[python-package] Separately check whether `pyarrow` and `cffi` are installed (#6785)

Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

python-package/lightgbm/basic.py

@@ -27,6 +27,7 @@ import numpy as np
 import scipy.sparse
 
 from .compat import (
+    CFFI_INSTALLED,
     PANDAS_INSTALLED,
     PYARROW_INSTALLED,
     arrow_cffi,
@@ -1706,8 +1707,8 @@ class _InnerPredictor:
         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 @@ class Dataset:
         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 @@ try:
     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
@@ -316,19 +315,8 @@ except ImportError:
         def __init__(self, *args: Any, **kwargs: Any):
             pass
 
-    class arrow_cffi:  # type: ignore
-        """Dummy class for pyarrow.cffi.ffi."""
-
-        CData = None
-        addressof = None
-        cast = None
-        new = None
-
-        def __init__(self, *args: Any, **kwargs: Any):
-            pass
-
     class pa_compute:  # type: ignore
-        """Dummy class for pyarrow.compute."""
+        """Dummy class for pyarrow.compute module."""
 
         all = None
         equal = None
@@ -338,6 +326,24 @@ except ImportError:
     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."""
+
+        CData = None
+
+        def __init__(self, *args: Any, **kwargs: Any):
+            pass
+
+
 """cpu_count()"""
 try:
     from joblib import cpu_count

tests/python_package_test/conftest.py

 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 +454,32 @@ 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)
+    bst = lgb.train(
+        params={"num_leaves": 7, "verbose": -1},
+        train_set=lgb.Dataset(
+            data.to_pandas(),
+            label=labels.to_pandas(),
+        ),
+        num_boost_round=2,
+    )
+
+    with pytest.raises(
+        lgb.basic.LightGBMError, match="Cannot predict from Arrow without 'pyarrow' and 'cffi' installed."
+    ):
+        bst.predict(data)