feat: implement refactoring_opportunity_finder API (#210)

- compute_file_complexity(): AST-based cyclomatic complexity
- calculate_refactoring_score(): weighted scoring (complexity, size, churn, coverage)
- FileMetrics dataclass with all expected fields
- generate_proposals(): scan codebase and rank files

Closes #210

scripts/refactoring_opportunity_finder.py

@@ -1,44 +1,240 @@
 #!/usr/bin/env python3
 """
-Finds refactoring opportunities in codebases
+Refactoring Opportunity Finder
 
-Engine ID: 10.4
+Analyzes Python codebases for refactoring opportunities based on:
+- Cyclomatic complexity
+- File size and churn
+- Test coverage
+- Class/function counts
 
 Usage:
-    python3 scripts/refactoring_opportunity_finder.py --output proposals/refactoring_opportunity_finder.json
-    python3 scripts/refactoring_opportunity_finder.py --output proposals/refactoring_opportunity_finder.json --dry-run
+    python3 scripts/refactoring_opportunity_finder.py --root . --output proposals.json
+    python3 scripts/refactoring_opportunity_finder.py --root . --output proposals.json --dry-run
 """
 
 import argparse
+import ast
 import json
+import os
 import sys
+from dataclasses import dataclass, field
 from datetime import datetime, timezone
+from pathlib import Path
+from typing import List, 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()
-        }
-    ]
+@dataclass
+class FileMetrics:
+    """Metrics for a single file."""
+    path: str
+    lines: int
+    complexity: float
+    max_complexity: int
+    functions: int
+    classes: int
+    churn_30d: int = 0
+    churn_90d: int = 0
+    test_coverage: Optional[float] = None
+    refactoring_score: float = 0.0
+
+
+def _compute_function_complexity(node: ast.FunctionDef) -> int:
+    """Compute cyclomatic complexity of a single function."""
+    complexity = 1  # Base complexity
+    for child in ast.walk(node):
+        if isinstance(child, (ast.If, ast.While, ast.For)):
+            complexity += 1
+        elif isinstance(child, ast.BoolOp):
+            # and/or add complexity for each additional value
+            complexity += len(child.values) - 1
+        elif isinstance(child, ast.ExceptHandler):
+            complexity += 1
+        elif isinstance(child, ast.Assert):
+            complexity += 1
+        elif isinstance(child, ast.comprehension):
+            complexity += 1
+            complexity += len(child.ifs)
+    return complexity
+
+
+def compute_file_complexity(filepath: str) -> Tuple[float, int, int, int, int]:
+    """
+    Compute complexity metrics 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 (OSError, IOError):
+        return 0.0, 0, 0, 0, 0
+    
+    lines = source.count("\n") + 1
+    
+    try:
+        tree = ast.parse(source, filename=filepath)
+    except SyntaxError:
+        return 0.0, 0, 0, 0, lines
+    
+    functions = []
+    classes = []
+    
+    for node in ast.walk(tree):
+        if isinstance(node, ast.ClassDef):
+            classes.append(node)
+        elif isinstance(node, ast.FunctionDef):
+            functions.append(node)
+    
+    if not functions:
+        return 0.0, 0, len(functions), len(classes), lines
+    
+    complexities = [_compute_function_complexity(fn) for fn in functions]
+    avg = sum(complexities) / len(complexities)
+    max_c = max(complexities) if complexities else 0
+    
+    return round(avg, 2), max_c, len(functions), len(classes), lines
+
+
+def calculate_refactoring_score(metrics: FileMetrics) -> float:
+    """
+    Calculate a refactoring priority score (0-100) based on metrics.
+    
+    Higher score = more urgent refactoring candidate.
+    
+    Components:
+    - Complexity (0-30): weighted by avg and max complexity
+    - Size (0-20): larger files score higher
+    - Churn (0-25): frequently changed files score higher
+    - Coverage (0-15): low/no coverage scores higher
+    - Density (0-10): many functions/classes in small space
+    """
+    import math
+    
+    score = 0.0
+    
+    # Complexity component (0-30)
+    # avg=5 -> ~10, avg=10 -> ~20, avg=15+ -> ~30
+    complexity_score = min(30, metrics.complexity * 2)
+    # Bonus for high max complexity
+    if metrics.max_complexity > 10:
+        complexity_score = min(30, complexity_score + (metrics.max_complexity - 10))
+    score += complexity_score
+    
+    # Size component (0-20)
+    # 50 lines -> ~2, 200 lines -> ~8, 500 lines -> ~15, 1000+ -> ~20
+    if metrics.lines > 0:
+        size_score = min(20, math.log2(max(1, metrics.lines)) * 2.5)
+    else:
+        size_score = 0
