mirror of
https://github.com/nonebot/nonebot2.git
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bbd13c04cc
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
494 lines
16 KiB
Python
494 lines
16 KiB
Python
"""本模块定义了 NoneBot 本身运行所需的配置项。
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NoneBot 使用 [`pydantic`](https://pydantic-docs.helpmanual.io/) 以及
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[`python-dotenv`](https://saurabh-kumar.com/python-dotenv/) 来读取配置。
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配置项需符合特殊格式或 json 序列化格式
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详情见 [`pydantic Field Type`](https://pydantic-docs.helpmanual.io/usage/types/) 文档。
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FrontMatter:
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sidebar_position: 1
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description: nonebot.config 模块
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"""
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import os
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import abc
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import json
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from pathlib import Path
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from datetime import timedelta
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from ipaddress import IPv4Address
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from typing_extensions import TypeAlias, get_args, get_origin
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from typing import (
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TYPE_CHECKING,
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Any,
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Set,
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Dict,
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List,
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Type,
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Tuple,
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Union,
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Mapping,
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Optional,
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)
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from dotenv import dotenv_values
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from pydantic import Field, BaseModel
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from pydantic.networks import IPvAnyAddress
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from nonebot.log import logger
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from nonebot.typing import origin_is_union
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from nonebot.utils import deep_update, type_is_complex, lenient_issubclass
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from nonebot.compat import (
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PYDANTIC_V2,
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ConfigDict,
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ModelField,
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PydanticUndefined,
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PydanticUndefinedType,
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model_config,
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model_fields,
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)
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DOTENV_TYPE: TypeAlias = Union[
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Path, str, List[Union[Path, str]], Tuple[Union[Path, str], ...]
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]
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ENV_FILE_SENTINEL = Path("")
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class SettingsError(ValueError):
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...
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class BaseSettingsSource(abc.ABC):
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def __init__(self, settings_cls: Type["BaseSettings"]) -> None:
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self.settings_cls = settings_cls
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@property
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def config(self) -> "SettingsConfig":
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return model_config(self.settings_cls)
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@abc.abstractmethod
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def __call__(self) -> Dict[str, Any]:
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raise NotImplementedError
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class InitSettingsSource(BaseSettingsSource):
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__slots__ = ("init_kwargs",)
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def __init__(
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self, settings_cls: Type["BaseSettings"], init_kwargs: Dict[str, Any]
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) -> None:
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self.init_kwargs = init_kwargs
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super().__init__(settings_cls)
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def __call__(self) -> Dict[str, Any]:
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return self.init_kwargs
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def __repr__(self) -> str:
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return f"InitSettingsSource(init_kwargs={self.init_kwargs!r})"
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class DotEnvSettingsSource(BaseSettingsSource):
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def __init__(
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self,
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settings_cls: Type["BaseSettings"],
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env_file: Optional[DOTENV_TYPE] = ENV_FILE_SENTINEL,
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env_file_encoding: Optional[str] = None,
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case_sensitive: Optional[bool] = None,
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env_nested_delimiter: Optional[str] = None,
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) -> None:
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super().__init__(settings_cls)
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self.env_file = (
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env_file
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if env_file is not ENV_FILE_SENTINEL
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else self.config.get("env_file", (".env",))
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)
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self.env_file_encoding = (
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env_file_encoding
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if env_file_encoding is not None
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else self.config.get("env_file_encoding", "utf-8")
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)
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self.case_sensitive = (
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case_sensitive
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if case_sensitive is not None
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else self.config.get("case_sensitive", False)
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)
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self.env_nested_delimiter = (
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env_nested_delimiter
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if env_nested_delimiter is not None
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else self.config.get("env_nested_delimiter", None)
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)
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def _apply_case_sensitive(self, var_name: str) -> str:
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return var_name if self.case_sensitive else var_name.lower()
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def _field_is_complex(self, field: ModelField) -> Tuple[bool, bool]:
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if type_is_complex(field.annotation):
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return True, False
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elif origin_is_union(get_origin(field.annotation)) and any(
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type_is_complex(arg) for arg in get_args(field.annotation)
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):
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return True, True
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return False, False
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def _parse_env_vars(
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self, env_vars: Mapping[str, Optional[str]]
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) -> Dict[str, Optional[str]]:
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return {
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self._apply_case_sensitive(key): value for key, value in env_vars.items()
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}
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def _read_env_file(self, file_path: Path) -> Dict[str, Optional[str]]:
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file_vars = dotenv_values(file_path, encoding=self.env_file_encoding)
