bear-config 1.0.9

A useful Pydantic based config system with various options

Bear Config

A useful Pydantic based config system with various options

Installation

With uv: uv tool install bear-config

Configuration precedence

Values are merged in order; later sources override earlier ones:

1. default.toml
2. {env}.toml (for the active environment, e.g., dev.toml, prod.toml)
3. local.toml
4. Environment variables prefixed with your program name (e.g., MY_APP_...)

Search paths (by default): ~/.config/{program}/ and ./config/{program}/.

Quickstart

Define a Pydantic model for your settings, then load it with the ConfigManager.

from pydantic import BaseModel
from bear_config.config_manager import ConfigManager


class Database(BaseModel):
    host: str = "localhost"
    port: int = 5432


class Settings(BaseModel):
    database: Database = Database()
    debug: bool = False


config = ConfigManager[Settings](
    config_model=Settings,
    program_name="my_app",
    env="dev",
).config

print(config.database.host)
print(config.debug)

Environment variables can override nested keys using the program prefix. For example, MY_APP_DATABASE_HOST=prod.db and MY_APP_DEBUG=true will replace the corresponding fields after files are loaded.

Generating a default config

You can scaffold a TOML file with the model’s default values:

from bear_config.config_manager import ConfigManager

config_mgr = ConfigManager[Settings](Settings, program_name="my_app")
config_mgr.create_default_config()  # writes default.toml into the local config dir