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Puzzling OO design problem

I'm looking for a design to a problem I came across, which goes like
this (no, it's not homework):

1. There is a (single inheritance) hierarchy of domain classes, say
A<-B<-..<-Z (arrows point to the parent in the inheritance tree).
2. This hierarchy evolved over time to different versions for each
class. So for example, version's 1 hierarchy would be A_v1 <-B_v1
<-..<-Z_v1.
3. At runtime, only one version is selected by a factory function.

Up to this point, the inheritance graph would be the following:

A <- A_V1 ... <- A_Vn
^ ^ ^
| | |
B <- B_V1 ... <- B_Vn
.. . .
.. . .
.. . .
^ ^ ^
| | |
Z <- Z_V1 ... <- Z_Vn
This could be implemented either with multiple inheritance (e.g.
B_V1(B,A_V1)) or using the bridge design pattern |Z| times, one per
each row. Both solutions would be acceptable; there are no ambiguities
caused by the multiple inheritance (or they are resolved properly
whenever they occur).

Now the problem is that there are 'holes' in this inheritance lattice:
Not all versions introduced new variations of all types; for instance
B_V5 could be missing, meaning that the most recent earlier version of
B would be used in version 5 (say B_V2). My first thought was to create
all the missing classes dynamically, but it's somewhat obscure and it
may not be that simple. Is there a more elegant solution, either a
general design pattern or some clever python metaprogramming hack ?

George

Jul 18 '05 #1
18 1935
On Fri, Apr 08, 2005 at 04:42:52PM -0700, George Sakkis wrote:
I'm looking for a design to a problem I came across, which goes like
this (no, it's not homework):

1. There is a (single inheritance) hierarchy of domain classes, say
A<-B<-..<-Z (arrows point to the parent in the inheritance tree).
2. This hierarchy evolved over time to different versions for each
class. So for example, version's 1 hierarchy would be A_v1 <-B_v1
<-..<-Z_v1.
3. At runtime, only one version is selected by a factory function.

Up to this point, the inheritance graph would be the following:

A <- A_V1 ... <- A_Vn
^ ^ ^
| | |
B <- B_V1 ... <- B_Vn
. . .
. . .
. . .
^ ^ ^
| | |
Z <- Z_V1 ... <- Z_Vn
This could be implemented either with multiple inheritance (e.g.
B_V1(B,A_V1)) or using the bridge design pattern |Z| times, one per
each row. Both solutions would be acceptable; there are no ambiguities
caused by the multiple inheritance (or they are resolved properly
whenever they occur).

Now the problem is that there are 'holes' in this inheritance lattice:
Not all versions introduced new variations of all types; for instance
B_V5 could be missing, meaning that the most recent earlier version of
B would be used in version 5 (say B_V2). My first thought was to create
all the missing classes dynamically, but it's somewhat obscure and it
may not be that simple. Is there a more elegant solution, either a
general design pattern or some clever python metaprogramming hack ?


Err, you might want to explain what these things do instead of an
abstract description of how you are doing it. It looks like you are
using inheritance in the normal way _and_ you are using it to handle
versioning of some kind (maybe stable interface releases? I don't know).

Let us know what parts need inheritance for, and what you have
just been using a side effect of inheritance for as a convenience
(versioning, I think).

A more concrete example would be easier to comment on, if possible
do a simple one (maybe just two classes with two versions each).

-jackdied
Jul 18 '05 #2
> Err, you might want to explain what these things do instead of an
abstract description of how you are doing it. It looks like you are
using inheritance in the normal way _and_ you are using it to handle
versioning of some kind (maybe stable interface releases? I don't know).
Let us know what parts need inheritance for, and what you have
just been using a side effect of inheritance for as a convenience
(versioning, I think).

A more concrete example would be easier to comment on, if possible
do a simple one (maybe just two classes with two versions each).

-jackdied


I intentionally abstracted the problem to remove the irrelevant
details, but here's a more concrete (though still simplified) example.
I hope it is more clear now.

