Skip to main content

Class @decorator for defining exquisite settings configurations.

Project description

Build Status Coverage Status Documentation Status GitHub Release Status PyPI Release Status License Status

User configuration framework developed for dob.


config-decorator makes it easy to define a hierarchical collection of user-configurable key-value settings using Pythonic @decorator syntax. It can be used with a modern file round tripper, such as ConfigObj, to add a capable, robust user configuration subsystem to any application.


Here’s a simple example:

#!/usr/bin/env python3

from config_decorator import section

def generate_config():

    class ConfigRoot(object):
        '''Decorate an empty class to create the root settings section.'''

    class ConfigSection(object):
        '''Use the root settings section decorator to define setting groups.'''

            "The color",
            choices=['red', 'yellow', 'blue'],
        def color(self):
            return 'red'

            "The volume",
            validate=lambda val: 0 <= val and val <= 11,
        def volume(self):
            return 11

    class ConfigSection(object):
        '''Another settings section.'''

            "Is it funky yet?",
        def funky(self):
            # Because value_type=bool, str will be converted to bool.
            # - Useful for config files where all values are strings!
            return 'False'

            "A list of numbers I heard in a song",
        def cleopatra(self):
            return [5, 10, 15, 20, 25, 30, 35, 40]

            "Example showing how to use dashes in a settings name",
        def kick_out_the_jams(self):
            return "I done kicked em out!"

    return ConfigRoot

cfgroot = generate_config()

# The config object is subscriptable.
assert cfgroot['mood']['color'] == 'red'

# You can override defaults with user values.
cfgroot['mood']['color'] = 'blue'
assert cfgroot['mood']['color'] == 'blue'

# And you can always reset your values back to default.
assert cfgroot.mood.color.default == 'red'
assert cfgroot['mood']['color'] == 'red'

# The config object is attribute-aware (allows dot-notation).
cfgroot.vibe.cleopatra.value = 100
# And list-type values intelligently convert atoms to lists.
assert cfgroot.vibe.cleopatra.value == [100]

# The config object is environ-aware, and prefers values it reads
# from the environment over those from a config file.
import os
from config_decorator.key_chained_val import KeyChainedValue
KeyChainedValue._envvar_prefix = 'TEST_'
os.environ['TEST_MOOD_VOLUME'] = '8'
assert cfgroot.mood.volume.value == 8

# The config object can be flattened to a dict, which makes it easy
# to persist settings keys and values to disk using another package.
from configobj import ConfigObj
saved_cfg = ConfigObj('path/to/persisted/settings')

# Likewise, values can be read from a dictionary, which makes loading
# them from a file saved to disk easy to do as well.
saved_cfg = ConfigObj('path/to/persisted/settings')


  • A setting value may come from one or more sources, but the value of the most important source is the value used. A setting value may come from the following sources, ordered from most important to least:
    • A “forced” value set internally by the application.
    • A “cliarg” value read from command line arguments.
    • An “envvar” value read from an environment variable.
    • A “config” value read from a user-supplied dictionary (e.g., from an INI file loaded by ConfigObj).
    • A default value (determined by decorated method used to define the setting).
  • Each setting value is:
    • always type-checked, though the type check could be a no-op;
    • optionally validated, possibly against a user-supplied choices list;
    • always documented, either by the first decorator argument, or from the decorated method '''docstring''';
    • sometimes hidden (e.g., for developer-only or experimental settings, to keep the user from seeing the setting unless its value differs from the default value);
    • sometimes ephemeral, or not saved (e.g., for values based on other values that must be generated at runtime, after all value sources are loaded).


  • For complete usage examples, see this project’s tests/.
  • For a real-world usage example, see nark’s ConfigRoot and related.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for config-decorator, version 2.0.14
Filename, size File type Python version Upload date Hashes
Filename, size config_decorator-2.0.14-py3-none-any.whl (23.3 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size config-decorator-2.0.14.tar.gz (2.8 MB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page