fix: BaseFloat._check_scalar rejects invalid string values (#3586) (#3762)

* fix: BaseFloat._check_scalar rejects invalid string values (#3586)

BaseFloat._check_scalar returned True for all strings because the
FloatLike type union includes str. This allowed invalid strings like
'not valid' to pass the check and then raise a confusing ValueError
in _cast_scalar_unchecked instead of the expected TypeError.

Fix _check_scalar to validate string inputs by attempting conversion:
- Valid float strings (e.g. 'NaN', 'inf', '-inf', '1.5') return True
- Invalid strings (e.g. 'not valid') return False, causing cast_scalar
  to raise TypeError as expected

Add test cases for invalid string inputs to invalid_scalar_params.

Fixes #3586

* style: fix ruff formatting and TRY300 in _check_scalar

---------

Co-authored-by: Cipher <cipher@openclaw.ai>

Author: abishop1990

src/zarr/core/dtype/npy/float.py

@@ -201,6 +201,16 @@ def _check_scalar(self, data: object) -> TypeGuard[FloatLike]:
         TypeGuard[FloatLike]
             True if the input is a valid scalar value, False otherwise.
         """
+        if isinstance(data, str):
+            # Only accept strings that are valid float representations (e.g. "NaN", "inf").
+            # Plain strings that cannot be converted should return False so that cast_scalar
+            # raises TypeError rather than a confusing ValueError.
+            try:
+                self.to_native_dtype().type(data)
+            except (ValueError, OverflowError):
+                return False
+            else:
+                return True
         return isinstance(data, FloatLike)
 
     def _cast_scalar_unchecked(self, data: FloatLike) -> TFloatScalar_co:

tests/test_dtype/test_npy/test_float.py

@@ -65,7 +65,10 @@ class TestFloat16(_BaseTestFloat):
         (Float16(), -1.0, np.float16(-1.0)),
         (Float16(), "NaN", np.float16("NaN")),
     )
-    invalid_scalar_params = ((Float16(), {"set!"}),)
+    invalid_scalar_params = (
+        (Float16(), {"set!"}),
+        (Float16(), "not_a_float"),
+    )
     hex_string_params = (("0x7fc0", np.nan), ("0x7fc1", np.nan), ("0x3c00", 1.0))
     item_size_params = (Float16(),)
 
@@ -113,7 +116,10 @@ class TestFloat32(_BaseTestFloat):
         (Float32(), -1.0, np.float32(-1.0)),
         (Float32(), "NaN", np.float32("NaN")),
     )
-    invalid_scalar_params = ((Float32(), {"set!"}),)
+    invalid_scalar_params = (
+        (Float32(), {"set!"}),
+        (Float32(), "not_a_float"),
+    )
     hex_string_params = (("0x7fc00000", np.nan), ("0x7fc00001", np.nan), ("0x3f800000", 1.0))
     item_size_params = (Float32(),)
 
@@ -160,7 +166,10 @@ class TestFloat64(_BaseTestFloat):
         (Float64(), -1.0, np.float64(-1.0)),
         (Float64(), "NaN", np.float64("NaN")),
     )
-    invalid_scalar_params = ((Float64(), {"set!"}),)
+    invalid_scalar_params = (
+        (Float64(), {"set!"}),
+        (Float64(), "not_a_float"),
+    )
     hex_string_params = (
         ("0x7ff8000000000000", np.nan),
         ("0x7ff8000000000001", np.nan),