"""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