What happened?

I have just updated my development branch of xarray to latest main. No other changes. When using .chunk() on a Variable xarray crashes.

What did you expect to happen?

No crash

Minimal Complete Verifiable Example

```Python import numpy as np import pandas as pd import xarray as xr

t_size = 8000 t = np.arange(t_size) var = xr.Variable(dims=("T",), data=np.random.randn(t_size)).chunk() ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python Traceback (most recent call last):

File "C:\Users\J.W\AppData\Local\Temp\ipykernel_6480\4053253683.py", line 8, in <cell line: 8> var = xr.Variable(dims=("T",), data=np.random.randn(t_size)).chunk()

File "C:\Users\J.W\Documents\GitHub\xarray\xarray\core\variable.py", line 1249, in chunk chunkmanager = guess_chunkmanager(chunked_array_type)

File "C:\Users\J.W\Documents\GitHub\xarray\xarray\core\parallelcompat.py", line 87, in guess_chunkmanager raise ValueError(

ValueError: unrecognized chunk manager dask - must be one of: [] ```

Anything else we need to know?

Likely from #7019.

Environment

This adds typing to the dict values. Using variables as keys is apparently not permitted by mypy so that part has been removed.

Attempts to fix issues found in #5662.

When there's a lot of dims, create a new line and continue printing. If there's even more dims that even a few rows can't display them all then limit the number of dims displayed in similar fashion to coordinates.

Questions: * Where should this be used? Datasets, dataarrays, dimensions without coords? * Should dim_summary_limited be a straight replacement for dim_summary? I'm not super familiar with all the places it is used so I'm unsure. * Should we print the number of dims shown and the total number of dims? If yes, then we need to rethink how the dimensions are displayed, as it's not possible with the current style. See the example with short names.

• [x] Closes #5546
• [x] Tests added
• [x] Passes pre-commit run --all-files
• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

Test case: ```python import numpy as np import xarray as xr

A few dims with long names:

a = np.arange(0, 24) data_vars = dict() for i in a: data_vars[f"long_variable_name_{i}"] = xr.DataArray( name=f"long_variable_name_{i}", data=np.arange(0, 20), dims=[f"long_coord_name_{i}x"], coords={f"long_coord_name{i}x": np.arange(0, 20) * 2}, ) ds0 = xr.Dataset(data_vars) ds0.attrs = {f"attr{k}": 2 for k in a}

print(ds0) <xarray.Dataset> Dimensions: (long_coord_name_0_x: 20, long_coord_name_10_x: 20, long_coord_name_11_x: 20, long_coord_name_12_x: 20, long_coord_name_13_x: 20, long_coord_name_14_x: 20, long_coord_name_15_x: 20, long_coord_name_16_x: 20, long_coord_name_17_x: 20, long_coord_name_18_x: 20, long_coord_name_19_x: 20, long_coord_name_1_x: 20, long_coord_name_20_x: 20, long_coord_name_21_x: 20, long_coord_name_22_x: 20, long_coord_name_23_x: 20, long_coord_name_2_x: 20, long_coord_name_3_x: 20, long_coord_name_4_x: 20, long_coord_name_5_x: 20, long_coord_name_6_x: 20, long_coord_name_7_x: 20, long_coord_name_8_x: 20, long_coord_name_9_x: 20) Coordinates: (12/24) * long_coord_name_0_x (long_coord_name_0_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_1_x (long_coord_name_1_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_2_x (long_coord_name_2_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_3_x (long_coord_name_3_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_4_x (long_coord_name_4_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_5_x (long_coord_name_5_x) int32 0 2 4 6 8 ... 32 34 36 38 ... * long_coord_name_18_x (long_coord_name_18_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_19_x (long_coord_name_19_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_20_x (long_coord_name_20_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_21_x (long_coord_name_21_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_22_x (long_coord_name_22_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_23_x (long_coord_name_23_x) int32 0 2 4 6 ... 32 34 36 38 Data variables: (12/24) long_variable_name_0 (long_coord_name_0_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_1 (long_coord_name_1_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_2 (long_coord_name_2_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_3 (long_coord_name_3_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_4 (long_coord_name_4_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_5 (long_coord_name_5_x) int32 0 1 2 3 4 ... 16 17 18 19 ... long_variable_name_18 (long_coord_name_18_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_19 (long_coord_name_19_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_20 (long_coord_name_20_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_21 (long_coord_name_21_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_22 (long_coord_name_22_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_23 (long_coord_name_23_x) int32 0 1 2 3 ... 16 17 18 19 Attributes: (12/24) attr_0: 2 attr_1: 2 attr_2: 2 attr_3: 2 attr_4: 2 attr_5: 2 ... attr_18: 2 attr_19: 2 attr_20: 2 attr_21: 2 attr_22: 2 attr_23: 2 ```

