[python-package] Separately check whether pyarrow and cffi are installed

python-package/lightgbm/basic.py

@@ -27,6 +27,7 @@
 import scipy.sparse
 
 from .compat import (
+    CFFI_INSTALLED,
     PANDAS_INSTALLED,
     PYARROW_INSTALLED,
     arrow_cffi,
@@ -1706,8 +1707,8 @@ def __pred_for_pyarrow_table(
         predict_type: int,
     ) -> Tuple[np.ndarray, int]:
         """Predict for a PyArrow table."""
-        if not PYARROW_INSTALLED:
-            raise LightGBMError("Cannot predict from Arrow without `pyarrow` installed.")
+        if not (PYARROW_INSTALLED and CFFI_INSTALLED):
+            raise LightGBMError("Cannot predict from Arrow without 'pyarrow' and 'cffi' installed.")
 
         # Check that the input is valid: we only handle numbers (for now)
         if not all(arrow_is_integer(t) or arrow_is_floating(t) or arrow_is_boolean(t) for t in table.schema.types):
@@ -2458,8 +2459,8 @@ def __init_from_pyarrow_table(
         ref_dataset: Optional[_DatasetHandle],
     ) -> "Dataset":
         """Initialize data from a PyArrow table."""
-        if not PYARROW_INSTALLED:
-            raise LightGBMError("Cannot init dataframe from Arrow without `pyarrow` installed.")
+        if not (PYARROW_INSTALLED and CFFI_INSTALLED):
+            raise LightGBMError("Cannot init Dataset from Arrow without 'pyarrow' and 'cffi' installed.")
 
         # Check that the input is valid: we only handle numbers (for now)
         if not all(arrow_is_integer(t) or arrow_is_floating(t) or arrow_is_boolean(t) for t in table.schema.types):

python-package/lightgbm/compat.py

@@ -289,7 +289,6 @@ def __init__(self, *args: Any, **kwargs: Any):
     from pyarrow import ChunkedArray as pa_ChunkedArray
     from pyarrow import Table as pa_Table
     from pyarrow import chunked_array as pa_chunked_array
-    from pyarrow.cffi import ffi as arrow_cffi
     from pyarrow.types import is_boolean as arrow_is_boolean
     from pyarrow.types import is_floating as arrow_is_floating
     from pyarrow.types import is_integer as arrow_is_integer
@@ -316,6 +315,26 @@ class pa_Table:  # type: ignore
         def __init__(self, *args: Any, **kwargs: Any):
             pass
 
+    class pa_compute:  # type: ignore
+        """Dummy class for pyarrow.compute."""
+
+        all = None
+        equal = None
+
+    pa_chunked_array = None
+    arrow_is_boolean = None
+    arrow_is_integer = None
+    arrow_is_floating = None
+
+
+"""cffi"""
+try:
+    from pyarrow.cffi import ffi as arrow_cffi
+
+    CFFI_INSTALLED = True
+except ImportError:
+    CFFI_INSTALLED = False
+
     class arrow_cffi:  # type: ignore
         """Dummy class for pyarrow.cffi.ffi."""
 
@@ -327,16 +346,6 @@ class arrow_cffi:  # type: ignore
         def __init__(self, *args: Any, **kwargs: Any):
             pass
 
-    class pa_compute:  # type: ignore
-        """Dummy class for pyarrow.compute."""
-
-        all = None
-        equal = None
-
-    pa_chunked_array = None
-    arrow_is_boolean = None
-    arrow_is_integer = None
-    arrow_is_floating = None
 
 """cpu_count()"""
 try:

tests/python_package_test/conftest.py

@@ -1,6 +1,15 @@
 import numpy as np
 import pytest
 
+import lightgbm
+
+
+@pytest.fixture(scope="function")
+def missing_module_cffi(monkeypatch):
+    """Mock 'cffi' not being importable"""
+    monkeypatch.setattr(lightgbm.compat, "CFFI_INSTALLED", False)
+    monkeypatch.setattr(lightgbm.basic, "CFFI_INSTALLED", False)
+
 
 @pytest.fixture(scope="function")
 def rng():

tests/python_package_test/test_arrow.py

@@ -454,3 +454,33 @@ def test_arrow_feature_name_manual():
     )
     booster = lgb.train({"num_leaves": 7}, dataset, num_boost_round=5)
     assert booster.feature_name() == ["c", "d"]
+
+
+def test_dataset_construction_from_pa_table_without_cffi_raises_informative_error(missing_module_cffi):
+    with pytest.raises(
+        lgb.basic.LightGBMError, match="Cannot init Dataset from Arrow without 'pyarrow' and 'cffi' installed."
+    ):
+        lgb.Dataset(
+            generate_dummy_arrow_table(),
+            label=pa.array([0, 1, 0, 0, 1]),
+            params=dummy_dataset_params(),
+        ).construct()
+
+
+def test_predicting_from_pa_table_without_cffi_raises_informative_error(missing_module_cffi):
+    data = generate_random_arrow_table(num_columns=3, num_datapoints=1_000, seed=42)
+    labels = generate_random_arrow_array(num_datapoints=data.shape[0], seed=42)
+    dataset = lgb.Dataset(
+        data.to_pandas(),
+        label=labels.to_pandas(),
+    )
+
+    with pytest.raises(
+        lgb.basic.LightGBMError, match="Cannot predict from Arrow without 'pyarrow' and 'cffi' installed."
+    ):
+        bst = lgb.train(
+            params={"num_leaves": 7, "verbose": -1},
+            train_set=dataset,
+            num_boost_round=2,
+        )
+        bst.predict(data)