The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<0x1000000000000000000000000000000000000001: struct<nonce: string, balance: string, code: string, storage: struct<>>, 0x2000000000000000000000000000000000000002: struct<nonce: string, balance: string, code: string, storage: struct<>>>
to
{'0x3000000000000000000000000000000000000003': {'nonce': Value('string'), 'balance': Value('string'), 'code': Value('string'), 'storage': {}}}
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/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, 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 2303, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2149, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<0x1000000000000000000000000000000000000001: struct<nonce: string, balance: string, code: string, storage: struct<>>, 0x2000000000000000000000000000000000000002: struct<nonce: string, balance: string, code: string, storage: struct<>>>
to
{'0x3000000000000000000000000000000000000003': {'nonce': Value('string'), 'balance': Value('string'), 'code': Value('string'), 'storage': {}}}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Kaysentinel Fixtures
Curated differential-testing fixtures for the Kaysentinel project. Each fixture describes a pre-state, a transaction, and the expected post-execution behavior that a compliant Geth-side and Reth-side SSR extractor must agree on (see the main repo's docs/differential_testing.md for the design behind this).
Status
These fixtures are not yet verified against a real client. expected_ssr_root is null in every file — that field can only be filled in once a Geth or Reth extractor actually exists (Phase 2 of the implementation roadmap). Until then, treat the expected_* fields other than the root as the human-written spec of correct behavior, not as machine-verified ground truth.
Configs
eip1153_tstore— transient storage (EIP-1153) edge cases: reentrancy rollback, out-of-gas mid-sequence.eip6780_selfdestruct— post-Cancun SELFDESTRUCT lifecycle cases (EIP-6780): same-tx creation vs. pre-existing contract.
Load with the datasets library:
from datasets import load_dataset
ds = load_dataset("Sahek/kaysentinel-fixtures", "eip1153_tstore")
Provenance
These fixtures are original, hand-written test cases in Kaysentinel's own JSON schema. They're inspired by scenario categories covered in the real ethereum/execution-spec-tests project (e.g. its tests/cancun/eip1153_tstore suite and EIP-6780 reentrancy/self-destruct coverage) but are not copies of that repo's fixtures — EEST fixtures are generated by its own Python fill framework into a different, client-oriented format. If you need canonical, client-tested vectors, use EEST directly.
Planned but not yet added (see main repo roadmap, Phase 4)
fuzz_seeds/— high-entropy multi-account fuzzing inputs, for once two real extractors exist to compareproduction_traces/— real historical block extractions (e.g. viacryo), for extraction performance benchmarking
Both depend on Phase 1/2 (SSZ schema + extractors) being built first, so they're intentionally not included yet.
License
MIT — see LICENSE.
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