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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
description: string
time: list<item: double>
  child 0, item: double
set_target_data: list<item: struct<head: list<item: list<item: double>>, antennas: list<item: double>, body_yaw: doub (... 27 chars omitted)
  child 0, item: struct<head: list<item: list<item: double>>, antennas: list<item: double>, body_yaw: double, check_c (... 15 chars omitted)
      child 0, head: list<item: list<item: double>>
          child 0, item: list<item: double>
              child 0, item: double
      child 1, antennas: list<item: double>
          child 0, item: double
      child 2, body_yaw: double
      child 3, check_collision: bool
move_id: string
has_audio: bool
duration_seconds: double
to
{'move_id': Value('string'), 'description': Value('string'), 'duration_seconds': Value('float64'), 'has_audio': 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 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
              description: string
              time: list<item: double>
                child 0, item: double
              set_target_data: list<item: struct<head: list<item: list<item: double>>, antennas: list<item: double>, body_yaw: doub (... 27 chars omitted)
                child 0, item: struct<head: list<item: list<item: double>>, antennas: list<item: double>, body_yaw: double, check_c (... 15 chars omitted)
                    child 0, head: list<item: list<item: double>>
                        child 0, item: list<item: double>
                            child 0, item: double
                    child 1, antennas: list<item: double>
                        child 0, item: double
                    child 2, body_yaw: double
                    child 3, check_collision: bool
              move_id: string
              has_audio: bool
              duration_seconds: double
              to
              {'move_id': Value('string'), 'description': Value('string'), 'duration_seconds': Value('float64'), 'has_audio': Value('bool')}
              because column names don't match

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local_dataset • Reachy Mini Moves

        Community-contributed Marionette recordings captured on Reachy Mini.

        - **Moves uploaded:** 3
        - **Total motion time:** 26.1 seconds
        - **Audio tracks:** 3
        - **Last updated:** 2026-06-24T13:53:55Z

        Files live under `data/` — each move ships as a JSON trajectory (Reachy Mini emotions schema) plus an optional WAV recorded directly from the robot.

        ## How this dataset was produced

        These takes were recorded with the Marionette Reachy Mini app. Pick the moves to share, set your Hugging Face username, run `huggingface-cli login` once locally, then hit **Synchronize to Hugging Face dataset** inside Marionette. The app packages the selected files, generates this README, and uploads them to `TSad33/local-dataset`.

        ## Selected moves

        | Move | Duration | Audio | Recorded at (UTC) |
        | --- | --- | --- | --- |
        | `fart` | 3.0s | Yes | 2026-06-24 13:53 |

| aallrighty | 1.6s | Yes | 2026-06-24 13:44 | | ricky-piss-excellence | 21.5s | Yes | 2026-06-24 13:47 |

        ## Reuse

        - Cite this dataset as `TSad33/local-dataset`.
        - Keep the `reachy_mini_community_moves` tag when sharing derivatives so the community can discover related sets.
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