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remove gc

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jxxghp
2025-06-08 21:24:26 +08:00
parent 0a20234268
commit 203a111d1a
1 changed files with 160 additions and 71 deletions
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231
app/helper/memory.py
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@@ -104,57 +104,20 @@ class MemoryHelper(metaclass=Singleton):
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
snapshot_file = self._memory_snapshot_dir / f"memory_snapshot_{timestamp}.txt"
# 获取当前进程的内存使用情况
all_objects = muppy.get_objects()
sum1 = summary.summarize(all_objects)
# 获取系统内存使用情况
memory_usage = psutil.Process().memory_info().rss
# 写入内存快照文件
with open(snapshot_file, 'w', encoding='utf-8') as f:
f.write(f"内存快照时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
f.write(f"当前进程内存使用: {memory_usage / 1024 / 1024:.2f} MB\n")
f.write("=" * 80 + "\n")
f.write("对象类型统计:\n")
f.write("-" * 80 + "\n")
logger.info(f"开始创建内存快照: {snapshot_file}")
# 第一步：写入基本信息和对象类型统计
self._write_basic_info(snapshot_file, memory_usage)
# 第二步：分析并写入类实例内存使用情况
self._append_class_analysis(snapshot_file)
# 第三步：分析并写入大内存变量详情
self._append_variable_analysis(snapshot_file)
# 写入对象统计信息
for line in summary.format_(sum1):
f.write(line + "\n")
# 添加详细的类实例内存使用情况
f.write("\n" + "=" * 80 + "\n")
f.write("类实例内存使用情况 (按内存大小排序):\n")
f.write("-" * 80 + "\n")
try:
class_objects = self._get_class_memory_usage()
if class_objects:
for i, class_info in enumerate(class_objects[:50], 1): # 只显示前50个类
f.write(f"{i:3d}. {class_info['name']:<50} {class_info['size_mb']:>8.2f} MB ({class_info['count']} 个实例)\n")
else:
f.write("未找到有效的类实例信息\n")
except Exception as e:
logger.error(f"获取类实例信息失败: {e}")
f.write(f"获取类实例信息失败: {e}\n")
# 添加详细的变量内存使用情况
f.write("\n" + "=" * 80 + "\n")
f.write("大内存变量详情 (前100个):\n")
f.write("-" * 80 + "\n")
try:
large_variables = self._get_large_variables(100)
if large_variables:
for i, var_info in enumerate(large_variables, 1):
f.write(f"{i:3d}. {var_info['name']:<30} {var_info['type']:<15} {var_info['size_mb']:>8.2f} MB\n")
else:
f.write("未找到大内存变量\n")
except Exception as e:
logger.error(f"获取大内存变量信息失败: {e}")
f.write(f"获取变量信息失败: {e}\n")
logger.info(f"内存快照已保存: {snapshot_file}, 当前内存使用: {memory_usage / 1024 / 1024:.2f} MB")
# 清理过期的快照文件（保留最近30个）
@@ -163,6 +126,132 @@ class MemoryHelper(metaclass=Singleton):
except Exception as e:
logger.error(f"创建内存快照失败: {e}")
@staticmethod
def _write_basic_info(snapshot_file, memory_usage):
"""
写入基本信息和对象类型统计
"""
# 获取当前进程的内存使用情况
all_objects = muppy.get_objects()
sum1 = summary.summarize(all_objects)
with open(snapshot_file, 'w', encoding='utf-8') as f:
f.write(f"内存快照时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
f.write(f"当前进程内存使用: {memory_usage / 1024 / 1024:.2f} MB\n")
f.write("=" * 80 + "\n")
f.write("对象类型统计:\n")
f.write("-" * 80 + "\n")
# 写入对象统计信息
for line in summary.format_(sum1):
f.write(line + "\n")
# 立即刷新到磁盘
f.flush()
logger.debug("基本信息已写入快照文件")
def _append_class_analysis(self, snapshot_file):
"""
分析并追加类实例内存使用情况
"""
with open(snapshot_file, 'a', encoding='utf-8') as f:
f.write("\n" + "=" * 80 + "\n")
f.write("类实例内存使用情况 (按内存大小排序):\n")
f.write("-" * 80 + "\n")
f.write("正在分析中...\n")
# 立即刷新，让用户知道这部分开始了
f.flush()
try:
logger.debug("开始分析类实例内存使用情况")
class_objects = self._get_class_memory_usage()
# 重新打开文件，移除"正在分析中..."并写入实际结果
with open(snapshot_file, 'r', encoding='utf-8') as f:
content = f.read()
# 替换"正在分析中..."
content = content.replace("正在分析中...\n", "")
with open(snapshot_file, 'w', encoding='utf-8') as f:
f.write(content)
if class_objects:
# 只显示前100个类
for i, class_info in enumerate(class_objects[:100], 1):
f.write(f"{i:3d}. {class_info['name']:<50} "
f"{class_info['size_mb']:>8.2f} MB ({class_info['count']} 个实例)\n")
else:
f.write("未找到有效的类实例信息\n")
f.flush()
except Exception as e:
logger.error(f"获取类实例信息失败: {e}")
# 即使出错也要更新文件
with open(snapshot_file, 'r', encoding='utf-8') as f:
content = f.read()
content = content.replace("正在分析中...\n", f"获取类实例信息失败: {e}\n")
with open(snapshot_file, 'w', encoding='utf-8') as f:
f.write(content)
f.flush()
logger.debug("类实例分析已完成并写入")
def _append_variable_analysis(self, snapshot_file):
"""
分析并追加大内存变量详情
"""
with open(snapshot_file, 'a', encoding='utf-8') as f:
f.write("\n" + "=" * 80 + "\n")
f.write("大内存变量详情 (前100个):\n")
f.write("-" * 80 + "\n")
f.write("正在分析中...\n")
# 立即刷新，让用户知道这部分开始了
f.flush()
try:
logger.debug("开始分析大内存变量")
large_variables = self._get_large_variables(100)
# 重新打开文件，移除"正在分析中..."并写入实际结果
with open(snapshot_file, 'r', encoding='utf-8') as f:
content = f.read()
