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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
route_id: string
depot: struct<stop_id: string, address: string>
child 0, stop_id: string
child 1, address: string
legs: list<item: struct<from_stop_id: string, to_stop_id: string, from_address: string, to_address: string (... 62 chars omitted)
child 0, item: struct<from_stop_id: string, to_stop_id: string, from_address: string, to_address: string, distance_ (... 50 chars omitted)
child 0, from_stop_id: string
child 1, to_stop_id: string
child 2, from_address: string
child 3, to_address: string
child 4, distance_km: double
child 5, duration_minutes: int64
child 6, flag: string
stops: list<item: struct<stop_id: string, address: string, priority: string, package_id: string, cumulative (... 43 chars omitted)
child 0, item: struct<stop_id: string, address: string, priority: string, package_id: string, cumulative_arrival_mi (... 31 chars omitted)
child 0, stop_id: string
child 1, address: string
child 2, priority: string
child 3, package_id: string
child 4, cumulative_arrival_minutes: int64
child 5, decision: string
totals: struct<total_distance_km: double, total_driving_minutes: int64, total_service_minutes: int64, total_ (... 43 chars omitted)
child 0, total_distance_km: double
child 1, total_driving_minutes: int64
child 2, total_service_minutes: int64
child 3, total_route_minutes: int64
child 4, route_status: string
route_date: string
to
{'route_date': Value('string'), 'depot': {'stop_id': Value('string'), 'sequence': Value('int64'), 'address': Value('string'), 'customer_name': Value('string'), 'package_id': Value('null'), 'priority': Value('null'), 'service_minutes': Value('int64')}, 'stops': List({'stop_id': Value('string'), 'sequence': Value('int64'), 'address': Value('string'), 'customer_name': Value('string'), 'package_id': Value('string'), 'priority': Value('string'), 'service_minutes': Value('int64')})}
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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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
route_id: string
depot: struct<stop_id: string, address: string>
child 0, stop_id: string
child 1, address: string
legs: list<item: struct<from_stop_id: string, to_stop_id: string, from_address: string, to_address: string (... 62 chars omitted)
child 0, item: struct<from_stop_id: string, to_stop_id: string, from_address: string, to_address: string, distance_ (... 50 chars omitted)
child 0, from_stop_id: string
child 1, to_stop_id: string
child 2, from_address: string
child 3, to_address: string
child 4, distance_km: double
child 5, duration_minutes: int64
child 6, flag: string
stops: list<item: struct<stop_id: string, address: string, priority: string, package_id: string, cumulative (... 43 chars omitted)
child 0, item: struct<stop_id: string, address: string, priority: string, package_id: string, cumulative_arrival_mi (... 31 chars omitted)
child 0, stop_id: string
child 1, address: string
child 2, priority: string
child 3, package_id: string
child 4, cumulative_arrival_minutes: int64
child 5, decision: string
totals: struct<total_distance_km: double, total_driving_minutes: int64, total_service_minutes: int64, total_ (... 43 chars omitted)
child 0, total_distance_km: double
child 1, total_driving_minutes: int64
child 2, total_service_minutes: int64
child 3, total_route_minutes: int64
child 4, route_status: string
route_date: string
to
{'route_date': Value('string'), 'depot': {'stop_id': Value('string'), 'sequence': Value('int64'), 'address': Value('string'), 'customer_name': Value('string'), 'package_id': Value('null'), 'priority': Value('null'), 'service_minutes': Value('int64')}, 'stops': List({'stop_id': Value('string'), 'sequence': Value('int64'), 'address': Value('string'), 'customer_name': Value('string'), 'package_id': Value('string'), 'priority': Value('string'), 'service_minutes': 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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