object-settings 2.2

Simple object-oriented config library, where your settings are objects

object-settings 2.0

Simple-to-use object-oriented Python config library, where your settings are objects.

Their values have automatic validation and get saved to a file that's seamlessly written and read in the background, so you don't have to worry about any of it. This makes it quick to define and use settings (see examples below).

Installation & usage

This module is on PyPi, so you can just do pip install object-settings

After which it will be available with just the package name settings

import settings
settings.setup("Your app name")

your_option1 = settings.Toggle("Your first option label")
your_option2 = settings.Number("Your second option label")

Simple objects

For example, you can set a font size at the top of your ui file:

font = settings.Number(default=14)

...
someuilib.Label("Bababooey", size=font.value)
...
someuilib.Textbox("Lorem ipsum dolor...", font_size=font.value)
...

Or if a setting is only checked in one place, it can be used without defining a variable:

if settings.Toggle("Update app automatically", default=True):
    # do update

(it doesn't matter if the same setting is initialized multiple times)

Integration

The setting objects support "equals"-checking with actual values:

speed = settings.Number("Speed limit", 5)

print(speed == 5)
>> True
print(speed == 3)
>> False

In addition, they work with many type-specific operations:

for selection in settings.Multichoice():
    ...

if settings.Toggle():
    ...

Automatic storing

When a setting's value is read/set, object-settings automatically creates and updates a config file on the disk in the background. Any file deletions or unparsable external modifications are also handled.

By default, the files are saved to a standard config location, depending on the platform (uses appdirs package for paths). You can also set a custom directory for e.g. running in a Docker container.

Value validation

When a new value is set, it automatically gets validated and raises a ValueError if it doesn't pass. This validation includes more than just datatypes, for example numbers can have min/max limits or a path setting can be set to require an existing path.

Listen for changes

If you have some update function that you want to be called when a setting is changed, you can add that function as a listener:

setting.add_listener(your_function)

Now the function will be called every time when a new value is set.

Sections

Optionally, if you have a lot of settings, you can organize them into sections (which also works well with UIs)

download_options = settings.Section("Downloader settings")
speed = settings.Number("Speed limit", 5, section=download_options)
dir = settings.Path("Target directory", '/home/yomama/Downloads', section=download_options)
server = settings.Choice("Mirror", ["Europe", "Asia", "America", "Africa"], "Asia", section=download_options)

Setting types

List of currently available setting types:

• Toggle (bool)
• Choice (str) [from a list of options]
• Multichoice (list) [of things from a list of options]
• Text (str)
• Path (str)
• Number (int)