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Allow string formatting of scalar DataArrays #5981

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merged 8 commits into from
May 9, 2022

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fmaussion
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@fmaussion fmaussion commented Nov 12, 2021

This is a first try at formatting dataarray scalars. Here is the current behavior:

In [1]: import xarray as xr
   ...: import numpy as np

In [2]: a = np.array(1)
   ...: da = xr.DataArray(a)

In [3]: print(a)
1

In [4]: print(da)
<xarray.DataArray ()>
array(1)

In [5]: print('{}'.format(a))
1

In [6]: print('{}'.format(da))
<xarray.DataArray ()>
array(1)

In [7]: print('{:.3f}'.format(a))
1.000

In [8]: print('{:.3f}'.format(da))
1.000

In [9]: a = np.array([1, 2])
   ...: da = xr.DataArray(a)

In [10]: print('{}'.format(a))
[1 2]

In [11]: print('{}'.format(da))
<xarray.DataArray (dim_0: 2)>
array([1, 2])
Dimensions without coordinates: dim_0

In [12]: print('{:.3f}'.format(a))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-12-c5afc7863e89> in <module>
----> 1 print('{:.3f}'.format(a))

TypeError: unsupported format string passed to numpy.ndarray.__format__

In [13]: print('{:.3f}'.format(da))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-13-bddebd8462bd> in <module>
----> 1 print('{:.3f}'.format(da))

~/disk/Dropbox/HomeDocs/git/xarray/xarray/core/common.py in __format__(self, format_spec)
    162             return formatting.array_repr(self)
    163         # Else why fall back to numpy
--> 164         return self.values.__format__(format_spec)
    165 
    166     def _iter(self: Any) -> Iterator[Any]:

TypeError: unsupported format string passed to numpy.ndarray.__format__

I don't think there is any backwards compatibility issue but lets see if the tests pass

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fmaussion commented Nov 12, 2021

Note that there would be a way to change the behavior to:

print(da) -> lengthy repr
print('{}'.format(da) -> fall back to numpy.__format__

This would break backwards compatibility, but I think it would be my preference - there are some chances that it brakes some code (in documentation pages maybe?), but I don't think that many people rely on '{}'.format(da) to return __repr__ ...

Comment on lines 418 to 426
assert var.__format__("") == "<xarray.DataArray ()>\narray(0)"
assert var.__format__("d") == "0"
assert var.__format__(".2f") == "0.00"

var = xr.DataArray([0])
assert var.__format__("") == (
"<xarray.DataArray (dim_0: 1)>\narray([0])"
"\nDimensions without coordinates: dim_0"
)
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Suggested change
assert var.__format__("") == "<xarray.DataArray ()>\narray(0)"
assert var.__format__("d") == "0"
assert var.__format__(".2f") == "0.00"
var = xr.DataArray([0])
assert var.__format__("") == (
"<xarray.DataArray (dim_0: 1)>\narray([0])"
"\nDimensions without coordinates: dim_0"
)
assert var.__format__("") == var.__repr__()
assert var.__format__("d") == "0"
assert var.__format__(".2f") == "0.00"
var = xr.DataArray([0])
assert var.__format__("") == var.__repr__()

repr style can change over time. I think this should work.

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Thanks that makes sense!

However I think I would like to simplify this even more and always call ndarray.__format__ when DataArray.__format__ is called. This won't be backwards compatible but I think this would be better and more predictable.

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Side note: with this design (no call to repr() in format()) we would mimick numpy's behavior:

a = np.array([0.1, 0.2])
a.__format__("")
Out[16]: '[0.1 0.2]'
a.__repr__()
Out[17]: 'array([0.1, 0.2])'

However I'm quite surprised as to why .__format__("") works on non-scalar arrays but not with other specifiers - this is discussed somehow in numpy/numpy#5543 . I think it's okay for xarray to defer to whatever numpy is doing here, but of course we can also keep the status-quo, it's quite a small change after all.

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@Illviljan and other devs - I still think this small change would be a nice addition for accessibility and teaching. Let me know if we can purse or if I should close this.

