Datasets:

---

jbduran

/

think-dataset-clean

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
chars_after_clean_before_prior: int64
chars_kept: int64
chars_raw: int64
finished_at: timestamp[s]
mean_prior_kept: double
n_input: int64
n_kept: int64
n_removed: int64
output_shard: string
removed_by_reason: struct<ocr_artifacts: int64, prior_high: int64, prior_low: int64>
  child 0, ocr_artifacts: int64
  child 1, prior_high: int64
  child 2, prior_low: int64
source_shard: string
started_at: timestamp[s]
mean_log_prior_percentiles: struct<1: double, 10: double, 2.5: double, 25: double, 5: double, 50: double, 75: double, 90: double (... 39 chars omitted)
  child 0, 1: double
  child 1, 10: double
  child 2, 2.5: double
  child 3, 25: double
  child 4, 5: double
  child 5, 50: double
  child 6, 75: double
  child 7, 90: double
  child 8, 95: double
  child 9, 97.5: double
  child 10, 99: double
high: double
low: double
sample_structural_kept: int64
prior_band: list<item: double>
  child 0, item: double
sample_structural_removed: struct<ocr_artifacts: int64>
  child 0, ocr_artifacts: int64
sample_raw_docs_seen: int64
sample_prior_docs: int64
estimated_prior_removed_pct: double
to
{'estimated_prior_removed_pct': Value('float64'), 'high': Value('float64'), 'low': Value('float64'), 'mean_log_prior_percentiles': {'1': Value('float64'), '10': Value('float64'), '2.5': Value('float64'), '25': Value('float64'), '5': Value('float64'), '50': Value('float64'), '75': Value('float64'), '90': Value('float64'), '95': Value('float64'), '97.5': Value('float64'), '99': Value('float64')}, 'prior_band': List(Value('float64')), 'sample_prior_docs': Value('int64'), 'sample_raw_docs_seen': Value('int64'), 'sample_structural_kept': Value('int64'), 'sample_structural_removed': {'ocr_artifacts': 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 478, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              chars_after_clean_before_prior: int64
              chars_kept: int64
              chars_raw: int64
              finished_at: timestamp[s]
              mean_prior_kept: double
              n_input: int64
              n_kept: int64
              n_removed: int64
              output_shard: string
              removed_by_reason: struct<ocr_artifacts: int64, prior_high: int64, prior_low: int64>
                child 0, ocr_artifacts: int64
                child 1, prior_high: int64
                child 2, prior_low: int64
              source_shard: string
              started_at: timestamp[s]
              mean_log_prior_percentiles: struct<1: double, 10: double, 2.5: double, 25: double, 5: double, 50: double, 75: double, 90: double (... 39 chars omitted)
                child 0, 1: double
                child 1, 10: double
                child 2, 2.5: double
                child 3, 25: double
                child 4, 5: double
                child 5, 50: double
                child 6, 75: double
                child 7, 90: double
                child 8, 95: double
                child 9, 97.5: double
                child 10, 99: double
              high: double
              low: double
              sample_structural_kept: int64
              prior_band: list<item: double>
                child 0, item: double
              sample_structural_removed: struct<ocr_artifacts: int64>
                child 0, ocr_artifacts: int64
              sample_raw_docs_seen: int64
              sample_prior_docs: int64
              estimated_prior_removed_pct: double
              to
              {'estimated_prior_removed_pct': Value('float64'), 'high': Value('float64'), 'low': Value('float64'), 'mean_log_prior_percentiles': {'1': Value('float64'), '10': Value('float64'), '2.5': Value('float64'), '25': Value('float64'), '5': Value('float64'), '50': Value('float64'), '75': Value('float64'), '90': Value('float64'), '95': Value('float64'), '97.5': Value('float64'), '99': Value('float64')}, 'prior_band': List(Value('float64')), 'sample_prior_docs': Value('int64'), 'sample_raw_docs_seen': Value('int64'), 'sample_structural_kept': Value('int64'), 'sample_structural_removed': {'ocr_artifacts': Value('int64')}}
              because column names don't match