fix(python): Fix fill null types

py-polars/polars/lazyframe/frame.py

@@ -5667,15 +5667,15 @@ def fill_null(
         │ 4   ┆ 13.0 │
         └─────┴──────┘
         """
-        dtypes: Sequence[PolarsDataType]
+        dtypes: Sequence[PolarsDataType] | None
 
         if value is not None:
 
             def infer_dtype(value: Any) -> PolarsDataType:
                 return next(iter(self.select(value).collect_schema().values()))
 
             if isinstance(value, pl.Expr):
-                dtypes = [infer_dtype(value)]
+                dtypes = None
             elif isinstance(value, bool):
                 dtypes = [Boolean]
             elif matches_supertype and isinstance(value, (int, float)):
@@ -5707,9 +5707,12 @@ def infer_dtype(value: Any) -> PolarsDataType:
                 dtypes = [String, Categorical]
             else:
                 # fallback; anything not explicitly handled above
-                dtypes = [infer_dtype(F.lit(value))]
+                dtypes = None
 
-            return self.with_columns(F.col(dtypes).fill_null(value, strategy, limit))
+            if dtypes:
+                return self.with_columns(
+                    F.col(dtypes).fill_null(value, strategy, limit)
+                )
 
         return self.select(F.all().fill_null(value, strategy, limit))
 

py-polars/tests/unit/operations/test_fill_null.py

@@ -35,3 +35,17 @@ def test_fill_null_f32_with_lit() -> None:
     # ensure the literal integer does not upcast the f32 to an f64
     df = pl.DataFrame({"a": [1.1, 1.2]}, schema=[("a", pl.Float32)])
     assert df.fill_null(value=0).dtypes == [pl.Float32]
+
+
+def test_fill_null_lit_() -> None:
+    df = pl.DataFrame(
+        {
+            "a": pl.Series([1, None], dtype=pl.Int32),
+            "b": pl.Series([None, 2], dtype=pl.UInt32),
+            "c": pl.Series([None, 2], dtype=pl.Int64),
+        }
+    )
+    assert (
+        df.fill_null(pl.lit(0)).select(pl.all().null_count()).transpose().sum().item()
+        == 0
+    )