feat: adding the rest ofthe nutrition properties from schema.org (#4301)

This commit is contained in:
Tom Brennan
2024-10-13 09:04:29 -04:00
committed by GitHub
parent 3aea229f2d
commit 02c0fe993b
16 changed files with 279 additions and 57 deletions

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@@ -9,28 +9,52 @@ class Nutrition(SqlAlchemyBase):
__tablename__ = "recipe_nutrition"
id: Mapped[int] = mapped_column(sa.Integer, primary_key=True)
recipe_id: Mapped[GUID | None] = mapped_column(GUID, sa.ForeignKey("recipes.id"), index=True)
calories: Mapped[str | None] = mapped_column(sa.String)
carbohydrate_content: Mapped[str | None] = mapped_column(sa.String)
cholesterol_content: Mapped[str | None] = mapped_column(sa.String)
fat_content: Mapped[str | None] = mapped_column(sa.String)
fiber_content: Mapped[str | None] = mapped_column(sa.String)
protein_content: Mapped[str | None] = mapped_column(sa.String)
carbohydrate_content: Mapped[str | None] = mapped_column(sa.String)
saturated_fat_content: Mapped[str | None] = mapped_column(sa.String)
# `serving_size` is not a scaling factor, but a per-serving volume or mass
# according to schema.org. E.g., "2 L", "500 g", "5 cups", etc.
#
# Ignoring for now because it's too difficult to work around variable units
# in translation for the frontend. Also, it causes cognitive dissonance wrt
# "servings" (i.e., "serves 2" etc.), which is an unrelated concept that
# might cause confusion.
#
# serving_size: Mapped[str | None] = mapped_column(sa.String)
sodium_content: Mapped[str | None] = mapped_column(sa.String)
sugar_content: Mapped[str | None] = mapped_column(sa.String)
trans_fat_content: Mapped[str | None] = mapped_column(sa.String)
unsaturated_fat_content: Mapped[str | None] = mapped_column(sa.String)
def __init__(
self,
calories=None,
carbohydrate_content=None,
cholesterol_content=None,
fat_content=None,
fiber_content=None,
protein_content=None,
saturated_fat_content=None,
sodium_content=None,
sugar_content=None,
carbohydrate_content=None,
trans_fat_content=None,
unsaturated_fat_content=None,
) -> None:
self.calories = calories
self.carbohydrate_content = carbohydrate_content
self.cholesterol_content = cholesterol_content
self.fat_content = fat_content
self.fiber_content = fiber_content
self.protein_content = protein_content
self.saturated_fat_content = saturated_fat_content
self.sodium_content = sodium_content
self.sugar_content = sugar_content
self.carbohydrate_content = carbohydrate_content
self.trans_fat_content = trans_fat_content
self.unsaturated_fat_content = unsaturated_fat_content

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@@ -187,7 +187,7 @@ class RecipeModel(SqlAlchemyBase, BaseMixins):
settings: dict | None = None,
**_,
) -> None:
self.nutrition = Nutrition(**nutrition) if nutrition else Nutrition()
self.nutrition = Nutrition(**(nutrition or {}))
if recipe_instructions is not None:
self.recipe_instructions = [RecipeInstruction(**step, session=session) for step in recipe_instructions]
@@ -198,7 +198,7 @@ class RecipeModel(SqlAlchemyBase, BaseMixins):
if assets:
self.assets = [RecipeAsset(**a) for a in assets]
self.settings = RecipeSettings(**settings) if settings else RecipeSettings()
self.settings = RecipeSettings(**(settings or {}))
if notes:
self.notes = [Note(**n) for n in notes]

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@@ -104,15 +104,7 @@ def content_with_meta(group_slug: str, recipe: Recipe) -> str:
ingredients.append(s)
nutrition: dict[str, str | None] = {}
if recipe.nutrition:
nutrition["calories"] = recipe.nutrition.calories
nutrition["fatContent"] = recipe.nutrition.fat_content
nutrition["fiberContent"] = recipe.nutrition.fiber_content
nutrition["proteinContent"] = recipe.nutrition.protein_content
nutrition["carbohydrateContent"] = recipe.nutrition.carbohydrate_content
nutrition["sodiumContent"] = recipe.nutrition.sodium_content
nutrition["sugarContent"] = recipe.nutrition.sugar_content
nutrition: dict[str, str | None] = recipe.nutrition.model_dump(by_alias=True) if recipe.nutrition else {}
as_schema_org = {
"@context": "https://schema.org",

