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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
option: string
option_name: string
signal_date: timestamp[s]
last_data_date: timestamp[s]
generated_at: string
pick: string
conviction: double
source: string
scores: struct<VNQ: double, SLV: double, TLT: double, GLD: double, HYG: double, MBB: double, LQD: double, PF (... 10 chars omitted)
  child 0, VNQ: double
  child 1, SLV: double
  child 2, TLT: double
  child 3, GLD: double
  child 4, HYG: double
  child 5, MBB: double
  child 6, LQD: double
  child 7, PFF: double
causal_method: string
top_causal_links: list<item: struct<from: string, to: string, strength: double>>
  child 0, item: struct<from: string, to: string, strength: double>
      child 0, from: string
      child 1, to: string
      child 2, strength: double
fixed_window: struct<pick: string, scores: struct<PFF: double, MBB: double, GLD: double, VNQ: double, LQD: double, (... 157 chars omitted)
  child 0, pick: string
  child 1, scores: struct<PFF: double, MBB: double, GLD: double, VNQ: double, LQD: double, HYG: double, TLT: double, SL (... 10 chars omitted)
      child 0, PFF: double
      child 1, MBB: double
      child 2, GLD: double
      child 3, VNQ: double
      child 4, LQD: double
      child 5, HYG: double
      child 6, TLT: double
      child 7, SLV: double
  child 2, test_start: timestamp[s]
  child 3, oos_return: double
  child 4, oos_vol: double
  child 5, oos_sharpe: double
  child 6, hit_rate: double
  child 7, max_dd: double
shrinking_window: struct<winning_window: int64, winning_train_start: t
...
w: int64
      child 1, winning_train_start: timestamp[s]
      child 2, winning_train_end: timestamp[s]
      child 3, pick: string
      child 4, scores: struct<XME: double, XLP: double, XLE: double, XLU: double, XLF: double, XLY: double, IWM: double, SP (... 114 chars omitted)
          child 0, XME: double
          child 1, XLP: double
          child 2, XLE: double
          child 3, XLU: double
          child 4, XLF: double
          child 5, XLY: double
          child 6, IWM: double
          child 7, SPY: double
          child 8, QQQ: double
          child 9, IWF: double
          child 10, XLV: double
          child 11, XLI: double
          child 12, XBI: double
          child 13, XLK: double
          child 14, XSD: double
          child 15, GDX: double
      child 5, oos_return: double
      child 6, oos_vol: double
      child 7, oos_sharpe: double
      child 8, oos_hit_rate: double
      child 9, oos_max_dd: double
      child 10, all_windows: list<item: struct<window_id: int64, train_start: timestamp[s], pick: string, oos_return: double, oos (... 33 chars omitted)
          child 0, item: struct<window_id: int64, train_start: timestamp[s], pick: string, oos_return: double, oos_sharpe: do (... 21 chars omitted)
              child 0, window_id: int64
              child 1, train_start: timestamp[s]
              child 2, pick: string
              child 3, oos_return: double
              child 4, oos_sharpe: double
              child 5, method: string
to
{'generated_at': Value('string'), 'option_A': {'option': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'source': Value('string'), 'scores': {'VNQ': Value('float64'), 'SLV': Value('float64'), 'TLT': Value('float64'), 'GLD': Value('float64'), 'HYG': Value('float64'), 'MBB': Value('float64'), 'LQD': Value('float64'), 'PFF': Value('float64')}, 'causal_method': Value('string'), 'top_causal_links': List({'from': Value('string'), 'to': Value('string'), 'strength': Value('float64')}), 'fixed_window': {'pick': Value('string'), 'scores': {'PFF': Value('float64'), 'MBB': Value('float64'), 'GLD': Value('float64'), 'VNQ': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'TLT': Value('float64'), 'SLV': Value('float64')}, 'test_start': Value('timestamp[s]'), 'oos_return': Value('float64'), 'oos_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'hit_rate': Value('float64'), 'max_dd': Value('float64')}, 'shrinking_window': {'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'pick': Value('string'), 'scores': {'VNQ': Value('float64'), 'SLV': Value('float64'), 'TLT': Value('float64'), 'GLD': Value('float64'), 'HYG': Value('float64'), 'MBB': Value('float64'), 'LQD': Value('float64'), 'PFF': Value('float64')}, 'oos_return': Value('
...
