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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
run_date: timestamp[s]
config: struct<lookback_window: int64, n_simulations: int64, margin_model: string, tail_adjustment_lambda: d (... 6 chars omitted)
child 0, lookback_window: int64
child 1, n_simulations: int64
child 2, margin_model: string
child 3, tail_adjustment_lambda: double
daily_trading: struct<universes: struct<FI_COMMODITIES: struct<TLT: struct<expected_return: double, var_95: double, (... 4680 chars omitted)
child 0, universes: struct<FI_COMMODITIES: struct<TLT: struct<expected_return: double, var_95: double, es_95: double, co (... 4252 chars omitted)
child 0, FI_COMMODITIES: struct<TLT: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>, (... 558 chars omitted)
child 0, TLT: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>
child 0, expected_return: double
child 1, var_95: double
child 2, es_95: double
child 3, combined_score: double
child 1, VCIT: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>
child 0, expected_return: double
child 1, var_95: double
child 2, es_95: double
child 3, combined_score: double
child 2, LQD: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>
child 0, expected_return: double
child 1, var_95: double
...
child 1, expected_return_raw: double
child 2, copula_score: double
child 3, es_95: struct<point: double, lower: double, upper: double>
child 0, point: double
child 1, lower: double
child 2, upper: double
child 4, var_95: struct<point: double, lower: double, upper: double>
child 0, point: double
child 1, lower: double
child 2, upper: double
child 5, dof: double
child 6, t_copula_adj_score: double
child 3, training_start: timestamp[s]
child 4, training_end: timestamp[s]
child 5, n_observations: int64
child 2, shrinking: struct<ticker: string, conviction: double, num_windows: int64, num_pick_windows: int64, windows: lis (... 97 chars omitted)
child 0, ticker: string
child 1, conviction: double
child 2, num_windows: int64
child 3, num_pick_windows: int64
child 4, windows: list<item: struct<window_start: int64, window_end: int64, ticker: string, expected_return: double>>
child 0, item: struct<window_start: int64, window_end: int64, ticker: string, expected_return: double>
child 0, window_start: int64
child 1, window_end: int64
child 2, ticker: string
child 3, expected_return: double
to
{'run_date': Value('timestamp[s]'), 'config': {'HF_DATA_REPO': Value('string'), 'HF_DATA_FILE': Value('string'), 'HF_OUTPUT_REPO': Value('string'), 'FI_COMMODITIES_TICKERS': List(Value('string')), 'EQUITY_SECTORS_TICKERS': List(Value('string')), 'ALL_TICKERS': List(Value('string')), 'UNIVERSES': {'FI_COMMODITIES': List(Value('string')), 'EQUITY_SECTORS': List(Value('string')), 'COMBINED': List(Value('string'))}, 'MACRO_COLS': List(Value('string')), 'DAILY_LOOKBACK': Value('int64'), 'GLOBAL_TRAIN_START': Value('timestamp[s]'), 'N_SIMULATIONS': Value('int64'), 'TAIL_ADJUSTMENT_LAMBDA': Value('float64'), 'RISK_FREE_RATE_ANNUAL': Value('float64'), 'USE_GARCH': Value('bool'), 'GARCH_P': Value('int64'), 'GARCH_Q': Value('int64'), 'GARCH_DIST': Value('string'), 'BOOTSTRAP_SAMPLES': Value('int64'), 'MOMENTUM_WINDOW': Value('int64'), 'MIN_OBSERVATIONS': Value('int64'), 'GLOBAL_MIN_OBSERVATIONS': Value('int64'), 'SHRINKING_WINDOW_START_YEARS': List(Value('int64')), 'TODAY': Value('timestamp[s]')}, 'universes': {'FI_COMMODITIES': {'daily': {'mode_name': Value('string'), 'top_picks': List({'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}), 'universes': {'TLT': {'ticker': Value('string'), 'e
...
