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Failed

gpkit.tests.t_examples.TestExamples.test_performance_modeling_cvxopt (from gpkit.tests.t_examples.TestExamples-20201215130810)

Failing for the past 1 build (Since Failed #756 )
Took 1 sec.

Error Message

No module named 'ipysankeywidget'

Stacktrace

Traceback (most recent call last):
  File "C:\Users\jenkins\workspace\CE_gpkit_Push_unit_tests\buildnode\windows10x64\optimizer\cvxopt\gpkit\tests\helpers.py", line 55, in test
    testfn(name, import_dict, path)(self)
  File "C:\Users\jenkins\workspace\CE_gpkit_Push_unit_tests\buildnode\windows10x64\optimizer\cvxopt\gpkit\tests\helpers.py", line 87, in test
    imported[name] = importlib.import_module(name)
  File "c:\anaconda3\lib\importlib\__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 728, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "C:\Users\jenkins\workspace\CE_gpkit_Push_unit_tests\buildnode\windows10x64\optimizer\cvxopt\docs\source\examples\performance_modeling.py", line 247, in <module>
    from gpkit.interactive.sankey import Sankey
  File "C:\Users\jenkins\workspace\CE_gpkit_Push_unit_tests\buildnode\windows10x64\optimizer\cvxopt\gpkit\interactive\sankey.py", line 8, in <module>
    from ipysankeywidget import SankeyWidget
ModuleNotFoundError: No module named 'ipysankeywidget'
		

Standard Output

	

Standard Error

C:\Users\jenkins\workspace\CE_gpkit_Push_unit_tests\buildnode\windows10x64\optimizer\cvxopt\gpkit\keydict.py:245: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
  value = np.array([clean_value(key, v) for v in value])