A simple tool for loading YAML
and JSON
configuration/settings using
pydantic2
.
There is also a version for pydantic1
, see release/v1
. Major
versions of this package will match the major version of the respective
pydantic
release.
This project can be helpful for projects that have large configuration files,
nested configuration files, or for those of us who don't like writing large .env
files. It is also worth noting that due to the backwards compatability between
YAML
and JSON
that this will also parse JSON
configuration.
This can also be helpful when writing out application settings in kubernetes
/helm, where most configuration is written as YAML
. In such a case we may
want to validate/store our settings as YAML
as writing JSON
and
JSON
strings can be compersome due to syntax error in larger documents.
Install using pip
:
.. code:: bash
pip install yaml-settings-pydantic
First, it is worth reading the pydantic_settings
docs about additional sources: https://docs.pydantic.dev/latest/usage/pydantic_settings/
Additionally see the example in ./tests/examples/__init__.py
. It is gaurenteed to
work as its contents are tested. It contains information on how to write nested
configurations.
There are three classes worth knowing about:
YamlSettingsConfigDict
-- pydantic_settings.SetttingsConfigDict
extended to include the fields used by CreateYamlSettings
.
CreateYamlSettings
-- The pydantic PydanticBaseSettingsSource
that
will analyze your class for the following class variables:
__env_yaml_files__
or model_config.yaml_files
.__env_yaml_reload__
or model_config.yaml_reload
.CreateYamlSettings
does not have to be used at all, but can be helpful if
you don't want to use BaseYamlSettings
for any reason.
BaseYamlSettings
-- Use this directly as done in the example below. This
is 'the easy way'.
The shortest possible example is as follows:
.. code:: python
from yaml_settings_pydantic import BaseYamlSettings
class MySettings(BaseYamlSettings): env_yaml_files = "settings.yaml"
setttingOne: str
settingTwo: str
...
...
Note that the above example can also be written like
.. code:: python
from yaml_settings_pydantic import BaseYamlSettings, YamlSettingsConfigDict
class MySettings(BaseYamlSettings): model_config = YamlSettingsConfigDict(yaml_files="settings.yaml")
setttingOne: str
settingTwo: str
...
...
which is more like pydantic v2. The 'dunder' specifications will take priority
over their equivalent model_config
specifications. These map as follows:
.. code:: text
+-----------------------+------------------+ | dunder | model_config | +-----------------------+------------------+ | env_yaml_files | yaml_files | | env_yaml_reload | yaml_reload | +-----------------------+------------------+