pydantic-config 0.2.3

Support for Pydantic settings configuration file loading

Pydantic Config

Support for Pydantic settings configuration file loading

Installation

pip install pydantic-config

Optional Dependencies

Pydantic-Config has the following optional dependencies:

• yaml - pip install pydantic-config[yaml]
• toml - pip install pydantic-config[toml]

You can install all the optional dependencies with pip install pydantic-config[all]

Usage

# config.toml
app_name = "Python Application"
description = "Test application description"

from pydantic_config import SettingsModel, SettingsConfig


class Settings(SettingsModel):
    app_id: str = 1
    app_name: str = None
    description: str = None
    log_level: str = 'INFO'
    
    model_config = SettingsConfig(
        config_file='config.toml',
    )


settings = Settings()
print(settings)
# app_id='1' app_name='Python Application' description='Test application description' log_level='INFO'

Using multiple config files

Multiple config files can be loaded by passing a list of file names. Files will be loaded in the order they are listed. Meaning later files in the list will take priority over earlier files.

# config.toml
app_name = "Python Application"
description = "Test application description"

// config.json
{
  "description": "Description from JSON file",
  "log_level": "WARNING"
}

from pydantic_config import SettingsModel, SettingsConfig


class Settings(SettingsModel):
    app_id: str = 1
    app_name: str = 'App Name'
    description: str = None
    log_level: str = 'INFO'
    
    model_config = SettingsConfig(
        config_file=['config.toml', 'config.json']  # The config.json file will take priority over config.toml
    )

settings = Settings()
print(settings)
# app_id='1' app_name='Python Application' description='Description from JSON file' log_level='WARNING'

Supported file formats

Currently, the following file formats are supported:

• .yaml Requires pyyaml package
• .toml Requires toml package
• .json
• .ini

Merging

If your configurations have existing list or dict variables the contents will be merged by default. To disable this behavior and override the contents instead you can set the config_merge option to False in the settings Config class.

# config.toml
[foo]
item1 = "value1"

# config2.toml
[foo]
item2 = "value2"

from pydantic_config import SettingsModel, SettingsConfig


class Settings(SettingsModel):
    foo: dict = {}
    
    model_config = SettingsConfig(
        config_file=['config.toml', 'config2.toml'],
        config_merge= True,
    )


settings = Settings()
print(settings)
# foo={'item1': 'value1', 'item2': 'value2'}

# If config_merge=False then config2.toml would ovverride the values from config.toml
# foo={'item2': 'value2'}

Duplicate items in merged lists

By default, only unique list items will be merged. To disable this behavior and keep all items of a list regardless of duplication set the config_merge_unique option to False.