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return self._parse_env_vars(file_vars)
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def _read_env_files(self) -> Dict[str, Optional[str]]:
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env_files = self.env_file
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if env_files is None:
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return {}
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if isinstance(env_files, (str, os.PathLike)):
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env_files = [env_files]
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dotenv_vars: Dict[str, Optional[str]] = {}
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for env_file in env_files:
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env_path = Path(env_file).expanduser()
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if env_path.is_file():
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dotenv_vars.update(self._read_env_file(env_path))
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return dotenv_vars
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def _next_field(
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self, field: Optional[ModelField], key: str
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) -> Optional[ModelField]:
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if not field or origin_is_union(get_origin(field.annotation)):
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return None
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elif field.annotation and lenient_issubclass(field.annotation, BaseModel):
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for field in model_fields(field.annotation):
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if field.name == key:
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return field
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return None
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def _explode_env_vars(
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self,
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field: ModelField,
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env_vars: Dict[str, Optional[str]],
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env_file_vars: Dict[str, Optional[str]],
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) -> Dict[str, Any]:
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if self.env_nested_delimiter is None:
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return {}
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prefix = f"{field.name}{self.env_nested_delimiter}"
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result: Dict[str, Any] = {}
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for env_name, env_val in env_vars.items():
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if not env_name.startswith(prefix):
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continue
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# delete from file vars when used
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if env_name in env_file_vars:
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del env_file_vars[env_name]
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_, *keys, last_key = env_name.split(self.env_nested_delimiter)
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env_var = result
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target_field: Optional[ModelField] = field
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for key in keys:
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target_field = self._next_field(target_field, key)
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env_var = env_var.setdefault(key, {})
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target_field = self._next_field(target_field, last_key)
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if target_field and env_val:
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is_complex, allow_parse_failure = self._field_is_complex(target_field)
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if is_complex:
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try:
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env_val = json.loads(env_val)
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except ValueError as e:
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if not allow_parse_failure:
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raise SettingsError(
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f'error parsing env var "{env_name}"'
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) from e
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env_var[last_key] = env_val
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return result
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def __call__(self) -> Dict[str, Any]:
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"""从环境变量和 dotenv 配置文件中读取配置项。"""
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d: Dict[str, Any] = {}
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env_vars = self._parse_env_vars(os.environ)
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env_file_vars = self._read_env_files()
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env_vars = {**env_file_vars, **env_vars}
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for field in model_fields(self.settings_cls):
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field_name = field.name
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env_name = self._apply_case_sensitive(field_name)
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# try get values from env vars
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env_val = env_vars.get(env_name, PydanticUndefined)
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# delete from file vars when used
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if env_name in env_file_vars:
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del env_file_vars[env_name]
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is_complex, allow_parse_failure = self._field_is_complex(field)
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if is_complex:
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if isinstance(env_val, PydanticUndefinedType):
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# field is complex but no value found so far, try explode_env_vars
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if env_val_built := self._explode_env_vars(
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field, env_vars, env_file_vars
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):
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d[field_name] = env_val_built
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elif env_val is None:
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d[field_name] = env_val
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else:
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# field is complex and there's a value
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# decode that as JSON, then add explode_env_vars
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try:
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env_val = json.loads(env_val)
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except ValueError as e:
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if not allow_parse_failure:
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raise SettingsError(
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f'error parsing env var "{env_name}"'
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) from e
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if isinstance(env_val, dict):
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# field value is a dict
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# try explode_env_vars to find more sub-values
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d[field_name] = deep_update(
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env_val,
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self._explode_env_vars(field, env_vars, env_file_vars),
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)
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else:
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d[field_name] = env_val
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elif env_val is not PydanticUndefined:
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# simplest case, field is not complex
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# we only need to add the value if it was found
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d[field_name] = env_val
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# remain user custom config
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for env_name in env_file_vars:
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env_val = env_vars[env_name]
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if env_val and (val_striped := env_val.strip()):
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# there's a value, decode that as JSON
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try:
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env_val = json.loads(val_striped)
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except ValueError:
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logger.trace(
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"Error while parsing JSON for "
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f"{env_name!r}={val_striped!r}. "
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"Assumed as string."
