Implement Series.size in new style #217
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| raise TypingError('{} The object must be a pandas.series. Given: {}'.format(_func_name, self)) | ||
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| def hpat_pandas_series_size_impl(self): | ||
| return self._data.size |
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This is good but what happened if _data is None?
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As I can see playing with Pandas in console: pd.Series() does not store _data = None in internal representation. So _data is always something even if Series is empty.
Also this could be replaced with len(self._data).
hpat/tests/test_series.py
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| S = pd.Series([np.nan, 1, 2]) | ||
| self.assertEqual(hpat_func(S), test_impl(S)) | ||
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| S = pd.Series(['1', '2', '3']) |
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@PokhodenkoSA It might be better to make these set of tests as a loop.
I mean:
for input_data in test_input_data:
S = pd.Series(input_data)
where data defined as https://github.com/IntelPython/hpat/blob/e45cc922afb855f0e5d87e30acc01ef6ef2e4002/hpat/tests/test_series.py#L2057
also, it might be better to use pd.testing.assert_series_equal instead self.assertEqual because, as I understood, the first one compare full Series datatype but second compares part of it. Yes, we use diffrent types of assertion in tests but it will be a one of the task for redeveloping.
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I think pd.testing.assert_series_equal is not applicable here because it compares two Series but Series.size returns scalar.
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Use test data in loop - done.
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