fix: implement refactoring_opportunity_finder API (#210)

The test file expects compute_file_complexity(), calculate_refactoring_score(),
and FileMetrics from the script, but only a stub generate_proposals() existed.

Implemented:
- compute_file_complexity(): AST-based cyclomatic complexity analysis
- calculate_refactoring_score(): weighted scoring (complexity, size, churn, coverage)
- FileMetrics: dataclass with all required fields
- Full generate_proposals() that scans directories and produces scored proposals

All 10 tests pass. py_compile succeeds.

Closes #210

.gitignore

@@ -0,0 +1,2 @@
+__pycache__/
+*.pyc

scripts/refactoring_opportunity_finder.py

@@ -10,37 +10,273 @@ Usage:
 """
 
 import argparse
+import ast
 import json
+import os
 import sys
+from dataclasses import dataclass, field
 from datetime import datetime, timezone
+from typing import Optional, Tuple
 
 
-def generate_proposals():
-    """Generate sample proposals for this engine."""
-    # TODO: Implement actual proposal generation logic
-    return [
-        {
-            "title": f"Sample improvement from 10.4",
-            "description": "This is a sample improvement proposal",
-            "impact": 5,
-            "effort": 3,
-            "category": "improvement",
-            "source_engine": "10.4",
-            "timestamp": datetime.now(timezone.utc).isoformat()
-        }
-    ]
+# ── Data Classes ────────────────────────────────────────────────────────
 
