mirror of
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230 lines
7.3 KiB
Python
230 lines
7.3 KiB
Python
"""本模块模块实现了依赖注入的定义与处理。
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FrontMatter:
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mdx:
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format: md
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sidebar_position: 0
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description: nonebot.dependencies 模块
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"""
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import abc
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import inspect
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from functools import partial
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from dataclasses import field, dataclass
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from collections.abc import Iterable, Awaitable
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from typing import Any, Generic, TypeVar, Callable, Optional, cast
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import anyio
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from exceptiongroup import BaseExceptionGroup, catch
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from nonebot.log import logger
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from nonebot.typing import _DependentCallable
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from nonebot.exception import SkippedException
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from nonebot.compat import FieldInfo, ModelField, PydanticUndefined
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from nonebot.utils import (
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run_sync,
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run_coro_with_shield,
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is_coroutine_callable,
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flatten_exception_group,
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)
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from .utils import check_field_type, get_typed_signature
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R = TypeVar("R")
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T = TypeVar("T", bound="Dependent")
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class Param(abc.ABC, FieldInfo):
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"""依赖注入的基本单元 —— 参数。
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继承自 `pydantic.fields.FieldInfo`,用于描述参数信息(不包括参数名)。
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"""
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def __init__(self, *args, validate: bool = False, **kwargs: Any) -> None:
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super().__init__(*args, **kwargs)
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self.validate = validate
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@classmethod
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def _check_param(
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cls, param: inspect.Parameter, allow_types: tuple[type["Param"], ...]
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) -> Optional["Param"]:
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return
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@classmethod
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def _check_parameterless(
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cls, value: Any, allow_types: tuple[type["Param"], ...]
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) -> Optional["Param"]:
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return
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@abc.abstractmethod
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async def _solve(self, **kwargs: Any) -> Any:
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raise NotImplementedError
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async def _check(self, **kwargs: Any) -> None:
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return
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@dataclass(frozen=True)
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class Dependent(Generic[R]):
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"""依赖注入容器
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参数:
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call: 依赖注入的可调用对象,可以是任何 Callable 对象
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pre_checkers: 依赖注入解析前的参数检查
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params: 具名参数列表
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parameterless: 匿名参数列表
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allow_types: 允许的参数类型
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"""
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call: _DependentCallable[R]
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params: tuple[ModelField, ...] = field(default_factory=tuple)
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parameterless: tuple[Param, ...] = field(default_factory=tuple)
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def __repr__(self) -> str:
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if inspect.isfunction(self.call) or inspect.isclass(self.call):
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call_str = self.call.__name__
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else:
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call_str = repr(self.call)
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return (
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f"Dependent(call={call_str}"
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+ (f", parameterless={self.parameterless}" if self.parameterless else "")
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+ ")"
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)
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async def __call__(self, **kwargs: Any) -> R:
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exception: Optional[BaseExceptionGroup[SkippedException]] = None
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def _handle_skipped(exc_group: BaseExceptionGroup[SkippedException]):
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nonlocal exception
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exception = exc_group
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# raise one of the exceptions instead
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excs = list(flatten_exception_group(exc_group))
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logger.trace(f"{self} skipped due to {excs}")
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with catch({SkippedException: _handle_skipped}):
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# do pre-check
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await self.check(**kwargs)
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# solve param values
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values = await self.solve(**kwargs)
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# call function
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if is_coroutine_callable(self.call):
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return await cast(Callable[..., Awaitable[R]], self.call)(**values)
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else:
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return await run_sync(cast(Callable[..., R], self.call))(**values)
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raise exception
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@staticmethod
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def parse_params(
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call: _DependentCallable[R], allow_types: tuple[type[Param], ...]
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) -> tuple[ModelField, ...]:
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fields: list[ModelField] = []
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params = get_typed_signature(call).parameters.values()
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for param in params:
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if isinstance(param.default, Param):
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field_info = param.default
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else:
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for allow_type in allow_types:
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if field_info := allow_type._check_param(param, allow_types):
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break
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else:
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raise ValueError(
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f"Unknown parameter {param.name} "
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f"for function {call} with type {param.annotation}"
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)
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annotation: Any = Any
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if param.annotation is not param.empty:
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annotation = param.annotation
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fields.append(
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ModelField.construct(
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name=param.name, annotation=annotation, field_info=field_info
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)
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)
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return tuple(fields)
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@staticmethod
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def parse_parameterless(
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parameterless: tuple[Any, ...], allow_types: tuple[type[Param], ...]
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) -> tuple[Param, ...]:
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parameterless_params: list[Param] = []
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for value in parameterless:
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for allow_type in allow_types:
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if param := allow_type._check_parameterless(value, allow_types):
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break
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else:
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raise ValueError(f"Unknown parameterless {value}")
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parameterless_params.append(param)
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return tuple(parameterless_params)
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@classmethod
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def parse(
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cls,
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*,
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call: _DependentCallable[R],
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parameterless: Optional[Iterable[Any]] = None,
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allow_types: Iterable[type[Param]],
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) -> "Dependent[R]":
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allow_types = tuple(allow_types)
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params = cls.parse_params(call, allow_types)
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parameterless_params = (
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()
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if parameterless is None
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else cls.parse_parameterless(tuple(parameterless), allow_types)
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)
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return cls(call, params, parameterless_params)
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async def check(self, **params: Any) -> None:
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if self.parameterless:
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async with anyio.create_task_group() as tg:
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for param in self.parameterless:
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tg.start_soon(partial(param._check, **params))
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if self.params:
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async with anyio.create_task_group() as tg:
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for param in self.params:
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tg.start_soon(
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partial(cast(Param, param.field_info)._check, **params)
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)
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async def _solve_field(self, field: ModelField, params: dict[str, Any]) -> Any:
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param = cast(Param, field.field_info)
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value = await param._solve(**params)
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if value is PydanticUndefined:
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value = field.get_default()
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v = check_field_type(field, value)
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return v if param.validate else value
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async def solve(self, **params: Any) -> dict[str, Any]:
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# solve parameterless
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for param in self.parameterless:
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await param._solve(**params)
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# solve param values
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result: dict[str, Any] = {}
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if not self.params:
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return result
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async def _solve_field(field: ModelField, params: dict[str, Any]) -> None:
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value = await self._solve_field(field, params)
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result[field.name] = value
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async with anyio.create_task_group() as tg:
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for field in self.params:
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# shield the task to prevent cancellation
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# when one of the tasks raises an exception
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# this will improve the dependency cache reusability
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tg.start_soon(run_coro_with_shield, _solve_field(field, params))
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return result
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__autodoc__ = {"CustomConfig": False}
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