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I'm not sure if we can fix this in pandas, but I ran into this recently:
In [10]: d = {'foo': 1, 'bar': [{'what': {'footttttttttttttttttttttttttttttttttt': pd.Timestamp('2011-01-01')}}] * 10} In [11]: pprint.pprint(d) <SNIP> lib/python3.5/pprint.py in _format_dict_items(self, items, stream, indent, allowance, context, level) 344 self._format(ent, stream, indent + len(rep) + 2, 345 allowance if last else 1, --> 346 context, level) 347 if not last: 348 write(delimnl) lib/python3.5/pprint.py in _format(self, object, stream, indent, allowance, context, level) 162 max_width = self._width - indent - allowance 163 if len(rep) > max_width: --> 164 p = self._dispatch.get(type(object).__repr__, None) 165 if p is not None: 166 context[objid] = 1 TypeError: unhashable type: 'instancemethod'
The text was updated successfully, but these errors were encountered:
not useful.......but
In [4]: pprint.saferepr(d) Out[4]: "{'bar': [{'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}, {'what': {'footttttttttttttttttttttttttttttttttt': Timestamp('2011-01-01 00:00:00')}}], 'foo': 1}"
Sorry, something went wrong.
I think if we could define _Timestamp to actually use __slots__. http://stackoverflow.com/questions/10401935/python-method-wrapper-type
_Timestamp
__slots__
but not really sure how cython does this.
33659fd
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I'm not sure if we can fix this in pandas, but I ran into this recently:
The text was updated successfully, but these errors were encountered: