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feat(database): 完成API层、Utils层和兼容层重构 (Stage 4-6)

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Stage 4: API层重构
=================
新增文件:
- api/crud.py (430行): CRUDBase泛型类，提供12个CRUD方法
  * get, get_by, get_multi, create, update, delete
  * count, exists, get_or_create, bulk_create, bulk_update
  * 集成缓存: 自动缓存读操作，写操作清除缓存
  * 集成批处理: 可选use_batch参数透明使用AdaptiveBatchScheduler

- api/query.py (461行): 高级查询构建器
  * QueryBuilder: 链式调用，MongoDB风格操作符
    - 操作符: __gt, __lt, __gte, __lte, __ne, __in, __nin, __like, __isnull
    - 方法: filter, filter_or, order_by, limit, offset, no_cache
    - 执行: all, first, count, exists, paginate
  * AggregateQuery: 聚合查询
    - sum, avg, max, min, group_by_count

- api/specialized.py (461行): 业务特定API
  * ActionRecords: store_action_info, get_recent_actions
  * Messages: get_chat_history, get_message_count, save_message
  * PersonInfo: get_or_create_person, update_person_affinity
  * ChatStreams: get_or_create_chat_stream, get_active_streams
  * LLMUsage: record_llm_usage, get_usage_statistics
  * UserRelationships: get_user_relationship, update_relationship_affinity

- 更新api/__init__.py: 导出所有API接口

Stage 5: Utils层实现
===================
新增文件:
- utils/decorators.py (320行): 数据库操作装饰器
  * @retry: 自动重试失败操作，指数退避
  * @timeout: 超时控制
  * @cached: 自动缓存函数结果
  * @measure_time: 性能测量，慢查询日志
  * @transactional: 事务管理，自动提交/回滚
  * @db_operation: 组合装饰器

- utils/monitoring.py (330行): 性能监控系统
  * DatabaseMonitor: 单例监控器
  * OperationMetrics: 操作指标 (次数、时间、错误)
  * DatabaseMetrics: 全局指标
    - 连接池统计
    - 缓存命中率
    - 批处理统计
    - 预加载统计
  * 便捷函数: get_monitor, record_operation, print_stats

- 更新utils/__init__.py: 导出装饰器和监控函数

Stage 6: 兼容层实现
==================
新增目录: compatibility/
- adapter.py (370行): 向后兼容适配器
  * 完全兼容旧API签名: db_query, db_save, db_get, store_action_info
  * 支持MongoDB风格操作符 (\, \, \)
  * 内部使用新架构 (QueryBuilder + CRUDBase)
  * 保持返回dict格式不变
  * MODEL_MAPPING: 25个模型映射

- __init__.py: 导出兼容API

更新database/__init__.py:
- 导出核心层 (engine, session, models, migration)
- 导出优化层 (cache, preloader, batch_scheduler)
- 导出API层 (CRUD, Query, 业务API)
- 导出Utils层 (装饰器, 监控)
- 导出兼容层 (db_query, db_save等)

核心特性
========
 类型安全: Generic[T]提供完整类型推断
 缓存透明: 自动缓存，用户无需关心
 批处理透明: 可选批处理，自动优化高频写入
 链式查询: 流畅的API设计
 业务封装: 常用操作封装成便捷函数
 向后兼容: 兼容层保证现有代码无缝迁移
 性能监控: 完整的指标收集和报告

统计数据
========
- 新增文件: 7个
- 代码行数: ~2050行
- API函数: 14个业务API + 6个装饰器
- 兼容函数: 5个 (db_query, db_save, db_get等)

