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fix: fix nutrition schema #437

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Merged
raphael0202 merged 1 commit into from
Feb 19, 2026
Merged

fix: fix nutrition schema #437

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4 changes: 2 additions & 2 deletions openfoodfacts/types.py
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Original file line number Diff line number Diff line change
Expand Up @@ -941,11 +941,11 @@ class NutritionV3AggregatedSet(BaseModel):
class NutritionV3InputSet(BaseModel):
preparation: Literal["as_sold", "prepared"]
per: Literal["serving", "100g", "100ml"]
per_quantity: int
per_unit: Literal["g", "ml"]
source: str = Field(
examples=["packaging", "manufacturer", "database-usda", "estimate"]
)
per_quantity: float | None = None
per_unit: Literal["g", "ml"] | None = None
source_description: str | None = None
last_updated_t: int | None = Field(
None, description="timestamp of the last update of the input set"
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102 changes: 101 additions & 1 deletion tests/unit/test_types.py
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Original file line number Diff line number Diff line change
Expand Up @@ -269,8 +269,108 @@ def test_from_product_type_invalid():
}


# With missing er_quantity and per_unit in the input_set
NUTRITION_4 = {
"input_sets": [
{
"last_updated_t": 1771468068,
"per_unit": "g",
"source": "packaging",
"per": "100g",
"per_quantity": 100,
"nutrients": {"nova-group": {"unit": "", "value": 4, "value_string": "4"}},
"preparation": "as_sold",
},
{
"per_unit": "g",
"source_description": "Estimate from ingredients",
"preparation": "as_sold",
"nutrients": {
"fruits-vegetables-legumes": {
"value_string": "0",
"unit": "%",
"value": 0,
"modifier": "~",
},
"added-sugars": {
"value": 0.182291666666664,
"modifier": "~",
"unit": "g",
"value_string": "0.182291666666664",
},
"fruits-vegetables-nuts": {
"value_string": "0",
"value": 0,
"modifier": "~",
"unit": "%",
},
},
"per_quantity": 100,
"per": "100g",
"source": "estimate",
},
{
"source": "packaging",
"per": "serving",
"preparation": "as_sold",
"nutrients": {
"energy-kj": {"unit": "kJ", "value_computed": 0},
"carbohydrates": {"value_string": "0", "unit": "g", "value": 0},
"energy-kcal": {
"value_string": "0",
"value": 0,
"value_computed": 0,
"unit": "kcal",
},
"fat": {"value_string": "0", "unit": "g", "value": 0},
"proteins": {"value_string": "0", "value": 0, "unit": "g"},
},
},
],
"aggregated_set": {
"per": "100g",
"preparation": "as_sold",
"nutrients": {
"fruits-vegetables-legumes": {
"source_per": "100g",
"source_index": 1,
"value": 0,
"modifier": "~",
"unit": "%",
"source": "estimate",
},
"added-sugars": {
"unit": "g",
"source": "estimate",
"modifier": "~",
"value": 0.182291666666664,
"source_index": 1,
"source_per": "100g",
},
"nova-group": {
"value": 4,
"source": "packaging",
"unit": "",
"source_per": "100g",
"source_index": 0,
},
"fruits-vegetables-nuts": {
"modifier": "~",
"value": 0,
"source": "estimate",
"unit": "%",
"source_per": "100g",
"source_index": 1,
},
},
},
}


class TestNutritionV3:
@pytest.mark.parametrize("obj", [NUTRITION_1, NUTRITION_2, NUTRITION_3])
@pytest.mark.parametrize(
"obj", [NUTRITION_1, NUTRITION_2, NUTRITION_3, NUTRITION_4]
)
def test_parse(self, obj: JSONType):
NutritionV3.model_validate(obj)

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