Store config in the environment

https://12factor.net/config

The twelve-factor app stores config in environment variables (often shortened to env vars or env). Env vars are easy to change between deploys without changing any code; unlike config files, there is little chance of them being checked into the code repo accidentally; and unlike custom config files, or other config mechanisms such as Java System Properties, they are a language- and OS-agnostic standard.

pydantic_settings

https://fastapi.tiangolo.com/advanced/settings/#reading-a-env-file

fastapi推荐

https://docs.pydantic.dev/latest/concepts/pydantic_settings/#usage

from typing import Any, Callable, Set

from pydantic import (
    AliasChoices,
    AmqpDsn,
    BaseModel,
    Field,
    ImportString,
    PostgresDsn,
    RedisDsn,
)

from pydantic_settings import BaseSettings, SettingsConfigDict


class SubModel(BaseModel):
    foo: str = 'bar'
    apple: int = 1


class Settings(BaseSettings):
    auth_key: str = Field(validation_alias='my_auth_key')  

    api_key: str = Field(alias='my_api_key')  

    redis_dsn: RedisDsn = Field(
        'redis://user:pass@localhost:6379/1',
        validation_alias=AliasChoices('service_redis_dsn', 'redis_url'),  (3)
    )
    pg_dsn: PostgresDsn = 'postgres://user:pass@localhost:5432/foobar'
    amqp_dsn: AmqpDsn = 'amqp://user:pass@localhost:5672/'

    special_function: ImportString[Callable[[Any], Any]] = 'math.cos'  (4)

    # to override domains:
    # export my_prefix_domains='["foo.com", "bar.com"]'
    domains: Set[str] = set()

    # to override more_settings:
    # export my_prefix_more_settings='{"foo": "x", "apple": 1}'
    more_settings: SubModel = SubModel()

    model_config = SettingsConfigDict(env_prefix='my_prefix_')  (5)


print(Settings().model_dump())
"""
{
    'auth_key': 'xxx',
    'api_key': 'xxx',
    'redis_dsn': Url('redis://user:pass@localhost:6379/1'),
    'pg_dsn': MultiHostUrl('postgres://user:pass@localhost:5432/foobar'),
    'amqp_dsn': Url('amqp://user:pass@localhost:5672/'),
    'special_function': math.cos,
    'domains': set(),
    'more_settings': {'foo': 'bar', 'apple': 1},
}
"""

使用.env覆盖默认值， 但是最终环境会覆盖.env值

from pydantic_settings import BaseSettings, SettingsConfigDict

'''
default -> env file -> env variable
'''
class Settings(BaseSettings):
    PATH: str = "Awesome API"
    USER: str = "xxx"
    TEST: str = "yyy"

    model_config = SettingsConfigDict(env_file=".env")

if __name__ == "__main__":
    src.machine_learning_workflow_pipeline()

    print("---------------------------")
    print(Settings().PATH)
    print(Settings().USER)
    print(Settings().TEST)

dynaconf

https://www.dynaconf.com/#reading-settings-from-files

Features¶

• Inspired by the 12-factor application guide
• Settings management (default values, validation, parsing, templating)
• Protection of sensitive information (passwords/tokens)
• Multiple file formats toml|yaml|json|ini|py and also customizable loaders.
• Full support for environment variables to override existing settings (dotenv support included).
• Optional layered system for multi environments [default, development, testing, production] (also called multi profiles)
• Built-in support for Hashicorp Vault and Redis as settings and secrets storage.
• Built-in extensions for Django and Flask web frameworks.
• CLI for common operations such as init, list, write, validate, export.