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Configuration manager for Python applications.

Project description

Magic-settings

Installation

pip install magic-settings

Using settings from yaml file

pip install magic-settings[yaml]

Initialization

Project settings class declaration

from magic_settings import BaseSettings, Property
from functools import partial

class MySettings(BaseSettings):
    VERSION = Property(types=str)
    PROJECT_DIR = Property(types=str)
    LOGGING_LEVEL = Property(default='INFO', choices=['NOTSET', 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'])
    RETRIES_NUMBER = Property(types=int, converts=[int])
    COEFFICIENT = Property(types=float, converts=[float])
    DEBUG = Property(types=bool, converts=[int, bool], default=False)
    DISTRIBUTED_SERVICE_HOST_NAMES = Property(types=list, converts=[partial(str.split, sep=',')])

Class Property is a descriptor with following parameters:

  • types - Type of value or a tuple of possible types. It is a ValueError if value is not one of the types.
  • validators - List of callable objects each of which is successively applied to value. Raises ValueError if value does not pass at least one of the validations (if any validation function returns False).
  • choices - List of any objects. If value is not in choices - raises ValueError. When using this parameter, parameters types and validators are ignored.
  • default - Sets the default value of Property.
  • converts - List of callable objects. It is a chain of transformations that are successively applied to the value and overwrite it each time. It applies to value only if value is a string. Raises ValueError if value at least one of the transformations failed to apply.

Property classes

Besides Property following classes may be used for standard types:

  • BoolProperty: accepts boolean values, converts case-insensitive true or false to appropriate python boolean value. Also this property accepts numbers (0 is False, 1 is True).
  • FloatProperty: accepts float number values.
  • IntProperty: accepts integer number values.
  • StringProperty: accepts string values.
  • StringListProperty: accepts list of strings. You can specify delimiter in constructor of this class (, is default value).
  • HostListProperty: accepts list of hosts. Each host is a tuple containing a string hostname and an int port. Pairs should be divided by comma, hostname and port should be divided by colon. For example, 192.168.20.1:80,www.yandex.ru:1234,localhost:8888 will be converted into [('192.168.20.1', 80), ('www.yandex.ru', 1234), ('localhost', 8888)].

Above example may be simplified using these properties:

from magic_settings import (BaseSettings, Property,
                            BoolProperty, FloatProperty, IntProperty, StringListProperty, StringProperty)

class MySettings(BaseSettings):
    VERSION = StringProperty()
    PROJECT_DIR = StringProperty()
    LOGGING_LEVEL = Property(default='INFO', choices=['NOTSET', 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'])
    RETRIES_NUMBER = IntProperty()
    COEFFICIENT = FloatProperty()
    DEBUG = BoolProperty(default=False)
    DISTRIBUTED_SERVICE_HOST_NAMES = StringListProperty()

Settings configuration

Settings configuration occurs at the stage of creating a Settings object.

from my_project import my_module, my_awesome_module
from my_config import MySettings

settings = MySettings(
    modules=[my_module, my_awesome_module],
    prefix='MY_PROJECT_ENV_SETTINGS',
    dotenv_path='/path/to/my/env',
    override_env=True,
    yaml_settings_path='/path/to/my/yaml/settings.yaml',
    use_env=True
)

Parameters

  • modules: List of Python modules with variables to import. Default None.

  • prefix: The prefix with which the environment variables are taken. Default - None.

    settings.py

    class MySettings(BaseSettings):
        PSYDUCK = Property(types=str)
    

    .env

    MYPROJECT_PSYDUCK=Owowowow
    

    some_other_place.py

    settings = MySettings(prefix='MYPROJECT')
    

    or

    settings = MySettings(prefix='MYPROJECT_')
    
  • dotenv_path: Path to env-file. Default - None. Using for exporting variables from env-file to environment. If dotenv_path is None - walking up the directory tree looking for the specified file - called .env by default.

  • override_env: True - override existing system environment variables with variables from .env - file, False - do not override. Default - False.

  • yaml_settings_path: Path to yaml config file. Default - None.

  • use_env: True - use environment variables. Default - True.

Exceptions

ValueError: If modules type is not list or NoneType and if type of element in modules is not ModuleType.

Settings loading

Loading settings can be initiated anywhere in the project.

from where_your_settings import settings

settings.init()

If called again, it goes through the configuration files and update properties.

