fixups

src/ert/run_models/everest_run_model.py

@@ -3,6 +3,7 @@
 import copy
 import datetime
 import functools
+import json
 import logging
 import os
 import queue
@@ -300,7 +301,7 @@ def __init__(
         optimization_callback: OptimizerCallback,
         display_all_jobs: bool = True,
     ):
-        self._add_defaults(everest_config)
+        everest_config = self._add_defaults(everest_config)
 
         Path(everest_config.log_dir).mkdir(parents=True)
         Path(everest_config.optimization_output_dir).mkdir(parents=True)
@@ -341,7 +342,7 @@ def __init__(
         self.num_retries_per_iter = 0  # OK?
 
     @staticmethod
-    def _add_defaults(config: EverestConfig):
+    def _add_defaults(config: EverestConfig) -> EverestConfig:
         """This function exists as a temporary mechanism to default configurations that
         needs to be global in the sense that they should carry over both to ropt and ERT.
         When the proper mechanism for this is implemented this code
@@ -372,24 +373,23 @@ def create(
         simulation_callback: Optional[SimulationCallback] = None,
         optimization_callback: Optional[OptimizerCallback] = None,
         random_seed: Optional[int] = None,
-    ):
-        if simulation_callback is None:
-
-            def simulation_callback():
-                return None
+    ) -> EverestRunModel:
+        def default_simulation_callback(
+            simulation_status: SimulationStatus | None, event: str
+        ) -> str | None:
+            return None
 
-        if optimization_callback is None:
-
-            def optimization_callback():
-                return None
+        def default_optimization_callback() -> str | None:
+            return None
 
         ert_config = everest_to_ert_config(ever_config)
         return cls(
             random_seed=random_seed,
             config=ert_config,
             everest_config=ever_config,
-            simulation_callback=simulation_callback,
-            optimization_callback=optimization_callback,
+            simulation_callback=simulation_callback or default_simulation_callback,
+            optimization_callback=optimization_callback
+            or default_optimization_callback,
         )
 
     def run_experiment(
@@ -561,10 +561,9 @@ def description(cls) -> str:
         return "Run batches "
 
     @property
-    def result(self):
+    def result(self) -> Optional[seba_sqlite.sqlite_storage.OptimalResult]:
         return self._result
 
-    def __repr__(self):
-        return "EverestRunModel(config={})" % json.dumps(
-            self.everest_config, sort_keys=True, indent=2
-        )
+    def __repr__(self) -> str:
+        config_json = json.dumps(self.everest_config, sort_keys=True, indent=2)
+        return f"EverestRunModel(config={config_json})"

tests/everest/test_objective_type.py

@@ -21,4 +21,4 @@ def test_mathfunc_stddev(
     assert x1 == pytest.approx(0.5, abs=0.025)
     assert x2 == pytest.approx(0.5, abs=0.025)
 
-    assert workflow.result.total_objective < 0.0
+    assert run_model.result.total_objective < 0.0