bdict

A library allowing you to create an auto method-binding dict.

Ever dreamed of writing clean dicts pointing keys to methods? Fear no more!

Mainly used for event handlers, a binding dict consists of a mapping between any events or keys, to their appropriate handler functions within a class. Upon key lookup, the dict will bind the appropriate function to the instance of the class.

For an example:

class Server:
    """Typical server with a small mapping between event handlers and functions"""
    def __init__(self, name):
        self.name = name

    def on_connect(self, remote_host):
        print(self.name, remote_host)

    def on_connect(self, remote_host):
        print(self.name, remote_host)

    handlers = BDict({NewConnectionEvent: on_connect,
                      DisconnectonEvent: on_disconnect})

>>> s = Server("myserver")
>>> s.handlers[NewConnectionEvent]("1.2.3.4")
myserver 1.2.3.4

As you can see, after accessing the handlers dict, and upon key lookup, the dict bound the handler functions to the instance.

BDict also works with classmethods in a clean and fashioned way:

class MyClass:
    """Typical server with a small mapping between event handlers and functions"""            
    @classmethod
    def class_handle(cls):
        print(cls.__name__)

    handlers = BDict({"class_handle": class_handle})

>>> MyClass.handlers["class_handle"]
<bound method MyClass.class_handle of <class '__main__.MyClass'>>
>>> MyClass.handlers["class_handle"]()
MyClass

>>> inst = MyClass()
>>> inst.handlers["class_handle"]
<bound method MyClass.class_handle of <class '__main__.MyClass'>>
>>> inst.handlers["class_handle"]()
MyClass

Upon accessing the BDict through an instance, the BDict will be autocached on the BDict, allowing you to modify it's dictionary and not affect other instances!

>>> inst.handlers[123] = 456
>>> inst.handlers[123]
456
>>> inst2 = MyClass()
>>> inst2.handlers[123]
Traceback (most recent call last):
  ...
KeyError: 123

Usage:

BDict(dict_, *, strong=None, autocache=True)

dict_ can be a dict or an iterable of (key, value) pairs and will be used to initialize BDict.

strong defaults to None and configures whether BDict stores a strong reference to the instance. False will cause bdict to use only weak references but not work when the original instance dissapears. True forces a strong reference but might cause a cyclic reference if autocache is used. By default (recommended), BDict will attempt to use a weak reference and if it fails to bind the cache (due to the instance having __slots__ or autocache=False) it will use a strong reference.

autocache configures whether to cache the BDict on the instance. Caching results in faster access but does not work if __slots__ are defined, and will prevent changes made on the class'es BDict from appearing.

If an object is defined using __slots__, I highly suggest adding __weakref__ to the slots.