"""本模块定义了 NoneBot 本身运行所需的配置项。 NoneBot 使用 [`pydantic`](https://pydantic-docs.helpmanual.io/) 以及 [`python-dotenv`](https://saurabh-kumar.com/python-dotenv/) 来读取配置。 配置项需符合特殊格式或 json 序列化格式 详情见 [`pydantic Field Type`](https://pydantic-docs.helpmanual.io/usage/types/) 文档。 FrontMatter: sidebar_position: 1 description: nonebot.config 模块 """ import os import abc import json from pathlib import Path from datetime import timedelta from ipaddress import IPv4Address from collections.abc import Mapping from typing import TYPE_CHECKING, Any, Union, Optional from typing_extensions import TypeAlias, get_args, get_origin from dotenv import dotenv_values from pydantic import Field, BaseModel from pydantic.networks import IPvAnyAddress from nonebot.log import logger from nonebot.typing import origin_is_union from nonebot.utils import deep_update, type_is_complex, lenient_issubclass from nonebot.compat import ( PYDANTIC_V2, ConfigDict, ModelField, PydanticUndefined, PydanticUndefinedType, model_config, model_fields, ) DOTENV_TYPE: TypeAlias = Union[ Path, str, list[Union[Path, str]], tuple[Union[Path, str], ...] ] ENV_FILE_SENTINEL = Path("") class SettingsError(ValueError): ... class BaseSettingsSource(abc.ABC): def __init__(self, settings_cls: type["BaseSettings"]) -> None: self.settings_cls = settings_cls @property def config(self) -> "SettingsConfig": return model_config(self.settings_cls) @abc.abstractmethod def __call__(self) -> dict[str, Any]: raise NotImplementedError class InitSettingsSource(BaseSettingsSource): __slots__ = ("init_kwargs",) def __init__( self, settings_cls: type["BaseSettings"], init_kwargs: dict[str, Any] ) -> None: self.init_kwargs = init_kwargs super().__init__(settings_cls) def __call__(self) -> dict[str, Any]: return self.init_kwargs def __repr__(self) -> str: return f"InitSettingsSource(init_kwargs={self.init_kwargs!r})" class DotEnvSettingsSource(BaseSettingsSource): def __init__( self, settings_cls: type["BaseSettings"], env_file: Optional[DOTENV_TYPE] = ENV_FILE_SENTINEL, env_file_encoding: Optional[str] = None, case_sensitive: Optional[bool] = None, env_nested_delimiter: Optional[str] = None, ) -> None: super().__init__(settings_cls) self.env_file = ( env_file if env_file is not ENV_FILE_SENTINEL else self.config.get("env_file", (".env",)) ) self.env_file_encoding = ( env_file_encoding if env_file_encoding is not None else self.config.get("env_file_encoding", "utf-8") ) self.case_sensitive = ( case_sensitive if case_sensitive is not None else self.config.get("case_sensitive", False) ) self.env_nested_delimiter = ( env_nested_delimiter if env_nested_delimiter is not None else self.config.get("env_nested_delimiter", None) ) def _apply_case_sensitive(self, var_name: str) -> str: return var_name if self.case_sensitive else var_name.lower() def _field_is_complex(self, field: ModelField) -> tuple[bool, bool]: if type_is_complex(field.annotation): return True, False elif origin_is_union(get_origin(field.annotation)) and any( type_is_complex(arg) for arg in get_args(field.annotation) ): return True, True return False, False def _parse_env_vars( self, env_vars: Mapping[str, Optional[str]] ) -> dict[str, Optional[str]]: return { self._apply_case_sensitive(key): value for key, value in env_vars.items() } def _read_env_file(self, file_path: Path) -> dict[str, Optional[str]]: file_vars = dotenv_values(file_path, encoding=self.env_file_encoding) return self._parse_env_vars(file_vars) def _read_env_files(self) -> dict[str, Optional[str]]: env_files = self.env_file if env_files is None: return {} if isinstance(env_files, (str, os.PathLike)): env_files = [env_files] dotenv_vars: dict[str, Optional[str]] = {} for env_file in env_files: env_path = Path(env_file).expanduser() if env_path.is_file(): dotenv_vars.update(self._read_env_file(env_path)) return dotenv_vars def _next_field( self, field: Optional[ModelField], key: str ) -> Optional[ModelField]: if not field or origin_is_union(get_origin(field.annotation)): return