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* add universal toast plugin * add server side locales * integrate CRF++ into CI/CD Pipeline * docs(docs): 📝 add recipe parser docs * feat(backend): ✨ Continued work on ingredient parsers * add new model dest * feat(frontend): ✨ New ingredient parser page * formatting Co-authored-by: Hayden <hay-kot@pm.me>
44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
from dataclasses import dataclass
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from fractions import Fraction
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import pytest
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from mealie.services.parser_services.crfpp.processor import CRFIngredient, convert_list_to_crf_model
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@dataclass
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class TestIngredient:
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input: str
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quantity: float
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unit: str
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food: str
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comments: str
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# TODO - add more robust test cases
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test_ingredients = [
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TestIngredient("½ cup all-purpose flour", 0.5, "cup", "all-purpose flour", ""),
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TestIngredient("1 ½ teaspoons ground black pepper", 1.5, "teaspoon", "black pepper", "ground"),
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TestIngredient("⅔ cup unsweetened flaked coconut", 0.7, "cup", "coconut", "unsweetened flaked"),
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TestIngredient("⅓ cup panko bread crumbs", 0.3, "cup", "panko bread crumbs", ""),
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]
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def crf_exists() -> bool:
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import shutil
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return shutil.which("crf_test") is not None
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@pytest.mark.skipif(not crf_exists(), reason="CRF++ not installed")
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def test_nlp_parser():
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models: list[CRFIngredient] = convert_list_to_crf_model([x.input for x in test_ingredients])
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# Itterate over mdoels and test_ingreidnets to gether
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for model, test_ingredient in zip(models, test_ingredients):
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assert float(sum(Fraction(s) for s in model.qty.split())) == test_ingredient.quantity
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assert model.comment == test_ingredient.comments
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assert model.name == test_ingredient.food
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assert model.unit == test_ingredient.unit
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