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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
trade_date: timestamp[s]
sources: struct<scan: string, predictions: string>
child 0, scan: string
child 1, predictions: string
market: struct<scored: int64, universe: int64, predicted: int64, buy: int64, hold: int64, sell: int64, buy_p (... 30 chars omitted)
child 0, scored: int64
child 1, universe: int64
child 2, predicted: int64
child 3, buy: int64
child 4, hold: int64
child 5, sell: int64
child 6, buy_pct: double
child 7, sentiment: string
hot_groups: list<item: struct<name: string, rank: int64, score: double, breadth: double, stock_count: int64, met (... 265 chars omitted)
child 0, item: struct<name: string, rank: int64, score: double, breadth: double, stock_count: int64, metrics: struc (... 253 chars omitted)
child 0, name: string
child 1, rank: int64
child 2, score: double
child 3, breadth: double
child 4, stock_count: int64
child 5, metrics: struct<momentum_20d: double, volume_surge: double, institutional_net_20d: double, hot_breadth: doubl (... 2 chars omitted)
child 0, momentum_20d: double
child 1, volume_surge: double
child 2, institutional_net_20d: double
child 3, hot_breadth: double
child 6, leaders: list<item: struct<code: string, name: string, group: string, close: double, chg_5d: double, volume: (... 44 chars omitted)
child 0, item: struct<code: string, name: string, group: string, close: double, chg_5d: double, volume: double,
...
title: string, lines: list<item: string>>>, (... 16 chars omitted)
child 0, generated_at: string
child 1, sections: list<item: struct<title: string, lines: list<item: string>>>
child 0, item: struct<title: string, lines: list<item: string>>
child 0, title: string
child 1, lines: list<item: string>
child 0, item: string
child 2, source: string
stocks: list<item: struct<code: string, name: string, group: string, market: string, c: list<item: int64>>>
child 0, item: struct<code: string, name: string, group: string, market: string, c: list<item: int64>>
child 0, code: string
child 1, name: string
child 2, group: string
child 3, market: string
child 4, c: list<item: int64>
child 0, item: int64
universe_size: int64
study_generated_at: string
scored_count: int64
combinations: list<item: struct<key: string, keys: list<item: string>, names: list<item: string>, direction: int64 (... 96 chars omitted)
child 0, item: struct<key: string, keys: list<item: string>, names: list<item: string>, direction: int64, grade: st (... 84 chars omitted)
child 0, key: string
child 1, keys: list<item: string>
child 0, item: string
child 2, names: list<item: string>
child 0, item: string
child 3, direction: int64
child 4, grade: string
child 5, edge_pp: double
child 6, median_excess_5d: double
child 7, samples: int64
child 8, match_count: int64
to
{'generated_at': Value('string'), 'study_generated_at': Value('string'), 'universe_size': Value('int64'), 'scored_count': Value('int64'), 'combinations': List({'key': Value('string'), 'keys': List(Value('string')), 'names': List(Value('string')), 'direction': Value('int64'), 'grade': Value('string'), 'edge_pp': Value('float64'), 'median_excess_5d': Value('float64'), 'samples': Value('int64'), 'match_count': Value('int64')}), 'stocks': List({'code': Value('string'), 'name': Value('string'), 'group': Value('string'), 'market': Value('string'), 'c': List(Value('int64'))})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
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 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
generated_at: string
trade_date: timestamp[s]
sources: struct<scan: string, predictions: string>
child 0, scan: string
child 1, predictions: string
market: struct<scored: int64, universe: int64, predicted: int64, buy: int64, hold: int64, sell: int64, buy_p (... 30 chars omitted)
child 0, scored: int64
child 1, universe: int64
child 2, predicted: int64
child 3, buy: int64
child 4, hold: int64
child 5, sell: int64
child 6, buy_pct: double
child 7, sentiment: string
hot_groups: list<item: struct<name: string, rank: int64, score: double, breadth: double, stock_count: int64, met (... 265 chars omitted)
child 0, item: struct<name: string, rank: int64, score: double, breadth: double, stock_count: int64, metrics: struc (... 253 chars omitted)
child 0, name: string
child 1, rank: int64
child 2, score: double
child 3, breadth: double
child 4, stock_count: int64
child 5, metrics: struct<momentum_20d: double, volume_surge: double, institutional_net_20d: double, hot_breadth: doubl (... 2 chars omitted)
child 0, momentum_20d: double
child 1, volume_surge: double
child 2, institutional_net_20d: double
child 3, hot_breadth: double
child 6, leaders: list<item: struct<code: string, name: string, group: string, close: double, chg_5d: double, volume: (... 44 chars omitted)
child 0, item: struct<code: string, name: string, group: string, close: double, chg_5d: double, volume: double,
...
title: string, lines: list<item: string>>>, (... 16 chars omitted)
child 0, generated_at: string
child 1, sections: list<item: struct<title: string, lines: list<item: string>>>
child 0, item: struct<title: string, lines: list<item: string>>
child 0, title: string
child 1, lines: list<item: string>
child 0, item: string
child 2, source: string
stocks: list<item: struct<code: string, name: string, group: string, market: string, c: list<item: int64>>>
child 0, item: struct<code: string, name: string, group: string, market: string, c: list<item: int64>>
child 0, code: string
child 1, name: string
child 2, group: string
child 3, market: string
child 4, c: list<item: int64>
child 0, item: int64
universe_size: int64
study_generated_at: string
scored_count: int64
combinations: list<item: struct<key: string, keys: list<item: string>, names: list<item: string>, direction: int64 (... 96 chars omitted)
child 0, item: struct<key: string, keys: list<item: string>, names: list<item: string>, direction: int64, grade: st (... 84 chars omitted)
child 0, key: string
child 1, keys: list<item: string>
child 0, item: string
child 2, names: list<item: string>
child 0, item: string
child 3, direction: int64
child 4, grade: string
child 5, edge_pp: double
child 6, median_excess_5d: double
child 7, samples: int64
child 8, match_count: int64
to
{'generated_at': Value('string'), 'study_generated_at': Value('string'), 'universe_size': Value('int64'), 'scored_count': Value('int64'), 'combinations': List({'key': Value('string'), 'keys': List(Value('string')), 'names': List(Value('string')), 'direction': Value('int64'), 'grade': Value('string'), 'edge_pp': Value('float64'), 'median_excess_5d': Value('float64'), 'samples': Value('int64'), 'match_count': Value('int64')}), 'stocks': List({'code': Value('string'), 'name': Value('string'), 'group': Value('string'), 'market': Value('string'), 'c': List(Value('int64'))})}
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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