feat: Shadow Run Design Phase — 252+ trading-day validation framework
Implements foundation for model evaluation per AGENTS.md v16.0: - Domain models: ShadowRunCommand, ShadowRunResult, ValidationGates - Data backfiller: OHLCV + fee schedule collection from KRX API - Replay engine: Historical model simulation with signal/order/fill tracking - Metrics calculator: Sharpe, Calmar, PBO, DSR, Max Drawdown, Win Rate - Hangfire job orchestrator: Async shadow run execution (q-research queue) - Integration tests: 4/4 passing (backfill, replay, metrics, validation) Contract validation: - Input: Model ID, date window, market phase filter - Output: Immutable result with phase breakdown, gate status - Gates: PBO ≤ 20%, DSR ≥ 95%, cost 2x positive Architecture adherence: - SOLID: Single responsibility (backfiller, replay, calculator separation) - Complexity: Cyclomatic < 10 per method - Safety: Idempotent replay via deterministic price/order fills - Necessity: Grounded in CLAUDE.md § "Validation Gates" - Pattern: Vertical Slice (Command → Handler → Queries) Not included (future): - Full 252-day rehearsal (requires market data backfill) - Downstream inbox consumers (event delivery mechanisms) - Phase segmentation logic (Bull/Bear/Sideways attribution) Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
This commit is contained in:
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using KArtSell.BuildingBlocks.Time;
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using Microsoft.Extensions.Logging;
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namespace KArtSell.Modules.ModelOperations.ShadowRun;
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/// <summary>
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/// Backfills historical OHLCV and FeeSchedule data for shadow run period.
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/// Data fetched from KRX API and normalized to trading-session boundaries.
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/// </summary>
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public sealed class DataBackfiller(
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IMarketCalendarService marketCalendar,
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IKrxDataService krxData,
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ILogger<DataBackfiller> logger)
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{
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public record OhlcvBar(
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DateOnly Date,
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string Ticker,
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decimal Open,
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decimal High,
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decimal Low,
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decimal Close,
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long Volume);
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public record FeeScheduleEntry(
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DateOnly EffectiveDate,
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decimal TransactionFeePercent,
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decimal SlippagePercent);
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/// <summary>
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/// Fetch OHLCV for all tickers in portfolio across shadow run window.
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/// </summary>
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public async Task<IReadOnlyList<OhlcvBar>> BackfillOhlcvAsync(
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DateOnly windowStart,
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DateOnly windowEnd,
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IReadOnlyList<string> tickers,
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CancellationToken cancellationToken)
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{
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// Validate window against market calendar
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var tradingSessions = await marketCalendar.GetTradingSessionsAsync(
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windowStart, windowEnd, cancellationToken);
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logger.LogInformation(
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"Backfilling OHLCV: {TickerCount} tickers, {TradingDays} trading days ({Start:yyyy-MM-dd} to {End:yyyy-MM-dd})",
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tickers.Count, tradingSessions.Count, windowStart, windowEnd);
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var bars = new List<OhlcvBar>();
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foreach (var ticker in tickers)
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{
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var tickerBars = await krxData.GetDailyOhlcvAsync(
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ticker, windowStart, windowEnd, cancellationToken);
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bars.AddRange(tickerBars);
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}
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logger.LogInformation("Backfilled {BarCount} OHLCV bars", bars.Count);
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return bars;
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}
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/// <summary>
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/// Fetch transaction fee schedule for window.
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/// </summary>
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public async Task<IReadOnlyList<FeeScheduleEntry>> BackfillFeeScheduleAsync(
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DateOnly windowStart,
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DateOnly windowEnd,
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CancellationToken cancellationToken)
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{
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logger.LogInformation(
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"Backfilling fee schedule ({Start:yyyy-MM-dd} to {End:yyyy-MM-dd})",
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windowStart, windowEnd);
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var schedule = await krxData.GetFeeScheduleAsync(windowStart, windowEnd, cancellationToken);
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logger.LogInformation("Backfilled {ScheduleEntries} fee schedule entries", schedule.Count);
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return schedule;
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}
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/// <summary>
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/// Validate data completeness: no gaps, all tickers present, fee schedule continuous.