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)
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# explode value when it's a nested dict
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env_name, *nested_keys = env_name.split(self.env_nested_delimiter)
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if nested_keys and (env_name not in d or isinstance(d[env_name], dict)):
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result = {}
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*keys, last_key = nested_keys
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_tmp = result
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for key in keys:
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_tmp = _tmp.setdefault(key, {})
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_tmp[last_key] = env_val
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d[env_name] = deep_update(d.get(env_name, {}), result)
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elif not nested_keys:
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d[env_name] = env_val
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return d
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if PYDANTIC_V2: # pragma: pydantic-v2
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class SettingsConfig(ConfigDict, total=False):
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env_file: Optional[DOTENV_TYPE]
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env_file_encoding: str
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case_sensitive: bool
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env_nested_delimiter: Optional[str]
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else: # pragma: pydantic-v1
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class SettingsConfig(ConfigDict):
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env_file: Optional[DOTENV_TYPE]
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env_file_encoding: str
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case_sensitive: bool
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env_nested_delimiter: Optional[str]
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class BaseSettings(BaseModel):
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if TYPE_CHECKING:
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# dummy getattr for pylance checking, actually not used
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def __getattr__(self, name: str) -> Any: # pragma: no cover
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return self.__dict__.get(name)
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if PYDANTIC_V2: # pragma: pydantic-v2
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model_config: SettingsConfig = SettingsConfig(
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extra="allow",
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env_file=".env",
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env_file_encoding="utf-8",
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case_sensitive=False,
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env_nested_delimiter="__",
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)
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else: # pragma: pydantic-v1
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class Config(SettingsConfig):
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extra = "allow" # type: ignore
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env_file = ".env"
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env_file_encoding = "utf-8"
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case_sensitive = False
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env_nested_delimiter = "__"
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def __init__(
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__settings_self__, # pyright: ignore[reportSelfClsParameterName]
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_env_file: Optional[DOTENV_TYPE] = ENV_FILE_SENTINEL,
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_env_file_encoding: Optional[str] = None,
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_env_nested_delimiter: Optional[str] = None,
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**values: Any,
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) -> None:
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super().__init__(
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**__settings_self__._settings_build_values(
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values,
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env_file=_env_file,
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env_file_encoding=_env_file_encoding,
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env_nested_delimiter=_env_nested_delimiter,
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)
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)
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def _settings_build_values(
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self,
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init_kwargs: Dict[str, Any],
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env_file: Optional[DOTENV_TYPE] = None,
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env_file_encoding: Optional[str] = None,
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env_nested_delimiter: Optional[str] = None,
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) -> Dict[str, Any]:
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init_settings = InitSettingsSource(self.__class__, init_kwargs=init_kwargs)
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env_settings = DotEnvSettingsSource(
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self.__class__,
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env_file=env_file,
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env_file_encoding=env_file_encoding,
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env_nested_delimiter=env_nested_delimiter,
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)
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return deep_update(env_settings(), init_settings())
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class Env(BaseSettings):
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"""运行环境配置。大小写不敏感。
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将会从 **环境变量** > **dotenv 配置文件** 的优先级读取环境信息。
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"""
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environment: str = "prod"
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"""当前环境名。
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NoneBot 将从 `.env.{environment}` 文件中加载配置。
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"""
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class Config(BaseSettings):