None elif field.annotation and lenient_issubclass(field.annotation, BaseModel): for field in model_fields(field.annotation): if field.name == key: return field return None def _explode_env_vars( self, field: ModelField, env_vars: dict[str, Optional[str]], env_file_vars: dict[str, Optional[str]], ) -> dict[str, Any]: if self.env_nested_delimiter is None: return {} prefix = f"{field.name}{self.env_nested_delimiter}" result: dict[str, Any] = {} for env_name, env_val in env_vars.items(): if not env_name.startswith(prefix): continue # delete from file vars when used if env_name in env_file_vars: del env_file_vars[env_name] _, *keys, last_key = env_name.split(self.env_nested_delimiter) env_var = result target_field: Optional[ModelField] = field for key in keys: target_field = self._next_field(target_field, key) env_var = env_var.setdefault(key, {}) target_field = self._next_field(target_field, last_key) if target_field and env_val: is_complex, allow_parse_failure = self._field_is_complex(target_field) if is_complex: try: env_val = json.loads(env_val) except ValueError as e: if not allow_parse_failure: raise SettingsError( f'error parsing env var "{env_name}"' ) from e env_var[last_key] = env_val return result def __call__(self) -> dict[str, Any]: """从环境变量和 dotenv 配置文件中读取配置项。""" d: dict[str, Any] = {} env_vars = self._parse_env_vars(os.environ) env_file_vars = self._read_env_files() env_vars = {**env_file_vars, **env_vars} for field in model_fields(self.settings_cls): field_name = field.name env_name = self._apply_case_sensitive(field_name) # try get values from env vars env_val = env_vars.get(env_name, PydanticUndefined) # delete from file vars when used if env_name in env_file_vars: del env_file_vars[env_name] is_complex, allow_parse_failure = self._field_is_complex(field) if is_complex: if isinstance(env_val, PydanticUndefinedType): # field is complex but no value found so far, try explode_env_vars if env_val_built := self._explode_env_vars( field, env_vars, env_file_vars ): d[field_name] = env_val_built elif env_val is None: d[field_name] = env_val else: # field is complex and there's a value # decode that as JSON, then add explode_env_vars try: env_val = json.loads(env_val) except ValueError as e: if not allow_parse_failure: raise SettingsError( f'error parsing env var "{env_name}"' ) from e if isinstance(env_val, dict): # field value is a dict # try explode_env_vars to find more sub-values d[field_name] = deep_update( env_val, self._explode_env_vars(field, env_vars, env_file_vars), ) else: d[field_name] = env_val elif env_val is not PydanticUndefined: # simplest case, field is not complex # we only need to add the value if it was found d[field_name] = env_val # remain user custom config for env_name in env_file_vars: env_val = env_vars[env_name] if env_val and (val_striped := env_val.strip()): # there's a value, decode that as JSON try: env_val = json.loads(val_striped) except ValueError: logger.trace( "Error while parsing JSON for " f"{env_name!r}={val_striped!r}. " "Assumed as string." ) # explode value when it's a nested dict env_name, *nested_keys = env_name.split(self.env_nested_delimiter) if nested_keys and (env_name not in d or isinstance(d[env_name], dict)): result = {} *keys, last_key = nested_keys _tmp = result for key in keys: _tmp = _tmp.setdefault(key, {}) _tmp[last_key] = env_val d[env_name] = deep_update(d.get(env_name, {}), result) elif not nested_keys: d[env_name] = env_val return d if PYDANTIC_V2: # pragma: pydantic-v2 class SettingsConfig(ConfigDict, total=False): env_file: Optional[DOTENV_TYPE] env_file_encoding: str case_sensitive: bool env_nested_delimiter: Optional[str] else: # pragma: pydantic-v1 class SettingsConfig(ConfigDict): env_file: Optional[DOTENV_TYPE] env_file_encoding: str case_sensitive: bool env_nested_delimiter: Optional[str] class BaseSettings(BaseModel): if TYPE_CHECKING: # dummy getattr for pylance checking, actually not used def __getattr__(self, name: str) -> Any: # pragma: no cover return self.