Comments (1)
Pydantic can be used in a very sleek and efficient way as a settings manager. One or multiple classes can be defined, i.e. in a settings.py
:
from pathlib import Path
from pydantic import BaseModel
class SettingsTest(BaseModel):
# For all types, see https://pydantic-docs.helpmanual.io/usage/types/
basePath: Path = "/some/path"
answer: int = 42
class Config:
# General config options for the model. See https://pydantic-docs.helpmanual.io/usage/model_config/
# For Setting-specific options, see https://pydantic-docs.helpmanual.io/usage/settings/
# This is prefixed to env vars.
# To set answer, you'd have to do an export SET_TEST_ANSWER=24
env_prefix = "set_test_"
SETTINGS = SettingsTest()
If settings are needed in another place, the constant can be imported and used like so:
from settings import SETTINGS
def main():
print("Pydantic settings demo")
print("The Answer to the Ultimate Question of Life, the Universe, and Everything is {}".format(SETTINGS.answer))
print("Set basepath is: {}".format(SETTINGS.basePath))
if __name__ == "__main__":
main()
The variables in the settings class are initialized the first time the settings class is imported somewhere. If any environment variables are set (i.e. SET_TEST_ANSWER=21
), they take precedence over the default values.
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