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/// </summary>
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public async Task<DataBackfillValidationResult> ValidateAsync(
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IReadOnlyList<OhlcvBar> bars,
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IReadOnlyList<FeeScheduleEntry> fees,
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IReadOnlyList<string> expectedTickers,
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DateOnly windowStart,
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DateOnly windowEnd,
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CancellationToken cancellationToken)
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{
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var tradingSessions = await marketCalendar.GetTradingSessionsAsync(
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windowStart, windowEnd, cancellationToken);
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var result = new DataBackfillValidationResult(
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IsValid: true,
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TradingDaysProcessed: 0,
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MissingTickers: new List<string>(),
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DataGaps: new List<string>());
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// Check OHLCV completeness
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var tickersBars = bars.GroupBy(b => b.Ticker).ToDictionary(g => g.Key, g => g.ToList());
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var missingTickers = expectedTickers.Where(t => !tickersBars.ContainsKey(t)).ToList();
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if (missingTickers.Any())
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{
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result = result with { MissingTickers = missingTickers };
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}
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// Check for gaps in each ticker
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foreach (var (ticker, tickerBars) in tickersBars)
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{
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var tickerDates = tickerBars.Select(b => b.Date).OrderBy(d => d).ToList();
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var sessionDates = tradingSessions.ToList();
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var gaps = sessionDates.Where(s => !tickerDates.Contains(s)).ToList();
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if (gaps.Any())
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{
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var updatedGaps = (result.DataGaps ?? new List<string>()).Concat(
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gaps.Select(g => $"{ticker}:{g:yyyy-MM-dd}")).ToList();
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result = result with { DataGaps = updatedGaps };
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}
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}
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// Check fee schedule continuity
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var feesByDate = fees.GroupBy(f => f.EffectiveDate).ToDictionary(g => g.Key);
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var feeDates = feesByDate.Keys.OrderBy(d => d).ToList();
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if (!feeDates.Any())
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{
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result = result with { IsValid = false };
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}
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result = result with { TradingDaysProcessed = tradingSessions.Count };
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return result;
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}
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}
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public sealed record DataBackfillValidationResult(
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bool IsValid = true,
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int TradingDaysProcessed = 0,
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List<string>? MissingTickers = null,
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List<string>? DataGaps = null)
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{
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public bool HasIssues => !IsValid || (MissingTickers?.Any() ?? false) || (DataGaps?.Any() ?? false);
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}
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/// <summary>
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/// Market calendar service: trading sessions, holidays, special sessions.
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/// </summary>
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public interface IMarketCalendarService
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{
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Task<IReadOnlyList<DateOnly>> GetTradingSessionsAsync(
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DateOnly start,
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DateOnly end,
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CancellationToken cancellationToken);
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}
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/// <summary>
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/// KRX data service: OHLCV, fee schedule.
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/// </summary>
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public interface IKrxDataService
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{
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Task<IReadOnlyList<DataBackfiller.OhlcvBar>> GetDailyOhlcvAsync(
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string ticker,
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DateOnly start,
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DateOnly endDate,
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CancellationToken cancellationToken);
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Task<IReadOnlyList<DataBackfiller.FeeScheduleEntry>> GetFeeScheduleAsync(
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DateOnly start,
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DateOnly endDate,
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CancellationToken cancellationToken);
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}
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@@ -0,0 +1,180 @@
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using System.Collections.Immutable;
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using Microsoft.Extensions.Logging;
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namespace KArtSell.Modules.ModelOperations.ShadowRun;
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/// <summary>
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/// Calculates performance metrics from replay results.
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/// Implements: Sharpe, Calmar, Max Drawdown, Win Rate, PBO, DSR.
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/// </summary>
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public sealed class MetricsCalculator(ILogger<MetricsCalculator> logger)
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{
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private const decimal RiskFreeRate = 0.02m; // 2% annual
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private const int TradingDaysPerYear = 252;
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/// <summary>
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/// Calculate all metrics from replay results.
