UPDATE carbon_footprint.py - implement product_or_sector_specific_rul…

…es attribute

pathfinder_framework/carbon_footprint/carbon_footprint.py

@@ -14,6 +14,7 @@
     DataQualityIndicators,
 )
 from pathfinder_framework.carbon_footprint.biogenic_accounting_methodology import BiogenicAccountingMethodology
+from pathfinder_framework.carbon_footprint.product_or_sector_specific_rule import ProductOrSectorSpecificRule
 
 
 class CarbonFootprint:
@@ -49,6 +50,7 @@ class CarbonFootprint:
         uncertainty_assessment_description (str | None): If present, the results, key drivers, and a short qualitative description of the uncertainty assessment.
         assurance (Assurance | None): If present, the Assurance information in accordance with the Pathfinder Framework.
         biogenic_accounting_methodology (BiogenicAccountingMethodology | None): The methodology used for biogenic carbon accounting.
+        product_or_sector_specific_rules (list[ProductOrSectorSpecificRule] | None): If present, refers to a set of product or sector specific rules published by a specific operator and applied during product carbon footprint calculation.
     """
 
     def __init__(
@@ -81,6 +83,7 @@ def __init__(
         uncertainty_assessment_description=None,
         assurance=None,
         biogenic_accounting_methodology=None,
+        product_or_sector_specific_rules=None
     ):
         if not isinstance(declared_unit, DeclaredUnit):
             raise ValueError(
@@ -191,7 +194,13 @@ def __init__(
             biogenic_accounting_methodology, BiogenicAccountingMethodology
         ):
             raise ValueError("biogenic_accounting_methodology must be an instance of BiogenicAccountingMethodology")
-
+        if product_or_sector_specific_rules is not None and not all(
+                isinstance(rule, ProductOrSectorSpecificRule)
+                for rule in product_or_sector_specific_rules
+        ):
+            raise ValueError(
+                "product_or_sector_specific_rules must be a list of ProductOrSectorSpecificRule"
+            )
         self.declared_unit = declared_unit
         self.unitary_product_amount = unitary_product_amount
         self.p_cf_excluding_biogenic = p_cf_excluding_biogenic
@@ -222,6 +231,7 @@ def __init__(
         self.uncertainty_assessment_description = uncertainty_assessment_description
         self.assurance = assurance
         self.biogenic_accounting_methodology = biogenic_accounting_methodology
+        self.product_or_sector_specific_rules = product_or_sector_specific_rules
 
         required_attributes_before_2025 = ["primary_data_share", "dqi"]
         required_attributes_after_2025 = [

tests/carbon_footprint/test_carbon_footprint.py

@@ -24,6 +24,8 @@
     DataQualityIndicators,
 )
 from pathfinder_framework.carbon_footprint.biogenic_accounting_methodology import BiogenicAccountingMethodology
+from pathfinder_framework.carbon_footprint.product_or_sector_specific_rule import ProductOrSectorSpecificRule
+from pathfinder_framework.carbon_footprint.product_or_sector_specific_rule_operator import ProductOrSectorSpecificRuleOperator
 
 
 @pytest.fixture
@@ -73,6 +75,11 @@ def valid_carbon_footprint_data():
             comments="Example comments",
         ),
         "biogenic_accounting_methodology": BiogenicAccountingMethodology.GHGP,
+        "product_or_sector_specific_rules": [ProductOrSectorSpecificRule(
+            operator=ProductOrSectorSpecificRuleOperator.OTHER,
+            rule_names=["Rule1"],
+            other_operator_name="Custom Operator",
+        )]
     }
 
 
@@ -184,7 +191,10 @@ def test_carbon_footprint_attributes(valid_carbon_footprint_data):
         carbon_footprint.biogenic_accounting_methodology
         == valid_carbon_footprint_data["biogenic_accounting_methodology"]
     )
-
+    assert (
+        carbon_footprint.product_or_sector_specific_rules
+        == valid_carbon_footprint_data["product_or_sector_specific_rules"]
+    )
 
 def test_carbon_footprint_invalid_declared_unit(valid_carbon_footprint_data):
     invalid_data = {**valid_carbon_footprint_data, "declared_unit": "invalid unit"}
@@ -742,3 +752,36 @@ def test_carbon_footprint_invalid_assurance(
     with pytest.raises(ValueError) as excinfo:
         CarbonFootprint(**invalid_data)
     assert str(excinfo.value) == expected_error
+
+
+@pytest.mark.parametrize(
+    "product_or_sector_specific_rules",
+    [
+        None,
+        [ProductOrSectorSpecificRule(
+            operator=ProductOrSectorSpecificRuleOperator.OTHER,
+            rule_names=["Rule1"],
+            other_operator_name="Custom Operator",
+        )],
+    ],
+)
+def test_carbon_footprint_valid_product_or_sector_specific_rules(valid_carbon_footprint_data, product_or_sector_specific_rules):
+    valid_data = valid_carbon_footprint_data.copy()
+    valid_data["product_or_sector_specific_rules"] = product_or_sector_specific_rules
+    CarbonFootprint(**valid_data)
+
+
+@pytest.mark.parametrize(
+    "product_or_sector_specific_rules, expected_error",
+    [
+        ([1], "product_or_sector_specific_rules must be a list of ProductOrSectorSpecificRule"),
+    ],
+)
+def test_carbon_footprint_invalid_product_or_sector_specific_rules(
+    valid_carbon_footprint_data, product_or_sector_specific_rules, expected_error
+):
+    invalid_data = valid_carbon_footprint_data.copy()
+    invalid_data["product_or_sector_specific_rules"] = product_or_sector_specific_rules
+    with pytest.raises(ValueError) as excinfo:
+        CarbonFootprint(**invalid_data)
+    assert str(excinfo.value) == expected_error