feat(fusion_accounting_bank_rec): matching strategies (AmountExact, FIFO, MultiInvoice)

Made-with: Cursor

fusion_accounting_bank_rec/services/__init__.py

@@ -1,2 +1,3 @@
 from . import memo_tokenizer
 from . import exchange_diff
+from . import matching_strategies

fusion_accounting_bank_rec/services/matching_strategies.py

@@ -0,0 +1,91 @@
+"""Matching strategy classes for the reconcile engine.
+
+Each strategy takes a bank amount + list of candidate journal items
+and returns a MatchResult with the picked ids + confidence + residual.
+Strategies are pure Python; no ORM dependency.
+"""
+
+from dataclasses import dataclass, field
+from itertools import combinations
+
+
+@dataclass
+class Candidate:
+    id: int
+    amount: float
+    partner_id: int
+    age_days: int
+
+
+@dataclass
+class MatchResult:
+    picked_ids: list[int] = field(default_factory=list)
+    confidence: float = 0.0
+    residual: float = 0.0  # bank_amount - sum(picked); positive = under-allocated
+    strategy_name: str = ""
+
+
+AMOUNT_TOLERANCE = 0.005  # currency rounding tolerance
+
+
+class AmountExactStrategy:
+    """Pick a single candidate whose amount equals the bank amount exactly.
+    If multiple candidates match exactly, pick the oldest (FIFO tiebreaker)."""
+
+    def match(self, *, bank_amount: float, candidates: list[Candidate]) -> MatchResult:
+        exact = [c for c in candidates if abs(c.amount - bank_amount) < AMOUNT_TOLERANCE]
+        if not exact:
+            return MatchResult(strategy_name='amount_exact')
+        oldest = max(exact, key=lambda c: c.age_days)
+        return MatchResult(
+            picked_ids=[oldest.id],
+            confidence=1.0,
+            residual=0.0,
+            strategy_name='amount_exact',
+        )
+
+
+class FIFOStrategy:
+    """Pick oldest candidates first until the bank amount is exhausted.
+    May produce partial reconcile residual if last candidate doesn't fit exactly."""
+
+    def match(self, *, bank_amount: float, candidates: list[Candidate]) -> MatchResult:
+        if not candidates:
+            return MatchResult(strategy_name='fifo')
+        oldest_first = sorted(candidates, key=lambda c: -c.age_days)
+        picked = []
+        remaining = bank_amount
+        for c in oldest_first:
+            if remaining <= AMOUNT_TOLERANCE:
+                break
+            picked.append(c.id)
+            remaining -= c.amount
+
+        confidence = 0.7 if remaining < AMOUNT_TOLERANCE else 0.5
+        return MatchResult(
+            picked_ids=picked,
+            confidence=confidence,
+            residual=remaining,
+            strategy_name='fifo',
+        )
+
+
+class MultiInvoiceStrategy:
+    """Find the smallest combination of candidates summing to the bank amount.
+    Bounded by max_combinations to keep complexity manageable."""
+
+    def __init__(self, max_combinations=3):
+        self.max_combinations = max_combinations
+
+    def match(self, *, bank_amount: float, candidates: list[Candidate]) -> MatchResult:
+        for k in range(2, self.max_combinations + 1):
+            for combo in combinations(candidates, k):
+                total = sum(c.amount for c in combo)
+                if abs(total - bank_amount) < AMOUNT_TOLERANCE:
+                    return MatchResult(
+                        picked_ids=[c.id for c in combo],
+                        confidence=0.85,
+                        residual=0.0,
+                        strategy_name=f'multi_invoice_{k}',
+                    )
+        return MatchResult(strategy_name='multi_invoice')