George

#=============================

def worldModelFactory(version):
if version < 2: return WorldModel()
else: return WorldModel_v2()

class WorldModel(object):

def __init__(self):
self.ourGoal = self.FieldObject(x=-50, y=0)
self.theirGoal = self.FieldObject(x=+50, y=0)
self.ball = self.MovableObject()
self.teammates = [self.Player(i) for i in xrange(1,12)]
self.opponents = [self.Player(i) for i in xrange(1,12)]

class FieldObject(object):
def __init__(self, id=None, x=0, y=0):
self.id = id
self._pos = (x,y)
def position(self):
'''Get or estimate the current position.'''
return self._pos

class MovableObject(FieldObject):
def speed(self):
'''Get or estimate the current speed.'''
# [implementation snipped]

class Player(MovableObject):
def passBall(self,power,teammate):
'''Pass the ball to the teammate.'''
# [implementation snipped]
class WorldModel_v2(WorldModel):

class FieldObject(WorldModel.FieldObject):
'''New implementation of FieldObject.'''
def position(self):
# [new implementation snipped]
pass

class MovableObject(WorldModel.MovableObject, FieldObject):
'''MovableObject didn't change since the previous version. The
only reason for this class is to make
WorldModel_v2.FieldObject
accessible to WorldModel_v2.Player.
'''
pass

class Player(WorldModel.Player, MovableObject):
'''New implementation of Player.'''
def passBall(self,power,teammate):
# WorldModel_v2.FieldObject.position() should be called
myPosition = self.position()
# [new implementation snipped]

#=============================

Jul 18 '05 #3
On Fri, Apr 08, 2005 at 06:40:54PM -0700, George Sakkis wrote:
Err, you might want to explain what these things do instead of an
abstract description of how you are doing it. It looks like you are
using inheritance in the normal way _and_ you are using it to handle
versioning of some kind (maybe stable interface releases? I don't know).

Let us know what parts need inheritance for, and what you have
just been using a side effect of inheritance for as a convenience
(versioning, I think).

A more concrete example would be easier to comment on, if possible
do a simple one (maybe just two classes with two versions each).

-jackdied


I intentionally abstracted the problem to remove the irrelevant
details, but here's a more concrete (though still simplified) example.
I hope it is more clear now.


<boiled down version of George's exmaple>
def worldModelFactory(version):
if version < 2: return WorldModel()
else: return WorldModel_v2()

class WorldModel_v1(object):
class Player(object):
def foo(self): pass # v1 implementation of foo()

class WorldModel_v2(object):
class Player(WorldModel_v2.Player):
def foo(self): pass # v2 implementation of foo()
So you are using the WorldModel_* classes as a namespace to hold a
set of classes that might inherit and extend or redefine the previous
classes in a WorldModel_* namespace. This seems to do what you wanted
in your original post, namely if a class is defined in v1 but not in v2
that v2 would just use v1's implementation. WorldModel_v2 will inherit
Player from _v1 by default, so that should work OK out of the box.

So you should be fine there, but I think your question is more practical
than "what is the proper OO way to do it?" which is a bit of a shibboleth
in python. We like "what is easiest and readable?" So here are some
practical recommendations (well, at least that's my intention).

Are you using the *_v1 naming convention for backwards compatibility?
Backwards compatibility is a giant pain in the ass, I notice you are
posting from a .edu address so if this is just something you are working
on by yourself or in a small group drop the versioning aspects from the
code. Talking to the other people in the group is easier.
From your example (which I over-pruned) it looks like you are using

the WorldModel namespace to define parameters for running an iteration
of a game. The classes under "WorldModel" are something like
the rules/physics definition (MovableObject), coordinates of the team-A
goalpost, coordinates of the team-B goalpost, team-A strategy (Player),
and team-B strategy (also Player). WorldModel would be the gameboard.

