Datasets:

---

P2SAMAPA

/

p2-etf-graph-node-grand-results

like 0

Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<global: struct<ticker: string, pred_return: double, all_pred_returns: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, metrics: struct<ann_return: double, ann_vol: double, sharpe: double, max_dd: double, hit_rate: double, cum_return: double, n_days: int64>, optimal_window: int64, test_start: timestamp[s], test_end: timestamp[s]>, adaptive: struct<ticker: string, pred_return: double, all_pred_returns: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, metrics: struct<ann_return: double, ann_vol: double, sharpe: double, max_dd: double, hit_rate: double, cum_return: double, n_days: int64>, optimal_window: int64, test_start: timestamp[s], test_end: timestamp[s], adaptive_window: int64, change_point_date: timestamp[s]>, daily: struct<ticker: string, pred_return: double, all_pred_returns: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, metrics: struct<ann_return: double, ann_vol: double, sharpe: double, max_dd: double, hit_rate: double, cum_return: double, n_days: int64>, optimal_window: int64, test_start: timestamp[s], test_end: timestamp[s]>>
to
{'global': {'ticker': Value('string'), 'pred_return': Value('float64'), 'all_pred_returns': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'metrics': {'ann_return': Value('float64'), 'ann_vol': Value('float64'), 'sharpe': Value('float64'), 'max_dd': Value('float64'), 'hit_rate': Value('float64'), 'cum_return': Value('float64'), 'n_days': Value('int64')}, 'test_start': Value('timestamp[s]'), 'test_end': Value('timestamp[s]')}, 'adaptive': {'ticker': Value('string'), 'pred_return': Value('float64'), 'all_pred_returns': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'adaptive_window': Value('int64'), 'change_point_date': Value('timestamp[s]'), 'metrics': {'ann_return': Value('float64'), 'ann_vol': Value('float64'), 'sharpe': Value('float64'), 'max_dd': Value('float64'), 'hit_rate': Value('float64'), 'cum_return': Value('float64'), 'n_days': Value('int64')}, 'test_start': Value('timestamp[s]'), 'test_end': Value('timestamp[s]')}}
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 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<global: struct<ticker: string, pred_return: double, all_pred_returns: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, metrics: struct<ann_return: double, ann_vol: double, sharpe: double, max_dd: double, hit_rate: double, cum_return: double, n_days: int64>, optimal_window: int64, test_start: timestamp[s], test_end: timestamp[s]>, adaptive: struct<ticker: string, pred_return: double, all_pred_returns: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, metrics: struct<ann_return: double, ann_vol: double, sharpe: double, max_dd: double, hit_rate: double, cum_return: double, n_days: int64>, optimal_window: int64, test_start: timestamp[s], test_end: timestamp[s], adaptive_window: int64, change_point_date: timestamp[s]>, daily: struct<ticker: string, pred_return: double, all_pred_returns: struct<TLT: double, VCIT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double>, metrics: struct<ann_return: double, ann_vol: double, sharpe: double, max_dd: double, hit_rate: double, cum_return: double, n_days: int64>, optimal_window: int64, test_start: timestamp[s], test_end: timestamp[s]>>
              to
              {'global': {'ticker': Value('string'), 'pred_return': Value('float64'), 'all_pred_returns': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'metrics': {'ann_return': Value('float64'), 'ann_vol': Value('float64'), 'sharpe': Value('float64'), 'max_dd': Value('float64'), 'hit_rate': Value('float64'), 'cum_return': Value('float64'), 'n_days': Value('int64')}, 'test_start': Value('timestamp[s]'), 'test_end': Value('timestamp[s]')}, 'adaptive': {'ticker': Value('string'), 'pred_return': Value('float64'), 'all_pred_returns': {'TLT': Value('float64'), 'VCIT': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'VNQ': Value('float64'), 'GLD': Value('float64'), 'SLV': Value('float64')}, 'adaptive_window': Value('int64'), 'change_point_date': Value('timestamp[s]'), 'metrics': {'ann_return': Value('float64'), 'ann_vol': Value('float64'), 'sharpe': Value('float64'), 'max_dd': Value('float64'), 'hit_rate': Value('float64'), 'cum_return': Value('float64'), 'n_days': Value('int64')}, 'test_start': Value('timestamp[s]'), 'test_end': Value('timestamp[s]')}}