"""MacroLens dataloader: canonical sample budgets + index generators.

Sits between the immutable benchmark artifacts (`data_small_caps/benchmark/`)
and the family runners (`baselines/`). Owns:

- `budgets.EVAL_N_PER_TASK`, `budgets.TRAIN_N_PER_TASK`, `budgets.SEED`:
  the canonical sample budgets per task. Single source of truth.
- `canonical_indices.get_canonical_indices(task, split)`: deterministic,
  stratified index generator with on-disk cache. Same indices for every
  method, so cross-method comparison on each task is fair.

Cache layout: `experiments/cache/canonical_indices/<key>/<split>_<task>.parquet`
where `<key>` encodes (n_eval, n_train, seed, stratifier_version).
Changing any cache-key dimension produces a new cache directory; the
immutable benchmark artifacts under `data_small_caps/` are NEVER touched
(the cache lives experiment-side, not in the dataset tree).
"""

from .budgets import (
    EVAL_N_PER_TASK,
    TRAIN_N_PER_TASK,
    SEED,
    STRATIFIER_VERSION,
    cache_key,
)
from .canonical_indices import get_canonical_indices, build_all

__all__ = [
    "EVAL_N_PER_TASK",
    "TRAIN_N_PER_TASK",
    "SEED",
    "STRATIFIER_VERSION",
    "cache_key",
    "get_canonical_indices",
    "build_all",
]