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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
date: timestamp[s]
timestamp: string
index: struct<breadth: double, geoRisk: int64, activity: int64, disagreement: int64>
child 0, breadth: double
child 1, geoRisk: int64
child 2, activity: int64
child 3, disagreement: int64
traditional: list<item: struct<price: double, symbol: string, changePct: double>>
child 0, item: struct<price: double, symbol: string, changePct: double>
child 0, price: double
child 1, symbol: string
child 2, changePct: double
topics: list<item: null>
child 0, item: null
topEdges: list<item: null>
child 0, item: null
divergences: list<item: struct<description: string, implication: string, affectedTickers: list<item: string>>>
child 0, item: struct<description: string, implication: string, affectedTickers: list<item: string>>
child 0, description: string
child 1, implication: string
child 2, affectedTickers: list<item: string>
child 0, item: string
markdown: string
markdownTokenEstimate: int64
backfilled: bool
to
{'date': Value('timestamp[s]'), 'timestamp': Value('string'), 'index': {'uncertainty': Value('int64'), 'geopolitical': Value('int64'), 'momentum': Value('float64')}, 'traditional': List({'symbol': Value('string'), 'price': Value('float64'), 'changePct': Value('float64')}), 'topics': List({'name': Value('string'), 'movers': List({'title': Value('string'), 'ticker': Value('string'), 'price': Value('float64'), 'delta': Value('int64'), 'volume': Value('float64'), 'venue': Value('string'), 'isAnchor': Value('bool')}), 'totalChanges': Value('int64')}), 'topEdges': List({'title': Value('string'), 'edge': Value('int64'), 'direction': Value('string'), 'price': Value('int64')}), 'divergences': List({'description': Value('string')}), 'markdown': Value('string'), 'markdownTokenEstimate': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
date: timestamp[s]
timestamp: string
index: struct<breadth: double, geoRisk: int64, activity: int64, disagreement: int64>
child 0, breadth: double
child 1, geoRisk: int64
child 2, activity: int64
child 3, disagreement: int64
traditional: list<item: struct<price: double, symbol: string, changePct: double>>
child 0, item: struct<price: double, symbol: string, changePct: double>
child 0, price: double
child 1, symbol: string
child 2, changePct: double
topics: list<item: null>
child 0, item: null
topEdges: list<item: null>
child 0, item: null
divergences: list<item: struct<description: string, implication: string, affectedTickers: list<item: string>>>
child 0, item: struct<description: string, implication: string, affectedTickers: list<item: string>>
child 0, description: string
child 1, implication: string
child 2, affectedTickers: list<item: string>
child 0, item: string
markdown: string
markdownTokenEstimate: int64
backfilled: bool
to
{'date': Value('timestamp[s]'), 'timestamp': Value('string'), 'index': {'uncertainty': Value('int64'), 'geopolitical': Value('int64'), 'momentum': Value('float64')}, 'traditional': List({'symbol': Value('string'), 'price': Value('float64'), 'changePct': Value('float64')}), 'topics': List({'name': Value('string'), 'movers': List({'title': Value('string'), 'ticker': Value('string'), 'price': Value('float64'), 'delta': Value('int64'), 'volume': Value('float64'), 'venue': Value('string'), 'isAnchor': Value('bool')}), 'totalChanges': Value('int64')}), 'topEdges': List({'title': Value('string'), 'edge': Value('int64'), 'direction': Value('string'), 'price': Value('int64')}), 'divergences': List({'description': Value('string')}), 'markdown': Value('string'), 'markdownTokenEstimate': Value('int64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
World State Daily
Daily end-of-day world state snapshots from Kalshi + Polymarket. Each JSON file captures consensus probabilities across tens of thousands of prediction markets, the SF Index (disagreement, geo-risk, breadth, activity), top edges, divergences, and a markdown summary.
License and Use
This dataset is released under Creative Commons Attribution 4.0 International (CC-BY-4.0; https://creativecommons.org/licenses/by/4.0/). You may use it freely for personal, research, educational, and commercial purposes — including training, evaluating, and fine-tuning machine-learning models. Attribution is required when the dataset is redistributed in substantially its original form or cited in published work; credit as "SimpleFunctions (simplefunctions.dev)".
Additional terms apply: you may not re-host this dataset, in whole or in substantial part, as an API or service that functionally substitutes for a SimpleFunctions endpoint. See Terms §13.2 at https://simplefunctions.dev/terms.
Provenance, update cadence, and schema are documented below.
Update cadence
Daily at 23:50 UTC.
Provenance
Source: https://simplefunctions.dev Generator: SimpleFunctions public data pipeline Contact: patrick@simplefunctions.dev
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