I am prototyping a new system in Python; the functionality is mostly numerical.
An important requirement is the ability to use different linear algebra back-ends: from individual user implementations to generic libraries, such as Numpy. The linear algebra implementation (that is, the back-end) must be independent from the interface.
My initial architectural attempt is as follows:
(1) Define the system interface
>>> v1 = Vector([1,2,3])
>>> v2 = Vector([4,5,6])
>>> print v1 * v2
>>> # prints "Vector([4, 10, 18])"
(2) Implement the code allowing to use that interface independently of the back-end
# this example uses numpy as the back-end, but I mean
# to do this for a general back-end
import numpy
def numpy_array(*args): # creates a numpy array from the arguments
return numpy.array(*args)
class VectorBase(type):
def __init__(cls, name, bases, attrs):
engine = attrs.pop("engine", None)
if not engine:
raise RuntimeError("you need to specify an engine")
# this implementation would change depending on `engine`
def new(cls, *args):
return numpy_array(*args)
setattr(cls, "new", classmethod(new))
class Vector(object):
__metaclass__ = VectorBase
# I could change this at run time
# and offer alternative back-ends
engine = "numpy"
@classmethod
def create(cls, v):
nv = cls()
nv._v = v
return nv
def __init__(self, *args):
self._v = None
if args:
self._v = self.new(*args)
def __repr__(self):
l = [item for item in self._v]
return "Vector(%s)" % repr(l)
def __mul__(self, other):
try:
return Vector.create(self._v * other._v)
except AttributeError:
return Vector.create(self._v * other)
def __rmul__(self, other):
return self.__mul__(other)
This simple example works as follows: the Vector class keeps a reference to a vector instance made by the back-end (numpy.ndarray in the example); all arithmetic calls are implemented by the interface, but their evaluation is deferred to the back-end.
In practice, the interface overloads all the appropriate operators and defers to the back-end (the example only shows __mul__ and __rmul__, but you can follow that the same would be done for every operation).
I am willing to loose some performance in exchange of customizability. Even while my example works, it does not feel right -- I would be crippling the back-end with so many constructor calls! This begs for a different metaclass implementation, allowing for a better call deferment.
So, how would you recommend that I implement this functionality? I need to stress the importance of keeping all of the system's Vector instances homogeneous and independent of the linear algebra back-end.
