Datasets:

THULab
/

freshretailnet_lt

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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FreshRetailNet-LT (TsFile)

Apache TsFile version of Dingdong-Inc/FreshRetailNet-LT.

Overview

FreshRetailNet-LT is the long-tail release of the FreshRetailNet benchmark for censored demand estimation in fresh retail: more than 20K store-product 90-day series of detailed hourly sales from fresh-retail stores, with organically occurring stockout events annotated. It keeps the same record layout as FreshRetailNet-50K (7 entity ids, dt, hours_sale, hours_stock_status, weather and flags).

Rows: train 7,869,549 + eval 70,000 daily store-product records.
Each record carries the 24 hourly sale values (hours_sale) and the 24 hourly stock-status flags (hours_stock_status) of that day.

Schema (TsFile structure)

Time (INT64, milliseconds) — dt (day) at midnight UTC-naive.
city_id, store_id, management_group_id, first_category_id, second_category_id, third_category_id, product_id (TAG, STRING) — the retail entity; query one series with WHERE store_id='..' AND product_id='..'.
hours_sale_00..hours_sale_23 (FIELD, FLOAT) — hourly sales of the day.
hours_stock_status_00..hours_stock_status_23 (FIELD, FLOAT) — hourly stock status (0/1 flags).
sale_amount, discount, precpt, avg_temperature, avg_humidity, avg_wind_level (FIELD, DOUBLE)
stock_hour6_22_cnt, activity_flag, holiday_flag (FIELD, INT64)

The 24-length vectors are flattened losslessly to scalar columns; no source column is dropped. train and eval are separate TsFile sets (freshretailnet_lt_train*.tsfile, freshretailnet_lt_eval*.tsfile).

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("freshretailnet_lt_eval_1.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())

Source & license

Original dataset: https://huggingface.co/datasets/Dingdong-Inc/FreshRetailNet-LT
License: CC-BY-4.0

Downloads last month: 59

Total file size:

778 MB