Allow empty SinglePointData objects. Perform validation that result e…

CHANGELOG.md

@@ -6,6 +6,10 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 
 ## [unreleased]
 
+### Changed
+
+- Moved single-point primary-result validation from `SinglePointData` to `ProgramOutput` so failed calculations can carry empty or partial `SinglePointData` while successful calculations still require their requested primary result.
+
 ## [0.17.2] - 2026-05-31
 
 ### Added

pyproject.toml

@@ -62,7 +62,7 @@ dev = [
     "pytest>=7.2.2",
     "pre-commit>=3.2.1",
     "pytest-cov>=4.0.0",
-    "qcelemental>=0.26.0",
+    "qcelemental>=0.50.4",
     "types-toml>=0.10.8.6",
     "types-pyyaml>=6.0.12.10",
     "rdkit>=2022.9.5",

src/qcdata/models/data.py

@@ -148,17 +148,6 @@ def return_result(self, calctype: CalcType) -> float | SerializableNDArray:
         """Return the primary result of the calculation."""
         return getattr(self, calctype.value)
 
-    @model_validator(mode="after")
-    def _ensure_results(self) -> Self:
-        """Ensure that at least one result is present."""
-        if all(result is None for result in [self.energy, self.gradient, self.hessian]):
-            raise ValueError(
-                "SinglePointResults requires either an energy, gradient, or hessian "
-                "value."
-            )
-        return self
-
-
 class OptimizationData(Files, CalcInfoData):
     """Computed data for an optimization (may be for a minimum or transition state).
 

src/qcdata/models/outputs.py

@@ -139,7 +139,7 @@ def _ensure_structured_results_on_success(self) -> Self:
 
     @model_validator(mode="after")
     def ensure_primary_result_on_success(self) -> Self:
-        if type(self.data) is SinglePointData:
+        if self.success is True and type(self.data) is SinglePointData:
             calctype_val = self.input_data.calctype.value  # type: ignore
             assert getattr(self.data, calctype_val) is not None, (
                 f"Missing the primary result: {calctype_val}."

tests/test_outputs.py

@@ -117,6 +117,21 @@ def test_primary_result_must_be_present_on_success(prog_output):
             ProgramOutput[ProgramInput, SinglePointData](**po_dict)
 
 
+def test_primary_result_can_be_missing_on_failure(prog_input_factory):
+    pi_gradient = prog_input_factory("gradient")
+    output = ProgramOutput[ProgramInput, SinglePointData](
+        success=False,
+        input_data=pi_gradient,
+        data=SinglePointData(extras={"program_version": "3.0.2"}),
+        traceback="Fake traceback",
+        provenance={"program": "qcdata-test-suite"},
+    )
+    assert output.data.energy is None
+    assert output.data.gradient is None
+    assert output.data.hessian is None
+    assert output.data.extras == {"program_version": "3.0.2"}
+
+
 @pytest.mark.parametrize(
     "input_data, data, success, expected_input_type, expected_result_type",
     [

tests/test_single_point_data.py

@@ -1,6 +1,4 @@
 import numpy as np
-import pytest
-from pydantic import ValidationError
 
 from qcdata import SinglePointData, Wavefunction
 
@@ -102,6 +100,8 @@ def test_wavefunction_to_numpy():
     assert wavefunction.scf_occupations_b.dtype == np.float64
 
 
-def test_ensure_result_present_on_single_point_data_validator():
-    with pytest.raises(ValidationError):
-        SinglePointData()
+def test_single_point_data_can_be_empty_for_partial_or_failed_outputs():
+    data = SinglePointData()
+    assert data.energy is None
+    assert data.gradient is None
+    assert data.hessian is None