+@dataclass
+class FileMetrics:
+    """Metrics for a single source file."""
+    path: str
+    lines: int = 0
+    complexity: float = 0.0
+    max_complexity: int = 0
+    functions: int = 0
+    classes: int = 0
+    churn_30d: int = 0
+    churn_90d: int = 0
+    test_coverage: Optional[float] = None
+    refactoring_score: float = 0.0
+
+
+# ── Complexity Analysis ─────────────────────────────────────────────────
+
+class ComplexityVisitor(ast.NodeVisitor):
+    """AST visitor that computes cyclomatic complexity per function."""
+
+    def __init__(self):
+        self.complexities = []
+        self.function_count = 0
+        self.class_count = 0
+        self._current_complexity = 0
+        self._in_function = False
+
+    def visit_FunctionDef(self, node):
+        self.function_count += 1
+        old_complexity = self._current_complexity
+        old_in_function = self._in_function
+        self._current_complexity = 1  # Base complexity
+        self._in_function = True
+
+        self.generic_visit(node)
+
+        self.complexities.append(self._current_complexity)
+        self._current_complexity = old_complexity
+        self._in_function = old_in_function
+
+    visit_AsyncFunctionDef = visit_FunctionDef
+
+    def visit_ClassDef(self, node):
+        self.class_count += 1
+        self.generic_visit(node)
+
+    def visit_If(self, node):
+        if self._in_function:
+            self._current_complexity += 1
+        self.generic_visit(node)
+
+    def visit_For(self, node):
+        if self._in_function:
+            self._current_complexity += 1
+        self.generic_visit(node)
+
+    visit_AsyncFor = visit_For
+
+    def visit_While(self, node):
+        if self._in_function:
+            self._current_complexity += 1
+        self.generic_visit(node)
+
+    def visit_ExceptHandler(self, node):
+        if self._in_function:
+            self._current_complexity += 1
+        self.generic_visit(node)
+
+    def visit_With(self, node):
+        if self._in_function:
+            self._current_complexity += 1
+        self.generic_visit(node)
+
+    visit_AsyncWith = visit_With
+
+    def visit_Assert(self, node):
+        if self._in_function:
+            self._current_complexity += 1
+        self.generic_visit(node)
+
+    def visit_BoolOp(self, node):
+        # Each 'and'/'or' adds a branch
+        if self._in_function:
+            self._current_complexity += len(node.values) - 1
+        self.generic_visit(node)
+
+    def visit_IfExp(self, node):
+        # Ternary expression
+        if self._in_function:
+            self._current_complexity += 1
+        self.generic_visit(node)
+
+
+def compute_file_complexity(filepath: str) -> Tuple[float, int, int, int, int]:
+    """
+    Compute cyclomatic complexity for a Python file.
+
+    Returns:
+        (avg_complexity, max_complexity, function_count, class_count, line_count)
+    """
+    try:
+        with open(filepath, 'r', encoding='utf-8', errors='replace') as f:
+            source = f.read()
+    except (IOError, OSError):
+        return 0.0, 0, 0, 0, 0
+
+    try:
+        tree = ast.parse(source, filename=filepath)
+    except SyntaxError:
+        return 0.0, 0, 0, 0, 0
+
+    visitor = ComplexityVisitor()
+    visitor.visit(tree)
+
+    line_count = len(source.splitlines())
+
+    if not visitor.complexities:
+        # No functions, but might have classes
+        return 0.0, 0, visitor.function_count, visitor.class_count, line_count
+
+    avg = sum(visitor.complexities) / len(visitor.complexities)
+    max_c = max(visitor.complexities)
+
+    return avg, max_c, visitor.function_count, visitor.class_count, line_count
+
+
+# ── Refactoring Score ───────────────────────────────────────────────────
+
+def calculate_refactoring_score(metrics: FileMetrics) -> float:
+    """
+    Calculate a refactoring priority score (0-100) based on file metrics.
+
+    Higher score = higher priority for refactoring.
+    Components:
+        - Complexity (0-30 points): higher avg/max complexity = higher score
+        - Size (0-20 points): larger files = higher score
+        - Churn (0-30 points): more changes recently = higher score
+        - Coverage (0-20 points): lower test coverage = higher score
+    """
+    score = 0.0
+
+    # Complexity component (0-30)
+    # avg=10+ or max=20+ → 30 points
+    complexity_score = min(30.0, (metrics.complexity * 2) + (metrics.max_complexity * 0.5))
+    score += max(0.0, complexity_score)
+
+    # Size component (0-20)
+    # 500+ lines → 20 points
+    size_score = min(20.0, metrics.lines / 25.0)
+    score += max(0.0, size_score)
+
+    # Churn component (0-30)
+    # Weighted: recent churn (30d) counts more than older (90d)
+    churn_score = min(30.0, (metrics.churn_30d * 2) + (metrics.churn_90d * 0.5))
+    score += max(0.0, churn_score)
+
+    # Coverage component (0-20)
+    # Lower coverage → higher score
+    if metrics.test_coverage is not None:
+        # coverage=0 → 20 points, coverage=1 → 0 points
+        coverage_score = (1.0 - metrics.test_coverage) * 20.0
+    else:
+        # No data → assume medium risk (10 points)
+        coverage_score = 10.0
+    score += max(0.0, coverage_score)
+
+    return min(100.0, max(0.0, score))
+
+
+# ── Proposal Generation ─────────────────────────────────────────────────
+
+def scan_directory(directory: str, extensions: tuple = ('.py',)) -> list:
+    """Scan directory for source files."""
+    files = []
+    for root, dirs, filenames in os.walk(directory):
+        # Skip hidden dirs and common non-source dirs
+        dirs[:] = [d for d in dirs if not d.startswith('.') and d not in (
+            '__pycache__', 'node_modules', 'venv', '.venv', 'env',
+            'build', 'dist', '.git', '.tox'
+        )]
+        for fname in filenames:
+            if any(fname.endswith(ext) for ext in extensions):
+                files.append(os.path.join(root, fname))
+    return files
+
+
+def generate_proposals(directory: str = '.', min_score: float = 30.0) -> list:
+    """Generate refactoring proposals by analyzing source files."""
+    proposals = []
+    files = scan_directory(directory)
+
+    for filepath in files:
+        avg, max_c, funcs, classes, lines = compute_file_complexity(filepath)
+
+        if funcs == 0 and classes == 0:
+            continue
+
+        metrics = FileMetrics(
+            path=filepath,
+            lines=lines,
+            complexity=avg,
+            max_complexity=max_c,
+            functions=funcs,
+            classes=classes
+        )
+        score = calculate_refactoring_score(metrics)
+        metrics.refactoring_score = score
+
+        if score >= min_score:
+            reasons = []
+            if max_c > 10:
+                reasons.append(f"high max complexity ({max_c})")
+            if avg > 5:
+                reasons.append(f"high avg complexity ({avg:.1f})")
+            if lines > 300:
+                reasons.append(f"large file ({lines} lines)")
+
+            proposals.append({
+                "title": f"Refactor {os.path.basename(filepath)} (score: {score:.0f})",
+                "description": f"{filepath}: {', '.join(reasons) if reasons else 'general improvement candidate'}",
+                "impact": min(10, int(score / 10)),
+                "effort": min(10, max(1, int(max_c / 3))),
+                "category": "refactoring",
+                "source_engine": "10.4",
+                "timestamp": datetime.now(timezone.utc).isoformat(),
+                "metrics": {
+                    "path": filepath,
+                    "score": round(score, 2),
+                    "avg_complexity": round(avg, 2),
+                    "max_complexity": max_c,
+                    "lines": lines,
+                    "functions": funcs,
+                    "classes": classes
+                }
+            })
+
+    # Sort by score descending
+    proposals.sort(key=lambda p: p.get('metrics', {}).get('score', 0), reverse=True)
+    return proposals
+
+
+# ── CLI ─────────────────────────────────────────────────────────────────
 
 def main():
     parser = argparse.ArgumentParser(description="Finds refactoring opportunities in codebases")
     parser.add_argument("--output", required=True, help="Output file for proposals")
     parser.add_argument("--dry-run", action="store_true", help="Don't write output file")
-    
+    parser.add_argument("--directory", default=".", help="Directory to scan")
+    parser.add_argument("--min-score", type=float, default=30.0, help="Minimum score threshold")
+
     args = parser.parse_args()
-    
-    proposals = generate_proposals()
-    
+
+    proposals = generate_proposals(args.directory, args.min_score)
+
     if not args.dry_run:
+        os.makedirs(os.path.dirname(args.output) or '.', exist_ok=True)
         with open(args.output, "w") as f:
             json.dump({"proposals": proposals}, f, indent=2)
         print(f"Generated {len(proposals)} proposals -> {args.output}")