'float64'), 'GDX': Value('float64'), 'XLY': Value('float64'), 'XLP': Value('float64'), 'XLF': Value('float64'), 'XLU': Value('float64'), 'IWM': Value('float64'), 'SPY': Value('float64'), 'XLK': Value('float64'), 'QQQ': Value('float64'), 'IWF': Value('float64'), 'XLI': Value('float64'), 'XSD': Value('float64'), 'XME': Value('float64'), 'XBI': Value('float64')}, 'test_start': Value('timestamp[s]'), 'oos_return': Value('float64'), 'oos_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'hit_rate': Value('float64'), 'max_dd': Value('float64')}, 'shrinking_window': {'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'pick': Value('string'), 'scores': {'XME': Value('float64'), 'XLP': Value('float64'), 'XLE': Value('float64'), 'XLU': Value('float64'), 'XLF': Value('float64'), 'XLY': Value('float64'), 'IWM': Value('float64'), 'SPY': Value('float64'), 'QQQ': Value('float64'), 'IWF': Value('float64'), 'XLV': Value('float64'), 'XLI': Value('float64'), 'XBI': Value('float64'), 'XLK': Value('float64'), 'XSD': Value('float64'), 'GDX': Value('float64')}, 'oos_return': Value('float64'), 'oos_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'oos_hit_rate': Value('float64'), 'oos_max_dd': Value('float64'), 'all_windows': List({'window_id': Value('int64'), 'train_start': Value('timestamp[s]'), 'pick': Value('string'), 'oos_return': Value('float64'), 'oos_sharpe': Value('float64'), 'method': Value('string')})}}}
because column names don't match
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 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              option: string
              option_name: string
              signal_date: timestamp[s]
              last_data_date: timestamp[s]
              generated_at: string
              pick: string
              conviction: double
              source: string
              scores: struct<VNQ: double, SLV: double, TLT: double, GLD: double, HYG: double, MBB: double, LQD: double, PF (... 10 chars omitted)
                child 0, VNQ: double
                child 1, SLV: double
                child 2, TLT: double
                child 3, GLD: double
                child 4, HYG: double
                child 5, MBB: double
                child 6, LQD: double
                child 7, PFF: double
              causal_method: string
              top_causal_links: list<item: struct<from: string, to: string, strength: double>>
                child 0, item: struct<from: string, to: string, strength: double>
                    child 0, from: string
                    child 1, to: string
                    child 2, strength: double
              fixed_window: struct<pick: string, scores: struct<PFF: double, MBB: double, GLD: double, VNQ: double, LQD: double, (... 157 chars omitted)
                child 0, pick: string
                child 1, scores: struct<PFF: double, MBB: double, GLD: double, VNQ: double, LQD: double, HYG: double, TLT: double, SL (... 10 chars omitted)
                    child 0, PFF: double
                    child 1, MBB: double
                    child 2, GLD: double
                    child 3, VNQ: double
                    child 4, LQD: double
                    child 5, HYG: double
                    child 6, TLT: double
                    child 7, SLV: double
                child 2, test_start: timestamp[s]
                child 3, oos_return: double
                child 4, oos_vol: double
                child 5, oos_sharpe: double
                child 6, hit_rate: double
                child 7, max_dd: double
              shrinking_window: struct<winning_window: int64, winning_train_start: t
              ...