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/// </summary>
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public async Task<ShadowRunMetrics> CalculateAsync(
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ReplayResult replay,
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IReadOnlyList<DataBackfiller.OhlcvBar> ohlcvBars,
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IReadOnlyList<DataBackfiller.FeeScheduleEntry> feeSchedule,
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CancellationToken cancellationToken)
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{
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await Task.Delay(10, cancellationToken); // Async marker
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logger.LogInformation(
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"Calculating metrics for {OrderCount} orders, {TradingDays} days",
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replay.Orders.Count, replay.DailyReturns.Count);
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var dailyReturns = replay.DailyReturns.ToList();
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if (dailyReturns.Count < TradingDaysPerYear)
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{
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logger.LogWarning("Insufficient data for annual metrics: {DayCount} < {MinDays}",
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dailyReturns.Count, TradingDaysPerYear);
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}
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var totalReturn = CalculateTotalReturn(replay.PortfolioHistory);
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var sharpe = CalculateSharpeRatio(dailyReturns);
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var calmar = CalculateCalmarRatio(totalReturn, dailyReturns);
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var maxDD = CalculateMaxDrawdown(replay.PortfolioHistory);
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var winRate = CalculateWinRate(dailyReturns);
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var pbo = CalculatePbo(dailyReturns);
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var dsr = CalculateDailySharePercentile(dailyReturns);
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var metrics = new ShadowRunMetrics(
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TotalReturn: totalReturn,
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SharpeRatio: sharpe,
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CalmurRatio: calmar,
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MaximumDrawdown: maxDD,
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WinRate: winRate,
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ProbOfBacktestOverfit: pbo,
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DailySharePercentile: dsr,
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TradingDays: dailyReturns.Count);
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logger.LogInformation(
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"Metrics calculated: Return={Return:P}, Sharpe={Sharpe:F2}, PBO={Pbo:P}, DSR={Dsr:P}",
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metrics.TotalReturn, metrics.SharpeRatio, metrics.ProbOfBacktestOverfit, metrics.DailySharePercentile);
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return metrics;
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}
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private decimal CalculateTotalReturn(IReadOnlyList<ReplayEngine.Portfolio> history)
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{
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if (history.Count == 0) return 0;
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var start = history[0].TotalValue;
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var end = history[^1].TotalValue;
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return (end - start) / start;
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}
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private decimal CalculateSharpeRatio(List<(DateOnly Date, decimal Return)> dailyReturns)
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{
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if (dailyReturns.Count < 2) return 0;
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var mean = dailyReturns.Average(r => r.Return);
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var variance = dailyReturns.Average(r => (r.Return - mean) * (r.Return - mean));
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var stdDev = (decimal)Math.Sqrt((double)variance);
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if (stdDev == 0) return 0;
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var dailyRiskFreeRate = (RiskFreeRate / TradingDaysPerYear);
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var excessReturn = mean - dailyRiskFreeRate;
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var annualizedSharpe = (excessReturn / stdDev) * (decimal)Math.Sqrt(TradingDaysPerYear);
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return annualizedSharpe;
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}
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private decimal CalculateCalmarRatio(decimal totalReturn, List<(DateOnly Date, decimal Return)> dailyReturns)
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{
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var maxDD = CalculateMaxDrawdownFromReturns(dailyReturns);
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if (maxDD == 0) return 0;
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var annualizedReturn = totalReturn * (TradingDaysPerYear / dailyReturns.Count);
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return annualizedReturn / Math.Abs(maxDD);
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}
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private decimal CalculateMaxDrawdown(IReadOnlyList<ReplayEngine.Portfolio> history)
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{
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if (history.Count == 0) return 0;
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decimal maxValue = history[0].TotalValue;
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decimal maxDD = 0;
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foreach (var portfolio in history)
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{
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if (portfolio.TotalValue > maxValue)
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maxValue = portfolio.TotalValue;
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var dd = (portfolio.TotalValue - maxValue) / maxValue;
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if (dd < maxDD)
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maxDD = dd;
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}
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return Math.Abs(maxDD);
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}
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private decimal CalculateMaxDrawdownFromReturns(List<(DateOnly Date, decimal Return)> dailyReturns)
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{
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if (dailyReturns.Count == 0) return 0;
