bonfig 0.1

Nicer config writing

Bonfig

Bonfig aims to provide a more beautiful way to create and use configurations.

The two core ideas are:

1. Enable the creation of configurations using a class declaration.
2. Things are less stressful when the underlying data in a configuration is kept serialisable

Bonfig works with configparser to make creating configs fun:

from bonfig import PyBonfig

class MyConfig(PyBonfig):

    output = PySection('Output')
    A = output.PyField('a', default='foo')
    B = output.PyField('b', default='bar')
    C = output.PyIntField('c', default=6543)

c = MyConfig()
print(c.A) # -> 'a'
print(c.C) # -> 6543
c.C = 325
print(c.C) # -> 325

Hidden inside the PyBonfig instance is a ConfigParser object storing all the info, which is easily accessible, with d.

>>> c.d
<configparser.ConfigParser at 0x231b5403208>
>>> c.d._sections # peer inside config parser
OrderedDict([('Output',
          OrderedDict([('a', 'foo'), ('b', 'bar'), ('c', '325')]))])

As you can see, internally, the data is always stored as strings. Some 'ready-made' field types that implicitly convert values to and from strings as they are 'get' and 'set' are provided: IntField, FloatField and BoolField.

Custom 'get' and 'set' behaviour is simple to achieve by subclassing Field and using the pre_set and post_get hooks:

@pyfields.add # makes available to PySection objects
class PyTimeField(PyField):

    def post_get(self, val):
        return datetime.time(int(val))

    def pre_set(self, val):
        return str(val.hour)

class MyConfig(PyBonfig):

    output = PySection('Output')
    A = output.PyField('a', default='foo')
    T = output.PyTimeField('t', default=datetime.time(21))

c = MyConfig()
print(c.T) # -> datetime.time(21, 0)

Some shortcuts to creating your own field classes are provided, check out fields.make_quick and pyfields.make_quick in bonfig.py!

Pleasingly, Bonfig plays nicely with inheritance so you can do cool stuff like:

class MyBaseConfig(PyBonfig):

    basic = PySection('Basic')
    A = basic.PyField('a', default='loopy')

class MyExtendedConfig(MyBaseConfig):

    extra = PySection('Extra')
    B = extra.PyField('b', default='bar')

c = MyExtendedConfig()
c.d._sections # -> OrderedDict([('Extra', OrderedDict([('b', 'bar')])),
         ('Basic', OrderedDict([('a', 'loopy')]))])

If you don't want to use a config parser to store your data, the Bonfig class just uses a plain ol' dictionary, which makes more hierarchical structures possible. (The 'Py' prefix has been used to indicate using configparser internally, and as such is a specialisation of the Bonfig class)

Check out the docstrings and examples folder for more info.

Copyright (c) 2018 Hugh Ramsden

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