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@@ -1,14 +1,24 @@
from pydantic import ConfigDict
from pydantic.alias_generators import to_camel
from mealie.schema._mealie import MealieModel
class Nutrition(MealieModel):
calories: str | None = None
fat_content: str | None = None
protein_content: str | None = None
carbohydrate_content: str | None = None
cholesterol_content: str | None = None
fat_content: str | None = None
fiber_content: str | None = None
protein_content: str | None = None
saturated_fat_content: str | None = None
sodium_content: str | None = None
sugar_content: str | None = None
model_config = ConfigDict(from_attributes=True, coerce_numbers_to_str=True)
trans_fat_content: str | None = None
unsaturated_fat_content: str | None = None
model_config = ConfigDict(
from_attributes=True,
coerce_numbers_to_str=True,
alias_generator=to_camel,
)

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@@ -12,6 +12,18 @@ from mealie.services.scraper import cleaner
from ._migration_base import BaseMigrator
from .utils.migration_helpers import scrape_image, split_by_line_break, split_by_semicolon
nutrition_map = {
"carbohydrate": "carbohydrateContent",
"protein": "proteinContent",
"fat": "fatContent",
"saturatedfat": "saturatedFatContent",
"transfat": "transFatContent",
"sodium": "sodiumContent",
"fiber": "fiberContent",
"sugar": "sugarContent",
"unsaturatedfat": "unsaturatedFatContent",
}
class MyRecipeBoxMigrator(BaseMigrator):
def __init__(self, **kwargs):
@@ -53,22 +65,26 @@ class MyRecipeBoxMigrator(BaseMigrator):
except Exception:
return None
def parse_nutrition(self, input: Any) -> dict | None:
if not input or not isinstance(input, str):
def parse_nutrition(self, input_: Any) -> dict | None:
if not input_ or not isinstance(input_, str):
return None
nutrition = {}
vals = [x.strip() for x in input.split(",") if x]
vals = (x.strip() for x in input_.split("\n") if x)
for val in vals:
try:
key, value = val.split(":", maxsplit=1)
key, value = (x.strip() for x in val.split(":", maxsplit=1))
if not (key and value):
continue
key = nutrition_map.get(key.lower(), key)
except ValueError:
continue
nutrition[key.strip()] = value.strip()
nutrition[key] = value
return cleaner.clean_nutrition(nutrition) if nutrition else None

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@@ -37,6 +37,19 @@ def get_value_as_string_or_none(dictionary: dict, key: str):
return None
nutrition_map = {
"Calories": "calories",
"Fat": "fatContent",
"Saturated Fat": "saturatedFatContent",
"Cholesterol": "cholesterolContent",
"Sodium": "sodiumContent",
"Sugar": "sugarContent",
"Carbohydrate": "carbohydrateContent",
"Fiber": "fiberContent",
"Protein": "proteinContent",
}
class PlanToEatMigrator(BaseMigrator):
def __init__(self, **kwargs):
super().__init__(**kwargs)
@@ -63,16 +76,7 @@ class PlanToEatMigrator(BaseMigrator):
def _parse_recipe_nutrition_from_row(self, row: dict) -> dict:
"""Parses the nutrition data from the row"""
nut_dict: dict = {}
nut_dict["calories"] = get_value_as_string_or_none(row, "Calories")
nut_dict["fatContent"] = get_value_as_string_or_none(row, "Fat")
nut_dict["proteinContent"] = get_value_as_string_or_none(row, "Protein")
nut_dict["carbohydrateContent"] = get_value_as_string_or_none(row, "Carbohydrate")
nut_dict["fiberContent"] = get_value_as_string_or_none(row, "Fiber")
nut_dict["sodiumContent"] = get_value_as_string_or_none(row, "Sodium")
nut_dict["sugarContent"] = get_value_as_string_or_none(row, "Sugar")
nut_dict = {normalized_k: row[k] for k, normalized_k in nutrition_map.items() if k in row}
return cleaner.clean_nutrition(nut_dict)

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@@ -495,7 +495,7 @@ def clean_nutrition(nutrition: dict | None) -> dict[str, str]:
list of valid keys
Assumptionas:
- All units are supplied in grams, expect sodium which maybe be in milligrams
- All units are supplied in grams, expect sodium and cholesterol which maybe be in milligrams
Returns:
dict[str, str]: If the argument is None, or not a dictionary, an empty dictionary is returned
@@ -509,9 +509,10 @@ def clean_nutrition(nutrition: dict | None) -> dict[str, str]:
if matched_digits := MATCH_DIGITS.search(val):
output_nutrition[key] = matched_digits.group(0).replace(",", ".")
if sodium := nutrition.get("sodiumContent", None):
if isinstance(sodium, str) and "m" not in sodium and "g" in sodium:
with contextlib.suppress(AttributeError, TypeError):
output_nutrition["sodiumContent"] = str(float(output_nutrition["sodiumContent"]) * 1000)
for key in ["sodiumContent", "cholesterolContent"]:
if val := nutrition.get(key, None):
if isinstance(val, str) and "m" not in val and "g" in val:
with contextlib.suppress(AttributeError, TypeError):
output_nutrition[key] = str(float(output_nutrition[key]) * 1000)
return output_nutrition