If so, make WorldModel just a board - drop putting Player etc under it
as a namespace, and give it a run() function that takes parameters.
Name the Player derivatives as PlayerDumb, PlayerSmart, PlayerAggressive
etc, you'll probably have a lot more of those than goals or physics rules.
The actual main routine would look something like

ob = WorldModel() # standard 100x100 board
winner = ob.run(physics=MovableObject, # defines friction and gravity
team_a_goal=(50,25),
team_b_goal=(5,5),
team_a_strategy=PlayerDumb,
team_b_strategy=PlayerAggressive,
)
print "Winner is ", winner

I wrote more than I meant to, but the basic idea is don't use classes
when you don't need to - it just makes things more complex. That
should give you more time to tackle the interesting parts (player
strategies, I'd imagine).

-jackdied
Jul 18 '05 #4
> <boiled down version of George's exmaple>

I'm not sure if it was clear to you, but my problem is the dummy
WorldModel_v1.MovableObject class. It doesn't do anything by itself,
but it has to be in the inheritance chain to make its descendants work
properly.
Are you using the *_v1 naming convention for backwards compatibility?
Backwards compatibility is a giant pain in the ass, I notice you are
posting from a .edu address so if this is just something you are working on by yourself or in a small group drop the versioning aspects from the code.


Sure, if there was a single version there would be no need for this
post, but that's not the point; backwards compatibilty is part of the
sad reality. I'm trying to write a client for a framework that has gone
through 9 protocol version changes so far and now goes for the 10th.
There are 5-7 different game object classes, so this makes 50-70
classes overall for the ten versions. Most of them would be dummy like
the WorldModel_v1.MovableObject in the example. So the candidate
solutions so far are:
1. Write the dummy classes by hand.
2. Generate them on the fly using some metaprogramming technique
(introspection/metaclass/?)
3. Find an appropriate design pattern that avoids the need for the
dummy classes.

Any ideas for (2) or (3) ?

George

Jul 18 '05 #5
George Sakkis <gs*****@rutgers.edu> wrote:
1. There is a (single inheritance) hierarchy of domain classes, say
A<-B<-..<-Z (arrows point to the parent in the inheritance tree).
2. This hierarchy evolved over time to different versions for each
class. So for example, version's 1 hierarchy would be A_v1 <-B_v1
<-..<-Z_v1.
3. At runtime, only one version is selected by a factory function. Up to this point, the inheritance graph would be the following:

A <- A_V1 ... <- A_Vn
^ ^ ^
| | |
B <- B_V1 ... <- B_Vn
. . .
. . .
. . .
^ ^ ^
| | |
Z <- Z_V1 ... <- Z_Vn
Interesting problem.
This could be implemented either with multiple inheritance (e.g.
B_V1(B,A_V1))
To help myself thinking about that, let's make a somewhat complicated
example, somewhere in the middle of the graph, with the possibility of
introducing a hole at B3. I also shorten A_Vn to An etc. Consider the
subgraph (with nonstandard annotations of method definition after the bar
(to save space) as explained below):

A2 | f <- A3 | f
^ ^
| |
B2 <- B3
^ ^
| |
C2 | g <- C3 | h

Assume a method g that is present in C2 but not changed in C3. Now g
calls a method f, which is inherited unchanged in C2 from A2 (and not
changed in B2, B3 or C3, either), but changed in A3. Finally, let h
call g in C3. As here the "inheritance columns" have "priority", one
would expect then g to call f in A3, and not in A2, for example.

So what you need is that every method, even if not originating from
the "real" class, is looked up first in the column above the "real"
class, then in the column left to that, and so on.

Ok. Multiple inheritance can often select priority for conflicting
methods. If you can specify yhat tou want "column priority" for
each class, you're fine.
or using the bridge design pattern |Z| times, one per each row.
When I read your description above, I also thought immediately
"bridge pattern", but then I tried to write down details,
and got stuck. How would you do it?
Now the problem is that there are 'holes' in this
inheritance lattice: Not all versions introduced new variations of
all types; [...] My first thought was to create all the missing classes dynamically,
but it's somewhat obscure and it may not be that simple. Is there a
more elegant solution, either a general design pattern or some
clever python metaprogramming hack ?


In the most general case, you need to access time the whole "upper
left" subgraph at class creation, collect all methods defined in this
subgraph with "column priority", and overwrite or add to that any
methods defined in the newly defined class.