```python

Many dims with long names:

a = np.arange(0, 200) data_vars = dict() for i in a: data_vars[f"long_variable_name_{i}"] = xr.DataArray( name=f"long_variable_name_{i}", data=np.arange(0, 20), dims=[f"long_coord_name_{i}x"], coords={f"long_coord_name{i}x": np.arange(0, 20) * 2}, ) ds1 = xr.Dataset(data_vars) ds1.attrs = {f"attr{k}": 2 for k in a}

print(ds1) <xarray.Dataset> Dimensions: (long_coord_name_0_x: 20, long_coord_name_100_x: 20, long_coord_name_101_x: 20, long_coord_name_102_x: 20, long_coord_name_103_x: 20, long_coord_name_104_x: 20, ... long_coord_name_94_x: 20, long_coord_name_95_x: 20, long_coord_name_96_x: 20, long_coord_name_97_x: 20, long_coord_name_98_x: 20, long_coord_name_99_x: 20, long_coord_name_9_x: 20) Coordinates: (12/200) * long_coord_name_0_x (long_coord_name_0_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_1_x (long_coord_name_1_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_2_x (long_coord_name_2_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_3_x (long_coord_name_3_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_4_x (long_coord_name_4_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_5_x (long_coord_name_5_x) int32 0 2 4 6 ... 32 34 36 38 ... * long_coord_name_194_x (long_coord_name_194_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_195_x (long_coord_name_195_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_196_x (long_coord_name_196_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_197_x (long_coord_name_197_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_198_x (long_coord_name_198_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_199_x (long_coord_name_199_x) int32 0 2 4 6 ... 34 36 38 Data variables: (12/200) long_variable_name_0 (long_coord_name_0_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_1 (long_coord_name_1_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_2 (long_coord_name_2_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_3 (long_coord_name_3_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_4 (long_coord_name_4_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_5 (long_coord_name_5_x) int32 0 1 2 3 ... 16 17 18 19 ... long_variable_name_194 (long_coord_name_194_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_195 (long_coord_name_195_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_196 (long_coord_name_196_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_197 (long_coord_name_197_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_198 (long_coord_name_198_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_199 (long_coord_name_199_x) int32 0 1 2 3 ... 17 18 19 Attributes: (12/200) attr_0: 2 attr_1: 2 attr_2: 2 attr_3: 2 attr_4: 2 attr_5: 2 ... attr_194: 2 attr_195: 2 attr_196: 2 attr_197: 2 attr_198: 2 attr_199: 2 ```

```python

Many dims with short names:

data_vars = dict() for i in a: data_vars[f"n_{i}"] = xr.DataArray( name=f"n_{i}", data=np.arange(0, 20), dims=[f"{i}x"], coords={f"{i}_x": np.arange(0, 20) * 2}, ) ds2 = xr.Dataset(data_vars) ds2.attrs = {f"attr{k}": 2 for k in a}

print(ds2) <xarray.Dataset> Dimensions: (0_x: 20, 100_x: 20, 101_x: 20, 102_x: 20, 103_x: 20, 104_x: 20, 105_x: 20, 106_x: 20, 107_x: 20, 108_x: 20, 109_x: 20, 10_x: 20, 110_x: 20, 111_x: 20, 112_x: 20, 113_x: 20, 114_x: 20, 115_x: 20, 116_x: 20, 117_x: 20, 118_x: 20, 119_x: 20, 11_x: 20, 120_x: 20, 121_x: 20, 122_x: 20, 123_x: 20, 124_x: 20, 125_x: 20, 126_x: 20, 127_x: 20, 128_x: 20, 129_x: 20, 12_x: 20, 130_x: 20, 131_x: 20, ... 71_x: 20, 72_x: 20, 73_x: 20, 74_x: 20, 75_x: 20, 76_x: 20, 77_x: 20, 78_x: 20, 79_x: 20, 7_x: 20, 80_x: 20, 81_x: 20, 82_x: 20, 83_x: 20, 84_x: 20, 85_x: 20, 86_x: 20, 87_x: 20, 88_x: 20, 89_x: 20, 8_x: 20, 90_x: 20, 91_x: 20, 92_x: 20, 93_x: 20, 94_x: 20, 95_x: 20, 96_x: 20, 97_x: 20, 98_x: 20, 99_x: 20, 9_x: 20) Coordinates: (12/200) * 0_x (0_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 1_x (1_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 2_x (2_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 3_x (3_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 4_x (4_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 5_x (5_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 ... * 194_x (194_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 195_x (195_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 196_x (196_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 197_x (197_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 198_x (198_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 199_x (199_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 Data variables: (12/200) n_0 (0_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_1 (1_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_2 (2_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_3 (3_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_4 (4_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_5 (5_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ... n_194 (194_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_195 (195_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_196 (196_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_197 (197_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_198 (198_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_199 (199_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Attributes: (12/200) attr_0: 2 attr_1: 2 attr_2: 2 attr_3: 2 attr_4: 2 attr_5: 2 ... attr_194: 2 attr_195: 2 attr_196: 2 attr_197: 2 attr_198: 2 attr_199: 2 ```

