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haykgrigorian
/
english-historical-corpus-1800-1875-15GB-sample

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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
sample_name: string
target_tokens: int64
estimated_tokens: int64
estimated_tokens_billion: double
records: int64
estimated_text_bytes: int64
estimated_text_gb_decimal: double
compressed_bytes: int64
compressed_gb_decimal: double
selection_method: string
nested_note: string
source_targets: struct<chronicling_america_langfiltered_prose: struct<target_tokens: int64, target_tokens_billion: d (... 845 chars omitted)
  child 0, chronicling_america_langfiltered_prose: struct<target_tokens: int64, target_tokens_billion: double, selected_records: int64, selected_estima (... 56 chars omitted)
      child 0, target_tokens: int64
      child 1, target_tokens_billion: double
      child 2, selected_records: int64
      child 3, selected_estimated_tokens: int64
      child 4, source_total_estimated_tokens: int64
  child 1, city_corpora_cleaned_txt: struct<target_tokens: int64, target_tokens_billion: double, selected_records: int64, selected_estima (... 56 chars omitted)
      child 0, target_tokens: int64
      child 1, target_tokens_billion: double
      child 2, selected_records: int64
      child 3, selected_estimated_tokens: int64
      child 4, source_total_estimated_tokens: int64
  child 2, internet_archive_postfiltered_prose: struct<target_tokens: int64, target_tokens_billion: double, selected_records: int64, selected_estima (... 56 chars omitted)
      child 0, target_tokens: int64
      child 1, target_tokens_billion: double
      child 2, selected_records: int64
      child 3, se
...
corpus_root: string
source_estimates: struct<chronicling_america_langfiltered_prose: struct<current_bytes: int64, estimated_tokens: int64, (... 495 chars omitted)
  child 0, chronicling_america_langfiltered_prose: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
      child 0, current_bytes: int64
      child 1, estimated_tokens: int64
      child 2, density_tokens_per_byte: double
  child 1, city_corpora_cleaned_txt: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
      child 0, current_bytes: int64
      child 1, estimated_tokens: int64
      child 2, density_tokens_per_byte: double
  child 2, internet_archive_postfiltered_prose: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
      child 0, current_bytes: int64
      child 1, estimated_tokens: int64
      child 2, density_tokens_per_byte: double
  child 3, london_v2_cleaned_txt: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
      child 0, current_bytes: int64
      child 1, estimated_tokens: int64
      child 2, density_tokens_per_byte: double
  child 4, lwm_strict_newspapers: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
      child 0, current_bytes: int64
      child 1, estimated_tokens: int64
      child 2, density_tokens_per_byte: double
total_estimated_tokens: int64
output_root: string
total_estimated_tokens_billion: double
to
{'corpus_root': Value('string'), 'output_root': Value('string'), 'records_seen': Value('int64'), 'source_estimates': {'chronicling_america_langfiltered_prose': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'city_corpora_cleaned_txt': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'internet_archive_postfiltered_prose': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'london_v2_cleaned_txt': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'lwm_strict_newspapers': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}}, 'total_estimated_tokens': Value('int64'), 'total_estimated_tokens_billion': Value('float64'), 'samples': List({'name': Value('string'), 'records': Value('int64'), 'estimated_tokens': Value('int64'), 'estimated_tokens_billion': Value('float64')})}
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
              sample_name: string
              target_tokens: int64
              estimated_tokens: int64
              estimated_tokens_billion: double
              records: int64
              estimated_text_bytes: int64
              estimated_text_gb_decimal: double
              compressed_bytes: int64
              compressed_gb_decimal: double
              selection_method: string
              nested_note: string
              source_targets: struct<chronicling_america_langfiltered_prose: struct<target_tokens: int64, target_tokens_billion: d (... 845 chars omitted)
                child 0, chronicling_america_langfiltered_prose: struct<target_tokens: int64, target_tokens_billion: double, selected_records: int64, selected_estima (... 56 chars omitted)
                    child 0, target_tokens: int64
                    child 1, target_tokens_billion: double
                    child 2, selected_records: int64
                    child 3, selected_estimated_tokens: int64
                    child 4, source_total_estimated_tokens: int64
                child 1, city_corpora_cleaned_txt: struct<target_tokens: int64, target_tokens_billion: double, selected_records: int64, selected_estima (... 56 chars omitted)
                    child 0, target_tokens: int64
                    child 1, target_tokens_billion: double
                    child 2, selected_records: int64
                    child 3, selected_estimated_tokens: int64
                    child 4, source_total_estimated_tokens: int64
                child 2, internet_archive_postfiltered_prose: struct<target_tokens: int64, target_tokens_billion: double, selected_records: int64, selected_estima (... 56 chars omitted)
                    child 0, target_tokens: int64
                    child 1, target_tokens_billion: double
                    child 2, selected_records: int64
                    child 3, se
              ...
              corpus_root: string
              source_estimates: struct<chronicling_america_langfiltered_prose: struct<current_bytes: int64, estimated_tokens: int64, (... 495 chars omitted)
                child 0, chronicling_america_langfiltered_prose: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
                    child 0, current_bytes: int64
                    child 1, estimated_tokens: int64
                    child 2, density_tokens_per_byte: double
                child 1, city_corpora_cleaned_txt: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
                    child 0, current_bytes: int64
                    child 1, estimated_tokens: int64
                    child 2, density_tokens_per_byte: double
                child 2, internet_archive_postfiltered_prose: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
                    child 0, current_bytes: int64
                    child 1, estimated_tokens: int64
                    child 2, density_tokens_per_byte: double
                child 3, london_v2_cleaned_txt: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
                    child 0, current_bytes: int64
                    child 1, estimated_tokens: int64
                    child 2, density_tokens_per_byte: double
                child 4, lwm_strict_newspapers: struct<current_bytes: int64, estimated_tokens: int64, density_tokens_per_byte: double>
                    child 0, current_bytes: int64
                    child 1, estimated_tokens: int64
                    child 2, density_tokens_per_byte: double
              total_estimated_tokens: int64
              output_root: string
              total_estimated_tokens_billion: double
              to
              {'corpus_root': Value('string'), 'output_root': Value('string'), 'records_seen': Value('int64'), 'source_estimates': {'chronicling_america_langfiltered_prose': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'city_corpora_cleaned_txt': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'internet_archive_postfiltered_prose': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'london_v2_cleaned_txt': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}, 'lwm_strict_newspapers': {'current_bytes': Value('int64'), 'estimated_tokens': Value('int64'), 'density_tokens_per_byte': Value('float64')}}, 'total_estimated_tokens': Value('int64'), 'total_estimated_tokens_billion': Value('float64'), 'samples': List({'name': Value('string'), 'records': Value('int64'), 'estimated_tokens': Value('int64'), 'estimated_tokens_billion': Value('float64')})}
              because column names don't match

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