Datasets:

THULab
/

spx

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 68, 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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S&P 500 Index History (TsFile format)

This dataset contains the historical S&P 500 index observations published in the source repository. Each dated row provides open, high, low, close, adjusted-close, and volume values for time-series forecasting and tabular analysis.

Modalities: Time-series

Source and scale

Original dataset: misikoff/SPX
Source revision: 498783fd0df5ad1f13c98e42329c60b8f8f9c6c1
Source file: ^SPX.csv (CSV)
Converted scale: 24,167 observations in one TsFile table.
Observed date range: 1928-01-03 through 2024-03-15.
Source split: one table; no validation or test split is defined.

TsFile schema

Column	Role	TsFile type	Source meaning
Time	TIME	INT64 (ms)	Source `Date`, parsed at UTC midnight
open	FIELD	DOUBLE	Opening index value
high	FIELD	DOUBLE	Highest index value
low	FIELD	DOUBLE	Lowest index value
close	FIELD	DOUBLE	Closing index value
adj_close	FIELD	DOUBLE	Adjusted closing index value
volume	FIELD	INT64	Source volume value

There are no TAG columns because the source contains one index series.

Conversion notes

Date is represented losslessly as integer-millisecond Time; the redundant source date text is not duplicated as a FIELD.
Source measurement names are normalized to lowercase TsFile identifiers; Adj Close becomes adj_close.
All 24,167 rows and all six measurements are retained. The conversion does not infer a market-data provider or provenance beyond the source card.

Files and usage

spx.tsfile

from tsfile import TsFileReader

with TsFileReader("spx.tsfile") as reader:
    table = next(iter(reader.get_all_table_schemas()))
    with reader.query_table(table, ["close", "volume"], batch_size=1024) as result:
        batch = result.read_arrow_batch()
        if batch is not None:
            print(batch.to_pandas().head())

License

The source dataset is licensed under the MIT License.

Usage

Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:

from pathlib import Path
from tsfile import TsFileReader

path = Path("spx.tsfile")
with TsFileReader(str(path)) as reader:
    schemas = reader.get_all_table_schemas()
    print("tables:", list(schemas))
    table_name = next(iter(schemas))
    table = schemas[table_name]
    columns = [column.get_column_name() for column in table.get_columns()]
    print("columns:", columns)
    field_names = [
        column.get_column_name()
        for column in table.get_columns()
        if column.get_column_name() not in {"Time", "time"}
    ]
    if field_names:
        with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
            batch = result.read_arrow_batch()
            if batch is not None:
                print(batch.to_pandas().head())

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