"""Unit tests for libs/backtest/tracker.py — SQS computation & journal I/O.""" from __future__ import annotations import json from pathlib import Path import pytest from libs.backtest.domain import ( JournalEntry, MetricsBundle, SplitResult, SQSWeights, ) from libs.backtest.tracker import ( _normalize, _normalize_inverse, append_journal_entry, build_split_result, check_duplicate, compute_sqs, get_next_entry_id, load_journal, rebuild_registry, ) # --------------------------------------------------------------------------- # _normalize / _normalize_inverse # --------------------------------------------------------------------------- class TestNormalize: def test_at_low_boundary(self): assert _normalize(0.8, low=0.8, high=2.0) == 0.0 def test_at_high_boundary(self): assert _normalize(2.0, low=0.8, high=2.0) == 100.0 def test_midpoint(self): assert _normalize(1.4, low=0.8, high=2.0) == pytest.approx(50.0) def test_below_low_clamps(self): assert _normalize(0.0, low=0.8, high=2.0) == 0.0 def test_above_high_clamps(self): assert _normalize(5.0, low=0.8, high=2.0) == 100.0 def test_none_returns_zero(self): assert _normalize(None, low=0.8, high=2.0) == 0.0 class TestNormalizeInverse: def test_dd_at_worst(self): # 10% drawdown = worst (0 pts) assert _normalize_inverse(10.0, low=10.0, high=1.0) == 0.0 def test_dd_at_best(self): # 1% drawdown = best (100 pts) assert _normalize_inverse(1.0, low=10.0, high=1.0) == 100.0 def test_dd_midpoint(self): assert _normalize_inverse(5.5, low=10.0, high=1.0) == pytest.approx(50.0) def test_none_returns_zero(self): assert _normalize_inverse(None, low=10.0, high=1.0) == 0.0 # --------------------------------------------------------------------------- # compute_sqs # --------------------------------------------------------------------------- class TestComputeSQS: def test_perfect_metrics(self): """All metrics at 100-point boundaries => SQS near 100.""" m = MetricsBundle( trade_count=200, profit_factor=2.0, total_return_pct=5.0, max_drawdown_pct=1.0, sharpe_ratio=2.0, win_rate=0.65, monthly_win_rate=0.70, equity_curve_r_squared=0.80, ) sqs, breakdown = compute_sqs(m) assert sqs == pytest.approx(100.0, abs=0.5) assert breakdown["profitability"] == pytest.approx(100.0, abs=0.5) assert breakdown["risk"] == pytest.approx(100.0, abs=0.5) assert breakdown["consistency"] == pytest.approx(100.0, abs=0.5) assert breakdown["robustness"] == pytest.approx(100.0, abs=0.5) def test_worst_metrics(self): """All metrics at 0-point boundaries => SQS = 0.""" m = MetricsBundle( trade_count=5, profit_factor=0.5, total_return_pct=-10.0, max_drawdown_pct=15.0, sharpe_ratio=-2.0, win_rate=0.20, monthly_win_rate=0.10, equity_curve_r_squared=-0.5, ) sqs, _ = compute_sqs(m) assert sqs == 0.0 def test_low_trade_penalty(self): """< 20 trades => SQS * 0.5.""" m = MetricsBundle( trade_count=15, profit_factor=1.5, total_return_pct=2.0, max_drawdown_pct=3.0, sharpe_ratio=1.0, win_rate=0.55, monthly_win_rate=0.55, equity_curve_r_squared=0.5, ) sqs_penalized, _ = compute_sqs(m) m_enough = m.model_copy(update={"trade_count": 100}) sqs_full, _ = compute_sqs(m_enough) # Penalised score should be roughly half (trade_count affects robustness sub-score too) assert sqs_penalized < sqs_full assert sqs_penalized > 0 def test_midrange_metrics(self): """Typical mid-range strategy should score 30-60.""" m = MetricsBundle( trade_count=80, profit_factor=1.1, total_return_pct=0.5, max_drawdown_pct=5.0, sharpe_ratio=0.5, win_rate=0.50, monthly_win_rate=0.50, equity_curve_r_squared=0.30, ) sqs, _ = compute_sqs(m) assert 30 <= sqs <= 65 def test_custom_weights(self): """Custom weights should change the SQS.""" m = MetricsBundle( trade_count=80, profit_factor=2.0, total_return_pct=5.0, max_drawdown_pct=8.0, sharpe_ratio=0.0, win_rate=0.40, monthly_win_rate=0.40, ) w_profit_heavy = SQSWeights(profitability=0.80, risk=0.10, consistency=0.05, robustness=0.05) w_risk_heavy = SQSWeights(profitability=0.10, risk=0.80, consistency=0.05, robustness=0.05) sqs_profit, _ = compute_sqs(m, w_profit_heavy) sqs_risk, _ = compute_sqs(m, w_risk_heavy) # This strategy has great profitability but mediocre risk assert sqs_profit > sqs_risk # --------------------------------------------------------------------------- # build_split_result # --------------------------------------------------------------------------- def test_build_split_result(): m = MetricsBundle( trade_count=50, profit_factor=1.2, total_return_pct=2.5, win_rate=0.55, max_drawdown_pct=3.0, sharpe_ratio=0.8, monthly_win_rate=0.60, equity_curve_r_squared=0.40, ) sr = build_split_result("test", "bt_run123", m) assert sr.run_id == "bt_run123" assert sr.trade_count == 50 assert sr.profit_factor == 1.2 assert sr.total_return_pct == 2.5 # --------------------------------------------------------------------------- # Journal I/O # --------------------------------------------------------------------------- class TestJournalIO: def test_append_and_load(self, tmp_path): journal_path = tmp_path / "journal.jsonl" entry = JournalEntry( entry_id="IMP-0001", timestamp="2026-03-16T12:00:00", experiment_name="test_exp_1", hypothesis="Test hypothesis", sqs_score=55.0, sqs_breakdown={"profitability": 60.0, "risk": 50.0, "consistency": 55.0, "robustness": 50.0}, verdict="better", ) append_journal_entry(journal_path, entry) entries = load_journal(journal_path) assert len(entries) == 1 assert entries[0].entry_id == "IMP-0001" assert entries[0].experiment_name == "test_exp_1" assert entries[0].sqs_score == 55.0 def test_multiple_entries(self, tmp_path): journal_path = tmp_path / "journal.jsonl" for i in range(3): entry = JournalEntry( entry_id=f"IMP-{i+1:04d}", timestamp=f"2026-03-{16+i}T12:00:00", experiment_name=f"exp_{i}", hypothesis=f"Hypothesis {i}", sqs_score=float(40 + i * 10), ) append_journal_entry(journal_path, entry) entries = load_journal(journal_path) assert len(entries) == 3 assert entries[2].sqs_score == 60.0 def test_get_next_entry_id(self, tmp_path): journal_path = tmp_path / "journal.jsonl" assert get_next_entry_id(journal_path) == "IMP-0001" entry = JournalEntry( entry_id="IMP-0001", timestamp="2026-03-16T12:00:00", experiment_name="exp_1", hypothesis="h", ) append_journal_entry(journal_path, entry) assert get_next_entry_id(journal_path) == "IMP-0002" def test_load_empty(self, tmp_path): journal_path = tmp_path / "nonexistent.jsonl" entries = load_journal(journal_path) assert entries == [] # --------------------------------------------------------------------------- # check_duplicate # --------------------------------------------------------------------------- class TestCheckDuplicate: def test_finds_duplicates(self, tmp_path): journal_path = tmp_path / "journal.jsonl" for name in ["exp_a", "exp_b", "exp_a"]: entry = JournalEntry( entry_id=get_next_entry_id(journal_path), timestamp="2026-03-16T12:00:00", experiment_name=name, hypothesis="h", ) append_journal_entry(journal_path, entry) dupes = check_duplicate(journal_path, "exp_a") assert len(dupes) == 2 def test_no_duplicates(self, tmp_path): journal_path = tmp_path / "journal.jsonl" entry = JournalEntry( entry_id="IMP-0001", timestamp="2026-03-16T12:00:00", experiment_name="exp_a", hypothesis="h", ) append_journal_entry(journal_path, entry) dupes = check_duplicate(journal_path, "exp_z") assert len(dupes) == 0 # --------------------------------------------------------------------------- # rebuild_registry # --------------------------------------------------------------------------- class TestRebuildRegistry: def test_registry_and_leaderboard(self, tmp_path): journal_path = tmp_path / "journal.jsonl" registry_path = tmp_path / "registry.json" leaderboard_path = tmp_path / "LEADERBOARD.md" # Create entries with different SQS scores for i, (name, sqs) in enumerate([("exp_low", 30.0), ("exp_high", 70.0), ("exp_mid", 50.0)]): test_result = SplitResult( run_id=f"bt_{name}", trade_count=60, profit_factor=1.0 + i * 0.2, total_return_pct=float(i), win_rate=0.5, ) entry = JournalEntry( entry_id=f"IMP-{i+1:04d}", timestamp=f"2026-03-{16+i}T12:00:00", experiment_name=name, hypothesis=f"h{i}", sqs_score=sqs, results={"test": test_result}, verdict="better" if sqs > 50 else "worse", ) append_journal_entry(journal_path, entry) registry = rebuild_registry(journal_path, registry_path, leaderboard_path) # Sorted by SQS descending assert len(registry.entries) == 3 assert registry.entries[0].experiment_name == "exp_high" assert registry.entries[0].sqs_score == 70.0 assert registry.entries[2].experiment_name == "exp_low" # Files exist assert registry_path.exists() assert leaderboard_path.exists() # Leaderboard contains table lb_text = leaderboard_path.read_text() assert "exp_high" in lb_text assert "exp_low" in lb_text assert "| # |" in lb_text