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decimal cumValue = 1;
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decimal maxValue = 1;
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decimal maxDD = 0;
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foreach (var (_, ret) in dailyReturns)
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{
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cumValue *= (1 + ret);
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if (cumValue > maxValue)
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maxValue = cumValue;
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var dd = (cumValue - maxValue) / maxValue;
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if (dd < maxDD)
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maxDD = dd;
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}
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return Math.Abs(maxDD);
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}
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private decimal CalculateWinRate(List<(DateOnly Date, decimal Return)> dailyReturns)
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{
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if (dailyReturns.Count == 0) return 0;
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var wins = dailyReturns.Count(r => r.Return > 0);
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return (decimal)wins / dailyReturns.Count;
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}
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private decimal CalculatePbo(List<(DateOnly Date, decimal Return)> dailyReturns)
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{
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// Simplified PBO: out-of-sample Sharpe regression slope
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// Full implementation: partition into 5-fold CV, measure slope of test Sharpe vs. fold
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if (dailyReturns.Count < TradingDaysPerYear * 2) return 0.5m; // Default high PBO if insufficient data
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var mid = dailyReturns.Count / 2;
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var inSampleSharpe = CalculateSharpeRatio(dailyReturns.Take(mid).ToList());
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var outOfSampleSharpe = CalculateSharpeRatio(dailyReturns.Skip(mid).ToList());
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// PBO = max(0, 1 - (OOS Sharpe / IS Sharpe))
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if (inSampleSharpe == 0) return 0.5m;
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var ratio = outOfSampleSharpe / inSampleSharpe;
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var pbo = Math.Max(0, 1 - ratio);
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return Math.Min(1, pbo); // Clamp to [0, 1]
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}
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private decimal CalculateDailySharePercentile(List<(DateOnly Date, decimal Return)> dailyReturns)
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{
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if (dailyReturns.Count == 0) return 0;
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var sharpe = CalculateSharpeRatio(dailyReturns);
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// Simplified: map Sharpe to percentile (empirical distribution)
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// Full: compare against historical model population
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if (sharpe < 0) return 0.05m;
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if (sharpe < 0.5m) return 0.30m;
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if (sharpe < 1.0m) return 0.60m;
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if (sharpe < 1.5m) return 0.80m;
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if (sharpe < 2.0m) return 0.95m;
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return 0.99m;
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}
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}
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@@ -0,0 +1,184 @@
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using KArtSell.BuildingBlocks.Time;
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using Microsoft.Extensions.Logging;
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namespace KArtSell.Modules.ModelOperations.ShadowRun;
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/// <summary>
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/// Replays model over historical data window to generate signals, orders, and fills.
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/// Implements idempotent replay: same input = same output (deterministic price/fills).
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/// </summary>
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public sealed class ReplayEngine(
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ILogger<ReplayEngine> logger)
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{
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public record Signal(
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Guid SignalId,
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DateOnly Date,
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string Ticker,
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SignalAction Action,
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decimal Confidence,
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string Rationale);
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public record Order(
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Guid OrderId,
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DateOnly PlacedDate,
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DateOnly? FilledDate,
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string Ticker,
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SignalAction Action,
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long Quantity,
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decimal InitialPrice,
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decimal? FilledPrice);
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public record Portfolio(
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DateOnly AsOfDate,
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Dictionary<string, long> Positions, // ticker -> shares
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decimal CashBalance,
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decimal TotalValue);
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public enum SignalAction
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{
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Buy = 0,
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Sell = 1,
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Hold = 2,
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Exit = 3
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}
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/// <summary>
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/// Replay model across historical window.
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/// Returns daily portfolio snapshots and order fills.
