♻️ Refactor (#318)

* 🔧 启用一些 ruff 的新规则

*  添加开发依赖 nonebot-adapter-qq

*  添加依赖 nonebot-plugin-session

*  添加依赖 nonebot-plugin-session-orm

* 🔧 忽略 ruff 规则 ISC001
format 冲突风险

* 🚨 修复 ruff 警报

* ♻️ 重构!

* ♻️ 恢复定时获取 TetraLeague 数据的功能

*  统一处理需要捕获的错误

*  记录用户触发的指令
This commit is contained in:
呵呵です
2024-05-14 15:03:46 +08:00
committed by GitHub
parent e6c3a32532
commit c8832bd1c9
79 changed files with 2629 additions and 2174 deletions

View File

@@ -1,16 +1,14 @@
from collections.abc import Callable, Sequence
from datetime import datetime
from typing import Any
from typing import Any, Literal
from nonebot.adapters import Message
from nonebot.compat import PYDANTIC_V2, type_validate_json
from nonebot_plugin_orm import Model
from pydantic import BaseModel, ValidationError
from sqlalchemy import JSON, DateTime, Dialect, PickleType, String, TypeDecorator
from sqlalchemy import JSON, DateTime, Dialect, String, TypeDecorator
from sqlalchemy.orm import Mapped, MappedAsDataclass, mapped_column
from typing_extensions import override
from ..game_data_processor.schemas import BaseProcessedData, BaseUser
from ..utils.typing import CommandType, GameType
@@ -18,8 +16,16 @@ class PydanticType(TypeDecorator):
impl = JSON
@override
def __init__(self, get_model: Callable[[], Sequence[type[BaseModel]]], *args: Any, **kwargs: Any):
self.get_model = get_model
def __init__(
self,
get_model: Sequence[Callable[[], Sequence[type[BaseModel]]]],
models: set[type[BaseModel]],
*args: Any,
**kwargs: Any,
):
for i in get_model:
models.update(i())
self.models = models
super().__init__(*args, **kwargs)
if PYDANTIC_V2:
@@ -27,7 +33,7 @@ class PydanticType(TypeDecorator):
@override
def process_bind_param(self, value: Any | None, dialect: Dialect) -> str:
# 将 Pydantic 模型实例转换为 JSON
if isinstance(value, tuple(self.get_model())):
if isinstance(value, tuple(self.pydantic_models)):
return value.model_dump_json(by_alias=True) # type: ignore[union-attr]
raise TypeError
else:
@@ -35,7 +41,7 @@ class PydanticType(TypeDecorator):
@override
def process_bind_param(self, value: Any | None, dialect: Dialect) -> str:
# 将 Pydantic 模型实例转换为 JSON
if isinstance(value, tuple(self.get_model())):
if isinstance(value, tuple(self.pydantic_models)):
return value.json(by_alias=True) # type: ignore[union-attr]
raise TypeError
@@ -43,7 +49,7 @@ class PydanticType(TypeDecorator):
def process_result_value(self, value: Any | None, dialect: Dialect) -> BaseModel:
# 将 JSON 转换回 Pydantic 模型实例
if isinstance(value, str | bytes):
for i in self.get_model():
for i in self.pydantic_models:
try:
return type_validate_json(i, value)
except ValidationError: # noqa: PERF203
@@ -59,20 +65,11 @@ class Bind(MappedAsDataclass, Model):
game_account: Mapped[str]
class HistoricalData(MappedAsDataclass, Model):
class TriggerHistoricalData(MappedAsDataclass, Model):
id: Mapped[int] = mapped_column(init=False, primary_key=True)
trigger_time: Mapped[datetime] = mapped_column(DateTime)
bot_platform: Mapped[str | None] = mapped_column(String(32))
bot_account: Mapped[str | None]
source_type: Mapped[str | None] = mapped_column(String(32), index=True)
source_account: Mapped[str | None] = mapped_column(index=True)
message: Mapped[Message | None] = mapped_column(PickleType)
game_platform: Mapped[GameType] = mapped_column(String(32), index=True, init=False)
command_type: Mapped[CommandType] = mapped_column(String(16), index=True, init=False)
command_args: Mapped[list[str]] = mapped_column(JSON, init=False)
user_unique_identifier: Mapped[str] = mapped_column(String(32), index=True, init=False)
game_user: Mapped[BaseUser] = mapped_column(PydanticType(get_model=BaseUser.__subclasses__), init=False)
processed_data: Mapped[BaseProcessedData] = mapped_column(
PydanticType(get_model=BaseProcessedData.__subclasses__), init=False
)
finish_time: Mapped[datetime] = mapped_column(DateTime, init=False)
session_persist_id: Mapped[int]
game_platform: Mapped[GameType] = mapped_column(String(32), index=True)
command_type: Mapped[CommandType | Literal['rank']] = mapped_column(String(16), index=True)
command_args: Mapped[list[str]] = mapped_column(JSON)
finish_time: Mapped[datetime] = mapped_column(DateTime)