Simple framework to parse multiple configuration files of different formats and update them.
The usage of this framework is straight-forward.
Create a Configuration instance. When creating one, give the inputs to read from as arguments. The input can be either a dictionary, to be immediately used, or alternatively a file name which ends on one of the supported file types below.
Afterwards, call the load function on the configuration instance. This
function allows to define additional inputs. It's a matter of choice whether
one wants to define the inputs in the constructor or in the load call.
The load function uses the previously defined configuration inputs. The
function builds one large configuration dictionary out of all the inputs.
Overlapping parameters are always overwritten.
This makes it easy to define configurations of different priorities. One good approach is to define the configuration inputs as follows:
[defaults, custom configuration, environment variables, command line arguments]
To access the values of the configuration, one can either use the regular access of dictionaries, e.g. a concatenation of gets(). Alternatively one can simply use dot notation. However, the most convenient way to access attributes of the configuration is the regular attribute access. The recursive nature of the framework makes it work like a charm.:
config = Configuration('api-config.json').load()
sample = config.get('api').get('hostname')
# Alternative dot notation
sample = config.get('api.hostname')
# Attribute notation
sample = config.api.hostname
If you, for some reason dislike the regular seperator '.' in the dot notation you can choose a custom one when initializing the configuration instance.
- json
- toml
The framework is solely implemented and tested on Linux. I can not guarantee for any expected behaviour on other platforms. If you use the framework on another platform, please share your experiences with me.
In addition, the attribute notation (config.api.hostname) is just tested for
the default seperator .. Since the . has a special meaning in Python, it is
easiest to use. To keep the framework simple and still flexible, we decided to
not add an internal representation to circumvent the seperator limitation.
MIT License Copyright (c) 2021 Max Resing
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