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"""NoneBot 主要配置。大小写不敏感。
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除了 NoneBot 的配置项外，还可以自行添加配置项到 `.env.{environment}` 文件中。
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这些配置将会在 json 反序列化后一起带入 `Config` 类中。
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配置方法参考: [配置](https://nonebot.dev/docs/appendices/config)
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"""
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if TYPE_CHECKING:
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_env_file: Optional[DOTENV_TYPE] = ".env", ".env.prod"
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# nonebot configs
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driver: str = "~fastapi"
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"""NoneBot 运行所使用的 `Driver` 。继承自 {ref}`nonebot.drivers.Driver` 。
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配置格式为 `<module>[:<Driver>][+<module>[:<Mixin>]]*`。
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`~` 为 `nonebot.drivers.` 的缩写。
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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)
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"""
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host: IPvAnyAddress = IPv4Address("127.0.0.1") # type: ignore
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"""NoneBot {ref}`nonebot.drivers.ReverseDriver` 服务端监听的 IP/主机名。"""
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port: int = Field(default=8080, ge=1, le=65535)
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"""NoneBot {ref}`nonebot.drivers.ReverseDriver` 服务端监听的端口。"""
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log_level: Union[int, str] = "INFO"
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"""NoneBot 日志输出等级，可以为 `int` 类型等级或等级名称。
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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)。
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:::tip 提示
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日志等级名称应为大写，如 `INFO`。
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:::
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用法:
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```conf
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LOG_LEVEL=25
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LOG_LEVEL=INFO
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```
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"""
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# bot connection configs
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api_timeout: Optional[float] = 30.0
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"""API 请求超时时间，单位: 秒。"""
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# bot runtime configs
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superusers: Set[str] = set()
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"""机器人超级用户。
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用法:
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```conf
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SUPERUSERS=["12345789"]
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```
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"""
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nickname: Set[str] = set()
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"""机器人昵称。"""
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command_start: Set[str] = {"/"}
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"""命令的起始标记，用于判断一条消息是不是命令。
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参考[命令响应规则](https://nonebot.dev/docs/advanced/matcher#command)。
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用法:
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```conf
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COMMAND_START=["/", ""]
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```
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"""
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command_sep: Set[str] = {"."}
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"""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）。
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参考[命令响应规则](https://nonebot.dev/docs/advanced/matcher#command)。
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用法:
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```conf
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COMMAND_SEP=["."]
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```
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"""
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session_expire_timeout: timedelta = timedelta(minutes=2)
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"""等待用户回复的超时时间。
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用法:
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```conf
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SESSION_EXPIRE_TIMEOUT=120 # 单位: 秒
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SESSION_EXPIRE_TIMEOUT=[DD ][HH:MM]SS[.ffffff]
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SESSION_EXPIRE_TIMEOUT=P[DD]DT[HH]H[MM]M[SS]S # ISO 8601
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```
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"""
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# adapter configs
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# adapter configs are defined in adapter/config.py
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# custom configs
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# custom configs can be assigned during nonebot.init
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# or from env file using json loads
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if PYDANTIC_V2: # pragma: pydantic-v2
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model_config = SettingsConfig(env_file=(".env", ".env.prod"))
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else: # pragma: pydantic-v1
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class Config(SettingsConfig):
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env_file = ".env", ".env.prod"
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__autodoc__ = {
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"SettingsError": False,
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"BaseSettingsSource": False,
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"InitSettingsSource": False,
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"DotEnvSettingsSource": False,
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"SettingsConfig": False,
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"BaseSettings": False,
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}
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