schmidt.florian
5977c81002
- German-dialect scalar parsers in Core (GermanNumber/Money/Date, ValueCell): decimal comma, thousands dot, unit suffixes, € currency, both date shapes. - Declarative MappingProfile + RowClassifier (skip summary/blank/all-zero rows) + CsvImporter (CsvHelper) staging readings/events/manual-costs, with auto swap detection on register decreases and month-end anchoring for interleaved oil dates. - Four built-in ReferenceProfiles (Strom/Wasser/Heizöl/Kosten). - ImportService: commit as revertible import_batch + wholesale consumption recompute per affected meter (NormalizationService/MeterConfigFactory), revert by batch. - Reconciliation tests: all 4 CSVs match the sheet's own columns within tolerance (electricity 5 meters + Netz Einsparung, water swap→12, oil tank incl. deliveries + burner hours, cost category totals). Commit/revert round-trip verified on Timescale. 69 tests green (53 Core + 16 integration). Known follow-up (polish): historical imports can contend with the 30-day compression policy's background job; tests pause it. Consider retry-on-deadlock or deferred compression for large historical imports in production. Claude-Session: https://claude.ai/code/session_01WujdMtMJPbxDpDnMeK22rr
73 lines
3.0 KiB
C#
73 lines
3.0 KiB
C#
using MeterVault.Core.Domain;
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using MeterVault.Core.Normalization;
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using MeterVault.Infrastructure.Import;
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using static MeterVault.Integration.Tests.Reconciliation.ReconciliationSupport;
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namespace MeterVault.Integration.Tests.Reconciliation;
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/// <summary>
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/// Reconciles the five electricity meters and a derived virtual meter against the Strom sheet's
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/// own Verbrauch / Netz Einsparung columns (SDD §2.2). Runs without a database.
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/// </summary>
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public sealed class ElectricityReconciliationTests
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{
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private static MeterConfig Cumulative(int id) =>
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new() { MeterId = id, Mode = MeterMode.CumulativeCounter, Unit = "kWh" };
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private static MeterConfig Generation(int id) =>
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new() { MeterId = id, Mode = MeterMode.GenerationCounter, Unit = "kWh" };
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[Theory]
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[InlineData(ReferenceProfiles.Haus, 7)] // Haus Verbrauch
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[InlineData(ReferenceProfiles.Netz, 8)] // Netz Verbrauch
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[InlineData(ReferenceProfiles.Auto, 9)] // Auto Verbrauch
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[InlineData(ReferenceProfiles.Solar1, 10)] // Solar Erzeugung 1
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[InlineData(ReferenceProfiles.Solar2, 11)] // Solar Erzeugung 2
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public void Meter_consumption_matches_the_sheet(int meterId, int oracleColumn)
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{
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var staged = Stage(ReferenceProfiles.Electricity(), Electricity);
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var config = meterId is ReferenceProfiles.Solar1 or ReferenceProfiles.Solar2
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? Generation(meterId)
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: Cumulative(meterId);
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var computed = ByMonth(Normalize(staged, config));
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var oracle = OracleByMonth(ReadRows(Electricity), dateColumn: 0, valueColumn: oracleColumn, firstDataRow: 1);
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AssertReconciles(computed, oracle, tolerance: 1.0, $"meter {meterId}", minMatches: 20);
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}
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[Fact]
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public void Netz_einsparung_virtual_matches_the_sheet()
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{
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var staged = Stage(ReferenceProfiles.Electricity(), Electricity);
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var haus = Normalize(staged, Cumulative(ReferenceProfiles.Haus));
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var netz = Normalize(staged, Cumulative(ReferenceProfiles.Netz));
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var engine = NormalizationEngine.CreateDefault();
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var virtualContext = new NormalizationContext
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{
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Meter = new MeterConfig
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{
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MeterId = 100,
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Mode = MeterMode.Virtual,
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Unit = "kWh",
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Virtual = new VirtualSpec
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{
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Expression = $"m{ReferenceProfiles.Haus} - m{ReferenceProfiles.Netz}",
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ReferencedMeterIds = [ReferenceProfiles.Haus, ReferenceProfiles.Netz],
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},
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},
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ReferencedSeries = new Dictionary<int, IReadOnlyList<Consumption>>
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{
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[ReferenceProfiles.Haus] = haus,
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[ReferenceProfiles.Netz] = netz,
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},
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};
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var computed = ByMonth(engine.Normalize(virtualContext));
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var oracle = OracleByMonth(ReadRows(Electricity), dateColumn: 0, valueColumn: 13, firstDataRow: 1); // Netz Einsparung
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AssertReconciles(computed, oracle, tolerance: 1.0, "Netz Einsparung", minMatches: 20);
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}
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}
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