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/1745#issuecomment-356390513,https://api.github.com/repos/pydata/xarray/issues/1745,356390513,MDEyOklzc3VlQ29tbWVudDM1NjM5MDUxMw==,1217238,2018-01-09T19:36:10Z,2018-01-09T19:36:10Z,MEMBER,Both the warning message and the upstream anaconda issue seem like good ideas to me.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-352152392,https://api.github.com/repos/pydata/xarray/issues/1745,352152392,MDEyOklzc3VlQ29tbWVudDM1MjE1MjM5Mg==,1217238,2017-12-16T01:58:02Z,2017-12-16T01:58:02Z,MEMBER,"If upgrating to a newer version of netcdf4-python isn't an option we might need to figure out a workaround for xarray....
It seems that anaconda is still distributing netCDF4 1.2.4, which doesn't help here.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-351788352,https://api.github.com/repos/pydata/xarray/issues/1745,351788352,MDEyOklzc3VlQ29tbWVudDM1MTc4ODM1Mg==,1217238,2017-12-14T17:58:05Z,2017-12-14T17:58:05Z,MEMBER,"Can you reproduce this just using netCDF4-python?
Try:
```
import netCDF4
ds = netCDF4.Dataset(path)
# print(ds)
print(ds.filepath())
```
If so, it would be good to file a bug upstream.
Actually, it looks like this might be https://github.com/Unidata/netcdf4-python/issues/506","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-351783850,https://api.github.com/repos/pydata/xarray/issues/1745,351783850,MDEyOklzc3VlQ29tbWVudDM1MTc4Mzg1MA==,1217238,2017-12-14T17:41:05Z,2017-12-14T17:41:11Z,MEMBER,"I think there is probably a bug buried inside the `netCDF4.Dataset.filepath()` method somewhere. For example, on netCDF4-python 1.2.4, this would crash if you have any non-ASCII characters in the path. But that doesn't seem to be the issue here.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-351780487,https://api.github.com/repos/pydata/xarray/issues/1745,351780487,MDEyOklzc3VlQ29tbWVudDM1MTc4MDQ4Nw==,1217238,2017-12-14T17:28:37Z,2017-12-14T17:28:37Z,MEMBER,@braaannigan can you try adding `print(repr(path))` to `is_remote_uri()` so we can see exactly what these offending strings look like?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-351779445,https://api.github.com/repos/pydata/xarray/issues/1745,351779445,MDEyOklzc3VlQ29tbWVudDM1MTc3OTQ0NQ==,1217238,2017-12-14T17:24:40Z,2017-12-14T17:24:40Z,MEMBER,"`re.match(pattern, string)` is equivalent to `re.search('^' + pattern, string)`, so arguably this is a cleaner solution anyways. But ideally I'd like to understand *why* this is a problem for you, so we can fix the underlying cause and not do it again.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-351765967,https://api.github.com/repos/pydata/xarray/issues/1745,351765967,MDEyOklzc3VlQ29tbWVudDM1MTc2NTk2Nw==,1217238,2017-12-14T16:41:19Z,2017-12-14T16:41:19Z,MEMBER,"@braaannigan what about replacing `re.search('^https?\://', path)` with `re.match('https?\://', path)`? Can you share the output of running `python -c 'import sys; print(sys.getfilesystemencoding())'` at the command line? Also, please try `engine='scipy'` or `engine='h5netcdf'` with `open_dataset`. The output of `xarray.show_versions()` would also be helpful.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-351470450,https://api.github.com/repos/pydata/xarray/issues/1745,351470450,MDEyOklzc3VlQ29tbWVudDM1MTQ3MDQ1MA==,1217238,2017-12-13T17:54:54Z,2017-12-13T17:54:54Z,MEMBER,"@braaannigan Can you share the name of your problematic file?
One possibility is that `re.search()` is not thread-safe, even though I don't think we call `is_remote_uri` from multiple threads. We can test that by adding a lock, and seeing if that resolves the issue. Try replacing `is_remote_uri` with:
```python
import threading
LOCK = threading.Lock()
def is_remote_uri(path):
with LOCK:
return bool(re.search('^https?\://', path))
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-347856861,https://api.github.com/repos/pydata/xarray/issues/1745,347856861,MDEyOklzc3VlQ29tbWVudDM0Nzg1Njg2MQ==,6213168,2017-11-29T13:15:29Z,2017-11-29T13:15:29Z,MEMBER,Only if the coords are tridimensional.. ,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-347819491,https://api.github.com/repos/pydata/xarray/issues/1745,347819491,MDEyOklzc3VlQ29tbWVudDM0NzgxOTQ5MQ==,1217238,2017-11-29T10:34:25Z,2017-11-29T10:34:25Z,MEMBER,"`(405*282*37)*20*8` bytes = 676 MB, so running out of memory here seems plausible to me.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-347815737,https://api.github.com/repos/pydata/xarray/issues/1745,347815737,MDEyOklzc3VlQ29tbWVudDM0NzgxNTczNw==,6213168,2017-11-29T10:19:52Z,2017-11-29T10:33:15Z,MEMBER,"It sounds weird. Even if all the 20 variables he's dropping were coords on the longest dim, and the code was loading them up into memory and then dropping them (that would be wrong - but I didn't check the code yet to verify if that's the case), then we're talking about... `405*20*73=~690k` points? That's about 5mb of RAM if they're float64?
@njweber2 how large are these files? Is it feasible to upload them somewhere? If not, could you write a script that generates equivalent dummy data and reproduce the problem with that? ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485
https://github.com/pydata/xarray/issues/1745#issuecomment-347811473,https://api.github.com/repos/pydata/xarray/issues/1745,347811473,MDEyOklzc3VlQ29tbWVudDM0NzgxMTQ3Mw==,1217238,2017-11-29T10:03:51Z,2017-11-29T10:03:51Z,MEMBER,"I think this was introduced by https://github.com/pydata/xarray/pull/1551, where we started loading coordinates that are compared for equality into memory. This speeds up `open_mfdataset`, but does increase memory usage.
We might consider adding an option for reduced memory usage at the price of speed. @crusaderky @jhamman @rabernat any thoughts?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,277538485