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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]
universe: string
module: string
graph_window: int64
latest_date: timestamp[s]
latest_scores: struct<GDX: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: (... 2290 chars omitted)
child 0, GDX: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 1, GLD: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 2, HYG: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 3, IWF: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 4, IWM: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
...
: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 22, XSD: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 23, CASH: struct<policy_weight: double>
child 0, policy_weight: double
latest_ranked: list<item: struct<ticker: string, composite_score: double, policy_weight: double, interventional_ret (... 23 chars omitted)
child 0, item: struct<ticker: string, composite_score: double, policy_weight: double, interventional_ret: double, r (... 11 chars omitted)
child 0, ticker: string
child 1, composite_score: double
child 2, policy_weight: double
child 3, interventional_ret: double
child 4, rank: int64
config: struct<graph_method: string, graph_window: int64, cf_penalty_wt: double, cash_threshold: double, top (... 35 chars omitted)
child 0, graph_method: string
child 1, graph_window: int64
child 2, cf_penalty_wt: double
child 3, cash_threshold: double
child 4, top_n: int64
child 5, oos_start: timestamp[s]
ckpt_meta: struct<train_date: timestamp[s], best_ep_ret: double, graph_method: string>
child 0, train_date: timestamp[s]
child 1, best_ep_ret: double
child 2, graph_method: string
to
{'run_date': Value('timestamp[s]'), 'universe': Value('string'), 'latest_date': Value('timestamp[s]'), 'latest_scores': {'GDX': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'GLD': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'HYG': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'IWF': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'IWM': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'LQD': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'QQQ': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'SLV': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'SPY': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'TLT': {'composite_score': Value('float64'), 'policy_weight': Value('float
...
, 'XLP': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XLU': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XLV': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XLY': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XME': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XSD': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'CASH': {'policy_weight': Value('float64')}}, 'latest_ranked': List({'ticker': Value('string'), 'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}), 'ckpt_meta': {'train_date': Value('timestamp[s]'), 'best_ep_ret': Value('float64'), 'graph_method': Value('string')}, 'config': {'graph_method': Value('string'), 'graph_window': Value('int64'), 'graph_refit_freq': Value('int64'), 'cf_penalty_wt': Value('float64'), 'cf_n_samples': Value('int64'), 'cash_threshold': Value('float64'), 'top_n': Value('int64'), 'oos_start': Value('timestamp[s]')}}
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]
universe: string
module: string
graph_window: int64
latest_date: timestamp[s]
latest_scores: struct<GDX: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: (... 2290 chars omitted)
child 0, GDX: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 1, GLD: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 2, HYG: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 3, IWF: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 4, IWM: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
...
: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 22, XSD: struct<composite_score: double, policy_weight: double, interventional_ret: double, rank: int64>
child 0, composite_score: double
child 1, policy_weight: double
child 2, interventional_ret: double
child 3, rank: int64
child 23, CASH: struct<policy_weight: double>
child 0, policy_weight: double
latest_ranked: list<item: struct<ticker: string, composite_score: double, policy_weight: double, interventional_ret (... 23 chars omitted)
child 0, item: struct<ticker: string, composite_score: double, policy_weight: double, interventional_ret: double, r (... 11 chars omitted)
child 0, ticker: string
child 1, composite_score: double
child 2, policy_weight: double
child 3, interventional_ret: double
child 4, rank: int64
config: struct<graph_method: string, graph_window: int64, cf_penalty_wt: double, cash_threshold: double, top (... 35 chars omitted)
child 0, graph_method: string
child 1, graph_window: int64
child 2, cf_penalty_wt: double
child 3, cash_threshold: double
child 4, top_n: int64
child 5, oos_start: timestamp[s]
ckpt_meta: struct<train_date: timestamp[s], best_ep_ret: double, graph_method: string>
child 0, train_date: timestamp[s]
child 1, best_ep_ret: double
child 2, graph_method: string
to
{'run_date': Value('timestamp[s]'), 'universe': Value('string'), 'latest_date': Value('timestamp[s]'), 'latest_scores': {'GDX': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'GLD': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'HYG': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'IWF': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'IWM': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'LQD': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'QQQ': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'SLV': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'SPY': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'TLT': {'composite_score': Value('float64'), 'policy_weight': Value('float
...
, 'XLP': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XLU': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XLV': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XLY': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XME': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'XSD': {'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}, 'CASH': {'policy_weight': Value('float64')}}, 'latest_ranked': List({'ticker': Value('string'), 'composite_score': Value('float64'), 'policy_weight': Value('float64'), 'interventional_ret': Value('float64'), 'rank': Value('int64')}), 'ckpt_meta': {'train_date': Value('timestamp[s]'), 'best_ep_ret': Value('float64'), 'graph_method': Value('string')}, 'config': {'graph_method': Value('string'), 'graph_window': Value('int64'), 'graph_refit_freq': Value('int64'), 'cf_penalty_wt': Value('float64'), 'cf_n_samples': Value('int64'), 'cash_threshold': Value('float64'), 'top_n': Value('int64'), 'oos_start': Value('timestamp[s]')}}
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