"""
Smoke-Tests für Universal-CSV-Import (Executor + Apple-Schlaf-Parser).

Nutzt einen minimalen Fake-Cursor (kein PostgreSQL), damit die Pipelines bei jedem
pytest-Lauf mitlaufen.
"""

from __future__ import annotations

import uuid

import pytest

from csv_parser.executor import run_universal_csv_import
from csv_parser.sleep_apple_import import detect_apple_sleep_csv_format


class _SeqCursor:
    """Minimaler Cursor: execute protokolliert; fetchone liefert vorgegebene Sequenz."""

    def __init__(self, fetch_sequence: list) -> None:
        self.executes: list[tuple[str, tuple | None]] = []
        self._fetch = list(fetch_sequence)

    def execute(self, sql: str, params=None) -> None:
        self.executes.append((sql, params))

    def fetchone(self):
        if self._fetch:
            return self._fetch.pop(0)
        return None


PID = "00000000-0000-0000-0000-000000000001"


def test_detect_apple_sleep_summary_vs_segment():
    assert detect_apple_sleep_csv_format(["Start", "End", "Total Sleep (hr)", "Core (hr)"]) == "summary"
    assert detect_apple_sleep_csv_format(["Start", "End", "Duration (hr)", "Value"]) == "segments"


def test_run_universal_import_sleep_one_night_inserts(monkeypatch):
    """Eine Summary-Zeile → INSERT; SELECT vorher ohne Treffer."""
    text = (
        "Start,End,Total Sleep (hr),Core (hr),Deep (hr),REM (hr),Awake (hr)\n"
        "2024-01-15 22:00:00,2024-01-16 06:00:00,8.0,5.0,1.0,1.5,0.5\n"
    )
    cur = _SeqCursor(
        [
            None,
            {"id": 101},
        ]
    )
    out = run_universal_csv_import(cur, PID, "sleep", text, "sleep.csv", {})
    assert out["rows_total"] >= 1
    assert out["rows_imported"] >= 1
    assert any("INSERT INTO sleep_log" in q[0] for q in cur.executes)


def test_run_universal_import_activity_insert(monkeypatch):
    monkeypatch.setattr(
        "csv_parser.executor._resolve_training_type_for_activity",
        lambda *_a, **_k: (None, None, None),
    )
    text = (
        "Workout Type,Start,End,Duration,Distance (km),Active Energy (kcal)\n"
        "Running,2024-01-15 08:00:00,2024-01-15 09:00:00,1:00:00,10.0,500\n"
    )
    mapping = {
        "delimiter": ",",
        "has_header": True,
        "field_mappings": {
            "Workout Type": "activity_type",
            "Start": "start_time",
            "End": "end_time",
            "Duration": "duration_min",
            "Distance (km)": "distance_km",
            "Active Energy (kcal)": "kcal_active",
        },
        "type_conversions": {
            "start_time": {"type": "datetime", "format": "yyyy-mm-dd HH:MM:SS", "flexible": True},
            "end_time": {"type": "datetime", "format": "yyyy-mm-dd HH:MM:SS", "flexible": True},
            "duration_min": {
                "type": "duration",
                "format": "HH:MM:SS",
                "target_unit": "minutes",
                "flexible": True,
            },
            "distance_km": {"type": "float", "decimal_separator": ".", "flexible": True},
            "kcal_active": {"type": "float", "decimal_separator": ".", "flexible": True},
        },
    }
    new_id = str(uuid.uuid4())
    cur = _SeqCursor([None, {"id": new_id}])
    out = run_universal_csv_import(cur, PID, "activity", text, "act.csv", mapping)
    assert out["rows_imported"] == 1
    assert out["new_entries"] == 1
    assert any("INSERT INTO activity_log" in q[0] for q in cur.executes)


