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Container for flexible class, instance, and function call options

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options helps encapsulate options and configuration data using a layered stacking model (a.k.a. nested contexts).

For most functions and many classes, options is overkill and not recommended. Python’s already-flexible function arguments, *args, **kwargs, and inheritance patterns are elegant and sufficient for 99.9% of all development situations.

options is intended for the 0.1%: highly functional classes that have many different options, that aim for “reasonable” or “intelligent” defaults and behaviors, that allow users to override those defaults at any time, and yet that aim for a simple, unobtrusive API.

In those cases, Python’s simpler built-in, inheritance-based model leads to fairly complex code as non-trivial options and argument-management code spreads through many individual methods. This is where options’s delegation-based approach begins to shine.


In a typical use, your class defines default option values. Subclasses can add, remove, or override options. Instances use class defaults, but they can be overridden when each instance is created. For any option an instance doesn’t override, the class default “shines through.”

So far, this isn’t very different from a typical use of Python’s standard instance and class variables. The next step is where options gets interesting.

Individual method calls can similarly override instance and class defaults. The options stated in each method call obtain only for the duration of the method’s execution. If the call doesn’t set a value, the instance value applies. If the instance didn’t set a value, its class default applies (and so on, to its superclasses, if any).

One step further, Python’s with statement can be used to set option values for essentially arbitrary duration. As soon as the with block exists, the option values automagically fall back to what they were before the with block. (In general, if any option is unset, its value falls back to what it was in the next higher layer.)

To recap: Python easily layers class, subclass, and instance settings. options layers class, subclass, and instance settings as well, but also adds method and transient settings. When Python mechanisms override a setting, they do so destructively; they cannot be “unset” without additional code. When a program using options overrides a setting, it does so non-destructively, layering the new settings atop the previous ones. When attributes are unset, they immediately fall back to their prior value (at whatever higher level it was last set).

Unfortunately, because this is a capability designed for high-end, edge-case situations, it’s hard to demonstrate its virtues with simple code. But we’ll give it a shot.

from options import Options, attrs

class Shape(object):

    options = Options(
        name   = None,
        color  = 'white',
        height = 10,
        width  = 10,

    def __init__(self, **kwargs):
        self.options = Shape.options.push(kwargs)

    def draw(self, **kwargs):
        opts = self.options.push(kwargs)
        print attrs(opts)

one = Shape(name='one')
one.draw(color='green', width=22)


color='white', width=10, name='one', height=10
color='red', width=10, name='one', height=10
color='green', width=22, name='one', height=10

So far we could do this with instance variables and standard arguments. It might look a bit like this:

class ClassicShape(object):

    def __init__(self, name=None, color='white', height=10, width=10):   = name
        self.color  = color
        self.height = height
        self.width  = width

but when we got to the draw method, things would be quite a bit messier.:

def draw(self, **kwargs):
    name   = kwargs.get('name',
    color  = kwargs.get('color',  self.color)
    height = kwargs.get('height', self.height)
    width  = kwargs.get('width',  self.width)
    print "color='{0}', width={1}, name='{2}', height={3}".format(color, width, name, height)

One problem here is that we broke apart the values provided to __init__() into separate instance variables, now we need to re-assemble them into something unified. And we need to explicitly choose between the **kwargs and the instance variables. It gets repetitive, and is not pretty. Another classic alternative, using native keyword arguments, is no better:

def draw2(self, name=None, color=None, height=None, width=None):
    name   = name   or
    color  = color  or self.color
    height = height or self.height
    width  = width  or self.width
    print "color='{0}', width={1}, name='{2}', height={3}".format(color, width, name, height)

If we add just a few more instance variables, we have the Mr. Creosote of class design on our hands. Every possible setting has to be managed in every method. It’s neither elegant nor scalable. Things get even worse if we want to set default values for all shapes in the class. We have to rework every method that uses values, the __init__ method, et cetera. We’ve entered “just one more wafer-thin mint…” territory.

But with options, it’s easy:

one.draw(height=44, color='yellow')


color='blue', width=10, name='one', height=10
color='blue', width=10, name='one', height=100
color='yellow', width=10, name='one', height=44

In one line, we reset the default for all Shape objects. (In typical usage we’d also define Shape.set() to transparently forward to Shape.options.set() for an even simpler resulting API.)

The more options and settings a class has, the more unwieldy the class and instance variable approach becomes, and the more desirable the delegation alternative. Inheritance is a great software pattern for many kinds of data and program structures–but it’s a bad, or at least incomplete, pattern for complex option and configuration handling.

For richly-featured classes, options’s delegation pattern is simpler. As the number of options grows, almost no additional code is required. More options impose no additional complexity and introduce no additional failure modes. Consolidating options into one place, and providing neat attribute-style access, keeps everything tidy. We can add new options or methods with confidence:

def is_tall(self, **kwargs):
    opts = self.options.push(kwargs)
    return opts.height > 100

Under the covers, options uses a variation on the ChainMap data structure (a multi-layer dictionary) to provide option stacking. Every option set is stacked on top of previously set option sets, with lower-level values shining through if they’re not set at higher levels. This stacking or overlay model resembles how local and global variables are managed in many programming languages.

This makes advanced use cases, such as temporary value changes, easy:

with one.settings(height=200, color='purple'):
    if is_tall(one):
        ...         # it is, but only within the ``with`` context

if is_tall(one):    # nope, not here!

Full disclosure: Doing temporary settings took more class setup code than is shown above. Four lines of code, to be precise.

As one final feature, consider “magical” parameters. Add the following code:

    height = lambda v, cur: cur.height + int(v) if isinstance(v, str) else v,
    width  = lambda v, cur: cur.width  + int(v) if isinstance(v, str) else v

Now, in addition to absolute height and width parameters specified with int (integer/numeric) values, your module auto-magically supports relative parameters for height and width.:



color='blue', width=210, name='one', height=10

Neat, huh?

For more, see this discussion of how to combat “configuration sprawl” and options full documentation on Read the Docs. For examples of options in use, see say and show.

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