              w: int64
                    child 1, winning_train_start: timestamp[s]
                    child 2, winning_train_end: timestamp[s]
                    child 3, pick: string
                    child 4, scores: struct<XME: double, XLP: double, XLE: double, XLU: double, XLF: double, XLY: double, IWM: double, SP (... 114 chars omitted)
                        child 0, XME: double
                        child 1, XLP: double
                        child 2, XLE: double
                        child 3, XLU: double
                        child 4, XLF: double
                        child 5, XLY: double
                        child 6, IWM: double
                        child 7, SPY: double
                        child 8, QQQ: double
                        child 9, IWF: double
                        child 10, XLV: double
                        child 11, XLI: double
                        child 12, XBI: double
                        child 13, XLK: double
                        child 14, XSD: double
                        child 15, GDX: double
                    child 5, oos_return: double
                    child 6, oos_vol: double
                    child 7, oos_sharpe: double
                    child 8, oos_hit_rate: double
                    child 9, oos_max_dd: double
                    child 10, all_windows: list<item: struct<window_id: int64, train_start: timestamp[s], pick: string, oos_return: double, oos (... 33 chars omitted)
                        child 0, item: struct<window_id: int64, train_start: timestamp[s], pick: string, oos_return: double, oos_sharpe: do (... 21 chars omitted)
                            child 0, window_id: int64
                            child 1, train_start: timestamp[s]
                            child 2, pick: string
                            child 3, oos_return: double
                            child 4, oos_sharpe: double
                            child 5, method: string
              to
              {'generated_at': Value('string'), 'option_A': {'option': Value('string'), 'option_name': Value('string'), 'signal_date': Value('timestamp[s]'), 'last_data_date': Value('timestamp[s]'), 'generated_at': Value('string'), 'pick': Value('string'), 'conviction': Value('float64'), 'source': Value('string'), 'scores': {'VNQ': Value('float64'), 'SLV': Value('float64'), 'TLT': Value('float64'), 'GLD': Value('float64'), 'HYG': Value('float64'), 'MBB': Value('float64'), 'LQD': Value('float64'), 'PFF': Value('float64')}, 'causal_method': Value('string'), 'top_causal_links': List({'from': Value('string'), 'to': Value('string'), 'strength': Value('float64')}), 'fixed_window': {'pick': Value('string'), 'scores': {'PFF': Value('float64'), 'MBB': Value('float64'), 'GLD': Value('float64'), 'VNQ': Value('float64'), 'LQD': Value('float64'), 'HYG': Value('float64'), 'TLT': Value('float64'), 'SLV': Value('float64')}, 'test_start': Value('timestamp[s]'), 'oos_return': Value('float64'), 'oos_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'hit_rate': Value('float64'), 'max_dd': Value('float64')}, 'shrinking_window': {'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'pick': Value('string'), 'scores': {'VNQ': Value('float64'), 'SLV': Value('float64'), 'TLT': Value('float64'), 'GLD': Value('float64'), 'HYG': Value('float64'), 'MBB': Value('float64'), 'LQD': Value('float64'), 'PFF': Value('float64')}, 'oos_return': Value('
              ...
              'float64'), 'GDX': Value('float64'), 'XLY': Value('float64'), 'XLP': Value('float64'), 'XLF': Value('float64'), 'XLU': Value('float64'), 'IWM': Value('float64'), 'SPY': Value('float64'), 'XLK': Value('float64'), 'QQQ': Value('float64'), 'IWF': Value('float64'), 'XLI': Value('float64'), 'XSD': Value('float64'), 'XME': Value('float64'), 'XBI': Value('float64')}, 'test_start': Value('timestamp[s]'), 'oos_return': Value('float64'), 'oos_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'hit_rate': Value('float64'), 'max_dd': Value('float64')}, 'shrinking_window': {'winning_window': Value('int64'), 'winning_train_start': Value('timestamp[s]'), 'winning_train_end': Value('timestamp[s]'), 'pick': Value('string'), 'scores': {'XME': Value('float64'), 'XLP': Value('float64'), 'XLE': Value('float64'), 'XLU': Value('float64'), 'XLF': Value('float64'), 'XLY': Value('float64'), 'IWM': Value('float64'), 'SPY': Value('float64'), 'QQQ': Value('float64'), 'IWF': Value('float64'), 'XLV': Value('float64'), 'XLI': Value('float64'), 'XBI': Value('float64'), 'XLK': Value('float64'), 'XSD': Value('float64'), 'GDX': Value('float64')}, 'oos_return': Value('float64'), 'oos_vol': Value('float64'), 'oos_sharpe': Value('float64'), 'oos_hit_rate': Value('float64'), 'oos_max_dd': Value('float64'), 'all_windows': List({'window_id': Value('int64'), 'train_start': Value('timestamp[s]'), 'pick': Value('string'), 'oos_return': Value('float64'), 'oos_sharpe': Value('float64'), 'method': Value('string')})}}}
              because column names don't match

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