Python component model
Edward Diener No Spam
eldiener_no_spam_here at earthlink.net
Tue Oct 10 17:29:58 EDT 2006
fumanchu wrote:
> Edward Diener No Spam wrote:
>> OK, here is my idea of what such a component model envisages as a list
>> of items. After this, unless I get some intelligent comments from people
>> who might be interested in what I envision, or something very similar, I
>> will be off to investigate it myself rather than do battle with the
>> horde of people who will just tell me that Python, being a great
>> language, does not need what I have suggested.
>
> [This quote hacked up by me:]
>> 1) Component property: This is a glorified attribute with a type that
>> a) can be specified in a "static" manner, or discovered dynamically,
>> b) has converters between a string and the actual value
>> c) has a getter function to retrieve the value if it is readable and a
>> setter function to set the value if it is writable.
>> d) be either readable or writable or both.
>> e) not any Python class attribute since a component has the right
>> to specify only certain values as manipulatable in a design-time
>> RAD environment.
>
> Whenever you say "glorified attribute", your first thought should be
> "Python descriptor" (but not your last--it's not a cure-all). They are
> able to do all of (a, b, c, d, e) which I marked in your text above.
> For example, here's a descriptor for
> attributes-you-want-to-persist-in-a-database from my ORM, Dejavu (see
> http://projects.amor.org/dejavu/browser/trunk/units.py#l290):
>
>
> class UnitProperty(object):
> """Data descriptor for Unit data which will persist in storage."""
>
> def __init__(self, type=unicode, index=False, hints=None, key=None,
> default=None):
> self.type = type
> self.index = index
> if hints is None: hints = {}
> self.hints = hints
> self.key = key
> self.default = default
>
> def __get__(self, unit, unitclass=None):
> if unit is None:
> # When calling on the class instead of an instance...
> return self
> else:
> return unit._properties[self.key]
>
> def __set__(self, unit, value):
> if self.coerce:
> value = self.coerce(unit, value)
> oldvalue = unit._properties[self.key]
> if oldvalue != value:
> unit._properties[self.key] = value
>
> def coerce(self, unit, value):
> if value is not None and not isinstance(value, self.type):
> # Try to cast the value to self.type.
> try:
> value = self.type(value)
> except Exception, x:
> x.args += (value, type(value))
> raise
> return value
>
> def __delete__(self, unit):
> raise AttributeError("Unit Properties may not be deleted.")
>
>> a) can be specified in a "static" manner, or discovered dynamically,
>
> The "component model" can either scan a class for instances of
> UnitProperty or keep a registry of them in the class or elsewhere (via
> a metaclass + add_property functions).
>
>> b) has converters between a string and the actual value
>
> Note the "coerce" function above. Something similar could be done for
> serialization (which I can prove in my case because I use UnitProperty
> to help produce SQL ;) but you could just as easily pickle
> unit._properties and be done with it.
>
>> c) has a getter function to retrieve the value if it is readable and a
>> setter function to set the value if it is writable.
>> d) be either readable or writable or both.
>
> Descriptors that only have __get__ are read-only; if they have __set__
> they are read-write.
>
>> e) not any Python class attribute since a component has the right
>> to specify only certain values as manipulatable in a design-time
>> RAD environment.
>
> Right. Descriptors allow the creator of a class to use "normal"
> attributes (including functions) which don't participate in the
> component model.
>
>> 2) Component event: This is an type which encapsulates an array, or a
>> list of callable objects with the same function signature, along with
>> the functionality to add and remove elements from the array, as well as
>> cycle through the array calling the callable objects as a particular
>> event is triggered. A component event is an event source for a
>> particular event. Component events have to be dicoverable by the Visual
>> RAD system so that an object's appropriate event handler, an event sink,
>> can be hooked to the component event itself, an event source, through a
>> design time interface which propagates the connection at run-time.
>
> This can be accomplished by creating a ComponentEvent descriptor whose
> __get__ returns an object with a __call__ method. Here's a base class
> for something similar (again, from Dejavu):
>
> class UnitAssociation(object):
> """Non-data descriptor method to retrieve related Units via
> attributes."""
>
> to_many = None
>
> def __init__(self, nearKey, farClass, farKey):
> # Since the keys will be used as kwarg keys, they must be
> strings.
> self.nearKey = str(nearKey)
> self.farKey = str(farKey)
>
> self.nearClass = None
> self.farClass = farClass
>
> def __get__(self, unit, unitclass=None):
> if unit is None:
> # When calling on the class instead of an instance...
> return self
> else:
> m = types.MethodType(self.related, unit, unitclass)
> return m
>
> def __delete__(self, unit):
> raise AttributeError("Unit Associations may not be deleted.")
>
> def related(self, unit, expr=None, **kwargs):
> raise NotImplementedError
>
> Subclasses override the "related" method, but a ComponentEvent class
> could just as easily do:
>
> def run(self, *args, **kwargs):
> for sink in self.sinks:
> sink(*args, **kwargs)
>
>> 3: Component serialization: A component which has its properties and
>> events set by a visual design-time RAD environment needs to be
>> serialized at design time and deserialized at run-time. This can be a
>> default serialization of all component properties and events, or the
>> component itself can participate in the serilization effort either
>> wholly or partly.
>
> In Dejavu, the UnitProperty class is your "component property" and the
> Unit class is the component. The Unit class has a copy method:
>
> def __copy__(self):
> newUnit = self.__class__()
> for key in self.properties:
> if key in self.identifiers:
> prop = getattr(self.__class__, key)
> newUnit._properties[key] = prop.default
> else:
> newUnit._properties[key] = self._properties[key]
> newUnit.sandbox = None
> return newUnit
>
> It wouldn't be hard to replace "newUnit._properties[key] =
> self._properties[key]" with "dump(self._properties[key])".
>
>> 4) Custom property and component editors: A component editor can present
>> a property editor or an editor for an entire component which the visual
>> design-time RAD environment can use to allow the programmer end-user of
>> the component to set or get component property values. Normally a design
>> time environment will present default property editors for each
>> component property type, but a component can override this.
>
> This is the hard part. I believe Dabo has done some work in this space,
> but this is where the tight coupling comes in between code and tool, a
> coupling which Python has traditionally resisted.
It's more of a coupling between a type and a tool. Only user-defined
types as component properties need their own property editor, whereas
all other Python types can be coupled with default property editors. Of
course the class designer must have a right to create their own property
editor for a particular type or a particular property of that type in
order to override the default property editors for a particular type.
>
>> 5) Custom type converters: A component should be able to specify a
>> custom converter for any property to convert, in both directions or
>> either direction, between the property's string value as seen by a
>> property editor and the actual value of the component property's type.
>
> A ComponentProperty descriptor could include a custom pair of methods
> to get/set as string. This is often done in web frameworks which need
> to coerce incoming string values to the correct type.
Thanks for your information abouit using descriptors. I will look into
it further but I really appreciate your example.
>
> All of which is to say: nobody's done this yet because parts 1, 2, 3
> and 5 are trivial to do with descriptors, but actually building a
> visual RAD environment is too much work. ;)
The idea of course is that with the correct component underpinnings and
perhaps high-level modules which make it easy for a visual RAD
environment to introspect the necessary component properties and
component events, as well as serialize them at design time and create
code to deserialize them at run-time, the work of creating a visual RAD
environment would not be so daunting.
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