A towel wrapped ConfigParser API.
Project description
Figs
Figs is a library for reading ini like configuration files easily. Figs leverages the ConfigParser module from python’s standard libraries.
I personally don’t like the ConfigParser API very much, so I wrote this. The idea is that the developer should have little overhead in thinking when using this library, i.e., an intuitive API.
Usage
If you are familiar with PyYaml or the standard library’s json modules, the following should be quite familiar to you.
To load a configuration, use the load/loads functions. The following return the same:
>>> # Takes a filename
>>> conf = figs.load('config.ini')
>>> # or a file-like object
>>> conf = figs.load(open('config.ini'))
>>> # Takes a string to be parsed
>>> conf = figs.loads('''\
[universe]
answer = 42
is_active = yes
status = expanding
''')
And, to dump configuration:
>>> # Takes a filename
>>> figs.dump(conf, 'config.ini')
>>> # or a file-like object
>>> figs.dump(conf, open('config.ini'))
>>> # Dump to string
>>> figs.dumps(conf)
[universe]
answer = 42
is_active = yes
status = expanding
>>> # You can also dump just a section
>>> figs.dumps(conf.universe)
answer = 42
is_active = yes
status = expanding
Those are the only functions in the figs module that you should be concerned with.
Once you have the config object, how’d you use it? Surprise surprise! Anyway you feel comfortable :)
Dictification
I know, you just want a dict of properties from the config file and be done with it. Lets see if you can guess how this can be done?:
>>> # Returns a dict like {'section-name': <Section object>}
>>> dict(conf)
>>> # Returns a dict like {'key': <TypeableStr object>}
>>> dict(conf.universe)
You should keep in mind that dict on does not automatically do a dict on its Section objects. The TypeableStr class is a subclass of unicode with a few methods added (as_bool, as_int and as_float).
If you want a dict of dicts, though, you can get that too.:
>>> figs.as_dict(conf)
>>> # or when loading
>>> conf = figs.load('config.ini', as_dict=True)
The loads method also takes the as_dict argument. Note that the as_dict has to be a keyword argument.
Accesses
>>> conf.universe.answer u'42' >>> conf.universe.answer.as_int 42 >>> conf.universe.is_active u'yes' >>> conf.universe.is_active.as_bool True >>> conf.universe.status u'expanding' >>> conf.universe['status'] u'expanding'
Similary to as_int as shown above, there are also as_bool (boolean conversion done similar to how ConfigParser.getboolean does) and as_float.
Check for presence
>>> 'universe' in conf True >>> 'multiverse' in conf False >>> 'answer' in conf.universe True >>> 'is_active' in conf.universe True >>> 'is-active' in conf.universe False
Modifying configs
Set new options…:
>>> conf.universe.is_active = False >>> conf.universe.planet_maker = 'Magrathea' >>> conf.universe['earth-owners'] = 'mice' >>> figs.dumps(conf) [universe] answer = 42 is_active = false status = expanding planet_maker = Magrathea earth-owners = mice
…on new sections:
>>> conf.multiverse.is_active = True >>> figs.dumps(conf) [universe] answer = 42 is_active = false status = expanding [multiverse] is_active = true
Deleting
The API is very boring isn’t it?:
>>> del conf.universe.answer >>> del conf.multiverse
Now what?
Well, if you have a life, get on with it. Seriously, there’s nothing else to reading config files here.
Meta
License
MIT License (http://mit.sharats.me).
Contributing
Code is available at the github repository. Clone. Modify. Send pull request. If the modification is fairly large, I prefer you open a github issue first to discuss it.
Changelog
- 0.1.2
Move to github.
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