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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<best_window_by_backtest: int64, best_window_data: struct<window: int64, top_etfs: list<item: struct<ticker: string, harmonic_score_norm: double, raw_score: double>>, all_scores_raw: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, all_scores_norm: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, backtest_avg_next_return: double>, all_windows: list<item: struct<window: int64, top_etfs: list<item: struct<ticker: string, harmonic_score_norm: double, raw_score: double>>, all_scores_raw: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, all_scores_norm: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, backtest_avg_next_return: double>>>
to
{'best_window_by_forward_return': Value('null'), 'best_window_data': Value('null'), 'all_windows': List({'window': Value('int64'), 'signal_date': Value('timestamp[s]'), 'top_etfs': List({'ticker': Value('string'), 'harmonic_score_norm': Value('float64'), 'raw_score': Value('float64')}), 'all_scores_raw': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'all_scores_norm': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'forward_return_21d': Value('null')})}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2255, in cast_table_to_schema
                  cast_array_to_feature(
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1804, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2011, in cast_array_to_feature
                  _c(array.field(name) if name in array_fields else null_array, subfeature)
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2101, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<best_window_by_backtest: int64, best_window_data: struct<window: int64, top_etfs: list<item: struct<ticker: string, harmonic_score_norm: double, raw_score: double>>, all_scores_raw: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, all_scores_norm: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, backtest_avg_next_return: double>, all_windows: list<item: struct<window: int64, top_etfs: list<item: struct<ticker: string, harmonic_score_norm: double, raw_score: double>>, all_scores_raw: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, all_scores_norm: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, backtest_avg_next_return: double>>>
              to
              {'best_window_by_forward_return': Value('null'), 'best_window_data': Value('null'), 'all_windows': List({'window': Value('int64'), 'signal_date': Value('timestamp[s]'), 'top_etfs': List({'ticker': Value('string'), 'harmonic_score_norm': Value('float64'), 'raw_score': Value('float64')}), 'all_scores_raw': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'all_scores_norm': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'forward_return_21d': Value('null')})}

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