first (part 2: other directories)

ai-engine/tests/test_skip_logic.py

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+"""
+Unit Test for NEW Skip Logic in BetRecommender
+==============================================
+Run with: python ai-engine/tests/test_skip_logic.py
+"""
+
+import os
+import sys
+import unittest
+from dataclasses import dataclass
+from typing import Optional
+
+# Add paths
+sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
+
+from core.calculators.bet_recommender import BetRecommender, RecommendationResult, MarketPredictionDTO
+from core.calculators.risk_assessor import RiskAnalysis
+from core.calculators.match_result_calculator import MatchResultPrediction
+from core.calculators.over_under_calculator import OverUnderPrediction
+from config.config_loader import get_config
+
+@dataclass
+class DummyContext:
+    """Minimal mock for CalculationContext"""
+    odds_data: dict
+
+class TestSkipLogic(unittest.TestCase):
+
+    def setUp(self):
+        # Mock config to pass into BetRecommender
+        self.mock_config = {
+            "recommendations.market_weights": {"MS": 1.0, "ÇŞ": 0.9, "BTTS": 0.9, "2.5 Üst/Alt": 0.9},
+            "recommendations.safe_markets": ["ÇŞ", "1.5 Üst/Alt"],
+            "recommendations.market_accuracy": {"MS": 65, "ÇŞ": 75, "BTTS": 60, "2.5 Üst/Alt": 65},
+            "recommendations.baseline_accuracy": 65.0,
+            "recommendations.confidence_threshold": 60,
+            "recommendations.value_confidence_min": 45,
+            "recommendations.value_confidence_max": 60,
+            "recommendations.value_edge_margin": 0.03,
+            "recommendations.value_upgrade_edge": 5.0,
+            "recommendations.risk_safe_boost": 1.2,
+            "recommendations.risk_ms_penalty_high": 0.5,
+            "recommendations.risk_other_penalty": 0.7,
+            "recommendations.risk_ms_penalty_medium": 0.8,
+        }
+        self.recommender = BetRecommender(self.mock_config)
+
+    def _make_risk(self, level="MEDIUM", is_surprise=False):
+        return RiskAnalysis(risk_level=level, is_surprise_risk=is_surprise, risk_score=0.5)
+
+    def _make_ms_pred(self, pick, conf):
+        # pick: "1", "X", "2"
+        probs = {"1": {"ms_home_prob": 0.5, "ms_draw_prob": 0.3, "ms_away_prob": 0.2},
+                 "X": {"ms_home_prob": 0.2, "ms_draw_prob": 0.5, "ms_away_prob": 0.3},
+                 "2": {"ms_home_prob": 0.2, "ms_draw_prob": 0.3, "ms_away_prob": 0.5}}
+        p = probs.get(pick, probs["1"])
+        return MatchResultPrediction(
+            ms_pick=pick, ms_confidence=conf,
+            dc_pick="1X", dc_confidence=0,
+            dc_1x_prob=0.7, dc_x2_prob=0.7, dc_12_prob=0.7,
+            **p
+        )
+
+    def _make_ou_pred(self):
+        return OverUnderPrediction(
+            ou25_pick="2.5 Üst", ou25_confidence=50.0,
+            over_25_prob=0.55, under_25_prob=0.45,
+            
+            btts_pick="Var", btts_confidence=50.0,
+            btts_yes_prob=0.55, btts_no_prob=0.45,
+            
+            ou15_pick="1.5 Üst", ou15_confidence=60.0, over_15_prob=0.7, under_15_prob=0.3,
+            ou35_pick="3.5 Alt", ou35_confidence=50.0, over_35_prob=0.3, under_35_prob=0.7
+        )
+
+    def test_low_confidence_should_skip(self):
+        """Confidence < 45% should be SKIPPED"""
+        ms_pred = self._make_ms_pred(pick="2", conf=40.0)
+        ou_pred = self._make_ou_pred()
+        risk = self._make_risk("MEDIUM")
+        ctx = DummyContext(odds_data={"ms_2": 2.5})
+
+        res = self.recommender.calculate(ctx, ms_pred, ou_pred, risk)
+        
+        # Check if MS bet is skipped
+        ms_bet = next((b for b in res.skipped_bets if b.market_type == "MS"), None)
+        self.assertIsNotNone(ms_bet, "MS bet with 40% conf should be skipped!")
+        self.assertTrue(ms_bet.is_skip)
+
+    def test_good_confidence_should_recommend(self):
+        """Confidence > 60% and Good Odds should be RECOMMENDED"""
+        ms_pred = self._make_ms_pred(pick="1", conf=70.0)
+        ou_pred = self._make_ou_pred()
+        risk = self._make_risk("MEDIUM")
+        # Odds 1.80 for 70% prob = Good Value (Need real odds for MS to pass)
+        ctx = DummyContext(odds_data={"ms_1": 1.80, "ou15_o": 1.50}) # Added ou15 odds
+
+        res = self.recommender.calculate(ctx, ms_pred, ou_pred, risk)
+
+        # Check if ANY bet is recommended (doesn't have to be MS, but usually is)
+        self.assertGreater(len(res.recommended_bets), 0, "At least one bet should be recommended!")
+        # Check that MS bet is NOT skipped
+        ms_bet = next((b for b in res.recommended_bets if b.market_type == "MS"), None)
+        if ms_bet:
+            self.assertFalse(ms_bet.is_skip)
+
+    def test_negative_edge_should_skip(self):
+        """Even with high confidence, if Odds are too low (Bad Value), SKIP"""
+        ms_pred = self._make_ms_pred(pick="1", conf=70.0) # 70% prob
+        ou_pred = self._make_ou_pred()
+        risk = self._make_risk("MEDIUM")
+        # Odds 1.10 -> Implied 90%. Our prob is 70%. Edge is -20% -> SKIP
+        ctx = DummyContext(odds_data={"ms_1": 1.10})
+
+        res = self.recommender.calculate(ctx, ms_pred, ou_pred, risk)
+
+        ms_bet = next((b for b in res.skipped_bets if b.market_type == "MS"), None)
+        self.assertIsNotNone(ms_bet, "MS bet with terrible odds (Negative Edge) should be skipped!")
+        self.assertTrue(ms_bet.is_skip)
+
+    def test_no_bets_recommendation(self):
+        """If all bets are low confidence, best_bet should be None"""
+        ms_pred = self._make_ms_pred(pick="1", conf=30.0) # Very low conf
+        ou_pred = self._make_ou_pred()
+        # Reset ALL OU confs to low
+        ou_pred.ou25_confidence = 30.0
+        ou_pred.btts_confidence = 30.0
+        ou_pred.ou15_confidence = 30.0 # This was 60 in setUp, causing the fail!
+        ou_pred.ou35_confidence = 30.0
+        
+        risk = self._make_risk("MEDIUM")
+        ctx = DummyContext(odds_data={"ms_1": 2.0})
+
+        res = self.recommender.calculate(ctx, ms_pred, ou_pred, risk)
+
+        self.assertIsNone(res.best_bet, "If everything is skipped, there should be no best_bet.")
+        self.assertEqual(len(res.recommended_bets), 0, "No bets should be recommended!")
+
+if __name__ == '__main__':
+    print("🧪 Running Skip Logic Unit Tests...")
+    print("="*50)
+    unittest.main(verbosity=2)