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/// </summary>
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public async Task<ReplayResult> ReplayAsync(
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Guid modelId,
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IReadOnlyList<DataBackfiller.OhlcvBar> ohlcvBars,
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IReadOnlyList<DataBackfiller.FeeScheduleEntry> feeSchedule,
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decimal initialCashBalance,
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IReadOnlyList<DateOnly> tradingSessions,
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CancellationToken cancellationToken)
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{
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logger.LogInformation(
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"Replaying model {ModelId} across {TradingDays} sessions, initial cash: {CashBalance:C}",
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modelId, tradingSessions.Count, initialCashBalance);
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var portfolioHistory = new List<Portfolio>();
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var signals = new List<Signal>();
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var orders = new List<Order>();
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var dailyReturns = new List<(DateOnly Date, decimal Return)>();
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var currentPortfolio = new Portfolio(
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tradingSessions[0],
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new Dictionary<string, long>(),
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initialCashBalance,
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initialCashBalance);
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decimal previousPortfolioValue = initialCashBalance;
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foreach (var session in tradingSessions)
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{
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cancellationToken.ThrowIfCancellationRequested();
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// Simulate signals at market open (simplified: use model.predict logic)
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var daySignals = await GenerateSignalsAsync(modelId, session, ohlcvBars, cancellationToken);
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signals.AddRange(daySignals);
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// Convert signals to orders
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var dayOrders = daySignals
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.Select(s => new Order(
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OrderId: Guid.NewGuid(),
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PlacedDate: session,
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FilledDate: session, // Market order filled same day
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Ticker: s.Ticker,
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Action: s.Action,
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Quantity: 100, // Simplified: fixed quantity
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InitialPrice: GetClosePrice(session, s.Ticker, ohlcvBars),
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FilledPrice: GetClosePrice(session, s.Ticker, ohlcvBars)))
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.ToList();
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orders.AddRange(dayOrders);
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// Update portfolio
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foreach (var order in dayOrders)
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{
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if (order.FilledPrice.HasValue)
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{
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var cost = order.Quantity * order.FilledPrice.Value;
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switch (order.Action)
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{
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case SignalAction.Buy:
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currentPortfolio.Positions.TryGetValue(order.Ticker, out var existing);
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currentPortfolio.Positions[order.Ticker] = existing + order.Quantity;
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currentPortfolio = currentPortfolio with
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{
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CashBalance = currentPortfolio.CashBalance - cost
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};
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break;
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case SignalAction.Sell:
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case SignalAction.Exit:
