Add tests and fixes for Daft integration

pyiceberg/table/__init__.py

@@ -1025,6 +1025,16 @@ def __repr__(self) -> str:
         result_str = f"{table_name}(\n  {schema_str}\n),\n{partition_str},\n{sort_order_str},\n{snapshot_str}"
         return result_str
 
+    def to_daft(self) -> daft.DataFrame:
+        """Read a Daft DataFrame lazily from this Iceberg table.
+
+        Returns:
+            daft.DataFrame: Unmaterialized Daft Dataframe created from the Iceberg table
+        """
+        import daft
+
+        return daft.read_iceberg(self)
+
 
 class StaticTable(Table):
     """Load a table directly from a metadata file (i.e., without using a catalog)."""
@@ -1382,16 +1392,6 @@ def to_ray(self) -> ray.data.dataset.Dataset:
 
         return ray.data.from_arrow(self.to_arrow())
 
-    def to_daft(self) -> daft.DataFrame:
-        """Read a Daft DataFrame lazily from this Iceberg table.
-
-        Returns:
-            daft.DataFrame: Unmaterialized Daft Dataframe created from the Iceberg table
-        """
-        import daft
-
-        return daft.read_iceberg(self)
-
 
 class MoveOperation(Enum):
     First = 1

tests/integration/test_reads.py

@@ -178,6 +178,28 @@ def test_pyarrow_limit(catalog: Catalog) -> None:
     assert len(full_result) == 10
 
 
+@pytest.mark.integration
+@pytest.mark.filterwarnings("ignore")
+@pytest.mark.parametrize('catalog', [pytest.lazy_fixture('catalog_hive'), pytest.lazy_fixture('catalog_rest')])
+def test_daft_nan(catalog: Catalog) -> None:
+    table_test_null_nan_rewritten = catalog.load_table("default.test_null_nan_rewritten")
+    df = table_test_null_nan_rewritten.to_daft()
+    assert df.count_rows() == 3
+    assert math.isnan(df.to_pydict()["col_numeric"][0])
+
+
+@pytest.mark.integration
+@pytest.mark.parametrize('catalog', [pytest.lazy_fixture('catalog_hive'), pytest.lazy_fixture('catalog_rest')])
+def test_daft_nan_rewritten(catalog: Catalog) -> None:
+    table_test_null_nan_rewritten = catalog.load_table("default.test_null_nan_rewritten")
+    df = table_test_null_nan_rewritten.to_daft()
+    df = df.where(df["col_numeric"].float.is_nan())
+    df = df.select("idx", "col_numeric")
+    assert df.count_rows() == 1
+    assert df.to_pydict()["idx"][0] == 1
+    assert math.isnan(df.to_pydict()["col_numeric"][0])
+
+
 @pytest.mark.integration
 @pytest.mark.filterwarnings("ignore")
 @pytest.mark.parametrize('catalog', [pytest.lazy_fixture('catalog_hive'), pytest.lazy_fixture('catalog_rest')])