using MeterVault.Core.Domain;
using MeterVault.Core.Normalization;
using MeterVault.Core.Parsing;
using MeterVault.Infrastructure.Import;

namespace MeterVault.Integration.Tests.Reconciliation;

/// <summary>
/// Shared helpers for the golden-fixture reconciliation tests. The CSVs are self-oracling: the
/// same file carries both the input (registers/levels/hours) and the expected output
/// (Verbrauch / Differenz Tank / Kosten columns). We parse input → normalize → compare against
/// the sheet's own columns (SDD §0.3, §13). No database is involved.
/// </summary>
internal static class ReconciliationSupport
{
    // Fixture file names (linked into fixtures/ in the test output).
    public const string Electricity = "Energiebilanz - Strom Verbrauch.csv";
    public const string Water = "Energiebilanz - Wasser.csv";
    public const string Oil = "Energiebilanz - Heizöl Verbrauch.csv";
    public const string Costs = "Energiebilanz - Kosten.csv";

    public static string FixturePath(string fileName) =>
        Path.Combine(AppContext.BaseDirectory, "fixtures", fileName);

    public static List<string[]> ReadRows(string fileName)
    {
        using var reader = new StreamReader(FixturePath(fileName));
        return CsvImporter.ReadRows(reader);
    }

    public static StagedImport Stage(MappingProfile profile, string fileName)
    {
        using var reader = new StreamReader(FixturePath(fileName));
        return new CsvImporter().Stage(profile, reader);
    }

    /// <summary>Normalizes one meter from a staged import using the given config.</summary>
    public static IReadOnlyList<Consumption> Normalize(StagedImport staged, MeterConfig config)
    {
        var engine = NormalizationEngine.CreateDefault();
        var context = new NormalizationContext
        {
            Meter = config,
            Readings = staged.Readings.Where(r => r.MeterId == config.MeterId).ToList(),
            Events = staged.Events.Where(e => e.MeterId == config.MeterId).ToList(),
        };

        return engine.Normalize(context);
    }

    /// <summary>Extracts a sheet oracle column keyed by month, using German number parsing.</summary>
    public static Dictionary<DateOnly, double> OracleByMonth(
        IReadOnlyList<string[]> rows, int dateColumn, int valueColumn, int firstDataRow)
    {
        var result = new Dictionary<DateOnly, double>();
        for (var r = firstDataRow; r < rows.Count; r++)
        {
            var row = rows[r];
            if (dateColumn >= row.Length || valueColumn >= row.Length)
            {
                continue;
            }

            if (!GermanDate.TryParse(row[dateColumn], out var date))
            {
                continue;
            }

            if (GermanNumber.TryParse(row[valueColumn], out var value))
            {
                result[new DateOnly(date.Year, date.Month, 1)] = value;
            }
        }

        return result;
    }

    public static DateOnly MonthKey(DateTimeOffset time) => new(time.Year, time.Month, 1);

    /// <summary>
    /// Asserts every month present in both computed and oracle agrees within tolerance, and that
    /// a meaningful number of months were actually compared (so an empty result can't pass).
    /// </summary>
    public static void AssertReconciles(
        IReadOnlyDictionary<DateOnly, double> computed,
        IReadOnlyDictionary<DateOnly, double> oracle,
        double tolerance,
        string label,
        int minMatches)
    {
        var matched = 0;
        foreach (var (month, expected) in oracle)
        {
            if (!computed.TryGetValue(month, out var actual))
            {
                continue;
            }

            matched++;
            Assert.True(
                Math.Abs(actual - expected) <= tolerance,
                $"{label} {month:yyyy-MM}: computed {actual:0.##} vs sheet {expected:0.##} (tol {tolerance}).");
        }

        Assert.True(matched >= minMatches, $"{label}: only {matched} months reconciled (expected ≥ {minMatches}).");
    }

    public static Dictionary<DateOnly, double> ByMonth(IReadOnlyList<Consumption> series) =>
        series.GroupBy(c => MonthKey(c.Time)).ToDictionary(g => g.Key, g => g.Sum(c => c.Amount));

    /// <summary>Consumption keyed by exact reading date (oil rows are event-dated, sometimes two per month).</summary>
    public static Dictionary<DateOnly, double> ByDate(IReadOnlyList<Consumption> series) =>
        series.GroupBy(c => DateOnly.FromDateTime(c.Time.UtcDateTime))
              .ToDictionary(g => g.Key, g => g.Sum(c => c.Amount));

    /// <summary>
    /// Extracts a sheet oracle column keyed by exact date, optionally transformed. Uses the same
    /// month-end anchoring as the importer so day-dated and month-dated rows align.
    /// </summary>
    public static Dictionary<DateOnly, double> OracleByDate(
        IReadOnlyList<string[]> rows, int dateColumn, int valueColumn, int firstDataRow,
        Func<double, double>? transform = null, bool anchorMonthsToEnd = true)
    {
        var result = new Dictionary<DateOnly, double>();
        for (var r = firstDataRow; r < rows.Count; r++)
        {
            var row = rows[r];
            if (dateColumn >= row.Length || valueColumn >= row.Length)
            {
                continue;
            }

            if (!ImportDate.TryResolve(row[dateColumn], anchorMonthsToEnd, out var date))
            {
                continue;
            }

            if (GermanNumber.TryParse(row[valueColumn], out var value))
            {
                result[date] = transform is null ? value : transform(value);
            }
        }

        return result;
    }
}