```python

DataArray with many dimensions:

dims = {f"dim_{v}": 2 for v in np.arange(12)} a = xr.DataArray( name="LongDataArrayName", data=np.random.randn(*dims.values()), dims=dims.keys(), coords={k: np.arange(v) * (i + 1) for i, (k, v) in enumerate(dims.items())}, ) print(a) <xarray.DataArray 'LongDataArrayName' (dim_0: 2, dim_1: 2, dim_2: 2, dim_3: 2, dim_4: 2, dim_5: 2, dim_6: 2, dim_7: 2, dim_8: 2, dim_9: 2, dim_10: 2, dim_11: 2)> array([[[[[[[[[[[[ 8.28296160e-01, 2.08993090e-01], [ 8.70468836e-01, 8.90423004e-01]],

            [[ 7.34784427e-01,  2.05408058e-01],
             [-8.57071909e-02,  8.44265228e-01]]],


           [[[-9.35953498e-01, -1.28911601e+00],
             [ 1.10041466e+00,  6.65778297e-02]],

            [[-1.20951652e+00,  6.75763964e-01],
             [-4.71836513e-02,  9.06088516e-01]]]],



          [[[[ 1.59629635e+00,  7.32189004e-01],
             [-3.93944434e-01,  2.46067012e+00]],

            [[ 1.20534658e-01, -1.10855175e+00],
             [ 1.75768289e+00,  1.82771876e+00]]],

... [[[ 1.24664897e+00, 1.72548620e+00], [-7.64230130e-02, -7.96243220e-01]],

            [[-7.02358327e-01,  2.20921513e+00],
             [-7.45919399e-01,  8.16166442e-01]]]],



          [[[[-1.06278662e+00, -3.01061594e-01],
             [-2.68674730e-01,  7.61941899e-01]],

            [[-7.40916926e-01,  1.85122750e+00],
             [-5.42460065e-02, -7.57741769e-01]]],


           [[[-4.12356234e-02,  7.41777992e-01],
             [-1.36243505e+00, -1.25845181e+00]],

            [[-7.42535368e-01,  1.13262286e-01],
             [ 1.03699306e+00, -8.51127899e-01]]]]]]]]]]]])

Coordinates: * dim_0 (dim_0) int32 0 1 * dim_1 (dim_1) int32 0 2 * dim_2 (dim_2) int32 0 3 * dim_3 (dim_3) int32 0 4 * dim_4 (dim_4) int32 0 5 * dim_5 (dim_5) int32 0 6 * dim_6 (dim_6) int32 0 7 * dim_7 (dim_7) int32 0 8 * dim_8 (dim_8) int32 0 9 * dim_9 (dim_9) int32 0 10 * dim_10 (dim_10) int32 0 11 * dim_11 (dim_11) int32 0 12 ```

```python

DataArray with many dimensions but no coords:

dims = {f"dim_{v}": 2 for v in np.arange(12)} a = xr.DataArray( name="LongDataArrayName", data=np.random.randn(*dims.values()), dims=dims.keys(), ) print(a) <xarray.DataArray 'LongDataArrayName' (dim_0: 2, dim_1: 2, dim_2: 2, dim_3: 2, dim_4: 2, dim_5: 2, dim_6: 2, dim_7: 2, dim_8: 2, dim_9: 2, dim_10: 2, dim_11: 2)> array([[[[[[[[[[[[ 2.53218063e-02, -2.01034380e+00], [ 3.07624042e-01, 1.82085569e-01]],

            [[ 1.23998647e+00,  2.80961964e-01],
             [ 5.22623248e-01, -2.10621456e-01]]],


           [[[ 1.55794218e+00, -1.32803310e+00],
             [-7.41474289e-01, -3.35995545e-01]],

            [[ 9.96489723e-03, -1.84197059e-01],
             [-1.24173835e+00,  4.94205388e-01]]]],



          [[[[-2.11962358e-01,  1.18012909e+00],
             [-4.62991218e-01, -9.49171994e-01]],

            [[ 3.90534280e-01, -2.63453002e+00],
             [ 3.57944636e-01,  2.16335768e-01]]],

... [[[-1.11275429e+00, -9.33574221e-01], [ 8.62574702e-01, 1.14185983e+00]],

            [[ 1.36795402e+00,  1.14331852e+00],
             [ 5.96785305e-01,  1.47307855e+00]]]],



          [[[[ 1.95270558e+00, -7.76150298e-01],
             [ 2.05301468e+00, -1.15633640e+00]],

            [[-9.45507288e-01,  1.21096830e+00],
             [ 1.59340121e+00, -3.60261023e-01]]],


           [[[ 2.25343528e+00, -2.84332626e-01],
             [ 1.86644712e-01, -2.78371182e-01]],

            [[-8.86245009e-01, -4.00356195e-01],
             [-2.44036388e-01, -1.53543170e+00]]]]]]]]]]]])

Dimensions without coordinates: dim_0, dim_1, dim_2, dim_3, dim_4, dim_5, dim_6, dim_7, dim_8, dim_9, dim_10, dim_11 ```