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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
registry: string
batch_id: string
status: string
report_file: string
submitted_at: timestamp[s]
currency: string
items: list<item: struct<sku: string, product_name: string, category: string, reference_price_cents: int64, (... 91 chars omitted)
  child 0, item: struct<sku: string, product_name: string, category: string, reference_price_cents: int64, current_pr (... 79 chars omitted)
      child 0, sku: string
      child 1, product_name: string
      child 2, category: string
      child 3, reference_price_cents: int64
      child 4, current_price_cents: int64
      child 5, availability: string
      child 6, price_source: string
      child 7, decision: string
company: string
report_id: string
supplier: string
generated_at: timestamp[s]
summary: struct<APPROVED: int64, REVIEW: int64, UNAVAILABLE: int64, UNVERIFIED: int64>
  child 0, APPROVED: int64
  child 1, REVIEW: int64
  child 2, UNAVAILABLE: int64
  child 3, UNVERIFIED: int64
to
{'report_id': Value('string'), 'company': Value('string'), 'supplier': Value('string'), 'currency': Value('string'), 'generated_at': Value('timestamp[s]'), 'items': List({'sku': Value('string'), 'product_name': Value('string'), 'category': Value('string'), 'reference_price_cents': Value('int64'), 'current_price_cents': Value('int64'), 'availability': Value('string'), 'price_source': Value('string'), 'decision': Value('string')}), 'summary': {'APPROVED': Value('int64'), 'REVIEW': Value('int64'), 'UNAVAILABLE': Value('int64'), 'UNVERIFIED': 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
              registry: string
              batch_id: string
              status: string
              report_file: string
              submitted_at: timestamp[s]
              currency: string
              items: list<item: struct<sku: string, product_name: string, category: string, reference_price_cents: int64, (... 91 chars omitted)
                child 0, item: struct<sku: string, product_name: string, category: string, reference_price_cents: int64, current_pr (... 79 chars omitted)
                    child 0, sku: string
                    child 1, product_name: string
                    child 2, category: string
                    child 3, reference_price_cents: int64
                    child 4, current_price_cents: int64
                    child 5, availability: string
                    child 6, price_source: string
                    child 7, decision: string
              company: string
              report_id: string
              supplier: string
              generated_at: timestamp[s]
              summary: struct<APPROVED: int64, REVIEW: int64, UNAVAILABLE: int64, UNVERIFIED: int64>
                child 0, APPROVED: int64
                child 1, REVIEW: int64
                child 2, UNAVAILABLE: int64
                child 3, UNVERIFIED: int64
              to
              {'report_id': Value('string'), 'company': Value('string'), 'supplier': Value('string'), 'currency': Value('string'), 'generated_at': Value('timestamp[s]'), 'items': List({'sku': Value('string'), 'product_name': Value('string'), 'category': Value('string'), 'reference_price_cents': Value('int64'), 'current_price_cents': Value('int64'), 'availability': Value('string'), 'price_source': Value('string'), 'decision': Value('string')}), 'summary': {'APPROVED': Value('int64'), 'REVIEW': Value('int64'), 'UNAVAILABLE': Value('int64'), 'UNVERIFIED': Value('int64')}}
              because column names don't match

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Derived: Quarterly Review Trend Report

Quarterly trend report derived from product review data.

Attribution & Redistribution

This dataset is derived from the following upstream source(s):

Upstream Source Repository License
github_fetch_huggingface_terminal_9046_nxauzm_upstream_product_reviews TianfuXinqu/github_fetch_huggingface_terminal_9046_nxauzm_upstream_product_reviews cc-by-nc-4.0

Redistribution is permitted under the cc-by-nc-4.0 license. Attribution to the upstream source(s) is required when redistributing this dataset.

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