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/5254#issuecomment-832454582,https://api.github.com/repos/pydata/xarray/issues/5254,832454582,MDEyOklzc3VlQ29tbWVudDgzMjQ1NDU4Mg==,22542812,2021-05-05T06:48:46Z,2021-05-05T06:48:46Z,NONE,"@mathause Indeed, I am using `engine=""h5netcdf"", invalid_netcdf=True`.
I would also agree on the point that expanding the `isinstance` is not the best solution. Duck typing makes reliable instance checks quite painful.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,874695249
https://github.com/pydata/xarray/issues/2292#issuecomment-722565840,https://api.github.com/repos/pydata/xarray/issues/2292,722565840,MDEyOklzc3VlQ29tbWVudDcyMjU2NTg0MA==,22542812,2020-11-05T18:41:24Z,2020-11-05T18:41:24Z,NONE,"I just came along this question as I tried something similar to @joshburkart. Using a string-enum instead, the code works in principle:
```python
import enum
import numpy as np
import pandas as pd
import xarray as xr
class CoordId(str, enum.Enum):
LAT = 'lat'
LON = 'lon'
pd.DataFrame({CoordId.LAT: [1,2,3]}).to_csv()
# Returns: ',CoordId.LAT\n0,1\n1,2\n2,3\n'
xr.DataArray(
data=np.arange(3 * 2).reshape(3, 2),
coords={CoordId.LAT: [1, 2, 3], CoordId.LON: [7, 8]},
dims=[CoordId.LAT, CoordId.LON],
)
# output
#
# array([[0, 1],
# [2, 3],
# [4, 5]])
# Coordinates:
# * lat (CoordId.LAT) int64 1 2 3
# * lon (CoordId.LON) int64 7 8
```
We however got somewhat ambivalent results, that the dimensions are still enum elements `dims = (, )`, but the coordinate names are the strings. After writing and reading the `DataArray`, everything is a plain string, we can still access the elements using the enum elements, as they are equal to the strings.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341643235
https://github.com/pydata/xarray/issues/4507#issuecomment-707800003,https://api.github.com/repos/pydata/xarray/issues/4507,707800003,MDEyOklzc3VlQ29tbWVudDcwNzgwMDAwMw==,22542812,2020-10-13T14:59:36Z,2020-10-13T14:59:36Z,NONE,"I agree, that the given example problem is related to a `tolerance`.
In principle, I see the problem in the current practice of just dropping data that doesn't align. If I perform an assignment `=`, I do not expect to lose any data.
Another example would be assigning:
```python
dataset['data2'] = xr.DataArray(np.random.random(50), dims=['x'], coords={'x': np.linspace(2, 12)})
```
This line of code would effectively do nothing, I generate data and upon assignment it is dropped.
But this might be a bit of a physiological question, what the governing design principle is. Personally I think, an assignment should only be possible if the assigned coordinates are a subset of the dataset's coordinates.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,720315478
https://github.com/pydata/xarray/issues/3583#issuecomment-560338657,https://api.github.com/repos/pydata/xarray/issues/3583,560338657,MDEyOklzc3VlQ29tbWVudDU2MDMzODY1Nw==,22542812,2019-12-02T10:40:23Z,2019-12-02T10:40:23Z,NONE,"I am very sorry, I didn't realize that there had been a new release. Everything is fine after updating.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,530448473
https://github.com/pydata/xarray/issues/3297#issuecomment-530680614,https://api.github.com/repos/pydata/xarray/issues/3297,530680614,MDEyOklzc3VlQ29tbWVudDUzMDY4MDYxNA==,22542812,2019-09-12T06:11:02Z,2019-09-12T06:11:02Z,NONE,"Sorry for the slow response, I have little time at the moment. The option `invalid_netcdf=True` is not yet in the latest release, is it? I get an `TypeError`.
I would have to use a manually installed version of `xarray` to use it, right?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,491215043
https://github.com/pydata/xarray/issues/3297#issuecomment-529689580,https://api.github.com/repos/pydata/xarray/issues/3297,529689580,MDEyOklzc3VlQ29tbWVudDUyOTY4OTU4MA==,22542812,2019-09-09T22:20:08Z,2019-09-09T22:20:08Z,NONE,"I agree that including it in NetCDF is the 'most sane' approach. I don't really know how much work it is, expanding the standard.
To be honest, I don't really care about NetCDF, for me `xarray` is just an incredible good way to make code more stable and readable (though it still has several usability issues). In my community everyone uses HDF5 anyway, so dropping compatibility is no big issue. I just want a way to persist data as it is and conveniently load it for plotting and post processing.
I would still encourage you to push saving of complex data. In most fields people use complex data and it is hard to convince them that they benefit from this great library, if saving simple data takes complicated keyword arguments and annoys you with warnings compared to a simple `np.savez` on regular `ndarray`s.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,491215043
https://github.com/pydata/xarray/issues/2799#issuecomment-529569885,https://api.github.com/repos/pydata/xarray/issues/2799,529569885,MDEyOklzc3VlQ29tbWVudDUyOTU2OTg4NQ==,22542812,2019-09-09T16:53:20Z,2019-09-09T16:53:20Z,NONE,"It might be interesting to see, if [pythran](https://pythran.readthedocs.io/en/latest/) is an alternative to Cython. It seems like it handles high level `numpy` quite well, and would retain the readability of Python. Of course, it has its own issues...
But it seems like other libraries like e.g. [scikit-image](https://github.com/scikit-image/scikit-image/issues/2956) made some good experience with it.
Sadly I can't be of much help, as I lack experience (and most importantly time).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,416962458