__dict__.get(name) if PYDANTIC_V2: # pragma: pydantic-v2 model_config = SettingsConfig( extra="allow", env_file=".env", env_file_encoding="utf-8", case_sensitive=False, env_nested_delimiter="__", ) else: # pragma: pydantic-v1 class Config(SettingsConfig): extra = "allow" # type: ignore env_file = ".env" env_file_encoding = "utf-8" case_sensitive = False env_nested_delimiter = "__" def __init__( __settings_self__, # pyright: ignore[reportSelfClsParameterName] _env_file: Optional[DOTENV_TYPE] = ENV_FILE_SENTINEL, _env_file_encoding: Optional[str] = None, _env_nested_delimiter: Optional[str] = None, **values: Any, ) -> None: super().__init__( **__settings_self__._settings_build_values( values, env_file=_env_file, env_file_encoding=_env_file_encoding, env_nested_delimiter=_env_nested_delimiter, ) ) def _settings_build_values( self, init_kwargs: dict[str, Any], env_file: Optional[DOTENV_TYPE] = None, env_file_encoding: Optional[str] = None, env_nested_delimiter: Optional[str] = None, ) -> dict[str, Any]: init_settings = InitSettingsSource(self.__class__, init_kwargs=init_kwargs) env_settings = DotEnvSettingsSource( self.__class__, env_file=env_file, env_file_encoding=env_file_encoding, env_nested_delimiter=env_nested_delimiter, ) return deep_update(env_settings(), init_settings()) class Env(BaseSettings): """运行环境配置。大小写不敏感。 将会从 **环境变量** > **dotenv 配置文件** 的优先级读取环境信息。 """ environment: str = "prod" """当前环境名。 NoneBot 将从 `.env.{environment}` 文件中加载配置。 """ class Config(BaseSettings): """NoneBot 主要配置。大小写不敏感。 除了 NoneBot 的配置项外,还可以自行添加配置项到 `.env.{environment}` 文件中。 这些配置将会在 json 反序列化后一起带入 `Config` 类中。 配置方法参考: [配置](https://nonebot.dev/docs/appendices/config) """ if TYPE_CHECKING: _env_file: Optional[DOTENV_TYPE] = ".env", ".env.prod" # nonebot configs driver: str = "~fastapi" """NoneBot 运行所使用的 `Driver` 。继承自 {ref}`nonebot.drivers.Driver` 。 配置格式为 `[:][+[:]]*`。 `~` 为 `nonebot.drivers.` 的缩写。 配置方法参考: [配置驱动器](https://nonebot.dev/docs/advanced/driver#%E9%85%8D%E7%BD%AE%E9%A9%B1%E5%8A%A8%E5%99%A8) """ host: IPvAnyAddress = IPv4Address("127.0.0.1") # type: ignore """NoneBot {ref}`nonebot.drivers.ReverseDriver` 服务端监听的 IP/主机名。""" port: int = Field(default=8080, ge=1, le=65535) """NoneBot {ref}`nonebot.drivers.ReverseDriver` 服务端监听的端口。""" log_level: Union[int, str] = "INFO" """NoneBot 日志输出等级,可以为 `int` 类型等级或等级名称。 参考 [记录日志](https://nonebot.dev/docs/appendices/log),[loguru 日志等级](https://loguru.readthedocs.io/en/stable/api/logger.html#levels)。 :::tip 提示 日志等级名称应为大写,如 `INFO`。 ::: 用法: ```conf LOG_LEVEL=25 LOG_LEVEL=INFO ``` """ # bot connection configs api_timeout: Optional[float] = 30.0 """API 请求超时时间,单位: 秒。""" # bot runtime configs superusers: set[str] = set() """机器人超级用户。 用法: ```conf SUPERUSERS=["12345789"] ``` """ nickname: set[str] = set() """机器人昵称。""" command_start: set[str] = {"/"} """命令的起始标记,用于判断一条消息是不是命令。 参考[命令响应规则](https://nonebot.dev/docs/advanced/matcher#command)。 用法: ```conf COMMAND_START=["/", ""] ``` """ command_sep: set[str] = {"."} """命令的分隔标记,用于将文本形式的命令切分为元组(实际的命令名)。 参考[命令响应规则](https://nonebot.dev/docs/advanced/matcher#command)。 用法: ```conf COMMAND_SEP=["."] ``` """ session_expire_timeout: timedelta = timedelta(minutes=2) """等待用户回复的超时时间。 用法: ```conf SESSION_EXPIRE_TIMEOUT=[-][DD]D[,][HH:MM:]SS[.ffffff] SESSION_EXPIRE_TIMEOUT=[±]P[DD]DT[HH]H[MM]M[SS]S # ISO 8601 ``` """ # adapter configs # adapter configs are defined in adapter/config.py # custom configs # custom configs can be assigned during nonebot.init # or from env file using json loads if PYDANTIC_V2: # pragma: pydantic-v2 model_config = SettingsConfig(env_file=(".env", ".env.prod")) else: # pragma: pydantic-v1 class Config( # pyright: ignore[reportIncompatibleVariableOverride] SettingsConfig ): env_file = ".env", ".env.prod" __autodoc__ = { "SettingsError": False, "BaseSettingsSource": False, "InitSettingsSource": False, "DotEnvSettingsSource": False, "SettingsConfig": False, "BaseSettings": False, }