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SHARProduction
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production-numeric-safety-fixtures

Tags:
numerical-safety
video-production
production-tooling
synthetic-data
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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
id: string
base_input: struct<durationSeconds: int64, tracks: list<item: struct<gainDb: int64>>, frameRate: int64, mix: str (... 69 chars omitted)
  child 0, durationSeconds: int64
  child 1, tracks: list<item: struct<gainDb: int64>>
      child 0, item: struct<gainDb: int64>
          child 0, gainDb: int64
  child 2, frameRate: int64
  child 3, mix: struct<offset: int64>
      child 0, offset: int64
  child 4, delivery: struct<audio: struct<loudness: int64>>
      child 0, audio: struct<loudness: int64>
          child 0, loudness: int64
mutations: list<item: struct<path: string, value_type: string>>
  child 0, item: struct<path: string, value_type: string>
      child 0, path: string
      child 1, value_type: string
expected_valid: bool
expected_issues: list<item: struct<path: string, value: string>>
  child 0, item: struct<path: string, value: string>
      child 0, path: string
      child 1, value: string
code_license: string
data_license: string
title: string
all_synthetic: bool
homepage: string
description: string
publisher: string
to
{'title': Value('string'), 'description': Value('string'), 'data_license': Value('string'), 'code_license': Value('string'), 'publisher': Value('string'), 'homepage': Value('string'), 'all_synthetic': Value('bool')}
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
              id: string
              base_input: struct<durationSeconds: int64, tracks: list<item: struct<gainDb: int64>>, frameRate: int64, mix: str (... 69 chars omitted)
                child 0, durationSeconds: int64
                child 1, tracks: list<item: struct<gainDb: int64>>
                    child 0, item: struct<gainDb: int64>
                        child 0, gainDb: int64
                child 2, frameRate: int64
                child 3, mix: struct<offset: int64>
                    child 0, offset: int64
                child 4, delivery: struct<audio: struct<loudness: int64>>
                    child 0, audio: struct<loudness: int64>
                        child 0, loudness: int64
              mutations: list<item: struct<path: string, value_type: string>>
                child 0, item: struct<path: string, value_type: string>
                    child 0, path: string
                    child 1, value_type: string
              expected_valid: bool
              expected_issues: list<item: struct<path: string, value: string>>
                child 0, item: struct<path: string, value: string>
                    child 0, path: string
                    child 1, value: string
              code_license: string
              data_license: string
              title: string
              all_synthetic: bool
              homepage: string
              description: string
              publisher: string
              to
              {'title': Value('string'), 'description': Value('string'), 'data_license': Value('string'), 'code_license': Value('string'), 'publisher': Value('string'), 'homepage': Value('string'), 'all_synthetic': Value('bool')}
              because column names don't match

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SHAR Production Numeric Safety Fixtures

Explicitly synthetic, JSON-safe fixtures for reproducing non-finite number tests in memory. JSON cannot encode NaN, Infinity or -Infinity, so each record stores a finite JSON base input and an explicit typed mutation. The paired MIT tool is production-numeric-safety-guard.

SHAR Production is an AI-hybrid video production studio: https://sharprod.com/
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