made suggested changes

src/ophyd_async/core/_table.py

@@ -63,7 +63,6 @@ def __add__(self, right: "Table") -> "Table":
             }
         )
 
-    @property
     def numpy_dtype(self) -> np.dtype:
         dtype = []
         for field_name, field_value in self.model_fields.items():
@@ -81,18 +80,16 @@ def numpy_dtype(self) -> np.dtype:
 
         return np.dtype(dtype)
 
-    @property
     def numpy_table(self):
         # It would be nice to be able to use np.transpose for this,
         # but it defaults to the largest dtype for everything.
-        dtype = self.numpy_dtype
+        dtype = self.numpy_dtype()
         transposed_list = [
-            np.array(tuple(row), dtype=dtype) for row in zip(*self.numpy_columns)
+            np.array(tuple(row), dtype=dtype) for row in zip(*self.numpy_columns())
         ]
         transposed = np.array(transposed_list, dtype=dtype)
         return transposed
 
-    @property
     def numpy_columns(self) -> list[np.ndarray]:
         """Columns in the table can be lists of string enums or numpy arrays.
 

src/ophyd_async/fastcs/panda/_table.py

@@ -51,7 +51,7 @@ class SeqTrigger(str, Enum):
     ),
     Field(default_factory=lambda: np.array([], dtype=np.bool_)),
 ]
-TriggerStr = Annotated[list[SeqTrigger], Field(default_factory=list)]
+TriggerStr = Annotated[Sequence[SeqTrigger], Field(default_factory=list)]
 
 
 class SeqTable(Table):

tests/fastcs/panda/test_table.py

@@ -216,7 +216,7 @@ def _assert_col_equal(column1, column2):
         _assert_col_equal(column1, column2)
 
     assert np.array_equal(
-        seq_table_from_pva_dict.numpy_columns,
+        seq_table_from_pva_dict.numpy_columns(),
         [
             np.array([1, 2, 3, 4], dtype=np.int32),
             np.array(
@@ -245,7 +245,7 @@ def _assert_col_equal(column1, column2):
             np.array([True, False, True, False], dtype=np.bool_),
         ],
     )
-    dtype = seq_table_from_pva_dict.numpy_dtype
+    dtype = seq_table_from_pva_dict.numpy_dtype()
     assert dtype == np.dtype(
         [
             ("repeats", np.int32),
@@ -269,7 +269,7 @@ def _assert_col_equal(column1, column2):
     )
 
     assert np.array_equal(
-        seq_table_from_pva_dict.numpy_table,
+        seq_table_from_pva_dict.numpy_table(),
         np.array(
             [
                 (

tests/fastcs/panda/test_trigger.py

@@ -138,12 +138,15 @@ def full_seq_table(trigger):
             outf2=np.array([1], dtype=np.bool_),
         )
 
-    with pytest.raises(ValidationError) as exc:
-        full_seq_table(np.array(["A"], dtype="U32"))
-    assert (
-        "Input should be 'Immediate', 'BITA=0', 'BITA=1', 'BITB=0', 'BITB=1', "
-        "'BITC... [type=enum, input_value='A', input_type=str_]"
-    ) in str(exc)
+    for attempted_table in [
+        np.array(["A"], dtype="U32"),
+        np.array(["Immediate"], dtype="U32"),
+        {"Immediate"},
+    ]:
+        with pytest.raises(ValidationError) as exc:
+            full_seq_table(attempted_table)
+        assert "Input should be an instance of Sequence" in str(exc)
+
     with pytest.raises(ValidationError) as exc:
         full_seq_table(["A"])
     assert (
@@ -152,9 +155,7 @@ def full_seq_table(trigger):
     ) in str(exc)
 
     # Pydantic is able to infer type from these
-    table = full_seq_table({"Immediate"})
-    assert table.trigger == ["Immediate"] == [SeqTrigger.IMMEDIATE]
-    table = full_seq_table({SeqTrigger.IMMEDIATE})
+    table = full_seq_table([SeqTrigger.IMMEDIATE])
     assert table.trigger == ["Immediate"] == [SeqTrigger.IMMEDIATE]
-    full_seq_table(np.array(["Immediate"], dtype="U32"))
+    table = full_seq_table(["Immediate"])
     assert table.trigger == ["Immediate"] == [SeqTrigger.IMMEDIATE]