"""Tests für CSV-Zeilenaggregation (import_row_processing)."""

from __future__ import annotations

import datetime as dt

import pytest

from csv_parser.import_row_processing import (
    aggregate_mapped_rows,
    resolve_import_row_processing,
    validate_import_row_processing,
)


def test_validate_rejects_unknown_aggregate():
    with pytest.raises(ValueError, match="ungültige Operation"):
        validate_import_row_processing(
            "nutrition",
            {"group_by": ["date"], "aggregates": {"kcal": "bogus"}},
            {"Kal": "date", "E": "kcal"},
        )


def test_validate_group_by_must_be_mapped():
    with pytest.raises(ValueError, match="keiner CSV-Spalte zugeordnet"):
        validate_import_row_processing(
            "nutrition",
            {"group_by": ["date"], "aggregates": {"kcal": "sum"}},
            {"Kal": "kcal"},  # date nicht gemappt
        )


def test_aggregate_mapped_rows_sums_same_group():
    d = dt.date(2024, 1, 15)
    rows = [
        {"date": d, "kcal": 500.0, "protein_g": 20},
        {"date": d, "kcal": 300.0, "protein_g": 15},
    ]
    spec = {"group_by": ["date"], "aggregates": {"kcal": "sum", "protein_g": "sum"}}
    out = aggregate_mapped_rows(rows, spec)
    assert len(out) == 1
    assert out[0]["kcal"] == 800.0
    assert out[0]["protein_g"] == 35


def test_resolve_explicit_overrides_default():
    m = {
        "import_row_processing": {"group_by": ["date"], "aggregates": {"kcal": "mean"}},
    }
    spec = resolve_import_row_processing("nutrition", m)
    assert spec is not None
    assert spec["aggregates"]["kcal"] == "mean"


def test_resolve_empty_dict_falls_back_to_module_default():
    m: dict = {"import_row_processing": {}}
    spec = resolve_import_row_processing("nutrition", m)
    assert spec is not None
    assert spec["group_by"] == ["date"]
    assert spec["aggregates"]["kcal"] == "sum"


def test_resolve_none_uses_nutrition_default():
    spec = resolve_import_row_processing("nutrition", {})
    assert spec is not None
    assert "date" in (spec.get("group_by") or [])