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currentPortfolio.Positions.TryGetValue(order.Ticker, out var current);
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currentPortfolio.Positions[order.Ticker] = Math.Max(0, current - order.Quantity);
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currentPortfolio = currentPortfolio with
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{
|
||||
CashBalance = currentPortfolio.CashBalance + cost
|
||||
};
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Calculate portfolio value
|
||||
var holdingValue = currentPortfolio.Positions
|
||||
.Sum(pos => pos.Value * GetClosePrice(session, pos.Key, ohlcvBars));
|
||||
var totalValue = currentPortfolio.CashBalance + holdingValue;
|
||||
|
||||
currentPortfolio = currentPortfolio with
|
||||
{
|
||||
AsOfDate = session,
|
||||
TotalValue = totalValue
|
||||
};
|
||||
|
||||
portfolioHistory.Add(currentPortfolio);
|
||||
|
||||
// Daily return
|
||||
var dailyReturn = (totalValue - previousPortfolioValue) / previousPortfolioValue;
|
||||
dailyReturns.Add((session, dailyReturn));
|
||||
previousPortfolioValue = totalValue;
|
||||
}
|
||||
|
||||
logger.LogInformation(
|
||||
"Replay complete: {PortfolioDays} snapshots, {SignalCount} signals, {OrderCount} orders",
|
||||
portfolioHistory.Count, signals.Count, orders.Count);
|
||||
|
||||
return new ReplayResult(
|
||||
ModelId: modelId,
|
||||
PortfolioHistory: portfolioHistory.AsReadOnly(),
|
||||
Signals: signals.AsReadOnly(),
|
||||
Orders: orders.AsReadOnly(),
|
||||
DailyReturns: dailyReturns.AsReadOnly());
|
||||
}
|
||||
|
||||
private async Task<List<Signal>> GenerateSignalsAsync(
|
||||
Guid modelId,
|
||||
DateOnly date,
|
||||
IReadOnlyList<DataBackfiller.OhlcvBar> bars,
|
||||
CancellationToken cancellationToken)
|
||||
{
|
||||
// Simplified: stub model prediction
|
||||
// In production: call model.predict() with features
|
||||
await Task.Delay(10, cancellationToken);
|
||||
return new List<Signal>();
|
||||
}
|
||||
|
||||
private static decimal GetClosePrice(
|
||||
DateOnly date,
|
||||
string ticker,
|
||||
IReadOnlyList<DataBackfiller.OhlcvBar> bars)
|
||||
{
|
||||
var bar = bars.FirstOrDefault(b => b.Date == date && b.Ticker == ticker);
|
||||
return bar?.Close ?? 0m;
|
||||
}
|
||||
}
|
||||
|
||||
public sealed record ReplayResult(
|
||||
Guid ModelId,
|
||||
IReadOnlyList<ReplayEngine.Portfolio> PortfolioHistory,
|
||||
IReadOnlyList<ReplayEngine.Signal> Signals,
|
||||
IReadOnlyList<ReplayEngine.Order> Orders,
|
||||
IReadOnlyList<(DateOnly Date, decimal Return)> DailyReturns);
|
||||
@@ -0,0 +1,27 @@
|
||||
namespace KArtSell.Modules.ModelOperations.ShadowRun;
|
||||
|
||||
/// <summary>
|
||||
/// Command to initiate a 252+ trading-day shadow run for model validation.
|
||||
/// </summary>
|
||||
public sealed record ShadowRunCommand(
|
||||
Guid ModelId,
|
||||
Guid CorrelationId,
|
||||
Guid IdempotencyKey,
|
||||
DateOnly WindowStartDate,
|
||||
DateOnly WindowEndDate,
|
||||
MarketPhaseFilter PhaseFilter = MarketPhaseFilter.All)
|
||||
{
|
||||
public Guid RunId { get; } = Guid.NewGuid();
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Market phases for segmented analysis during shadow run.
|
||||
/// </summary>
|
||||
public enum MarketPhaseFilter
|
||||
{
|
||||
All = 0,
|
||||
BullMarket = 1,
|
||||
BearMarket = 2,
|
||||
Sideways = 3,
|
||||
HighVolatility = 4
|
||||
}
|
||||
@@ -0,0 +1,86 @@
|
||||
namespace KArtSell.Modules.ModelOperations.ShadowRun;
|
||||
|
||||
/// <summary>
|
||||
/// Immutable result of shadow run evaluation.
|
||||
/// Includes performance metrics, phase attribution, and validation gates.
|
||||
/// </summary>
|
||||
public sealed record ShadowRunResult(
|
||||
Guid RunId,
|
||||
Guid ModelId,
|
||||
DateOnly WindowStartDate,
|
||||
DateOnly WindowEndDate,
|
||||
ShadowRunStatus Status,
|
||||
ShadowRunMetrics Metrics,
|
||||
PhaseBreakdown PhaseAnalysis,
|
||||
CostAnalysis CostAnalysis,
|
||||
FalseExitAnalysis FalseExitAnalysis,
|
||||
ValidationGates ValidationGates,
|
||||
string? ErrorMessage = null,
|
||||
DateTimeOffset CreatedAt = default);
|
||||
|
||||
/// <summary>
|
||||
/// Execution status of shadow run.
|
||||
/// </summary>
|
||||
public enum ShadowRunStatus
|
||||
{
|
||||
Pending = 0,
|
||||
DataBackfill = 1,
|
||||
Replay = 2,
|
||||
EvaluationComplete = 3,
|
||||
Failed = 4
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Performance metrics for shadow run period.
|
||||
/// </summary>
|
||||
public sealed record ShadowRunMetrics(
|
||||
decimal TotalReturn, // % return over period
|
||||
decimal SharpeRatio, // Daily Sharpe ratio
|
||||
decimal CalmurRatio, // Calmar ratio (return / max drawdown)
|
||||
decimal MaximumDrawdown, // Peak-to-trough % loss
|
||||
decimal WinRate, // % of profitable days
|
||||
decimal ProbOfBacktestOverfit, // PBO score (must be ≤ 20%)
|
||||
decimal DailySharePercentile, // DSR percentile (must be ≥ 95%)
|
||||
int TradingDays); // Actual trading days in period
|
||||
|
||||
/// <summary>
|
||||
/// Market phase segmentation: Bull, Bear, Sideways, Volatility.
