Up to Python 2.1, old-style classes were the only flavour available to the user.
The concept of (old-style) class is unrelated to the concept of type:
if x
is an instance of an old-style class, then x.__class__
designates the class of x
, but type(x)
is always <type
'instance'>
.
This reflects the fact that all old-style instances, independently of
their class, are implemented with a single built-in type, called
instance.
New-style classes were introduced in Python 2.2 to unify the concepts of class and type.
A new-style class is simply a user-defined type, no more, no less.
If x is an instance of a new-style class, then type(x)
is typically
the same as x.__class__
(although this is not guaranteed – a
new-style class instance is permitted to override the value returned
for x.__class__
).
The major motivation for introducing new-style classes is to provide a unified object model with a full meta-model.
It also has a number of immediate benefits, like the ability to
subclass most built-in types, or the introduction of "descriptors",
which enable computed properties.
For compatibility reasons, classes are still old-style by default.
New-style classes are created by specifying another new-style class
(i.e. a type) as a parent class, or the "top-level type" object if no
other parent is needed.
The behaviour of new-style classes differs from that of old-style
classes in a number of important details in addition to what type
returns.
Some of these changes are fundamental to the new object model, like
the way special methods are invoked. Others are "fixes" that could not
be implemented before for compatibility concerns, like the method
resolution order in case of multiple inheritance.
Python 3 only has new-style classes.
No matter if you subclass from object
or not, classes are new-style
in Python 3.
Best Answer
You need to decide if you want an existential or universal quantification on that type. Universal quantification, ala:
yields a proof obligation that Num and Ord instances exist for the type 'a' but doesn't actually help all that much, because all it does is give you an obligation when you go to use the Point class by constructing a value of that type or when you go to pattern match it.
In almost all cases you are better off defining
and making each of your instances contingent on the extra information you want.
This lets you pass around and construct fewer superfluous dictionaries and increases the number of scenarios in which your Point2 data type can be used.
On the other hand existential quantification can let you say that you don't care what the type is at all (closer to what you actually requested, type wise) at the expense that you can't use anything on it except for the operations provided by the constraints you specified -- a pretty poor fit here.