Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<gameMap: string, difficulty: string, donateGold: bool, donateTroops: bool, gameType: string, gameMode: string, gameMapSize: string, publicGameModifiers: string, nations: string, bots: int64, infiniteGold: bool, infiniteTroops: bool, instantBuild: bool, randomSpawn: bool, maxPlayers: int64, spawnImmunityDuration: int64, disabledUnits: list<item: null>, startingGold: int64, disableClanTags: bool>
to
{'gameMap': Value('string'), 'difficulty': Value('string'), 'donateGold': Value('bool'), 'donateTroops': Value('bool'), 'gameType': Value('string'), 'gameMode': Value('string'), 'gameMapSize': Value('string'), 'publicGameModifiers': Json(decode=True), 'nations': Value('string'), 'bots': Value('int64'), 'infiniteGold': Value('bool'), 'infiniteTroops': Value('bool'), 'instantBuild': Value('bool'), 'randomSpawn': Value('bool'), 'maxPlayers': Value('int64'), 'spawnImmunityDuration': Value('int64'), 'disabledUnits': List(Value('null')), 'disableClanTags': Value('bool')}
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 2059, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
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<gameMap: string, difficulty: string, donateGold: bool, donateTroops: bool, gameType: string, gameMode: string, gameMapSize: string, publicGameModifiers: string, nations: string, bots: int64, infiniteGold: bool, infiniteTroops: bool, instantBuild: bool, randomSpawn: bool, maxPlayers: int64, spawnImmunityDuration: int64, disabledUnits: list<item: null>, startingGold: int64, disableClanTags: bool>
to
{'gameMap': Value('string'), 'difficulty': Value('string'), 'donateGold': Value('bool'), 'donateTroops': Value('bool'), 'gameType': Value('string'), 'gameMode': Value('string'), 'gameMapSize': Value('string'), 'publicGameModifiers': Json(decode=True), 'nations': Value('string'), 'bots': Value('int64'), 'infiniteGold': Value('bool'), 'infiniteTroops': Value('bool'), 'instantBuild': Value('bool'), 'randomSpawn': Value('bool'), 'maxPlayers': Value('int64'), 'spawnImmunityDuration': Value('int64'), 'disabledUnits': List(Value('null')), 'disableClanTags': Value('bool')}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.
OpenFront.io archived human games
285 real public multiplayer games of OpenFront.io (10-116 humans per lobby, all maps, FFA + team modes), pulled from the game's public archive API and replayed through the deterministic engine (openfrontio/OpenFrontIO) to regenerate full state trajectories. ~420k snapshots at 10-tick (1s) cadence.
Every game passed the engine's embedded state-hash verification during replay (games that desynced were discarded), so snapshots are bit-exact reconstructions of what the players actually saw. Player identities are stripped by the API; usernames remain.
Generated by and documented at github.com/djmango/openfront-ai.
Contents
maps/<map>.tar— replayed snapshots, one game directory per game, same format v3 as openfront-snapshots:terrain.bin,states/t<tick>.bin.gz(tile ownership grid),states/t<tick>.json.gz(players, diplomacy, units, attacks),meta.json(+gitCommit,hashesChecked,numHumans).records/<gitCommit>/<gameID>.json.gz— the raw archived game records: full per-turn human intent logs (every attack, boat, build, nuke, alliance, betrayal, donation, emote). Replay them withdatagen/replay.tsfrom the repo (engine checked out at the matching commit), or use them directly for behavior cloning.
Why
Bot self-play data (openfront-snapshots) covers the state space thinly: built-in nations rarely ally, betray, nuke, or invade by sea. Human games supply realistic territory shapes and the full diplomatic/military action distribution — both better observation coverage for encoders and (state, human action) pairs for imitation pretraining.
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