Add a test for unexpected failing of validation with multiple units

nomenclature/codelist.py

@@ -7,7 +7,7 @@
 import pandas as pd
 import yaml
 from pyam import IamDataFrame
-from pyam.utils import is_list_like, write_sheet, pattern_match
+from pyam.utils import is_list_like, write_sheet, pattern_match, to_list
 from pydantic import BaseModel, ValidationInfo, field_validator
 from pydantic_core import PydanticCustomError
 
@@ -622,7 +622,7 @@ def validate_units(
             (variable, unit, self.mapping[variable].unit)
             for variable, unit in unit_mapping.items()
             if variable in self.variables
-            and not set(unit) == set(self.mapping[variable].unit)
+            and unit not in to_list(self.mapping[variable].unit)
         ]:
             lst = [
                 f"'{v}' - expected: {'one of ' if isinstance(e, list) else ''}"

tests/data/codelist/illegal_chars/char_in_external_repo/nomenclature.yaml

@@ -9,4 +9,4 @@ definitions:
     repository:
       - common-definitions
 check_illegal_characters: true
-illegal_characters: ['"' , ";"]  # these are known to be present in common-definitions variables
+illegal_characters: ["'"]  # these are known to be present in common-definitions variables

tests/data/data_structure_definition/extras_nc/variable/variables.yaml

@@ -3,7 +3,7 @@
     unit: EJ/yr
 - Primary Energy|Coal:
     definition: Primary energy consumption of coal
-    unit: EJ/yr
+    unit: [EJ/yr, GWh/yr]
 - Variable (w/ bunkers):
     definition: This is a variable with special characters for testing purposes
     unit: EJ/yr

tests/test_validation.py

@@ -67,6 +67,15 @@ def test_validation_fails_region(simple_definition, simple_df, caplog):
     )
 
 
+def test_validation_multiple_units(extras_definition, simple_df):
+    """Validating against a VariableCode with multiple units works as expected"""
+    extras_definition.validate(
+        simple_df
+        .filter(variable="Primary Energy|Coal")
+        .rename(unit={"EJ/yr": "GWh/yr"})
+    )
+
+
 def test_validation_with_custom_dimension(simple_df):
     """Check validation with a custom DataStructureDefinition dimension"""