issues

Working in a notebook (and presumably, anywhere else that uses the HTML formatter to show an array), non-string attribute keys cause an exception. The output then falls back to the repr value.

```python console In [1]: import xarray as xr

In [2]: data = xr.DataArray([1, 2, 3], attrs={1: 3.14})

In [3]: data.attrs Out[3]: {1: 3.14}

In [4]: data python traceback

---

AttributeError Traceback (most recent call last) /usr/lib/python3.9/site-packages/IPython/core/formatters.py in call(self, obj) 343 method = get_real_method(obj, self.print_method) 344 if method is not None: --> 345 return method() 346 return None 347 else:

~/software/external/xarray/xarray/core/common.py in repr_html(self) 148 if OPTIONS["display_style"] == "text": 149 return f"

{escape(repr(self))}

" --> 150 return formatting_html.array_repr(self) 151 152 def _iter(self: Any) -> Iterator[Any]:

~/software/external/xarray/xarray/core/formatting_html.py in array_repr(arr) 269 sections.append(coord_section(arr.coords)) 270 --> 271 sections.append(attr_section(arr.attrs)) 272 273 return _obj_repr(arr, header_components, sections)

~/software/external/xarray/xarray/core/formatting_html.py in _mapping_section(mapping, name, details_func, max_items_collapse, enabled) 171 return collapsible_section( 172 name, --> 173 details=details_func(mapping), 174 n_items=n_items, 175 enabled=enabled,

~/software/external/xarray/xarray/core/formatting_html.py in summarize_attrs(attrs) 47 48 def summarize_attrs(attrs): ---> 49 attrs_dl = "".join( 50 f"<dt>{escape(k)} :</dt>" f"<dd>{escape(str(v))}</dd>" 51 for k, v in attrs.items()

~/software/external/xarray/xarray/core/formatting_html.py in <genexpr>(.0) 48 def summarize_attrs(attrs): 49 attrs_dl = "".join( ---> 50 f"<dt>{escape(k)} :</dt>" f"<dd>{escape(str(v))}</dd>" 51 for k, v in attrs.items() 52 )

/usr/lib/python3.9/html/init.py in escape(s, quote) 17 translated. 18 """ ---> 19 s = s.replace("&", "&") # Must be done first! 20 s = s.replace("<", "<") 21 s = s.replace(">", ">")

AttributeError: 'int' object has no attribute 'replace' python console Out[4]: <xarray.DataArray (dim_0: 3)> array([1, 2, 3]) Dimensions without coordinates: dim_0 Attributes: 1: 3.14 ```

Environment:

Output of <tt>xr.show_versions()</tt>

INSTALLED VERSIONS ------------------ commit: c91983d4765b23e0474231c85057d31f9b6b2f33 python: 3.9.2 (default, Feb 20 2021, 18:40:11) [GCC 10.2.0] python-bits: 64 OS: Linux OS-release: 5.11.13-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_NZ.UTF-8 LOCALE: en_NZ.UTF-8 libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 0.17.0 pandas: 1.2.3 numpy: 1.20.1 scipy: 1.6.2 netCDF4: 1.5.6 pydap: None h5netcdf: 0.10.0 h5py: 3.2.1 Nio: None zarr: None cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.2 cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.03.0 distributed: 2021.03.0 matplotlib: 3.4.1 cartopy: 0.18.0 seaborn: None numbagg: None pint: None setuptools: 54.2.0 pip: 20.3.1 conda: None pytest: 6.2.3 IPython: 7.22.0 sphinx: 3.5.4

Datasets opened from disk are cached with a key based (amongst other things) on their filename. If you have the same filename in different directories, and open them after changing directory, a cache collision occurs as the filename is the same and so the first opened dataset is always returned.

Minimal Complete Verifiable Example:

```python import os from pathlib import Path import tempfile

import numpy as np import xarray as xr

with tempfile.TemporaryDirectory() as d: base = Path(d).resolve()

# Create some data in separate directories but with same filename.
(base / "zeros").mkdir()
z_fn = base / "zeros" / "data.nc"
xr.DataArray(np.zeros((5, 5), dtype=int)).to_netcdf(z_fn)
(base / "ones").mkdir()
o_fn = base / "ones" / "data.nc"
xr.DataArray(np.ones((5, 5), dtype=int)).to_netcdf(o_fn)

# Open with the absolute path and check we get what we expect.
z_abs = xr.open_dataarray(z_fn)
o_abs = xr.open_dataarray(o_fn)
assert (z_abs == 0).all(), "zeros with absolute path incorrect"
assert (o_abs == 1).all(), "zeros with absolute path incorrect"

# Open with relative path from base directory.
os.chdir(base)
z_base = xr.open_dataarray("zeros/data.nc")
o_base = xr.open_dataarray("ones/data.nc")
assert (z_base == 0).all(), "zeros with relative path from base incorrect"
assert (o_base == 1).all(), "zeros with relative path from base incorrect"