@Illviljan Illviljan added the plan to merge Final call for comments label May 3, 2022
@Illviljan Illviljan merged commit bbb14a5 into pydata:main May 9, 2022
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Thanks @fmaussion!

dcherian added a commit to dcherian/xarray that referenced this pull request May 20, 2022
* main: (24 commits)
  Fix overflow issue in decode_cf_datetime for dtypes <= np.uint32 (pydata#6598)
  Enable flox in GroupBy and resample (pydata#5734)
  Add setuptools as dependency in ASV benchmark CI (pydata#6609)
  change polyval dim ordering (pydata#6601)
  re-add timedelta support for polyval (pydata#6599)
  Minor Dataset.map docstr clarification (pydata#6595)
  New inline_array kwarg for open_dataset (pydata#6566)
  Fix polyval overloads (pydata#6593)
  Restore old MultiIndex dropping behaviour (pydata#6592)
  [docs] add Dataset.assign_coords example (pydata#6336) (pydata#6558)
  Fix zarr append dtype checks (pydata#6476)
  Add missing space in exception message (pydata#6590)
  Doc Link to accessors list in extending-xarray.rst (pydata#6587)
  Fix Dataset/DataArray.isel with drop=True and scalar DataArray indexes (pydata#6579)
  Add some warnings about rechunking to the docs (pydata#6569)
  [pre-commit.ci] pre-commit autoupdate (pydata#6584)
  terminology.rst: fix link to Unidata's "netcdf_dataset_components" (pydata#6583)
  Allow string formatting of scalar DataArrays (pydata#5981)
  Fix mypy issues & reenable in tests (pydata#6581)
  polyval: Use Horner's algorithm + support chunked inputs (pydata#6548)
  ...
dcherian added a commit to headtr1ck/xarray that referenced this pull request May 20, 2022
commit 398f1b6
Author: dcherian <[email protected]>
Date:   Fri May 20 08:47:56 2022 -0600

    Backward compatibility dask

commit bde40e4
Merge: 0783df3 4cae8d0
Author: dcherian <[email protected]>
Date:   Fri May 20 07:54:48 2022 -0600

    Merge branch 'main' into dask-datetime-to-numeric

    * main:
      concatenate docs style (pydata#6621)
      Typing for open_dataset/array/mfdataset and to_netcdf/zarr (pydata#6612)
      {full,zeros,ones}_like typing (pydata#6611)

commit 0783df3
Merge: 5cff4f1 8de7061
Author: dcherian <[email protected]>
Date:   Sun May 15 21:03:50 2022 -0600

    Merge branch 'main' into dask-datetime-to-numeric

    * main: (24 commits)
      Fix overflow issue in decode_cf_datetime for dtypes <= np.uint32 (pydata#6598)
      Enable flox in GroupBy and resample (pydata#5734)
      Add setuptools as dependency in ASV benchmark CI (pydata#6609)
      change polyval dim ordering (pydata#6601)
      re-add timedelta support for polyval (pydata#6599)
      Minor Dataset.map docstr clarification (pydata#6595)
      New inline_array kwarg for open_dataset (pydata#6566)
      Fix polyval overloads (pydata#6593)
      Restore old MultiIndex dropping behaviour (pydata#6592)
      [docs] add Dataset.assign_coords example (pydata#6336) (pydata#6558)
      Fix zarr append dtype checks (pydata#6476)
      Add missing space in exception message (pydata#6590)
      Doc Link to accessors list in extending-xarray.rst (pydata#6587)
      Fix Dataset/DataArray.isel with drop=True and scalar DataArray indexes (pydata#6579)
      Add some warnings about rechunking to the docs (pydata#6569)
      [pre-commit.ci] pre-commit autoupdate (pydata#6584)
      terminology.rst: fix link to Unidata's "netcdf_dataset_components" (pydata#6583)
      Allow string formatting of scalar DataArrays (pydata#5981)
      Fix mypy issues & reenable in tests (pydata#6581)
      polyval: Use Horner's algorithm + support chunked inputs (pydata#6548)
      ...

commit 5cff4f1
Merge: dfe200d 6144c61
Author: Maximilian Roos <[email protected]>
Date:   Sun May 1 15:16:33 2022 -0700

    Merge branch 'main' into dask-datetime-to-numeric

commit dfe200d
Author: dcherian <[email protected]>
Date:   Sun May 1 11:04:03 2022 -0600

    Minor cleanup

commit 35ed378
Author: dcherian <[email protected]>
Date:   Sun May 1 10:57:36 2022 -0600

    Support dask arrays in datetime_to_numeric
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