Settings priority

In case of intersection of settings the following priority will be applied: my_module -> my_awesome_module -> .env -> settings.yaml

class MySettings(BaseSettings):
    PSYDUCK = Property(types=str)

my_module.py

PSYDUCK = 'one'

my_awesome_module.py

PSYDUCK = 'two'

.env

MYPROJECTPREFIX_PSYDUCK=env

setting.yaml

PSYDUCK: yaml

Examples

>>> settings = MySettings(modules=[my_module])
>>> settings.PSYDUCK
'one'
>>> settings = MySettings(modules=[my_module, my_awesome_module])
>>> settings.PSYDUCK
'two'
>>> settings = MySettings(modules=[my_awesome_module, my_module])
>>> settings.PSYDUCK
'one'
>>> settings = MySettings(modules=[my_module, my_awesome_module], dotenv_path='/path/to/dotenv')
>>> settings.PSYDUCK
'env'
>>> settings = MySettings(modules=[my_module, my_awesome_module], dotenv_path='/path/to/dotenv', use_env=False)
>>> settings.PSYDUCK
'two'
>>> settings = MySettings(modules=[my_module, my_awesome_module], dotenv_path='/path/to/dotenv', yaml_settings_path='/path/to/yaml/settings.yaml')
>>> settings.PSYDUCK
'yaml'

Temporary Property override

my_module.py

PIKACHU = 'Psyduck_is_not_fine'
PSYDUCK = 'Owowowow'
from my_project import my_module
from my_config import MySettings

class MySettings(BaseSettings):
    PSYDUCK = Property(types=str)
    PIKACHU = Property(types=str)

settings = MySettings(modules=[my_module])
settings.init()

with settings.temp_set_attributes(PSYDUCK='I_am_ok', PIKACHU='Psyduck_is_ok'):
    print(settings.PSYDUCK) # 'I_am_ok'
    print(settings.PIKACHU) # 'Psyduck_is_ok'
print(settings.PSYDUCK) # 'Owowowow'
print(settings.PIKACHU) # 'Psyduck_is_not_fine'

Method temp_set_attributes is not thread-safe.

Settings list

You can use methods to_dict(), to_json() to get current settings:

from magic_settings import BaseSettings, Property

class MySettings(BaseSettings):
    PSYDUCK = Property(types=str)
    PIKACHU = Property(types=str)

settings = MySettings(dotenv_path='12345.env')
settings.PIKACHU = '3'
settings.PSYDUCK = '12345'

pprint(settings.to_dict())

{
    'properties': {
        'PIKACHU': '3',
        'PSYDUCK': '12345'
    },
    'sources': [{
        'source_type': 'dotenv',
        'address': {
            'dotenv_path': '12345.env',
            'override': False
        }
    }]
}

Validation

It is recommended to use following BaseSettings class methods during redefinition update_settings_from_source method:

  1. pre_validate - check that types are configured correctly; check that the values from choices and the default pass the type check.
  2. post_validate - check if each Property is assigned a value.

Dynamic settings

Implementing a custom dynamic settings source

Example with storing settings in dict source:

from magic_settings import BaseDynamicSettings, Property

source = {
    'JIGGLYPUFF': 'pink'
}

class BaseDynamicSettingsDict(BaseDynamicSettings):
    async def update_settings_from_source(self):
        super().update_config(**source)

    async def update_config(self, **kwargs):
        source.update(kwargs)
        return super().update_config(**kwargs)

Definition of project`s dynamic settings class

class MyDynamicSettings(BaseDynamicSettingsDict):
    JIGGLYPUFF = Property(types=str)

Dynamic Settings Initialization

loop = asyncio.get_event_loop()
dynamic_settings = MyDynamicSettings(loop=loop, update_period=5, task_retries_number=5)
  • update_period: time between updating settings from source, in seconds.
  • task_retries_number: the number of attempts to update the settings when an exception occurred before stopping the task.

Dynamic settings update

Updating settings only once

await dynamic_settings.update_settings_from_source()

Starting the update loop

await dynamic_settings.start_update()

Stopping the update loop

await dynamic_settings.stop_update()

Writing settings into the source

await dynamic_settings.update_config(JIGGLYPUFF='magenta')

Exceptions

  • magic_settings.DynamicSettingsSourceError - this exception should be selected if the settings source in the class inherited from BaseDynamicSettings is unavailable.

Project details


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