com/pydata/xarray/pull/6542#issuecomment-1165862649 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85Ffab5 | andersy005 13301940 | 2022-06-24T19:18:08Z | 2022-06-24T19:18:08Z | MEMBER | my bad :) thank you for reporting this in #6720. I'm going to look into what;s going on |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1165821172 | https://github.com/pydata/xarray/pull/6542#issuecomment-1165821172 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85FfQT0 | delgadom 3698640 | 2022-06-24T18:18:47Z | 2022-06-24T18:18:47Z | CONTRIBUTOR | @andersy005 last I saw this was still not building on readthedocs! I never figured out how to get around the build timeout are you sure this PR was good to go? |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1164899177 | https://github.com/pydata/xarray/pull/6542#issuecomment-1164899177 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85FbvNp | andersy005 13301940 | 2022-06-23T21:31:01Z | 2022-06-23T21:31:01Z | MEMBER | Thank you, @delgadom! |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1123949197 | https://github.com/pydata/xarray/pull/6542#issuecomment-1123949197 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85C_hqN | delgadom 3698640 | 2022-05-11T15:45:24Z | 2022-05-11T15:45:24Z | CONTRIBUTOR |
@jakirkham appreciate that! And just to clarify my confusion/frustration in the past was simply around the issue that I'm documenting here, which I've finally figured out! so hopefully this will help resolve the problem for future users. I agree with Ryan that there might be some changes in the defaults that could be helpful here, though setting intuitive defaults other than zarr's defaults could get messy for complex datasets with a mix of dask and in-memory arrays. But I think that's all on the xarray side? |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1122811102 | https://github.com/pydata/xarray/pull/6542#issuecomment-1122811102 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85C7Lze | jakirkham 3019665 | 2022-05-10T20:06:06Z | 2022-05-10T20:06:06Z | NONE |
It could make sense to refer to or if similar ideas come up here it may be worth mentioning in this change
Not at all.
If there's anything you need help with or would like to discuss, please don't hesitate to raise a Zarr issue. We also enabled GH discussions over there so if that fits better feel free to use that 🙂 |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1122796867 | https://github.com/pydata/xarray/pull/6542#issuecomment-1122796867 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85C7IVD | delgadom 3698640 | 2022-05-10T19:48:34Z | 2022-05-10T19:49:04Z | CONTRIBUTOR | @jakirkham were you thinking a reference to the dask docs for more info on optimal chunk sizing and aligning with storage? or are you suggesting the proposed docs change is too complex? 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 |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1122790681 | https://github.com/pydata/xarray/pull/6542#issuecomment-1122790681 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85C7G0Z | delgadom 3698640 | 2022-05-10T19:41:12Z | 2022-05-10T19:41:12Z | CONTRIBUTOR | thank you all for being patient with this PR! seems the build failed again for the same reason. I think there might be something wrong with my examples, though it beats me what the issue is. As far as I can tell, most builds come in somewhere in the mid 900s range on readthedocs but my branch consistently times out at 1900s. I'll see if I can muster a bit of time to run through the exact rtd build workflow and figure out what's going on but probably won't get to it until this weekend. |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1121958961 | https://github.com/pydata/xarray/pull/6542#issuecomment-1121958961 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85C37wx | max-sixty 5635139 | 2022-05-10T05:51:15Z | 2022-05-10T05:51:15Z | MEMBER |
That's not fun at all. FWIW most seem to pass, so you may have been unlucky. I restarted the build by merging main into the branch. Let's hope this completes. Thanks a lot for both the contribution and your patience @delgadom ... |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1121430268 | https://github.com/pydata/xarray/pull/6542#issuecomment-1121430268 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85C16r8 | jakirkham 3019665 | 2022-05-09T18:23:03Z | 2022-05-09T18:23:03Z | NONE | FWIW there's a similar doc page about chunk size in Dask that may be worth borrowing from |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1119775222 | https://github.com/pydata/xarray/pull/6542#issuecomment-1119775222 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85Cvmn2 | delgadom 3698640 | 2022-05-06T16:07:44Z | 2022-05-06T16:07:44Z | CONTRIBUTOR | now I'm getting reproducible build timeouts 😭 The docs build alone (just Thanks for all the help everyone! |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1118786888 | https://github.com/pydata/xarray/pull/6542#issuecomment-1118786888 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85Cr1VI | delgadom 3698640 | 2022-05-05T16:36:02Z | 2022-05-05T16:36:02Z | CONTRIBUTOR | @dcherian - yep I was trying to follow that guide closely but was still struggling with building using conda on my laptop's miniconda environment. The sphinx ipython directive