munch-ease-backend/recipes/__init__.py

import re
from typing import Optional

from ingredients import match_existing_products, parse_ingredient_from_nlp
from api.dtos import MemberRef
from recipes.models import Recipe as Recipe
from recipes.repository import (
    compute_prev_cursor as compute_prev_cursor,
    count_all as count_all,
    count_by_name as count_by_name,
    count_all_scoped as count_all_scoped,
    count_by_name_scoped as count_by_name_scoped,
    find_recipe_by_id as find_recipe_by_id,
    find_recipe_by_id_scoped as find_recipe_by_id_scoped,
    find_recipes_by_name as find_recipes_by_name,
    find_recipes_by_name_paged as find_recipes_by_name_paged,
    find_recipes_by_name_paged_scoped as find_recipes_by_name_paged_scoped,
    get_all as get_all,
    get_all_paged as get_all_paged,
    get_all_paged_scoped as get_all_paged_scoped,
    insert_recipe as insert_recipe,
    insert_recipe_scoped as insert_recipe_scoped,
    load_recipe_ingredients as load_recipe_ingredients,
    row_to_recipe as row_to_recipe,
)
from recipes.scraping import (
    scrape_recipe_ldata as _scrape_recipe_ldata,
    scrape_recipe_ldata_from_html as _scrape_recipe_ldata_from_html,
)


async def parse_recipe(conn, created_by, url: str, log=None, dump_dir: str | None = None) -> Optional[Recipe]:
    """Parse a recipe from a URL. Returns None if parsing fails.

    Accepts an optional log callable taking a single string argument; when provided,
    the scraper will emit diagnostic messages useful for manual testing.
    """
    ldata = await _scrape_recipe_ldata(url, log=log, dump_dir=dump_dir)

    if ldata:
        return await _get_recipe_from_ldata(conn, url, ldata, created_by)
    return None


async def parse_recipe_from_html(conn, created_by, base_url: str, html: str, log=None) -> Optional[Recipe]:
    """Parse a recipe from raw HTML (offline). Returns None if parsing fails.

    This mirrors parse_recipe() but uses already-downloaded HTML via the offline
    scraper entrypoint. Useful for tests/assertions against saved snapshots.
    """
    ldata = _scrape_recipe_ldata_from_html(html, base_url, log=log)
    if ldata:
        return await _get_recipe_from_ldata(conn, base_url, ldata, created_by)
    return None


def find_yield(recipe_ldata: dict) -> int:
    if "recipeYield" in recipe_ldata:
        yield_vals = recipe_ldata["recipeYield"]
        if not isinstance(yield_vals, list):
            yield_vals = [yield_vals]

        for val in yield_vals:
            try:
                return int(val)
            except ValueError:
                pass

        for val in yield_vals:
            match = re.match(r"(\d+)", val)
            if match:
                return int(match.group(1))

    return 4


async def _get_recipe_from_ldata(conn, url: str, ldata: dict, created_by) -> Recipe:
    ingredients = [
        parse_ingredient_from_nlp(ingredient) for ingredient in ldata["recipeIngredient"]
    ]
    ingredients = await match_existing_products(conn, ingredients)
    name = ldata["name"] if "name" in ldata else url
    images = ldata["image"] if "image" in ldata else []
    serves = find_yield(ldata)

    if isinstance(images, list) and len(images) > 0 and isinstance(images[0], dict):
        images = [image["url"] for image in images]

    if isinstance(images, dict):
        images = [images["url"]]

    if isinstance(images, str):
        images = [images]

    # Ensure created_by is a MemberRef (not a full User) to satisfy model typing
    mref = (
        MemberRef(id=created_by.id, display_name=created_by.display_name)
        if created_by is not None
        else None
    )
    return Recipe(
        id=-1,
        name=name,
        link=url,
        serves=serves,
        image_urls=images,
        ingredients=ingredients,
        created_by=mref,
        created_by_id=created_by.id if created_by is not None else -1,
    )