Fixing repr errors in Jupyter Notebooks

python

jupyter

Published

December 21, 2020

When running the Kaggle API method dataset_list_files in a Jupyter notebook I got an error about __repr__ returning a non-string. At first I thought the function was broken, but then I realised it was just how it was displaying in Jupyter that was breaking because the issues were all in IPython:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
IPython/core/formatters.py in __call__(self, obj)
    700                 type_pprinters=self.type_printers,
    701                 deferred_pprinters=self.deferred_printers)
--> 702             printer.pretty(obj)
    703             printer.flush()
    704             return stream.getvalue()

IPython/lib/pretty.py in pretty(self, obj)
    392                         if cls is not object \
    393                                 and callable(cls.__dict__.get('__repr__')):
--> 394                             return _repr_pprint(obj, self, cycle)
    395 
    396             return _default_pprint(obj, self, cycle)

IPython/lib/pretty.py in _repr_pprint(obj, p, cycle)
    698     """A pprint that just redirects to the normal repr function."""
    699     # Find newlines and replace them with p.break_()
--> 700     output = repr(obj)
    701     lines = output.splitlines()
    702     with p.group():

TypeError: __repr__ returned non-string (type NoneType)

By assigning the output, rather than displaying it, the error goes away. If I try to display the output I get the same error again. By running type I can see that it’s a kaggle.models.kaggle_models_extended.ListFilesResult, and by running dir I can see that the two non-special attributes are error_message and files. The files contains the files I want and does have a working repr. So I can monkeypatch the class:

from kaggle.models.kaggle_models_extended import ListFilesResult
ListFilesResult.__repr__ = lambda self: repr(self.files)

Then displaying the result works just fine in Jupyter.