def test_run_universal_import_vitals_baseline_upsert_insert_path():
    text = (
        "Start,Resting Heart Rate,Heart Rate Variability,VO2 Max\n"
        "2024-01-15 07:00:00,55,45,42.5\n"
    )
    mapping = {
        "delimiter": ",",
        "has_header": True,
        "field_mappings": {
            "Start": "date",
            "Resting Heart Rate": "resting_hr",
            "Heart Rate Variability": "hrv",
            "VO2 Max": "vo2_max",
        },
        "type_conversions": {
            "date": {
                "type": "datetime",
                "format": "yyyy-mm-dd HH:MM:SS",
                "extract": "date_only",
                "flexible": True,
            },
            "resting_hr": {"type": "int", "flexible": True},
            "hrv": {"type": "int", "flexible": True},
            "vo2_max": {"type": "float", "decimal_separator": ".", "flexible": True},
        },
    }
    cur = _SeqCursor([{"inserted": True, "id": "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"}])
    out = run_universal_csv_import(cur, PID, "vitals_baseline", text, "v.csv", mapping)
    assert out["rows_imported"] == 1
    assert any("INSERT INTO vitals_baseline" in q[0] for q in cur.executes)


def test_run_universal_import_activity_garmin_time_plus_date_columns(monkeypatch):
    """Datum in eigener Spalte, Uhrzeit wie bei Garmin nur als Uhrzeit."""
    monkeypatch.setattr(
        "csv_parser.executor._resolve_training_type_for_activity",
        lambda *_a, **_k: (None, None, None),
    )
    text = (
        "Activity Type,Date,Time,Duration,Distance,Calories,Avg HR\n"
        "Run,2024-01-20,08:30:00,0:45:00,8.0,400,140\n"
    )
    mapping = {
        "delimiter": ",",
        "has_header": True,
        "field_mappings": {
            "Activity Type": "activity_type",
            "Date": "date",
            "Time": "start_time",
            "Duration": "duration_min",
            "Distance": "distance_km",
            "Calories": "kcal_active",
            "Avg HR": "hr_avg",
        },
        "type_conversions": {
            "date": {"type": "date", "format": "yyyy-mm-dd", "flexible": True},
            "start_time": {"type": "time", "format": "HH:MM:SS", "flexible": True},
            "duration_min": {
                "type": "duration",
                "format": "HH:MM:SS",
                "target_unit": "minutes",
                "flexible": True,
            },
            "distance_km": {"type": "float", "decimal_separator": ".", "flexible": True},
            "kcal_active": {"type": "float", "decimal_separator": ".", "flexible": True},
            "hr_avg": {"type": "int", "flexible": True},
        },
    }
    new_id = str(uuid.uuid4())
    cur = _SeqCursor([None, {"id": new_id}])
    out = run_universal_csv_import(cur, PID, "activity", text, "garmin.csv", mapping)
    assert out["rows_imported"] == 1
    # Duplicate-Key muss Datum + kombinierte Startzeit enthalten
    assert any(
        params and "2024-01-20 08:30:00" in str(params)
        for _sql, params in cur.executes
        if params
    )


def test_run_universal_import_nutrition_two_rows_same_day_aggregates_to_one_row():
    """Modul-Default: mehrere CSV-Zeilen pro Tag → Summe, ein nutrition_log-Eintrag."""
    text = (
        "Date,Kalorien,Protein,Fett,KH\n"
        "2024-01-15,500,10,20,30\n"
        "2024-01-15,300,5,10,15\n"
    )
    mapping = {
        "delimiter": ",",
        "has_header": True,
        "field_mappings": {
            "Date": "date",
            "Kalorien": "kcal",
            "Protein": "protein_g",
            "Fett": "fat_g",
            "KH": "carbs_g",
        },
        "type_conversions": {
            "date": {"type": "date", "format": "yyyy-mm-dd", "flexible": True},
            "kcal": {"type": "float", "decimal_separator": ".", "flexible": True},
            "protein_g": {"type": "float", "decimal_separator": ".", "flexible": True},
            "fat_g": {"type": "float", "decimal_separator": ".", "flexible": True},
            "carbs_g": {"type": "float", "decimal_separator": ".", "flexible": True},
        },
    }
    cur = _SeqCursor([None])
    out = run_universal_csv_import(cur, PID, "nutrition", text, "n.csv", mapping)
    assert out["rows_total"] == 2
    assert out["rows_imported"] == 1
    insert_sqls = [q for q in cur.executes if "INSERT INTO nutrition_log" in q[0]]
    assert len(insert_sqls) == 1
    params = insert_sqls[0][1]
    # (eid, profile_id, iso, kcal, prot, fat, carbs)
    assert params[3] == 800.0
    assert params[4] == 15.0
    assert params[5] == 30.0
    assert params[6] == 45.0