hexo-bootstrap-corpus

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
game_hash: string
moves: list<item: list<item: int64>>
  child 0, item: list<item: int64>
      child 0, item: int64
winner: int64
source: string
elo: list<item: int64>
  child 0, item: int64
includes_metadata: bool
sha256: string
winner_convention: string
input_dirs: list<item: string>
  child 0, item: string
source_filter: string
schema_version: int64
file: string
created_at: string
coordinate_system: string
format: string
name: string
n_games: int64
bytes: int64
n_duplicates_dropped: int64
encoding: string
dedup_key: string
to
{'name': Value('string'), 'schema_version': Value('int64'), 'format': Value('string'), 'encoding': Value('string'), 'n_games': Value('int64'), 'n_duplicates_dropped': Value('int64'), 'dedup_key': Value('string'), 'winner_convention': Value('string'), 'coordinate_system': Value('string'), 'source_filter': Value('string'), 'includes_metadata': Value('bool'), 'input_dirs': List(Value('string')), 'file': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string'), 'created_at': Value('string')}
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 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, 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 130, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              game_hash: string
              moves: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              winner: int64
              source: string
              elo: list<item: int64>
                child 0, item: int64
              includes_metadata: bool
              sha256: string
              winner_convention: string
              input_dirs: list<item: string>
                child 0, item: string
              source_filter: string
              schema_version: int64
              file: string
              created_at: string
              coordinate_system: string
              format: string
              name: string
              n_games: int64
              bytes: int64
              n_duplicates_dropped: int64
              encoding: string
              dedup_key: string
              to
              {'name': Value('string'), 'schema_version': Value('int64'), 'format': Value('string'), 'encoding': Value('string'), 'n_games': Value('int64'), 'n_duplicates_dropped': Value('int64'), 'dedup_key': Value('string'), 'winner_convention': Value('string'), 'coordinate_system': Value('string'), 'source_filter': Value('string'), 'includes_metadata': Value('bool'), 'input_dirs': List(Value('string')), 'file': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string'), 'created_at': Value('string')}
              because column names don't match

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Hexo Human Corpus

Encoding-free corpus of 6,902 decisive human Hex Tac Toe games — hexagonal grid, six-in-a-row to win (player 1 opens with 1 move, then both players play 2 moves per turn; the board is theoretically infinite).

Each line is one game as a raw axial move list + outcome. Nothing about any neural-network encoding is baked in — no planes, no fixed board size, no action space. Read it with the stdlib json module and build whatever representation you want.

Files

file	description
`hexo_human_corpus.jsonl`	the corpus — one game per line
`SCHEMA.md`	full per-line schema + conventions
`dataset_metadata.json`	provenance: counts, sha256, source filter

Schema

One JSON object per line:

{"game_hash":"0f8c6bdfc55e7f6f","moves":[[0,0],[2,-2],[-3,3]],"winner":1,"source":"human","elo":[898,955]}

field	type	meaning
`game_hash`	string (16 hex)	SHA-256 of the move sequence — stable content/dedup key
`moves`	array of `[x, y]`	axial hex coords `(x,y)=(q,r)`, in play order
`winner`	`1` or `-1`	`1` = first player (X) wins, `-1` = second player (O)
`source`	string	`"human"`
`elo`	`[int\|null, int\|null]`	`[elo_p1, elo_p2]`

Conventions

Axial hex coordinates (x, y); the board is infinite so values can be negative. The first player's forced opener is always (0, 0).
Replay moves in order to reconstruct any board state.
Only decisive (six-in-a-row) games are included — there are no draws.

Usage

import json

games = [json.loads(line) for line in open("hexo_human_corpus.jsonl")]
print(len(games), "games")          # 6902
g = games[0]
print(g["moves"], g["winner"])      # [[0,0], [2,-2], ...]  1

Provenance

Rated human games filtered to: rated, ≥20 moves, decisive by six-in-a-row. Per-game elo is each player's rating at game time. Games are anonymised (player ids dropped; only relative Elo retained). See dataset_metadata.json for the exact sha256 and counts.

License: MIT.

Downloads last month: 31

Total file size:

3.7 MB