Datasets:

azithromycin
/

williamdgomez_SNOW.SB

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
              tsfile.exceptions.FileOpenError: 28: 
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
                  scan = self._scan_metadata(all_files)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
                  with self._open_reader(file) as reader:
                       ~~~~~~~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
                  return TsFileReader(file)
                File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
              SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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SNOW.SB TsFile

This repository is an Apache TsFile conversion of the LeRobot dataset williamdgomez/SNOW.SB. The original Hugging Face repository and its commit history identify williamdgomez as the dataset author/uploader. The source dataset was created with LeRobot v3.0 for the lekiwi_client robot.

Source Dataset

Dataset: williamdgomez/SNOW.SB
Author/uploader: williamdgomez
License: Apache-2.0
Task: Pick up the block and place it in the bin
Split: train (0:91)
Sampling rate: 24 fps
Scale: 91 episodes, 73,578 frames, 1 task
Source data shards: 91 Parquet files under data/chunk-000/file-*.parquet
Source video files: 273 MP4 files, 91 per camera stream

The source video streams are stored at videos/:

videos/observation.images.front/chunk-000/file-{file_index:03d}.mp4
videos/observation.images.wrist/chunk-000/file-{file_index:03d}.mp4
videos/observation.images.top/chunk-000/file-{file_index:03d}.mp4

Videos are not included in this TsFile repository. They remain available in the original Hugging Face dataset and can be aligned with rows using episode_index, frame_index, and the source meta/episodes offsets.

Converted Files

TsFile: data/williamdgomez_snow_sb.tsfile
Table: williamdgomez_snow_sb
Rows: 73,578
Devices: 91 (episode_index x task_index)
Time precision: milliseconds
Metadata: meta/ mirrors the source metadata; meta/info.json records the TsFile path and conversion mapping.

Schema

Time is round(timestamp * 1000) and is stored in milliseconds. The source timestamp is dropped after this conversion because it is exactly the seconds representation of Time; Time restarts at zero for each episode.

Column group	TsFile columns	Type / role
Time	`Time`	INT64/TIMESTAMP, TIME
Tags	`episode_index`, `task_index`	TAG/device segments
Frame metadata	`frame_index`, `sample_index`	INT64 FIELD; `sample_index` is source `index`
Action	`action_0` ... `action_8`	FLOAT FIELD, flattened from `action[9]`
Observation	`observation_state_0` ... `observation_state_8`	FLOAT FIELD, flattened from `observation.state[9]`

Vector names preserve their source prefixes (. becomes _) and append a zero-based element index. The three video features (observation.images.front, .wrist, .top) are omitted from the TsFile because TsFile stores the numeric time-series table while the original MP4 files remain at the source URL.

Encoding and Compression

The local conversion used the type-aware TsFile writer profile requested for this dataset:

FLOAT/DOUBLE: GORILLA with LZ4
INT32/INT64 and Time: TS_2DIFF with LZ4
BOOLEAN (if present): RLE with LZ4
TAG columns: TsFile table/device TAG mechanism

The generated TsFile is 1,456,157 bytes. The merged staged Parquet is 1,235,578 bytes, and the 91 source Parquet shards total 3,152,836 bytes.

Validation

Apache TsFile Python SDK readback succeeded. The TsFile metadata row count and query readback both equal the staged Parquet count: 73,578 rows. All 91 episode devices have monotonic Time values with no duplicate (episode_index, task_index, Time) keys.

Usage

from tsfile import TsFileReader

reader = TsFileReader("data/williamdgomez_snow_sb.tsfile")
table = reader.get_all_table_schemas()["williamdgomez_snow_sb"]
columns = [c.get_column_name() for c in table.get_columns() if c.get_column_name() != "Time"]

with reader.query_table("williamdgomez_snow_sb", columns, batch_size=65536) as result:
    batch = result.read_arrow_batch()