I don't know enough about the intricacies of Python's class creation
to make a concrete suggestion, but I'd think that would be possible
with the help of __metaclass__. You would need some sort of
repository for the complete inheritance. One way to do that would
be to create the chain A ... Z first, letting A inherit from some
special class with __metaclass__ set, and then store an array
of all versions somewhere inside the class namespace.

You'd also need some special syntax to create a new version of a class
(say, again inheriting from some special class with __metaclass__
set). You could set the version inside the class definition, and then
let the __metaclass__ routine disable the normal inheritance
mechanism, and add missing methods as appropriate.

This could for example look like

class A(Versioning):
...

class B(A):
...

class C(B):
def h ...
...

class A2(NewVersion,A):
__version__ = 2
def f(): ...

class B2(NewVersion,B):
__version__ = 2

class C2(NewVersion,C):
__version__ = 2
def g(): ... f() ...

class A3(NewVersion,A):
__version__ = 3
def f(): ...

class C3(NewVersion,C):
__version__ = 3
def h(): ... g() ...

with a hole at B3, as in the example. C3 will get g from C2 and f from
A3, and hence the call chain will work correctly. Also, C3 will have no
base classes (or maybe only the __metaclass__ ones), the inherited
class A, B, C are just used by the class creation process to find
out where to look for the inheritance matrix.

Others who know more about the class creation mechanism will no doubt
improve this suggestion, point out my errors, and tell you how to
implement it :-) Note that you're basically completely changing the
normal inheritance mechanism, and the class objects will be larger,
because they'll have to copy all the necessary methods.

I cannot think of any pattern that would give similar flexibility.

- Dirk
Jul 18 '05 #6
George Sakkis wrote:
<boiled down version of George's exmaple>

I'm not sure if it was clear to you, but my problem is the dummy
WorldModel_v1.MovableObject class. It doesn't do anything by itself,
but it has to be in the inheritance chain to make its descendants work
properly.

George,

since you explicit allowed metaprogramming hacks :-), how about something like
this (not tested beyond what you see):

class WorldVersion(type):
"""WorldVersion instances are World classes
If a World inherits from another World: Field, Movable, Player
automatically inherit from their corresponding superclasses"""

def __new__(self, name, bases, clsdict):
clslist = set(["Field", "Movable", "Player"])
baseworld = bases[0]
if type(baseworld) is self:
for cls in clslist:
base = getattr(baseworld,cls)
target = clsdict.setdefault(cls, base)
if base is target:
continue
oldbases = list(target.__bases__)
if base in target.__bases__:
continue
try:
oldbases[oldbases.index(object)] = base
except ValueError:
oldbases.append(base)
target = type(target.__name__, tuple(oldbases),
dict(target.__dict__))
clsdict[cls] = target

return type.__new__(self,name, bases, clsdict)

class World1(object):
__metaclass__ = WorldVersion
class Field(object):
def position(self):
print "Positioning in World1"
class Movable(Field):
def move(self):
print "Moving in World1"
class Player(Movable):
def passBall(self):
print "Passing in World1"

class World2(World1):
__metaclass__ = WorldVersion
class Field(object):
def position(self):
print "Positioning in World2"
class Movable(Field): # You still need placeholder classes
# but they are trivial
pass
class Player(Movable):
def passBall(self):
print "Passing in World2"

class World3(World2):
__metaclass__ = WorldVersion
class Player(object):
def passBall(self):
print "Passing in World3"

p3 = World3.Player()
p3.move() Moving in World1 p3.position() Positioning in World2 p3.passBall() Passing in World2


Michael

Jul 18 '05 #7
"Michael Spencer" <ma**@telcopartners.com> wrote:

George,

since you explicit allowed metaprogramming hacks :-), how about something like this (not tested beyond what you see):

[snipped]


