fix: override type to NULL for None values in RowsResponse encode

_get_row_types now sets the type nibble to ValueType.NULL for None
values, matching Go's per-row type header behavior where the nibble
reflects the actual value, not the column schema. Previously, encoding
a RowsResponse with explicit column_types and None values in rows
crashed with EncodeError after the issue 094 fix.

Closes #137

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: antoineleclair

src/dqlitewire/messages/responses.py

@@ -254,14 +254,24 @@ def _get_row_types(self, row_idx: int, row: list[Any]) -> list[ValueType]:
         return value cannot silently rewrite the message's private
         copy. This preserves the aliasing invariant that
         ``__post_init__`` establishes (issue 042, issue 052).
+
+        None values override the declared type to NULL, matching Go's
+        per-row type header behavior where the nibble reflects the actual
+        value, not the column schema (issue 137).
         """
         if self.row_types and row_idx < len(self.row_types):
-            return list(self.row_types[row_idx])
-        if self.column_types:
-            return list(self.column_types)
-        # Infer from values
-
-        return [encode_value(v)[1] for v in row]
+            types = list(self.row_types[row_idx])
+        elif self.column_types:
+            types = list(self.column_types)
+        else:
+            # Infer from values
+            return [encode_value(v)[1] for v in row]
+
+        # Override type to NULL for None values, matching Go's behavior
+        for i, v in enumerate(row):
+            if v is None and i < len(types):
+                types[i] = ValueType.NULL
+        return types
 
     def encode_body(self) -> bytes:
         col_count = len(self.column_names)

tests/test_messages_responses.py

@@ -621,6 +621,52 @@ def test_empty_column_types_with_rows_ok(self) -> None:
         assert decoded.rows == [[42]]
 
 
+class TestRowsResponseNullInTypedColumn:
+    """137: None values in rows with explicit column types must encode correctly."""
+
+    def test_none_with_explicit_column_types(self) -> None:
+        """None in a TEXT column must encode as NULL, not crash."""
+        resp = RowsResponse(
+            column_names=["id", "name"],
+            column_types=[ValueType.INTEGER, ValueType.TEXT],
+            row_types=[[ValueType.INTEGER, ValueType.TEXT]],
+            rows=[[1, None]],
+        )
+        encoded = resp.encode_body()
+        decoded = RowsResponse.decode_body(encoded)
+        assert decoded.rows == [[1, None]]
+        # The type nibble for the None column should be NULL (5), not TEXT (3)
+        assert decoded.row_types[0][1] == ValueType.NULL
+
+    def test_none_with_explicit_row_types_integer(self) -> None:
+        """None in an INTEGER column with explicit row_types."""
+        resp = RowsResponse(
+            column_names=["val"],
+            column_types=[ValueType.INTEGER],
+            row_types=[[ValueType.INTEGER]],
+            rows=[[None]],
+        )
+        encoded = resp.encode_body()
+        decoded = RowsResponse.decode_body(encoded)
+        assert decoded.rows == [[None]]
+        assert decoded.row_types[0][0] == ValueType.NULL
+
+    def test_mixed_none_and_values(self) -> None:
+        """Row with mix of None and real values."""
+        resp = RowsResponse(
+            column_names=["a", "b", "c"],
+            column_types=[ValueType.INTEGER, ValueType.TEXT, ValueType.FLOAT],
+            row_types=[[ValueType.INTEGER, ValueType.TEXT, ValueType.FLOAT]],
+            rows=[[None, "hello", None]],
+        )
+        encoded = resp.encode_body()
+        decoded = RowsResponse.decode_body(encoded)
+        assert decoded.rows == [[None, "hello", None]]
+        assert decoded.row_types[0][0] == ValueType.NULL
+        assert decoded.row_types[0][1] == ValueType.TEXT
+        assert decoded.row_types[0][2] == ValueType.NULL
+
+
 class TestRowsResponseWordBoundary:
     """115: row header padding crosses word boundary at 17+ columns."""