# 替换最后的"正在分析中..."
content = content.replace("正在分析中...\n", "")
with open(snapshot_file, 'w', encoding='utf-8') as f:
f.write(content)
if large_variables:
for i, var_info in enumerate(large_variables, 1):
f.write(
f"{i:3d}. {var_info['name']:<30} {var_info['type']:<15} {var_info['size_mb']:>8.2f} MB\n")
else:
f.write("未找到大内存变量\n")
f.flush()
except Exception as e:
logger.error(f"获取大内存变量信息失败: {e}")
# 即使出错也要更新文件
with open(snapshot_file, 'r', encoding='utf-8') as f:
content = f.read()
content = content.replace("正在分析中...\n", f"获取变量信息失败: {e}\n")
with open(snapshot_file, 'w', encoding='utf-8') as f:
f.write(content)
f.flush()
logger.debug("大内存变量分析已完成并写入")
def _cleanup_old_snapshots(self):
"""
清理过期的内存快照文件，只保留最近的指定数量文件
@@ -186,20 +275,20 @@ class MemoryHelper(metaclass=Singleton):
class_info = {}
processed_count = 0
error_count = 0
# 获取所有对象
all_objects = muppy.get_objects()
logger.debug(f"开始分析 {len(all_objects)} 个对象的类实例内存使用情况")
for obj in all_objects:
try:
# 跳过类对象本身，统计类的实例
if isinstance(obj, type):
continue
# 获取对象的类名 - 这里可能会出错
obj_class = type(obj)
# 安全地获取类名
try:
if hasattr(obj_class, '__module__') and hasattr(obj_class, '__name__'):
@@ -210,15 +299,15 @@ class MemoryHelper(metaclass=Singleton):
# 如果获取类名失败，使用简单的类型描述
class_name = f"<unknown_class_{id(obj_class)}>"
logger.debug(f"获取类名失败: {e}")
# 计算对象的内存使用
size_bytes = asizeof.asizeof(obj)
if size_bytes < 100: # 跳过太小的对象
continue
size_mb = size_bytes / 1024 / 1024
processed_count += 1
if class_name in class_info:
class_info[class_name]['size_mb'] += size_mb
class_info[class_name]['count'] += 1
@@ -228,16 +317,16 @@ class MemoryHelper(metaclass=Singleton):
'size_mb': size_mb,
'count': 1
}
except Exception as e:
# 捕获所有可能的异常，包括SQLAlchemy、ORM等框架的异常
error_count += 1
if error_count <= 5: # 只记录前5个错误，避免日志过多
logger.debug(f"分析对象时出错: {e}")
continue
logger.debug(f"类实例分析完成: 处理了 {processed_count} 个对象, 遇到 {error_count} 个错误")
# 按内存大小排序
sorted_classes = sorted(class_info.values(), key=lambda x: x['size_mb'], reverse=True)
return sorted_classes
@@ -248,43 +337,43 @@ class MemoryHelper(metaclass=Singleton):
"""
large_vars = []
processed_count = 0
# 获取所有对象
all_objects = muppy.get_objects()
logger.debug(f"开始分析 {len(all_objects)} 个对象的内存使用情况")
for obj in all_objects:
# 跳过类对象
if isinstance(obj, type):
continue
try:
# 计算对象大小
size_bytes = asizeof.asizeof(obj)
# 只处理大于10KB的对象，提高分析效率
if size_bytes < 10240:
continue
size_mb = size_bytes / 1024 / 1024
processed_count += 1
# 获取对象信息
var_info = self._get_variable_info(obj, size_mb)
if var_info:
large_vars.append(var_info)
# 如果已经找到足够多的大对象，可以提前结束
if len(large_vars) >= limit * 2: # 多收集一些，后面排序筛选
break
except Exception as e:
# 更广泛的异常捕获
logger.debug(f"分析对象失败: {e}")
continue
logger.debug(f"处理了 {processed_count} 个大对象，找到 {len(large_vars)} 个有效变量")
# 按内存大小排序并返回前N个
large_vars.sort(key=lambda x: x['size_mb'], reverse=True)
return large_vars[:limit]
@@ -295,10 +384,10 @@ class MemoryHelper(metaclass=Singleton):
"""
try:
obj_type = type(obj).__name__
# 尝试获取变量名
var_name = self._get_variable_name(obj)
# 生成描述性信息
if isinstance(obj, dict):
key_count = len(obj)
@@ -316,13 +405,13 @@ class MemoryHelper(metaclass=Singleton):
if hasattr(obj, '__dict__'):
attr_count = len(obj.__dict__)
var_name += f" ({attr_count}个属性)"
return {
'name': var_name,
'type': obj_type,
'size_mb': size_mb
}
except Exception as e:
logger.debug(f"获取变量信息失败: {e}")
return None