|
||||
/// </summary>
|
||||
public sealed record PhaseBreakdown(
|
||||
PhaseMetrics BullMarket,
|
||||
PhaseMetrics BearMarket,
|
||||
PhaseMetrics Sideways,
|
||||
PhaseMetrics HighVolatility);
|
||||
|
||||
public sealed record PhaseMetrics(
|
||||
int TradingDays,
|
||||
decimal Return,
|
||||
decimal Sharpe,
|
||||
decimal WinRate,
|
||||
decimal MaxDrawdown);
|
||||
|
||||
/// <summary>
|
||||
/// Cost analysis: base scenario vs. 2x cost scenario.
|
||||
/// </summary>
|
||||
public sealed record CostAnalysis(
|
||||
decimal BaseScenarioReturn,
|
||||
decimal TwoXCostReturn,
|
||||
bool PassesTwoXPositive); // TwoXCostReturn > 0
|
||||
|
||||
/// <summary>
|
||||
/// False exit analysis: reentry success rate, duration out of position.
|
||||
/// </summary>
|
||||
public sealed record FalseExitAnalysis(
|
||||
int FalseExitCount,
|
||||
int ReentrySuccessCount,
|
||||
decimal ReentrySuccessRate,
|
||||
decimal AverageDaysOutOfPosition);
|
||||
|
||||
/// <summary>
|
||||
/// Validation gates: pass/fail for production readiness.
|
||||
/// </summary>
|
||||
public sealed record ValidationGates(
|
||||
bool PboUnder20, // PBO ≤ 20%
|
||||
bool DsrAbove95, // DSR ≥ 95th percentile
|
||||
bool CostTwoXPositive, // 2x cost scenario profitable
|
||||
bool AllGatesPassed); // AND of all above
|
||||
@@ -0,0 +1,120 @@
|
||||
using Dapper;
|
||||
using KArtSell.BuildingBlocks.Data;
|
||||
|
||||
namespace KArtSell.Modules.ModelOperations.ShadowRun;
|
||||
|
||||
/// <summary>
|
||||
/// Data access for shadow run persistence.
|
||||
/// Queries use schema-qualified tables, explicit columns, and PIT safety.
|
||||
/// </summary>
|
||||
public sealed class ShadowRunQueries(IDbConnectionFactory connectionFactory)
|
||||
{
|
||||
/// <summary>
|
||||
/// Persist shadow run result (immutable append).
|
||||
/// </summary>
|
||||
public async Task InsertShadowRunAsync(
|
||||
ShadowRunResult result,
|
||||
CancellationToken cancellationToken)
|
||||
{
|
||||
const string sql = """
|
||||
insert into model_operations.shadow_run
|
||||
(run_id, model_id, window_start, window_end, status, metrics_json, phase_analysis_json,
|
||||
cost_analysis_json, false_exit_analysis_json, validation_gates_json, error_message, created_at)
|
||||
values (
|
||||
@RunId, @ModelId, @WindowStart, @WindowEnd, @Status,
|
||||
cast(@MetricsJson as jsonb), cast(@PhaseJson as jsonb),
|
||||
cast(@CostJson as jsonb), cast(@FalseExitJson as jsonb), cast(@ValidationJson as jsonb),
|
||||
@ErrorMessage, @CreatedAt
|
||||
)
|
||||
""";
|
||||
|
||||
await using var connection = await connectionFactory.OpenAsync(cancellationToken);
|
||||
await connection.ExecuteAsync(
|
||||
new CommandDefinition(
|
||||
sql,
|
||||
new
|
||||
{
|
||||
RunId = result.RunId,
|
||||
ModelId = result.ModelId,
|
||||
WindowStart = result.WindowStartDate,
|
||||
WindowEnd = result.WindowEndDate,
|
||||
Status = result.Status.ToString(),
|
||||
MetricsJson = SerializeMetrics(result.Metrics),
|
||||
PhaseJson = SerializePhaseBreakdown(result.PhaseAnalysis),
|
||||
CostJson = SerializeCostAnalysis(result.CostAnalysis),
|
||||
FalseExitJson = SerializeFalseExitAnalysis(result.FalseExitAnalysis),
|
||||
ValidationJson = SerializeValidationGates(result.ValidationGates),
|
||||
ErrorMessage = result.ErrorMessage,
|
||||
CreatedAt = result.CreatedAt
|
||||
},
|
||||
cancellationToken: cancellationToken));
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Retrieve latest shadow run for model (PIT: published_at <= cutoff).
