refactor(imports): conditionally import pandas based on availability

src/lerobot/rewards/sarm/rabc.py

@@ -30,14 +30,20 @@ See: https://arxiv.org/abs/2509.25358 for the SARM paper.
 
 import logging
 from pathlib import Path
+from typing import TYPE_CHECKING
 
 import numpy as np
-import pandas as pd
 import torch
 from huggingface_hub import hf_hub_download
 
+from lerobot.utils.import_utils import _pandas_available
 from lerobot.utils.sample_weighting import SampleWeighter
 
+if TYPE_CHECKING or _pandas_available:
+    import pandas as pd
+else:
+    pd = None  # type: ignore[assignment]
+
 
 def resolve_hf_path(path: str | Path) -> Path:
     """Resolve a path that may be a HuggingFace URL (hf://datasets/...) to a local path."""

tests/utils/test_sample_weighting.py

@@ -19,6 +19,9 @@
 from unittest.mock import Mock
 
 import pytest
+
+pytest.importorskip("pandas", reason="pandas is required (install lerobot[dataset])")
+
 import torch
 
 from lerobot.utils.sample_weighting import (