Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
target_id: string
target_sha256: string
wave1_total: int64
megadock_max_cohort_n: int64
megadock_wave_cutoffs: list<item: int64>
child 0, item: int64
hdock_confirmatory_n: int64
hdock_pool: string
hdock_stratum_counts: struct<0: int64, 1: int64, 2: int64, 3: int64>
child 0, 0: int64
child 1, 1: int64
child 2, 2: int64
child 3, 3: int64
cohort_sha256: string
selected_before_conventional_docking: bool
uses_megadock_results: bool
uses_hdock_results: bool
megadock_selection_design: string
megadock_wave_order_design: string
hdock_selection_design: string
hdock_order_design: string
interpretation: string
protocol_amendment: string
megadock_checkpoint_cutoffs: list<item: int64>
child 0, item: int64
megadock_population_complete: bool
megadock_stratified_prefix_n: int64
to
{'target_id': Value('string'), 'target_sha256': Value('string'), 'wave1_total': Value('int64'), 'megadock_max_cohort_n': Value('int64'), 'megadock_checkpoint_cutoffs': List(Value('int64')), 'megadock_stratified_prefix_n': Value('int64'), 'megadock_population_complete': Value('bool'), 'hdock_confirmatory_n': Value('int64'), 'hdock_pool': Value('string'), 'hdock_stratum_counts': {'0': Value('int64'), '1': Value('int64'), '2': Value('int64'), '3': Value('int64')}, 'cohort_sha256': Value('string'), 'selected_before_conventional_docking': Value('bool'), 'uses_megadock_results': Value('bool'), 'uses_hdock_results': Value('bool'), 'megadock_selection_design': Value('string'), 'megadock_wave_order_design': Value('string'), 'hdock_selection_design': Value('string'), 'hdock_order_design': Value('string'), 'protocol_amendment': Value('string'), 'interpretation': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 343, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
target_id: string
target_sha256: string
wave1_total: int64
megadock_max_cohort_n: int64
megadock_wave_cutoffs: list<item: int64>
child 0, item: int64
hdock_confirmatory_n: int64
hdock_pool: string
hdock_stratum_counts: struct<0: int64, 1: int64, 2: int64, 3: int64>
child 0, 0: int64
child 1, 1: int64
child 2, 2: int64
child 3, 3: int64
cohort_sha256: string
selected_before_conventional_docking: bool
uses_megadock_results: bool
uses_hdock_results: bool
megadock_selection_design: string
megadock_wave_order_design: string
hdock_selection_design: string
hdock_order_design: string
interpretation: string
protocol_amendment: string
megadock_checkpoint_cutoffs: list<item: int64>
child 0, item: int64
megadock_population_complete: bool
megadock_stratified_prefix_n: int64
to
{'target_id': Value('string'), 'target_sha256': Value('string'), 'wave1_total': Value('int64'), 'megadock_max_cohort_n': Value('int64'), 'megadock_checkpoint_cutoffs': List(Value('int64')), 'megadock_stratified_prefix_n': Value('int64'), 'megadock_population_complete': Value('bool'), 'hdock_confirmatory_n': Value('int64'), 'hdock_pool': Value('string'), 'hdock_stratum_counts': {'0': Value('int64'), '1': Value('int64'), '2': Value('int64'), '3': Value('int64')}, 'cohort_sha256': Value('string'), 'selected_before_conventional_docking': Value('bool'), 'uses_megadock_results': Value('bool'), 'uses_hdock_results': Value('bool'), 'megadock_selection_design': Value('string'), 'megadock_wave_order_design': Value('string'), 'hdock_selection_design': Value('string'), 'hdock_order_design': Value('string'), 'protocol_amendment': Value('string'), 'interpretation': 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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