下一步
======
- 更新28个文件的import语句 (从sqlalchemy_database_api迁移)
- 移动旧文件到old/目录
- 编写Stage 4-6的测试
- 集成测试验证兼容性
This commit is contained in:
Windpicker-owo
2025-11-01 13:27:33 +08:00
parent aae84ec454
commit 61de975d73
10 changed files with 2563 additions and 5 deletions
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src/common/database/compatibility/adapter.py Normal file
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"""兼容层适配器
提供向后兼容的API，将旧的数据库API调用转换为新架构的调用
保持原有函数签名和行为不变
"""
import time
from typing import Any, Optional
import orjson
from sqlalchemy import and_, asc, desc, select
from src.common.database.api import (
CRUDBase,
QueryBuilder,
store_action_info as new_store_action_info,
)
from src.common.database.core.models import (
ActionRecords,
CacheEntries,
ChatStreams,
Emoji,
Expression,
GraphEdges,
GraphNodes,
ImageDescriptions,
Images,
LLMUsage,
MaiZoneScheduleStatus,
Memory,
Messages,
OnlineTime,
PersonInfo,
PermissionNodes,
Schedule,
ThinkingLog,
UserPermissions,
UserRelationships,
)
from src.common.database.core.session import get_db_session
from src.common.logger import get_logger
logger = get_logger("database.compatibility")
# 模型映射表，用于通过名称获取模型类
MODEL_MAPPING = {
"Messages": Messages,
"ActionRecords": ActionRecords,
"PersonInfo": PersonInfo,
"ChatStreams": ChatStreams,
"LLMUsage": LLMUsage,
"Emoji": Emoji,
"Images": Images,
"ImageDescriptions": ImageDescriptions,
"OnlineTime": OnlineTime,
"Memory": Memory,
"Expression": Expression,
"ThinkingLog": ThinkingLog,
"GraphNodes": GraphNodes,
"GraphEdges": GraphEdges,
"Schedule": Schedule,
"MaiZoneScheduleStatus": MaiZoneScheduleStatus,
"CacheEntries": CacheEntries,
"UserRelationships": UserRelationships,
"PermissionNodes": PermissionNodes,
"UserPermissions": UserPermissions,
}
# 为每个模型创建CRUD实例
_crud_instances = {name: CRUDBase(model) for name, model in MODEL_MAPPING.items()}
async def build_filters(model_class, filters: dict[str, Any]):
"""构建查询过滤条件（兼容MongoDB风格操作符）
Args:
model_class: SQLAlchemy模型类
filters: 过滤条件字典
Returns:
条件列表
"""
conditions = []
for field_name, value in filters.items():
if not hasattr(model_class, field_name):
logger.warning(f"模型 {model_class.__name__} 中不存在字段 '{field_name}'")
continue
field = getattr(model_class, field_name)
if isinstance(value, dict):
# 处理 MongoDB 风格的操作符
for op, op_value in value.items():
if op == "$gt":
conditions.append(field > op_value)
elif op == "$lt":
conditions.append(field < op_value)
elif op == "$gte":
conditions.append(field >= op_value)
elif op == "$lte":
conditions.append(field <= op_value)
elif op == "$ne":
conditions.append(field != op_value)
elif op == "$in":
conditions.append(field.in_(op_value))
elif op == "$nin":
conditions.append(~field.in_(op_value))
else:
logger.warning(f"未知操作符 '{op}' (字段: '{field_name}')")
else:
# 直接相等比较
conditions.append(field == value)
return conditions
def _model_to_dict(instance) -> dict[str, Any]:
"""将模型实例转换为字典
Args:
instance: 模型实例
Returns:
字典表示
"""
if instance is None:
return None
result = {}
for column in instance.__table__.columns:
result[column.name] = getattr(instance, column.name)
return result
async def db_query(
model_class,
data: Optional[dict[str, Any]] = None,
query_type: Optional[str] = "get",
filters: Optional[dict[str, Any]] = None,
limit: Optional[int] = None,
order_by: Optional[list[str]] = None,
single_result: Optional[bool] = False,
) -> list[dict[str, Any]] | dict[str, Any] | None:
"""执行异步数据库查询操作（兼容旧API）
Args:
model_class: SQLAlchemy模型类
data: 用于创建或更新的数据字典
query_type: 查询类型 ("get", "create", "update", "delete", "count")
filters: 过滤条件字典
limit: 限制结果数量
order_by: 排序字段，前缀'-'表示降序
single_result: 是否只返回单个结果
Returns:
根据查询类型返回相应结果
"""
try:
if query_type not in ["get", "create", "update", "delete", "count"]:
raise ValueError("query_type must be 'get', 'create', 'update', 'delete' or 'count'")
# 获取CRUD实例
model_name = model_class.__name__
crud = _crud_instances.get(model_name)
if not crud:
crud = CRUDBase(model_class)
if query_type == "get":
# 使用QueryBuilder
query_builder = QueryBuilder(model_class)
# 应用过滤条件
if filters:
# 将MongoDB风格过滤器转换为QueryBuilder格式
for field_name, value in filters.items():
if isinstance(value, dict):
