from data_layer.food_suggest import (
    collapse_key,
    name_tokens,
    score_name_match,
    suggest_batch,
    suggest_for_name,
)


def _index(*foods):
    index = {"foods": [], "by_collapse": {}, "by_token": {}, "by_prefix": {}, "by_suffix": {}}
    for food in foods:
        food["_c"] = collapse_key(food["name_de"])
        food["_t"] = name_tokens(food["name_de"])
        if food["_c"]:
            index["by_collapse"].setdefault(food["_c"], []).append(food)
            index["by_prefix"].setdefault(food["_c"][:4], []).append(food)
            if len(food["_c"]) >= 4:
                index["by_suffix"].setdefault(food["_c"][-4:], []).append(food)
        for tok in food["_t"]:
            index["by_token"].setdefault(tok, []).append(food)
    return index


def test_collapse_treats_space_as_same():
    assert collapse_key("Haferflocken") == collapse_key("Hafer Flocken")


def test_haferflocken_ranks_simple_name_first():
    index = {
        "foods": [],
        "by_collapse": {},
        "by_token": {},
        "by_prefix": {},
        "by_suffix": {},
    }
    simple = {"id": "1", "name_de": "Hafer Flocken", "name_en": "oat flakes", "bls_code": "C131111", "catalog_kind": "official_bls"}
    dish = {"id": "2", "name_de": "Milch-Getreide-Brei, mit Haferflocken und Apfelsaft (geeignet für Beikost)", "name_en": "", "bls_code": "X", "catalog_kind": "official_bls"}
    for food in (simple, dish):
        food["_c"] = collapse_key(food["name_de"])
        index["by_collapse"].setdefault(food["_c"], []).append(food)
        index["by_prefix"].setdefault(food["_c"][:4], []).append(food)
        index["by_suffix"].setdefault(food["_c"][-4:], []).append(food)
    packed = suggest_for_name(index, "Haferflocken", limit=3)
    assert packed["suggestions"][0]["name_de"] == "Hafer Flocken"
    assert packed["suggestions"][0]["score"] >= score_name_match("Haferflocken", dish["name_de"])


def test_close_scores_are_ambiguous():
    a = {"id": "1", "name_de": "Olivenöl nativ", "name_en": "", "bls_code": "A", "catalog_kind": "official_bls"}
    b = {"id": "2", "name_de": "Olivenöl raffiniert", "name_en": "", "bls_code": "B", "catalog_kind": "official_bls"}
    index = {"foods": [], "by_collapse": {}, "by_token": {}, "by_prefix": {}, "by_suffix": {}}
    for food in (a, b):
        food["_c"] = collapse_key(food["name_de"])
        index["by_prefix"].setdefault(food["_c"][:4], []).append(food)
        for tok in food["name_de"].lower().replace(",", "").split():
            if len(tok) >= 2:
                index["by_token"].setdefault(tok, []).append(food)
    packed = suggest_for_name(index, "Olivenöl", limit=3)
    assert packed["ambiguous"] is True
    assert packed["suggestion_count"] >= 2


def test_large_prefix_bucket_keeps_exact_collapse():
    index = {"foods": [], "by_collapse": {}, "by_token": {}, "by_prefix": {}, "by_suffix": {}}
    target = {"id": "hit", "name_de": "Hafer Flocken", "name_en": "", "bls_code": "C", "catalog_kind": "official_bls"}
    target["_c"] = collapse_key(target["name_de"])
    index["by_collapse"][target["_c"]] = [target]
    index["by_prefix"][target["_c"][:4]] = [target] + [
        {"id": str(i), "name_de": f"Hafer Gericht {i}", "name_en": "", "_c": f"hafergericht{i}"}
        for i in range(80)
    ]
    packed = suggest_for_name(index, "Haferflocken", limit=3)
    assert packed["suggestions"][0]["name_de"] == "Hafer Flocken"


def test_suggest_batch_dedupes_names():
    class _Cur:
        def execute(self, *args, **kwargs):
            return None
        def fetchall(self):
            return []

    out = suggest_batch(_Cur(), None, ["Haferflocken", "Haferflocken", ""], limit=2)
    assert "Haferflocken" in out
    assert out["Haferflocken"]["suggestions"] == []


def test_number_tokens_keep_decimal_fat():
    assert "9.5" in name_tokens("Joghurt 9,5%")
    assert "10" in name_tokens("Joghurt, aus Kuhmilch, 10 % Fett")


def test_joghurt_10_ranks_above_35():
    light = {"id": "a", "name_de": "Joghurt >3,5% Fett", "name_en": "", "bls_code": "M", "catalog_kind": "official_bls"}
    full = {
        "id": "b",
        "name_de": "Joghurt, aus Kuhmilch, 10 % Fett",
        "name_en": "",
        "bls_code": "N",
        "catalog_kind": "official_bls",
    }
    index = _index(light, full)
    for query in ("Joghurt 10%", "Joghurt 9,5%", "Joghurt 10"):
        packed = suggest_for_name(index, query, limit=3)
        assert packed["suggestions"][0]["name_de"] == full["name_de"], query
        assert packed["suggestions"][0]["score"] > score_name_match(query, light["name_de"])