kept running in the wrong conda environment, even after deleting sphinx, ipython, and ipykernel on my base env and making sure the env I was running |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1118775756 | https://github.com/pydata/xarray/pull/6542#issuecomment-1118775756 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85CrynM | delgadom 3698640 | 2022-05-05T16:31:06Z | 2022-05-05T16:31:06Z | CONTRIBUTOR | !!! @andersy005 thank you so much! yes - I was using a shallow clone inside the docker version of the build. I really appreciate the review and for catching my error. I'll clean this up and push the changes. |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1118110207 | https://github.com/pydata/xarray/pull/6542#issuecomment-1118110207 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85CpQH_ | andersy005 13301940 | 2022-05-05T02:37:36Z | 2022-05-05T02:37:36Z | MEMBER |
looking at the reported xarray version, i'm curious... 🧐 are you using a shallow git clone of xarray? I'm able to reproduce the version issue via these steps:
```bash conda list xarray ─╯ packages in environment at /Users/andersy005/mambaforge/envs/test:Name Version Build Channelxarray 0.1.dev1+g126051f dev_0 <develop> ``` |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1115281749 | https://github.com/pydata/xarray/pull/6542#issuecomment-1115281749 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85CedlV | dcherian 2448579 | 2022-05-02T19:33:05Z | 2022-05-02T19:33:05Z | MEMBER | Does this part of the docs help |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1114097888 | https://github.com/pydata/xarray/pull/6542#issuecomment-1114097888 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85CZ8jg | delgadom 3698640 | 2022-05-01T01:47:27Z | 2022-05-01T01:47:27Z | CONTRIBUTOR | sorry I know I said I'd fix this but I'm having a very hard time figuring out what is wrong and how to build the docs. I had to set up a docker image to build them because I couldn't get the ipython directive to use the right conda env on my laptop, and now I'm getting a version error when pandas encounters the default build number on my fork. I'm a bit embarrassed that I can't figure this out, but... I think I might need a hand getting this across the finish line 😕 ``` .... 13 1597.6 reading sources... [ 97%] getting-started-guide/faq13 1600.8 reading sources... [ 97%] getting-started-guide/index13 1600.8 reading sources... [ 97%] getting-started-guide/installing13 1601.0 reading sources... [ 97%] getting-started-guide/quick-overview13 1609.3 WARNING:13 1609.3 >>>-------------------------------------------------------------------------13 1609.3 Exception in /xarray/doc/getting-started-guide/quick-overview.rst at block ending on line 16913 1609.3 Specify :okexcept: as an option in the ipython:: block to suppress this message13 1609.3 ---------------------------------------------------------------------------13 1609.3 ImportError Traceback (most recent call last)13 1609.3 Input In [40], in <cell line: 1>()13 1609.3 ----> 1 series.to_xarray()13 1609.313 1609.3 File /srv/conda/envs/xarray-doc/lib/python3.9/site-packages/pandas/core/generic.py:3173, in NDFrame.to_xarray(self)13 1609.3 3096 @final13 1609.3 3097 def to_xarray(self):13 1609.3 3098 """13 1609.3 3099 Return an xarray object from the pandas object.13 1609.3 310013 1609.3 (...)13 1609.3 3171 speed (date, animal) int64 350 18 361 1513 1609.3 3172 """13 1609.3 -> 3173 xarray = import_optional_dependency("xarray")13 1609.3 3175 if self.ndim == 1:13 1609.3 3176 return xarray.DataArray.from_series(self)13 1609.313 1609.3 File /srv/conda/envs/xarray-doc/lib/python3.9/site-packages/pandas/compat/_optional.py:164, in import_optional_dependency(name, extra, errors, min_version)13 1609.3 162 return None13 1609.3 163 elif errors == "raise":13 1609.3 --> 164 raise ImportError(msg)13 1609.3 166 return module13 1609.313 1609.3 ImportError: Pandas requires version '0.15.1' or newer of 'xarray' (version '0.1.dev1+gfdf7303' currently installed).13 1609.313 1609.3 <<<-------------------------------------------------------------------------13 1609.313 1609.3 Exception occurred:13 1609.3 File "/srv/conda/envs/xarray-doc/lib/python3.9/site-packages/IPython/sphinxext/ipython_directive.py", line 584, in process_input13 1609.3 raise RuntimeError('Non Expected exception in
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1113712207 | https://github.com/pydata/xarray/pull/6542#issuecomment-1113712207 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85CYeZP | delgadom 3698640 | 2022-04-29T20:44:43Z | 2022-04-29T20:44:43Z | CONTRIBUTOR | hmmm seems I've messed something up in the docs build. apologize for the churn - will fix. |
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docs on specifying chunks in to_zarr encoding arg 1221393104 | |
1113613457 | https://github.com/pydata/xarray/pull/6542#issuecomment-1113613457 | https://api.github.com/repos/pydata/xarray/issues/6542 | IC_kwDOAMm_X85CYGSR | max-sixty 5635139 | 2022-04-29T18:44:00Z | 2022-04-29T18:44:00Z | MEMBER | This looks very well-written @delgadom , thank you! I'll let someone who knows the content better do a review too. |
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docs on specifying chunks in to_zarr encoding arg 1221393104 |
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