feat: export PostgreSQL training dataset as JSON

src/dotnet/QuantEngine.Application/Services/LearningDatasetService.cs

@@ -0,0 +1,29 @@
+using System.Text.Json;
+using QuantEngine.Core.Interfaces;
+
+namespace QuantEngine.Application.Services;
+
+public sealed class LearningDatasetService
+{
+    private readonly ILearningDatasetReader _reader;
+
+    public LearningDatasetService(ILearningDatasetReader reader) => _reader = reader;
+
+    public async Task<string> ExportJsonAsync(string outputPath, int limit = 1000)
+    {
+        var rows = await _reader.ReadTrainingExamplesAsync(limit);
+        var payload = new
+        {
+            formula_id = "ENGINE_HISTORY_TRAINING_DATASET_V1",
+            gate = rows.Count > 0 ? "PASS" : "DATA_MISSING",
+            generated_at = DateTimeOffset.UtcNow,
+            sample_count = rows.Count,
+            source = "engine_history.training_example_v1",
+            rows
+        };
+        var path = Path.GetFullPath(outputPath);
+        Directory.CreateDirectory(Path.GetDirectoryName(path)!);
+        await File.WriteAllTextAsync(path, JsonSerializer.Serialize(payload, new JsonSerializerOptions { WriteIndented = true }));
+        return path;
+    }
+}

src/dotnet/QuantEngine.Core/Interfaces/ILearningDatasetReader.cs

@@ -0,0 +1,6 @@
+namespace QuantEngine.Core.Interfaces;
+
+public interface ILearningDatasetReader
+{
+    Task<IReadOnlyList<IDictionary<string, object?>>> ReadTrainingExamplesAsync(int limit = 1000);
+}

src/dotnet/QuantEngine.Infrastructure/Repositories/LearningDatasetReader.cs

@@ -0,0 +1,24 @@
+using Dapper;
+using QuantEngine.Core.Interfaces;
+using QuantEngine.Infrastructure.Data;
+
+namespace QuantEngine.Infrastructure.Repositories;
+
+public sealed class LearningDatasetReader : ILearningDatasetReader
+{
+    private readonly IDbConnectionFactory _connectionFactory;
+
+    public LearningDatasetReader(IDbConnectionFactory connectionFactory) => _connectionFactory = connectionFactory;
+
+    public async Task<IReadOnlyList<IDictionary<string, object?>>> ReadTrainingExamplesAsync(int limit = 1000)
+    {
+        if (limit is < 1 or > 10000)
+            throw new ArgumentOutOfRangeException(nameof(limit));
+
+        using var connection = _connectionFactory.CreateConnection();
+        var rows = await connection.QueryAsync(
+            "SELECT * FROM engine_history.training_example_v1 ORDER BY decided_at DESC LIMIT @Limit",
+            new { Limit = limit });
+        return rows.Select(row => (IDictionary<string, object?>)row).ToList();
+    }
+}

src/dotnet/QuantEngine.Web/Program.cs

@@ -97,7 +97,9 @@ try
     builder.Services.AddScoped<IWorkspaceRepository, WorkspaceRepository>();
     builder.Services.AddScoped<IPostgresqlHistoryStore, PostgresqlHistoryStore>();
     builder.Services.AddScoped<INormalizedLearningStore, NormalizedLearningStore>();
+    builder.Services.AddScoped<ILearningDatasetReader, LearningDatasetReader>();
     builder.Services.AddScoped<DecisionLearningService>();
+    builder.Services.AddScoped<LearningDatasetService>();
     builder.Services.AddScoped<IPostgresqlHistorySnapshotReader, PostgresqlHistorySnapshotReader>();
     builder.Services.AddScoped<HistoryIngestionService>();
     builder.Services.AddScoped<ICollectionRepository, CollectionRepository>();