# Open from containing directory.
os.chdir(base / "zeros")
z_local = xr.open_dataarray("data.nc")
os.chdir(base / "ones")
o_local = xr.open_dataarray("data.nc")
assert (z_local == 0).all(), "zeros opened from containing dir incorrect"
assert (o_local == 1).all(), "ones opened from containing dir incorrect"

```

What happened: On master, the final assertion is triggered as the cache returns the zeros array instead of the ones.

What you expected to happen: No assertion.

Anything else we need to know?: This was introduced in 50d97e9d. I found this with the above test script (named cache_bug.py) with a Git bisect session:

console $ git bisect start master v0.16.2 Bisecting: 88 revisions left to test after this (roughly 7 steps) [d555172c7d069ca9cf7a9a32bfd5f422be133861] Allow swap_dims to take kwargs (#4841) $ git bisect run python cache_bug.py ... 50d97e9d35bac783850827fa66ff5eb768e62905 is the first bad commit ...

I then manually confirmed this by running the script on 50d97e9d and its parent.

The caching is performed by xarray.backends.file_manager.CachingFileManager. The obvious solution would be to use pathlib / os.path (whichever is preferred in xarray) to convert the paths to absolute before caching. For example, changing the default netCDF4 backend from

https://github.com/pydata/xarray/blob/e56905889c836c736152b11a7e6117a229715975/xarray/backends/netCDF4_.py#L375-L377

to

python manager = CachingFileManager( netCDF4.Dataset, os.path.abspath(filename), mode=mode, kwargs=kwargs )

fixes this for me. I guess this should be done (if needed) by each backend to keep CachingFileManager as general as possible.

If my analysis and proposed solution seems correct, I'm happy to work up a pull request with these fixes and some regression tests.

If you're wondering about the use case where I bumped into this problem: we're using Click for a CLI, and using its test helpers. One of these (isolated_filesystem) creates and changes into an empty temporary directory before running the CLI function under test, so we can use open_dataset("output.nc") to load the CLI output for checking. Since it does this in the same process, using a parametrized test function means the first created file is always loaded for checking. Took a while to track down what was happening!

Environment:

Output of <tt>xr.show_versions()</tt>

INSTALLED VERSIONS ------------------ commit: ec4e8b5f279e28588eee8ff43a328ca6c2f89f01 python: 3.9.2 (default, Feb 20 2021, 18:40:11) [GCC 10.2.0] python-bits: 64 OS: Linux OS-release: 5.11.11-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_NZ.UTF-8 LOCALE: en_NZ.UTF-8 libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 0.17.0 pandas: 1.2.3 numpy: 1.20.1 scipy: 1.6.2 netCDF4: 1.5.6 pydap: None h5netcdf: 0.9.0 h5py: 3.1.0 Nio: None zarr: None cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.1 cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.03.0 distributed: 2021.03.0 matplotlib: 3.4.1 cartopy: 0.18.0 seaborn: None numbagg: None pint: None setuptools: 54.2.0 pip: 20.3.1 conda: None pytest: 6.2.3 IPython: 7.22.0 sphinx: 3.5.2

If I use the sum method on a lazy array with min_count != None then evaluation is forced. If there is some limitation of the implementation which means it cannot be added to the computation graph for lazy evaluation then this should be mentioned in the docs.

Minimal Complete Verifiable Example:

```python import numpy as np import xarray as xr

def worker(da): if da.shape == (0, 0): return da

raise RuntimeError("I was evaluated")

da = xr.DataArray( np.random.normal(size=(20, 500)), dims=("x", "y"), coords=(np.arange(20), np.arange(500)), )

da = da.chunk(dict(x=5)) lazy = da.map_blocks(worker) result1 = lazy.sum("x", skipna=True) result2 = lazy.sum("x", skipna=True, min_count=5)

```

What happened: RuntimeError: I was evaluated

What you expected to happen: No output or exceptions, as the result1 and result2 arrays are not printed or saved.

Environment:

Output of <tt>xr.show_versions()</tt>

INSTALLED VERSIONS ------------------ commit: None python: 3.9.1 (default, Feb 6 2021, 06:49:13) [GCC 10.2.0] python-bits: 64 OS: Linux OS-release: 5.10.15-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_NZ.UTF-8 LOCALE: en_NZ.UTF-8 libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 0.16.2 pandas: 1.2.1 numpy: 1.20.0 scipy: 1.6.0 netCDF4: 1.5.5.1 pydap: None h5netcdf: 0.9.0 h5py: 3.1.0 Nio: None zarr: None cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.0 cfgrib: None iris: None bottleneck: 1.3.2 dask: 2020.12.0 distributed: 2020.12.0 matplotlib: 3.3.4 cartopy: 0.18.0 seaborn: None numbagg: None pint: None setuptools: 53.0.0 pip: 20.3.1 conda: None pytest: 6.2.1 IPython: 7.19.0 sphinx: 3.4.3