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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
generated_at: string
option_A: struct<option: string, mode: string, option_name: string, signal_date: timestamp[s], last_data_date: (... 447 chars omitted)
child 0, option: string
child 1, mode: string
child 2, option_name: string
child 3, signal_date: timestamp[s]
child 4, last_data_date: timestamp[s]
child 5, generated_at: string
child 6, pick: string
child 7, conviction: double
child 8, weights: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, PFF: double, MB (... 10 chars omitted)
child 0, TLT: double
child 1, LQD: double
child 2, HYG: double
child 3, VNQ: double
child 4, GLD: double
child 5, SLV: double
child 6, PFF: double
child 7, MBB: double
child 9, regime_context: struct<VIX: double, T10Y2Y: double, HY_SPREAD: double, USD_INDEX: double>
child 0, VIX: double
child 1, T10Y2Y: double
child 2, HY_SPREAD: double
child 3, USD_INDEX: double
child 10, macro_stress: double
child 11, trained_at: string
child 12, winning_loss: string
child 13, test_sharpe: double
child 14, test_ann_return: double
child 15, model_n_params: int64
child 16, actual_return: null
child 17, hit: null
option_B: struct<option: string, mode: string, option_name: string, signal_date: timestamp[s], last_data_date: (... 604 chars omitted)
child 0, option: string
child 1, mode: string
child 2, option_name: string
child 3, signal_date: timestamp[s]
child 4,
...
ild 4, last_data_date: timestamp[s]
child 5, generated_at: string
child 6, pick: string
child 7, conviction: double
child 8, weights: struct<SPY: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XL (... 167 chars omitted)
child 0, SPY: double
child 1, QQQ: double
child 2, XLK: double
child 3, XLF: double
child 4, XLE: double
child 5, XLV: double
child 6, XLI: double
child 7, XLY: double
child 8, XLP: double
child 9, XLU: double
child 10, GDX: double
child 11, XLB: double
child 12, IWF: double
child 13, IWD: double
child 14, IWO: double
child 15, XSD: double
child 16, XBI: double
child 17, XLRE: double
child 18, IWM: double
child 19, XME: double
child 9, regime_context: struct<VIX: double, T10Y2Y: double, HY_SPREAD: double, USD_INDEX: double>
child 0, VIX: double
child 1, T10Y2Y: double
child 2, HY_SPREAD: double
child 3, USD_INDEX: double
child 10, macro_stress: double
child 11, trained_at: string
child 12, winning_window: int64
child 13, winning_train_start: timestamp[s]
child 14, winning_train_end: timestamp[s]
child 15, winning_loss: string
child 16, oos_ann_return: double
child 17, oos_sharpe: double
child 18, actual_return: null
child 19, hit: null
n_trading_days: int64
update_type: string
last_trading_day: timestamp[s]
last_updated: string
last_run_status: string
to
{'last_updated': Value('string'), 'last_trading_day': Value('timestamp[s]'), 'n_trading_days': Value('int64'), 'update_type': Value('string'), 'last_run_status': 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
generated_at: string
option_A: struct<option: string, mode: string, option_name: string, signal_date: timestamp[s], last_data_date: (... 447 chars omitted)
child 0, option: string
child 1, mode: string
child 2, option_name: string
child 3, signal_date: timestamp[s]
child 4, last_data_date: timestamp[s]
child 5, generated_at: string
child 6, pick: string
child 7, conviction: double
child 8, weights: struct<TLT: double, LQD: double, HYG: double, VNQ: double, GLD: double, SLV: double, PFF: double, MB (... 10 chars omitted)
child 0, TLT: double
child 1, LQD: double
child 2, HYG: double
child 3, VNQ: double
child 4, GLD: double
child 5, SLV: double
child 6, PFF: double
child 7, MBB: double
child 9, regime_context: struct<VIX: double, T10Y2Y: double, HY_SPREAD: double, USD_INDEX: double>
child 0, VIX: double
child 1, T10Y2Y: double
child 2, HY_SPREAD: double
child 3, USD_INDEX: double
child 10, macro_stress: double
child 11, trained_at: string
child 12, winning_loss: string
child 13, test_sharpe: double
child 14, test_ann_return: double
child 15, model_n_params: int64
child 16, actual_return: null
child 17, hit: null
option_B: struct<option: string, mode: string, option_name: string, signal_date: timestamp[s], last_data_date: (... 604 chars omitted)
child 0, option: string
child 1, mode: string
child 2, option_name: string
child 3, signal_date: timestamp[s]
child 4,
...
ild 4, last_data_date: timestamp[s]
child 5, generated_at: string
child 6, pick: string
child 7, conviction: double
child 8, weights: struct<SPY: double, QQQ: double, XLK: double, XLF: double, XLE: double, XLV: double, XLI: double, XL (... 167 chars omitted)
child 0, SPY: double
child 1, QQQ: double
child 2, XLK: double
child 3, XLF: double
child 4, XLE: double
child 5, XLV: double
child 6, XLI: double
child 7, XLY: double
child 8, XLP: double
child 9, XLU: double
child 10, GDX: double
child 11, XLB: double
child 12, IWF: double
child 13, IWD: double
child 14, IWO: double
child 15, XSD: double
child 16, XBI: double
child 17, XLRE: double
child 18, IWM: double
child 19, XME: double
child 9, regime_context: struct<VIX: double, T10Y2Y: double, HY_SPREAD: double, USD_INDEX: double>
child 0, VIX: double
child 1, T10Y2Y: double
child 2, HY_SPREAD: double
child 3, USD_INDEX: double
child 10, macro_stress: double
child 11, trained_at: string
child 12, winning_window: int64
child 13, winning_train_start: timestamp[s]
child 14, winning_train_end: timestamp[s]
child 15, winning_loss: string
child 16, oos_ann_return: double
child 17, oos_sharpe: double
child 18, actual_return: null
child 19, hit: null
n_trading_days: int64
update_type: string
last_trading_day: timestamp[s]
last_updated: string
last_run_status: string
to
{'last_updated': Value('string'), 'last_trading_day': Value('timestamp[s]'), 'n_trading_days': Value('int64'), 'update_type': Value('string'), 'last_run_status': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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