nonebot2/nonebot/utils.py
Ju4tCode bbd13c04cc
Feature: 兼容 Pydantic v2 (#2544)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2024-01-26 11:12:57 +08:00

330 lines
9.3 KiB
Python

"""本模块包含了 NoneBot 的一些工具函数
FrontMatter:
sidebar_position: 8
description: nonebot.utils 模块
"""
import re
import json
import asyncio
import inspect
import importlib
import dataclasses
from pathlib import Path
from collections import deque
from contextvars import copy_context
from functools import wraps, partial
from contextlib import asynccontextmanager
from typing_extensions import ParamSpec, get_args, override, get_origin
from typing import (
Any,
Dict,
Type,
Tuple,
Union,
Generic,
Mapping,
TypeVar,
Callable,
Optional,
Sequence,
Coroutine,
AsyncGenerator,
ContextManager,
overload,
)
from pydantic import BaseModel
from nonebot.log import logger
from nonebot.typing import (
is_none_type,
origin_is_union,
origin_is_literal,
all_literal_values,
)
P = ParamSpec("P")
R = TypeVar("R")
T = TypeVar("T")
K = TypeVar("K")
V = TypeVar("V")
def escape_tag(s: str) -> str:
"""用于记录带颜色日志时转义 `<tag>` 类型特殊标签
参考: [loguru color 标签](https://loguru.readthedocs.io/en/stable/api/logger.html#color)
参数:
s: 需要转义的字符串
"""
return re.sub(r"</?((?:[fb]g\s)?[^<>\s]*)>", r"\\\g<0>", s)
def deep_update(
mapping: Dict[K, Any], *updating_mappings: Dict[K, Any]
) -> Dict[K, Any]:
"""深度更新合并字典"""
updated_mapping = mapping.copy()
for updating_mapping in updating_mappings:
for k, v in updating_mapping.items():
if (
k in updated_mapping
and isinstance(updated_mapping[k], dict)
and isinstance(v, dict)
):
updated_mapping[k] = deep_update(updated_mapping[k], v)
else:
updated_mapping[k] = v
return updated_mapping
def lenient_issubclass(
cls: Any, class_or_tuple: Union[Type[Any], Tuple[Type[Any], ...]]
) -> bool:
"""检查 cls 是否是 class_or_tuple 中的一个类型子类并忽略类型错误。"""
try:
return isinstance(cls, type) and issubclass(cls, class_or_tuple)
except TypeError:
return False
def generic_check_issubclass(
cls: Any, class_or_tuple: Union[Type[Any], Tuple[Type[Any], ...]]
) -> bool:
"""检查 cls 是否是 class_or_tuple 中的一个类型子类。
特别的:
- 如果 cls 是 `typing.Union` 或 `types.UnionType` 类型,
则会检查其中的所有类型是否是 class_or_tuple 中一个类型的子类或 None。
- 如果 cls 是 `typing.Literal` 类型,
则会检查其中的所有值是否是 class_or_tuple 中一个类型的实例。
- 如果 cls 是 `typing.TypeVar` 类型,
则会检查其 `__bound__` 或 `__constraints__`
是否是 class_or_tuple 中一个类型的子类或 None。
"""
try:
return issubclass(cls, class_or_tuple)
except TypeError:
origin = get_origin(cls)
if origin_is_union(origin):
return all(
is_none_type(type_) or generic_check_issubclass(type_, class_or_tuple)
for type_ in get_args(cls)
)
elif origin_is_literal(origin):
return all(
is_none_type(value) or isinstance(value, class_or_tuple)
for value in all_literal_values(cls)
)
# ensure generic List, Dict can be checked
elif origin:
# avoid class check error (typing.Final, typing.ClassVar, etc...)
try:
return issubclass(origin, class_or_tuple)
except TypeError:
return False
elif isinstance(cls, TypeVar):
if cls.__constraints__:
return all(
is_none_type(type_)
or generic_check_issubclass(type_, class_or_tuple)
for type_ in cls.__constraints__
)
elif cls.__bound__:
return generic_check_issubclass(cls.__bound__, class_or_tuple)
return False
def type_is_complex(type_: Type[Any]) -> bool:
"""检查 type_ 是否是复杂类型"""
origin = get_origin(type_)
return _type_is_complex_inner(type_) or _type_is_complex_inner(origin)
def _type_is_complex_inner(type_: Optional[Type[Any]]) -> bool:
if lenient_issubclass(type_, (str, bytes)):
return False
return lenient_issubclass(
type_, (BaseModel, Mapping, Sequence, tuple, set, frozenset, deque)
) or dataclasses.is_dataclass(type_)
def is_coroutine_callable(call: Callable[..., Any]) -> bool:
"""检查 call 是否是一个 callable 协程函数"""
if inspect.isroutine(call):
return inspect.iscoroutinefunction(call)
if inspect.isclass(call):
return False
func_ = getattr(call, "__call__", None)
return inspect.iscoroutinefunction(func_)
def is_gen_callable(call: Callable[..., Any]) -> bool:
"""检查 call 是否是一个生成器函数"""
if inspect.isgeneratorfunction(call):
return True
func_ = getattr(call, "__call__", None)
return inspect.isgeneratorfunction(func_)
def is_async_gen_callable(call: Callable[..., Any]) -> bool:
"""检查 call 是否是一个异步生成器函数"""
if inspect.isasyncgenfunction(call):
return True
func_ = getattr(call, "__call__", None)
return inspect.isasyncgenfunction(func_)
def run_sync(call: Callable[P, R]) -> Callable[P, Coroutine[None, None, R]]:
"""一个用于包装 sync function 为 async function 的装饰器
参数:
call: 被装饰的同步函数
"""
@wraps(call)
async def _wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
loop = asyncio.get_running_loop()
pfunc = partial(call, *args, **kwargs)
context = copy_context()
result = await loop.run_in_executor(None, partial(context.run, pfunc))
return result
return _wrapper
@asynccontextmanager
async def run_sync_ctx_manager(
cm: ContextManager[T],
) -> AsyncGenerator[T, None]:
"""一个用于包装 sync context manager 为 async context manager 的执行函数"""
try:
yield await run_sync(cm.__enter__)()
except Exception as e:
ok = await run_sync(cm.__exit__)(type(e), e, None)
if not ok:
raise e
else:
await run_sync(cm.__exit__)(None, None, None)
@overload
async def run_coro_with_catch(
coro: Coroutine[Any, Any, T],
exc: Tuple[Type[Exception], ...],
return_on_err: None = None,
) -> Union[T, None]:
...
@overload
async def run_coro_with_catch(
coro: Coroutine[Any, Any, T],
exc: Tuple[Type[Exception], ...],
return_on_err: R,
) -> Union[T, R]:
...
async def run_coro_with_catch(
coro: Coroutine[Any, Any, T],
exc: Tuple[Type[Exception], ...],
return_on_err: Optional[R] = None,
) -> Optional[Union[T, R]]:
"""运行协程并当遇到指定异常时返回指定值。
参数:
coro: 要运行的协程
exc: 要捕获的异常
return_on_err: 当发生异常时返回的值
返回:
协程的返回值或发生异常时的指定值
"""
try:
return await coro
except exc:
return return_on_err
def get_name(obj: Any) -> str:
"""获取对象的名称"""
if inspect.isfunction(obj) or inspect.isclass(obj):
return obj.__name__
return obj.__class__.__name__
def path_to_module_name(path: Path) -> str:
"""转换路径为模块名"""
rel_path = path.resolve().relative_to(Path.cwd().resolve())
if rel_path.stem == "__init__":
return ".".join(rel_path.parts[:-1])
else:
return ".".join(rel_path.parts[:-1] + (rel_path.stem,))
def resolve_dot_notation(
obj_str: str, default_attr: str, default_prefix: Optional[str] = None
) -> Any:
"""解析并导入点分表示法的对象"""
modulename, _, cls = obj_str.partition(":")
if default_prefix is not None and modulename.startswith("~"):
modulename = default_prefix + modulename[1:]
module = importlib.import_module(modulename)
if not cls:
return getattr(module, default_attr)
instance = module
for attr_str in cls.split("."):
instance = getattr(instance, attr_str)
return instance
class classproperty(Generic[T]):
"""类属性装饰器"""
def __init__(self, func: Callable[[Any], T]) -> None:
self.func = func
def __get__(self, instance: Any, owner: Optional[Type[Any]] = None) -> T:
return self.func(type(instance) if owner is None else owner)
class DataclassEncoder(json.JSONEncoder):
"""可以序列化 {ref}`nonebot.adapters.Message`(List[Dataclass]) 的 `JSONEncoder`"""
@override
def default(self, o):
if dataclasses.is_dataclass(o):
return {f.name: getattr(o, f.name) for f in dataclasses.fields(o)}
return super().default(o)
def logger_wrapper(logger_name: str):
"""用于打印 adapter 的日志。
参数:
logger_name: adapter 的名称
返回:
日志记录函数
日志记录函数的参数:
- level: 日志等级
- message: 日志信息
- exception: 异常信息
"""
def log(level: str, message: str, exception: Optional[Exception] = None):
logger.opt(colors=True, exception=exception).log(
level, f"<m>{escape_tag(logger_name)}</m> | {message}"
)
return log