Datasets:

AlphaDojo
/

dojo_benchmark_kline

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
symbol: large_string
kline_t: large_string
bar_time: timestamp[ns]
open: double
high: double
low: double
close: double
vol: double
amount: double
change_p: double
tr: double
adj_factor_cum: int64
dividends: int64
splits: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1847
to
{'symbol': Value('large_string'), 'market': Value('large_string'), 'name_zh': Value('large_string'), 'name_en': Value('large_string'), 'sort_order': Value('int64')}
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/parquet/parquet.py", line 220, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, 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
              symbol: large_string
              kline_t: large_string
              bar_time: timestamp[ns]
              open: double
              high: double
              low: double
              close: double
              vol: double
              amount: double
              change_p: double
              tr: double
              adj_factor_cum: int64
              dividends: int64
              splits: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1847
              to
              {'symbol': Value('large_string'), 'market': Value('large_string'), 'name_zh': Value('large_string'), 'name_en': Value('large_string'), 'sort_order': Value('int64')}
              because column names don't match

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dojo_benchmark_kline — Benchmark Index Bars

Overview

Daily OHLCV for major broad and representative indices across US, CN, and HK (e.g. ^SPX, ^HSI, 000300.SS). Each row is one index on one trade date.

Files

File	Description
`data.parquet`	Index daily bars

Key Fields

Field	Description
`symbol`	Index code (e.g. `^SPX`, `000300.SS`)
`kline_t`	Bar interval; `"1D"` for daily bars
`bar_time`	Trade date
`open` / `high` / `low` / `close`	OHLC
`vol` / `amount`	Volume / turnover
`change_p`	Percent change

Scale (reference)

~4,650 rows (multiple indices × ~580 sessions; exact symbol set is defined by rows in data.parquet).

Related Datasets

dojo_stock_kline — same schema, equity symbols
dojo_sector_precomputed — sector-level indices complement broad benchmarks

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