for op, op_value in value.items():
if op == "$gt":
query_builder = query_builder.filter(**{f"{field_name}__gt": op_value})
elif op == "$lt":
query_builder = query_builder.filter(**{f"{field_name}__lt": op_value})
elif op == "$gte":
query_builder = query_builder.filter(**{f"{field_name}__gte": op_value})
elif op == "$lte":
query_builder = query_builder.filter(**{f"{field_name}__lte": op_value})
elif op == "$ne":
query_builder = query_builder.filter(**{f"{field_name}__ne": op_value})
elif op == "$in":
query_builder = query_builder.filter(**{f"{field_name}__in": op_value})
elif op == "$nin":
query_builder = query_builder.filter(**{f"{field_name}__nin": op_value})
else:
query_builder = query_builder.filter(**{field_name: value})
# 应用排序
if order_by:
query_builder = query_builder.order_by(*order_by)
# 应用限制
if limit:
query_builder = query_builder.limit(limit)
# 执行查询
if single_result:
result = await query_builder.first()
return _model_to_dict(result)
else:
results = await query_builder.all()
return [_model_to_dict(r) for r in results]
elif query_type == "create":
if not data:
logger.error("创建操作需要提供data参数")
return None
instance = await crud.create(data)
return _model_to_dict(instance)
elif query_type == "update":
if not filters or not data:
logger.error("更新操作需要提供filters和data参数")
return None
# 先查找记录
query_builder = QueryBuilder(model_class)
for field_name, value in filters.items():
query_builder = query_builder.filter(**{field_name: value})
instance = await query_builder.first()
if not instance:
logger.warning(f"未找到匹配的记录: {filters}")
return None
# 更新记录
updated = await crud.update(instance.id, data)
return _model_to_dict(updated)
elif query_type == "delete":
if not filters:
logger.error("删除操作需要提供filters参数")
return None
# 先查找记录
query_builder = QueryBuilder(model_class)
for field_name, value in filters.items():
query_builder = query_builder.filter(**{field_name: value})
instance = await query_builder.first()
if not instance:
logger.warning(f"未找到匹配的记录: {filters}")
return None
# 删除记录
success = await crud.delete(instance.id)
return {"deleted": success}
elif query_type == "count":
query_builder = QueryBuilder(model_class)
# 应用过滤条件
if filters:
for field_name, value in filters.items():
query_builder = query_builder.filter(**{field_name: value})
count = await query_builder.count()
return {"count": count}
except Exception as e:
logger.error(f"数据库操作失败: {e}", exc_info=True)
return None if single_result or query_type != "get" else []
async def db_save(
model_class,
data: dict[str, Any],
key_field: str,
key_value: Any,
) -> Optional[dict[str, Any]]:
"""保存或更新记录（兼容旧API）
Args:
model_class: SQLAlchemy模型类
data: 数据字典
key_field: 主键字段名
key_value: 主键值
Returns:
保存的记录数据或None
"""
try:
model_name = model_class.__name__
crud = _crud_instances.get(model_name)
if not crud:
crud = CRUDBase(model_class)
# 使用get_or_create
instance = await crud.get_or_create(
defaults=data,
**{key_field: key_value},
)
return _model_to_dict(instance)
except Exception as e:
logger.error(f"保存数据库记录出错: {e}", exc_info=True)
return None
async def db_get(
model_class,
filters: Optional[dict[str, Any]] = None,
limit: Optional[int] = None,
order_by: Optional[str] = None,
single_result: Optional[bool] = False,
) -> list[dict[str, Any]] | dict[str, Any] | None:
"""从数据库获取记录（兼容旧API）
Args:
model_class: SQLAlchemy模型类
filters: 过滤条件
limit: 结果数量限制
order_by: 排序字段，前缀'-'表示降序
single_result: 是否只返回单个结果
Returns:
记录数据或None
"""
order_by_list = [order_by] if order_by else None
return await db_query(
model_class=model_class,
query_type="get",
filters=filters,
limit=limit,
order_by=order_by_list,
single_result=single_result,
)
async def store_action_info(
chat_stream=None,
action_build_into_prompt: bool = False,
action_prompt_display: str = "",
action_done: bool = True,
thinking_id: str = "",
action_data: Optional[dict] = None,
action_name: str = "",
) -> Optional[dict[str, Any]]:
"""存储动作信息到数据库（兼容旧API）
直接使用新的specialized API
"""
return await new_store_action_info(
chat_stream=chat_stream,
action_build_into_prompt=action_build_into_prompt,
action_prompt_display=action_prompt_display,
action_done=action_done,
thinking_id=thinking_id,
action_data=action_data,
action_name=action_name,
)