以下是Python实现的脚本分析器，可以检测死循环和资源占用情况：
import ast
import sys
import time
import resource
from threading import Thread
class ScriptAnalyzer:
def __init__(self, script_path):
self.script_path = script_path
self.max_memory = 0
self.max_cpu = 0
self.timeout = 10 # 默认超时时间(秒)
def detect_infinite_loop(self, node):
"""检测AST中的潜在死循环"""
for child in ast.walk(node):
if isinstance(child, ast.While):
if not child.test or isinstance(child.test, ast.Constant) and child.test.value:
return True
return False
def analyze_resource_usage(self):
"""分析资源使用情况"""
start_time = time.time()
process = Thread(target=self._run_script)
process.start()
while process.is_alive():
if time.time() - start_time > self.timeout:
process.join(0)
return "Timeout: Possible infinite loop"
mem = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss
cpu = resource.getrusage(resource.RUSAGE_SELF).ru_utime
self.max_memory = max(self.max_memory, mem)
self.max_cpu = max(self.max_cpu, cpu)
return None
def _run_script(self):
"""执行目标脚本"""
with open(self.script_path) as f:
code = f.read()
exec(code, {'__name__': '__main__'})
def analyze(self):
"""主分析方法"""
with open(self.script_path) as f:
tree = ast.parse(f.read())
if self.detect_infinite_loop(tree):
return "Warning: Potential infinite loop detected"
result = self.analyze_resource_usage()
if result:
return result
return f"Analysis complete. Max memory: {self.max_memory} KB, Max CPU time: {self.max_cpu}s"
if __name__ == "__main__":
if len(sys.argv) < 2:
print("Usage: python script_analyzer.py
sys.exit(1)
analyzer = ScriptAnalyzer(sys.argv[1])
print(analyzer.analyze())
这个分析器通过AST解析检测潜在死循环，并监控内存和CPU使用情况。使用时需传入要分析的脚本路径，它会返回资源使用报告或潜在问题警告。
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