Add DataType equal and all_equal helpers

src/fastcs/datatypes/datatype.py

@@ -1,5 +1,6 @@
 import enum
 from abc import abstractmethod
+from collections.abc import Sequence
 from dataclasses import dataclass
 from typing import Any, Generic, TypeVar
 
@@ -28,6 +29,11 @@ class DataType(Generic[DType_T]):
     def dtype(self) -> type[DType_T]:  # Using property due to lack of Generic ClassVars
         raise NotImplementedError()
 
+    @property
+    @abstractmethod
+    def initial_value(self) -> DType_T:
+        raise NotImplementedError()
+
     def validate(self, value: Any) -> DType_T:
         """Validate a value against the datatype.
 
@@ -55,7 +61,32 @@ def validate(self, value: Any) -> DType_T:
         except (ValueError, TypeError) as e:
             raise ValueError(f"Failed to cast {value} to type {self.dtype}") from e
 
-    @property
-    @abstractmethod
-    def initial_value(self) -> DType_T:
-        raise NotImplementedError()
+    @staticmethod
+    def equal(value1: DType_T, value2: DType_T) -> bool:
+        """Compare two values for equality
+
+        Child classes can override this if the underlying type does not implement
+        ``__eq__`` or to define custom logic.
+
+        Args:
+            value1: The first value to compare
+            value2: The second value to compare
+
+        Returns:
+            `True` if the values are equal
+
+        """
+        return value1 == value2
+
+    @classmethod
+    def all_equal(cls, values: Sequence[DType_T]) -> bool:
+        """Compare a sequence of values for equality
+
+        Args:
+            values: Values to compare
+
+        Returns:
+            `True` if all values are equal, else `False`
+
+        """
+        return all(cls.equal(values[0], value) for value in values[1:])

src/fastcs/datatypes/table.py

@@ -30,3 +30,7 @@ def validate(self, value: Any) -> np.ndarray:
             )
 
         return _value
+
+    @staticmethod
+    def equal(value1: np.ndarray, value2: np.ndarray) -> bool:
+        return np.array_equal(value1, value2)

src/fastcs/datatypes/waveform.py

@@ -38,3 +38,7 @@ def validate(self, value: np.ndarray) -> np.ndarray:
             )
 
         return _value
+
+    @staticmethod
+    def equal(value1: np.ndarray, value2: np.ndarray) -> bool:
+        return np.array_equal(value1, value2)

tests/test_datatypes.py

@@ -3,10 +3,8 @@
 import numpy as np
 import pytest
 
-from fastcs.datatypes import DataType, Enum, Float, Int, Waveform
+from fastcs.datatypes import Bool, DataType, Enum, Float, Int, String, Table, Waveform
 from fastcs.datatypes._util import numpy_to_fastcs_datatype
-from fastcs.datatypes.bool import Bool
-from fastcs.datatypes.string import String
 
 
 def test_base_validate():
@@ -61,3 +59,49 @@ def test_validate(datatype, init_args, value):
 )
 def test_numpy_to_fastcs_datatype(numpy_type, fastcs_datatype):
     assert fastcs_datatype == numpy_to_fastcs_datatype(numpy_type)
+
+
+@pytest.mark.parametrize(
+    "fastcs_datatype, value1, value2, expected",
+    [
+        (Int(), 1, 1, True),
+        (Int(), 1, 2, False),
+        (Float(), 1.0, 1.0, True),
+        (Float(), 1.0, 2.0, False),
+        (Bool(), True, True, True),
+        (Bool(), True, False, False),
+        (String(), "foo", "foo", True),
+        (String(), "foo", "bar", False),
+        (Waveform(np.int16), np.array([1]), np.array([1]), True),
+        (Waveform(np.int16), np.array([1]), np.array([2]), False),
+        (
+            Table([("int", np.int16), ("bool", np.bool), ("str", np.dtype("S10"))]),
+            np.array([1, True, "foo"]),
+            np.array([1, True, "foo"]),
+            True,
+        ),
+        (
+            Table([("int", np.int16), ("bool", np.bool), ("str", np.dtype("S10"))]),
+            np.array([1, True, "foo"]),
+            np.array([2, False, "bar"]),
+            False,
+        ),
+    ],
+)
+def test_dataset_equal(fastcs_datatype: DataType, value1, value2, expected):
+    assert fastcs_datatype.equal(value1, value2) is expected
+
+
+@pytest.mark.parametrize(
+    "fastcs_datatype, values, expected",
+    [
+        (Int(), [1, 1], True),
+        (Int(), [1, 2], False),
+        (Float(), [1.0, 1.0], True),
+        (Float(), [1.0, 2.0], False),
+        (Bool(), [True, True], True),
+        (Bool(), [True, False], False),
+    ],
+)
+def test_dataset_all_equal(fastcs_datatype: DataType, values, expected):
+    assert fastcs_datatype.all_equal(values) is expected