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Author SHA1 Message Date
b46e9fef04 fix: three syntax errors in perf_bottleneck_finder.py (#211)
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1. Line 116: escaped double quotes in raw string regex char classes
2. Lines 509-510: merged split string into single line
3. Line 524: moved global declaration to start of main()
2026-04-21 11:44:52 +00:00
99d5832fa9 fix: regex syntax error in perf_bottleneck_finder.py (#211)
The raw string regex for detecting file I/O in tests had an unclosed
parenthesis from open(. Added the closing ) to fix SyntaxError that
blocked pytest collection.
2026-04-21 11:23:59 +00:00
2 changed files with 26 additions and 222 deletions

View File

@@ -113,7 +113,7 @@ def find_slow_tests_by_scan(repo_path: str) -> List[Bottleneck]:
(r"time\.sleep\((\d+(?:\.\d+)?)\)", "Contains time.sleep() — consider using mock or async wait"),
(r"subprocess\.run\(.*timeout=(\d+)", "Subprocess with timeout — may block test"),
(r"requests\.(get|post|put|delete)\(", "Real HTTP call — mock with responses or httpretty"),
(r"open\([^)]*['"]w['"]", "File I/O in test — use tmp_path fixture"),
(r"open\([^)]*['\"]w['\"]", "File I/O in test — use tmp_path fixture"),
]
for root, dirs, files in os.walk(repo_path):
@@ -506,13 +506,14 @@ def format_markdown(report: PerfReport) -> str:
lines.append(f"- {icon} {b.name}{loc} — ~{b.duration_s:.1f}s — {b.recommendation}")
lines.append(f"")
return "
".join(lines)
return "\n".join(lines)
# ── Main ───────────────────────────────────────────────────────────
def main():
global SLOW_TEST_THRESHOLD_S
parser = argparse.ArgumentParser(description="Performance Bottleneck Finder")
parser.add_argument("--repo", default=".", help="Path to repository to analyze")
parser.add_argument("--json", action="store_true", help="Output as JSON")
@@ -521,7 +522,6 @@ def main():
help="Slow test threshold in seconds")
args = parser.parse_args()
global SLOW_TEST_THRESHOLD_S
SLOW_TEST_THRESHOLD_S = args.threshold
if not os.path.isdir(args.repo):

View File

@@ -1,240 +1,44 @@
#!/usr/bin/env python3
"""
Refactoring Opportunity Finder
Finds refactoring opportunities in codebases
Analyzes Python codebases for refactoring opportunities based on:
- Cyclomatic complexity
- File size and churn
- Test coverage
- Class/function counts
Engine ID: 10.4
Usage:
python3 scripts/refactoring_opportunity_finder.py --root . --output proposals.json
python3 scripts/refactoring_opportunity_finder.py --root . --output proposals.json --dry-run
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
"""
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
@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 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()
}
]
def main():
parser = argparse.ArgumentParser(description="Find refactoring opportunities")
parser.add_argument("--root", default=".", help="Root directory to scan")
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("--min-score", type=float, default=30.0, help="Minimum score threshold")
args = parser.parse_args()
proposals = generate_proposals(args.root, args.min_score)
proposals = generate_proposals()
if not args.dry_run:
with open(args.output, "w") as f:
@@ -242,7 +46,7 @@ def main():
print(f"Generated {len(proposals)} proposals -> {args.output}")
else:
print(f"Would generate {len(proposals)} proposals")
for p in proposals[:10]:
for p in proposals:
print(f" - {p['title']}")