update dazls

openstef/data/dazls_stored_3.2.49.sav.license

@@ -0,0 +1,3 @@
+SPDX-FileCopyrightText: 2017-2023 Contributors to the OpenSTEF project <[email protected]>
+
+SPDX-License-Identifier: MPL-2.0

requirements.txt

@@ -12,7 +12,7 @@ plotly~=5.14
 pvlib==0.9.4
 pydantic~=1.10
 pymsteams~=0.2.2   # TODO remove teams dependency
-scikit-learn~=1.2
+scikit-learn~=1.3
 scipy~=1.10
 statsmodels~=0.13.5
 structlog~=23.1

test/unit/pipeline/test_create_component_forecast.py

@@ -2,12 +2,16 @@
 #
 # SPDX-License-Identifier: MPL-2.0
 from datetime import datetime, timedelta, timezone
-import unittest
 from test.unit.utils.base import BaseTestCase
 from test.unit.utils.data import TestData
+import joblib
 
 import pandas as pd
 
+from pathlib import Path
+
+PROJECT_ROOT = Path(__file__).parent.parent.parent.parent.absolute()
+
 from openstef.pipeline.create_component_forecast import (
     create_components_forecast_pipeline,
 )
@@ -18,7 +22,18 @@ def setUp(self) -> None:
         super().setUp()
         self.PJ = TestData.get_prediction_job(pid=307)
 
-    @unittest.skip("Does work offline, but not online.")
+    def test_load_dazls_model(self):
+        """Version updates of sklearn could break pickle.load
+        Let's test for that explicitly
+        Assert that loading the old model generates an exception and the new model does not"""
+
+        old_model_file = PROJECT_ROOT / "openstef/data/dazls_stored_3.2.49.sav"
+        new_model_file = PROJECT_ROOT / "openstef/data/dazls_stored.sav"
+
+        self.assertRaises(Exception, joblib.load, old_model_file)
+        dazls_model = joblib.load(new_model_file)
+        assert dazls_model
+
     def test_component_forecast_pipeline_happy_flow(self):
         # Test happy flow
         data = TestData.load("reference_sets/307-test-data.csv")