refactor(dotnet): normalize decision learning records
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@@ -25,6 +25,12 @@ public sealed class DecisionLearningService
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object? trace = null,
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object? provenance = null)
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{
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decisionKey = RequireValue(decisionKey, nameof(decisionKey));
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instrumentId = RequireValue(instrumentId, nameof(instrumentId));
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action = RequireValue(action, nameof(action));
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gate = RequireValue(gate, nameof(gate));
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sourceVersion = RequireValue(sourceVersion, nameof(sourceVersion));
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var decisionId = await _store.AppendDecisionAsync(new DecisionEventRecord(
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decisionKey,
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decidedAt,
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@@ -33,29 +39,30 @@ public sealed class DecisionLearningService
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gate,
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score,
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sourceVersion,
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JsonSerializer.Serialize(trace ?? new { }),
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JsonSerializer.Serialize(provenance ?? new { })));
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SerializeJson(trace),
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SerializeJson(provenance)));
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foreach (var factor in factors)
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foreach (var factor in factors ?? throw new ArgumentNullException(nameof(factors)))
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{
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var normalizedFactor = NormalizeFactor(factor);
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var observationId = await _store.AppendSourceObservationAsync(new SourceObservationRecord(
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factor.ObservedAt,
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normalizedFactor.ObservedAt,
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instrumentId,
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factor.SourceName,
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normalizedFactor.SourceName,
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sourceVersion,
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factor.PayloadJson,
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factor.ProvenanceJson));
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normalizedFactor.PayloadJson,
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normalizedFactor.ProvenanceJson));
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var factorObservationId = await _store.AppendFactorObservationAsync(new FactorObservationRecord(
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observationId,
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factor.FactorObservationId,
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factor.FactorId,
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factor.FactorVersion,
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factor.ObservedAt,
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factor.NumericValue,
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factor.TextValue,
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factor.Gate,
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factor.ProvenanceJson));
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await _store.AppendDecisionFactorEvidenceAsync(decisionId, factorObservationId, factor.Role);
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normalizedFactor.FactorObservationId,
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normalizedFactor.FactorId,
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normalizedFactor.FactorVersion,
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normalizedFactor.ObservedAt,
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normalizedFactor.NumericValue,
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normalizedFactor.TextValue,
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normalizedFactor.Gate,
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normalizedFactor.ProvenanceJson));
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await _store.AppendDecisionFactorEvidenceAsync(decisionId, factorObservationId, normalizedFactor.Role);
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}
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return decisionId;
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@@ -83,7 +90,36 @@ public sealed class DecisionLearningService
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excessReturn,
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outcomeClass,
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evaluationGate,
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JsonSerializer.Serialize(provenance ?? new { })));
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SerializeJson(provenance)));
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}
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private static string SerializeJson(object? value)
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=> JsonSerializer.Serialize(value ?? new { });
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private static string RequireValue(string value, string parameterName)
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{
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if (string.IsNullOrWhiteSpace(value))
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{
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throw new ArgumentException("Value is required.", parameterName);
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}
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return value.Trim();
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}
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private static FactorEvidenceInput NormalizeFactor(FactorEvidenceInput factor)
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{
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ArgumentNullException.ThrowIfNull(factor);
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return factor with
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{
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FactorId = RequireValue(factor.FactorId, nameof(factor.FactorId)),
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FactorVersion = RequireValue(factor.FactorVersion, nameof(factor.FactorVersion)),
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SourceName = RequireValue(factor.SourceName, nameof(factor.SourceName)),
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PayloadJson = RequireValue(factor.PayloadJson, nameof(factor.PayloadJson)),
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ProvenanceJson = RequireValue(factor.ProvenanceJson, nameof(factor.ProvenanceJson)),
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Gate = RequireValue(factor.Gate, nameof(factor.Gate)),
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Role = RequireValue(factor.Role, nameof(factor.Role))
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};
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}
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}
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@@ -0,0 +1,91 @@
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using Moq;
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using QuantEngine.Application.Services;
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using QuantEngine.Core.Interfaces;
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namespace QuantEngine.Core.Tests;
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public class DecisionLearningServiceTests
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{
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[Fact]
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public async Task RecordDecisionAsync_TrimsAndPersistsNormalizedPayloads()
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{
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var store = new Mock<INormalizedLearningStore>(MockBehavior.Strict);
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Guid decisionId = Guid.NewGuid();
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Guid factorObservationId = Guid.NewGuid();
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Guid sourceObservationId = Guid.NewGuid();
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store.Setup(s => s.AppendDecisionAsync(It.Is<DecisionEventRecord>(r =>
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r.DecisionKey == "decision-1" &&
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r.InstrumentId == "005930" &&
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r.Action == "BUY" &&
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r.Gate == "PASS" &&
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r.SourceVersion == "v1" &&
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r.TraceJson.Contains("\"mode\":\"test\"") &&
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r.ProvenanceJson.Contains("\"origin\":\"unit\"")))).ReturnsAsync(decisionId);
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store.Setup(s => s.AppendSourceObservationAsync(It.Is<SourceObservationRecord>(r =>
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r.InstrumentId == "005930" &&
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r.SourceName == "kis" &&
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r.SourceVersion == "v1" &&
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r.PayloadJson == "{}" &&
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r.ProvenanceJson == "{}"))).ReturnsAsync(sourceObservationId);
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store.Setup(s => s.AppendFactorObservationAsync(It.Is<FactorObservationRecord>(r =>
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r.ObservationId == sourceObservationId &&
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r.FactorObservationId != Guid.Empty &&
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r.FactorId == "factor_a" &&
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r.FactorVersion == "1.0" &&
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r.Gate == "PASS" &&
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r.ProvenanceJson == "{}"))).ReturnsAsync(factorObservationId);
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store.Setup(s => s.AppendDecisionFactorEvidenceAsync(decisionId, factorObservationId, "primary"))
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.Returns(Task.CompletedTask);
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var service = new DecisionLearningService(store.Object);
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var result = await service.RecordDecisionAsync(
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" decision-1 ",
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DateTimeOffset.Parse("2026-07-13T00:00:00Z"),
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" 005930 ",
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" BUY ",
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" PASS ",
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12.5m,
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" v1 ",
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new[]
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{
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new FactorEvidenceInput(
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Guid.NewGuid(),
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" factor_a ",
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" 1.0 ",
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DateTimeOffset.Parse("2026-07-13T00:00:00Z"),
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3.14m,
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null,
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" PASS ",
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" primary ",
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" kis ",
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"{}",
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"{}")
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},
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new { mode = "test" },
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new { origin = "unit" });
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Assert.Equal(decisionId, result);
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store.VerifyAll();
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}
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[Fact]
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public async Task RecordDecisionAsync_RejectsMissingFactors()
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{
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var service = new DecisionLearningService(new Mock<INormalizedLearningStore>().Object);
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await Assert.ThrowsAsync<ArgumentNullException>(() => service.RecordDecisionAsync(
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"decision-1",
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DateTimeOffset.UtcNow,
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"005930",
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"BUY",
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"PASS",
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null,
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"v1",
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null!));
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}
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}
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