'float64')}, 'XLK': {'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}, 'SPY': {'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}, 'VCIT': {'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}}, 'training_start': Value('timestamp[s]'), 'training_end': Value('timestamp[s]'), 'n_observations': Value('int64')}, 'shrinking': {'ticker': Value('string'), 'conviction': Value('float64'), 'num_windows': Value('int64'), 'num_pick_windows': Value('int64'), 'windows': List({'window_start': Value('int64'), 'window_end': Value('int64'), 'ticker': Value('string'), 'expected_return': Value('float64')})}}}}
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
run_date: timestamp[s]
config: struct<lookback_window: int64, n_simulations: int64, margin_model: string, tail_adjustment_lambda: d (... 6 chars omitted)
child 0, lookback_window: int64
child 1, n_simulations: int64
child 2, margin_model: string
child 3, tail_adjustment_lambda: double
daily_trading: struct<universes: struct<FI_COMMODITIES: struct<TLT: struct<expected_return: double, var_95: double, (... 4680 chars omitted)
child 0, universes: struct<FI_COMMODITIES: struct<TLT: struct<expected_return: double, var_95: double, es_95: double, co (... 4252 chars omitted)
child 0, FI_COMMODITIES: struct<TLT: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>, (... 558 chars omitted)
child 0, TLT: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>
child 0, expected_return: double
child 1, var_95: double
child 2, es_95: double
child 3, combined_score: double
child 1, VCIT: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>
child 0, expected_return: double
child 1, var_95: double
child 2, es_95: double
child 3, combined_score: double
child 2, LQD: struct<expected_return: double, var_95: double, es_95: double, combined_score: double>
child 0, expected_return: double
child 1, var_95: double
...
child 1, expected_return_raw: double
child 2, copula_score: double
child 3, es_95: struct<point: double, lower: double, upper: double>
child 0, point: double
child 1, lower: double
child 2, upper: double
child 4, var_95: struct<point: double, lower: double, upper: double>
child 0, point: double
child 1, lower: double
child 2, upper: double
child 5, dof: double
child 6, t_copula_adj_score: double
child 3, training_start: timestamp[s]
child 4, training_end: timestamp[s]
child 5, n_observations: int64
child 2, shrinking: struct<ticker: string, conviction: double, num_windows: int64, num_pick_windows: int64, windows: lis (... 97 chars omitted)
child 0, ticker: string
child 1, conviction: double
child 2, num_windows: int64
child 3, num_pick_windows: int64
child 4, windows: list<item: struct<window_start: int64, window_end: int64, ticker: string, expected_return: double>>
child 0, item: struct<window_start: int64, window_end: int64, ticker: string, expected_return: double>
child 0, window_start: int64
child 1, window_end: int64
child 2, ticker: string
child 3, expected_return: double
to
{'run_date': Value('timestamp[s]'), 'config': {'HF_DATA_REPO': Value('string'), 'HF_DATA_FILE': Value('string'), 'HF_OUTPUT_REPO': Value('string'), 'FI_COMMODITIES_TICKERS': List(Value('string')), 'EQUITY_SECTORS_TICKERS': List(Value('string')), 'ALL_TICKERS': List(Value('string')), 'UNIVERSES': {'FI_COMMODITIES': List(Value('string')), 'EQUITY_SECTORS': List(Value('string')), 'COMBINED': List(Value('string'))}, 'MACRO_COLS': List(Value('string')), 'DAILY_LOOKBACK': Value('int64'), 'GLOBAL_TRAIN_START': Value('timestamp[s]'), 'N_SIMULATIONS': Value('int64'), 'TAIL_ADJUSTMENT_LAMBDA': Value('float64'), 'RISK_FREE_RATE_ANNUAL': Value('float64'), 'USE_GARCH': Value('bool'), 'GARCH_P': Value('int64'), 'GARCH_Q': Value('int64'), 'GARCH_DIST': Value('string'), 'BOOTSTRAP_SAMPLES': Value('int64'), 'MOMENTUM_WINDOW': Value('int64'), 'MIN_OBSERVATIONS': Value('int64'), 'GLOBAL_MIN_OBSERVATIONS': Value('int64'), 'SHRINKING_WINDOW_START_YEARS': List(Value('int64')), 'TODAY': Value('timestamp[s]')}, 'universes': {'FI_COMMODITIES': {'daily': {'mode_name': Value('string'), 'top_picks': List({'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}), 'universes': {'TLT': {'ticker': Value('string'), 'e
...
'float64')}, 'XLK': {'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}, 'SPY': {'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}, 'VCIT': {'ticker': Value('string'), 'expected_return_raw': Value('float64'), 'copula_score': Value('float64'), 'es_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'var_95': {'point': Value('float64'), 'lower': Value('float64'), 'upper': Value('float64')}, 'dof': Value('float64'), 't_copula_adj_score': Value('float64')}}, 'training_start': Value('timestamp[s]'), 'training_end': Value('timestamp[s]'), 'n_observations': Value('int64')}, 'shrinking': {'ticker': Value('string'), 'conviction': Value('float64'), 'num_windows': Value('int64'), 'num_pick_windows': Value('int64'), 'windows': List({'window_start': Value('int64'), 'window_end': Value('int64'), 'ticker': Value('string'), 'expected_return': Value('float64')})}}}}
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