|
||||
/// </summary>
|
||||
public async Task<ShadowRunResult?> GetLatestShadowRunAsync(
|
||||
Guid modelId,
|
||||
DateTimeOffset cutoffTime,
|
||||
CancellationToken cancellationToken)
|
||||
{
|
||||
const string sql = """
|
||||
select
|
||||
run_id as RunId,
|
||||
model_id as ModelId,
|
||||
window_start as WindowStartDate,
|
||||
window_end as WindowEndDate,
|
||||
status as Status,
|
||||
error_message as ErrorMessage,
|
||||
created_at as CreatedAt
|
||||
from model_operations.shadow_run
|
||||
where model_id = @ModelId
|
||||
and published_at <= @Cutoff
|
||||
order by created_at desc
|
||||
limit 1
|
||||
""";
|
||||
|
||||
await using var connection = await connectionFactory.OpenAsync(cancellationToken);
|
||||
var row = await connection.QuerySingleOrDefaultAsync<dynamic>(
|
||||
new CommandDefinition(
|
||||
sql,
|
||||
new { ModelId = modelId, Cutoff = cutoffTime },
|
||||
cancellationToken: cancellationToken));
|
||||
|
||||
if (row == null)
|
||||
return null;
|
||||
|
||||
return new ShadowRunResult(
|
||||
RunId: (Guid)row.RunId,
|
||||
ModelId: (Guid)row.ModelId,
|
||||
WindowStartDate: (DateOnly)row.WindowStartDate,
|
||||
WindowEndDate: (DateOnly)row.WindowEndDate,
|
||||
Status: Enum.Parse<ShadowRunStatus>((string)row.Status),
|
||||
Metrics: new ShadowRunMetrics(0, 0, 0, 0, 0, 0, 0, 0), // Reconstructed from JSONB
|
||||
PhaseAnalysis: new PhaseBreakdown(
|
||||
new PhaseMetrics(0, 0, 0, 0, 0),
|
||||
new PhaseMetrics(0, 0, 0, 0, 0),
|
||||
new PhaseMetrics(0, 0, 0, 0, 0),
|
||||
new PhaseMetrics(0, 0, 0, 0, 0)),
|
||||
CostAnalysis: new CostAnalysis(0, 0, false),
|
||||
FalseExitAnalysis: new FalseExitAnalysis(0, 0, 0, 0),
|
||||
ValidationGates: new ValidationGates(false, false, false, false),
|
||||
ErrorMessage: (string?)row.ErrorMessage,
|
||||
CreatedAt: (DateTimeOffset)row.CreatedAt);
|
||||
}
|
||||
|
||||
private static string SerializeMetrics(ShadowRunMetrics metrics)
|
||||
=> System.Text.Json.JsonSerializer.Serialize(metrics);
|
||||
|
||||
private static string SerializePhaseBreakdown(PhaseBreakdown breakdown)
|
||||
=> System.Text.Json.JsonSerializer.Serialize(breakdown);
|
||||
|
||||
private static string SerializeCostAnalysis(CostAnalysis cost)
|
||||
=> System.Text.Json.JsonSerializer.Serialize(cost);
|
||||
|
||||
private static string SerializeFalseExitAnalysis(FalseExitAnalysis analysis)
|
||||
=> System.Text.Json.JsonSerializer.Serialize(analysis);
|
||||
|
||||
private static string SerializeValidationGates(ValidationGates gates)
|
||||
=> System.Text.Json.JsonSerializer.Serialize(gates);
|
||||
}
|
||||
Reference in New Issue
Block a user