+    score += size_score
+    
+    # Churn component (0-25)
+    # Weighted combination of 30d and 90d churn
+    churn_score = min(25, (metrics.churn_30d * 1.5) + (metrics.churn_90d * 0.5))
+    score += churn_score
+    
+    # Coverage component (0-15)
+    # Low coverage = higher score
+    if metrics.test_coverage is None:
+        # No data -> assume medium risk
+        score += 5
+    elif metrics.test_coverage < 0.3:
+        score += 15
+    elif metrics.test_coverage < 0.5:
+        score += 10
+    elif metrics.test_coverage < 0.8:
+        score += 5
+    # else: good coverage, no penalty
+    
+    # Density component (0-10)
+    # Many functions/classes packed into small space
+    if metrics.lines > 0:
+        density = (metrics.functions + metrics.classes * 3) / (metrics.lines / 100)
+        density_score = min(10, density * 2)
+    else:
+        density_score = 0
+    score += density_score
+    
+    return round(min(100, max(0, score)), 2)
+
+
+def analyze_file(filepath: str, root: str = ".") -> Optional[FileMetrics]:
+    """Analyze a single Python file and return metrics."""
+    try:
+        rel_path = os.path.relpath(filepath, root)
+    except ValueError:
+        rel_path = filepath
+    
+    avg, max_c, funcs, classes, lines = compute_file_complexity(filepath)
+    
+    metrics = FileMetrics(
+        path=rel_path,
+        lines=lines,
+        complexity=avg,
+        max_complexity=max_c,
+        functions=funcs,
+        classes=classes,
+    )
+    metrics.refactoring_score = calculate_refactoring_score(metrics)
+    return metrics
+
+
+def find_python_files(root: str) -> List[str]:
+    """Find all Python files under root, excluding common non-source dirs."""
+    skip_dirs = {".git", "__pycache__", ".tox", ".eggs", "node_modules", ".venv", "venv", "env"}
+    files = []
+    for dirpath, dirnames, filenames in os.walk(root):
+        dirnames[:] = [d for d in dirnames if d not in skip_dirs]
+        for fn in filenames:
+            if fn.endswith(".py"):
+                files.append(os.path.join(dirpath, fn))
+    return sorted(files)
+
+
+def generate_proposals(root: str = ".", min_score: float = 30.0) -> List[dict]:
+    """Generate refactoring proposals for the codebase."""
+    files = find_python_files(root)
+    proposals = []
+    
+    for filepath in files:
+        metrics = analyze_file(filepath, root)
+        if metrics and metrics.refactoring_score >= min_score:
+            proposals.append({
+                "title": f"Refactor {metrics.path} (score: {metrics.refactoring_score})",
+                "description": (
+                    f"File has complexity avg={metrics.complexity:.1f} max={metrics.max_complexity}, "
+                    f"{metrics.functions} functions, {metrics.classes} classes, {metrics.lines} lines."
+                ),
+                "impact": min(10, int(metrics.refactoring_score / 10)),
+                "effort": min(10, max(1, int(metrics.complexity / 2))),
+                "category": "refactoring",
+                "source_engine": "refactoring_opportunity_finder",
+                "timestamp": datetime.now(timezone.utc).isoformat(),
+                "metrics": {
+                    "path": metrics.path,
+                    "complexity": metrics.complexity,
+                    "max_complexity": metrics.max_complexity,
+                    "lines": metrics.lines,
+                    "refactoring_score": metrics.refactoring_score,
+                }
+            })
+    
+    # Sort by score descending
+    proposals.sort(key=lambda p: p.get("metrics", {}).get("refactoring_score", 0), reverse=True)
+    return proposals
 
 
 def main():
-    parser = argparse.ArgumentParser(description="Finds refactoring opportunities in codebases")
+    parser = argparse.ArgumentParser(description="Find refactoring opportunities")
+    parser.add_argument("--root", default=".", help="Root directory to scan")
     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("--min-score", type=float, default=30.0, help="Minimum score threshold")
     args = parser.parse_args()
     
-    proposals = generate_proposals()
+    proposals = generate_proposals(args.root, args.min_score)
     
     if not args.dry_run:
         with open(args.output, "w") as f:
@@ -46,7 +242,7 @@ def main():
         print(f"Generated {len(proposals)} proposals -> {args.output}")
     else:
         print(f"Would generate {len(proposals)} proposals")
-        for p in proposals:
+        for p in proposals[:10]:
             print(f"  - {p['title']}")