Datasets:

---

sgupta15

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pcxn-explore-data

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
edges: list<item: struct<pathway_b: string, correlation: double, neg_log10_p_value: double, neg_log10_fdr:  (... 8 chars omitted)
  child 0, item: struct<pathway_b: string, correlation: double, neg_log10_p_value: double, neg_log10_fdr: double>
      child 0, pathway_b: string
      child 1, correlation: double
      child 2, neg_log10_p_value: double
      child 3, neg_log10_fdr: double
pathways: list<item: struct<pathway_id: string, pathway_name: string, edge_count: int64, edge_count_in_slice:  (... 212 chars omitted)
  child 0, item: struct<pathway_id: string, pathway_name: string, edge_count: int64, edge_count_in_slice: int64, min_ (... 200 chars omitted)
      child 0, pathway_id: string
      child 1, pathway_name: string
      child 2, edge_count: int64
      child 3, edge_count_in_slice: int64
      child 4, min_correlation: double
      child 5, max_correlation: double
      child 6, min_neg_log10_p_value: double
      child 7, max_neg_log10_p_value: double
      child 8, min_neg_log10_fdr: double
      child 9, max_neg_log10_fdr: double
      child 10, collection: string
      child 11, source_db: string
collection_summary: struct<MSigDB_C2_CP: int64>
  child 0, MSigDB_C2_CP: int64
source_file: string
tissue_id: string
total_edges: int64
pvalue_mode: string
total_pathways: int64
columns: struct<pathway_b: string, correlation: string, p_value: string, fdr: string>
  child 0, pathway_b: string
  child 1, correlation: string
  child 2, p_value: string
  child 3, fdr: string
sort_by: string
slice_format: string
generated_at: timestamp[s]
to
{'tissue_id': Value('string'), 'generated_at': Value('timestamp[s]'), 'source_file': Value('string'), 'slice_format': Value('string'), 'sort_by': Value('string'), 'pvalue_mode': Value('string'), 'columns': {'pathway_b': Value('string'), 'correlation': Value('string'), 'p_value': Value('string'), 'fdr': Value('string')}, 'total_pathways': Value('int64'), 'total_edges': Value('int64'), 'pathways': List({'pathway_id': Value('string'), 'pathway_name': Value('string'), 'edge_count': Value('int64'), 'edge_count_in_slice': Value('int64'), 'min_correlation': Value('float64'), 'max_correlation': Value('float64'), 'min_neg_log10_p_value': Value('float64'), 'max_neg_log10_p_value': Value('float64'), 'min_neg_log10_fdr': Value('float64'), 'max_neg_log10_fdr': Value('float64'), 'collection': Value('string'), 'source_db': Value('string')}), 'collection_summary': {'MSigDB_C2_CP': 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
              edges: list<item: struct<pathway_b: string, correlation: double, neg_log10_p_value: double, neg_log10_fdr:  (... 8 chars omitted)
                child 0, item: struct<pathway_b: string, correlation: double, neg_log10_p_value: double, neg_log10_fdr: double>
                    child 0, pathway_b: string
                    child 1, correlation: double
                    child 2, neg_log10_p_value: double
                    child 3, neg_log10_fdr: double
              pathways: list<item: struct<pathway_id: string, pathway_name: string, edge_count: int64, edge_count_in_slice:  (... 212 chars omitted)
                child 0, item: struct<pathway_id: string, pathway_name: string, edge_count: int64, edge_count_in_slice: int64, min_ (... 200 chars omitted)
                    child 0, pathway_id: string
                    child 1, pathway_name: string
                    child 2, edge_count: int64
                    child 3, edge_count_in_slice: int64
                    child 4, min_correlation: double
                    child 5, max_correlation: double
                    child 6, min_neg_log10_p_value: double
                    child 7, max_neg_log10_p_value: double
                    child 8, min_neg_log10_fdr: double
                    child 9, max_neg_log10_fdr: double
                    child 10, collection: string
                    child 11, source_db: string
              collection_summary: struct<MSigDB_C2_CP: int64>
                child 0, MSigDB_C2_CP: int64
              source_file: string
              tissue_id: string
              total_edges: int64
              pvalue_mode: string
              total_pathways: int64
              columns: struct<pathway_b: string, correlation: string, p_value: string, fdr: string>
                child 0, pathway_b: string
                child 1, correlation: string
                child 2, p_value: string
                child 3, fdr: string
              sort_by: string
              slice_format: string
              generated_at: timestamp[s]
              to
              {'tissue_id': Value('string'), 'generated_at': Value('timestamp[s]'), 'source_file': Value('string'), 'slice_format': Value('string'), 'sort_by': Value('string'), 'pvalue_mode': Value('string'), 'columns': {'pathway_b': Value('string'), 'correlation': Value('string'), 'p_value': Value('string'), 'fdr': Value('string')}, 'total_pathways': Value('int64'), 'total_edges': Value('int64'), 'pathways': List({'pathway_id': Value('string'), 'pathway_name': Value('string'), 'edge_count': Value('int64'), 'edge_count_in_slice': Value('int64'), 'min_correlation': Value('float64'), 'max_correlation': Value('float64'), 'min_neg_log10_p_value': Value('float64'), 'max_neg_log10_p_value': Value('float64'), 'min_neg_log10_fdr': Value('float64'), 'max_neg_log10_fdr': Value('float64'), 'collection': Value('string'), 'source_db': Value('string')}), 'collection_summary': {'MSigDB_C2_CP': Value('int64')}}
              because column names don't match