Nice try, but ideally all boilerplate classes would rather be avoided
(at least being written explicitly). Also, it is not obvious in your
solution why and which placeholder classes have to be written (like
World2.Movable) and which do not. By the way, my current working
solution involves copying and pasting verbatim these classes :-) Below
is an abstracted example; note that the 'declaration string' of each
original class is exactly the same across all different versions after
the first (e.g. "class B(PreviousNamespace.B, A)").
#================================================= =====
# version_1.py

class Namespace:
class A(object):
def foo(self): return "version_1.foo()"
class B(A):
def bar(self): return "version_1.bar()"
class C(B):
def zen(self): return "version_1.zen()"
#================================================= =====
# version_2.py

from version_1 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
class A(PreviousNamespace.A):
def foo(self): return "version_2.foo()"
class B(PreviousNamespace.B, A):
pass
class C(PreviousNamespace.C, B):
pass
#================================================= =====
# version_3.py

from version_2 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
class A(PreviousNamespace.A):
pass
class B(PreviousNamespace.B, A):
def bar(self): return "version_3.bar()"
class C(PreviousNamespace.C, B):
pass

#================================================= =====
# test.py
# command: python test.py <#version>

def NamespaceFactory(version):
return __import__("version_%d" % version).Namespace

print NamespaceFactory(2).B().foo() # "version_2.foo()"
print NamespaceFactory(3).C().bar() # "version_3.bar()"

import sys, inspect
namespace = NamespaceFactory(int(sys.argv[1]))
# print the __mro__ of each 'inner' class
for name,cls in inspect.getmembers(namespace,
inspect.isclass):
print cls
for ancestor in cls.__mro__:
print "\t", ancestor

#================================================= =====

George

Jul 18 '05 #8
George Sakkis wrote:

Nice try, but ideally all boilerplate classes would rather be avoided
(at least being written explicitly).
It depends on how much magic you are prepared to accept; this goal is somewhat
in conflict with the next one...

Also, it is not obvious in your solution why and which placeholder classes have to be written (like
World2.Movable) and which do not.
It is systematic, if not obvious. You need place holder classes only if you
need to propagate new methods within a given world. More magic would make this
even less obvious.

By the way, my current working solution involves copying and pasting verbatim these classes :-)

It appears to be basically the same as mine except you spell out the previous
version explicitly (not that that's bad!)

Have you considered a 'macro' solution composing source? If I were handling so
many versions, I would want a complete class definition for each version rather
than having to scan many sources for each implementation.

Michael

Jul 18 '05 #9
Dirk Thierbach <dt********@usenet.arcornews.de> wrote:
Ok. Multiple inheritance can often select priority for conflicting
methods. If you can specify yhat tou want "column priority" for
each class, you're fine.


On second thought, I had doubts. Consider the following scenario:

A2 | f <- A3
^ ^
| |
B2 | f <- B3
^ ^
| |
C2 <- C3 | g

Assume g calls f. Since f is defined in B version 2, it should taken
over unchanged into B version 3, and that should be the version g
calls. However, with multiple inheritance doing depth-first search,
giving the "upper" class priority over the "left", the first path
searched is B3 - A3 - A2, and hence it finds f at A2. A quick test
confirms this for old-style classes, which failed in exactly that
way. But with new-style classes, it works, and finds f at B2 instead.

So I dug through the documentation and found that new-style classes
compute a monotonic linearization of the inheritance graph, observing
local precedence order, using the algorithm also used in Dylan
described here:

http://www.webcom.com/haahr/dylan/li...-oopsla96.html

And this algorithm will even work correctly if one leaves out B3
in the example above, inheriting directly as in C3(A3,C2), because
the ordering constraint that A2 comes before B2 will still be
valid in the linearization for C3.

However, in the following case (shortening the notation even more)
it will fail, if a method defined at C3 is looked up at D4:

A1 - A2 - A3 - A4 - ...
| | | |
B1 - B2 - + - B4 - ...
| | | |
C1 - + - C3 - + - ...
| | | |
D1 - D2 - + - D4 - ...
| | | |

The solution is simply to include C3 in the list of parents of D4, as
in D4(C3,B4,D2). So for every hole in a column, you have to include
the first class (or classes, if the hole spans multiple rows) to the
left of the hole as parents if the class just below the hole, in order
from bottom to top. This adds the missing constraints, and should
solve the problem without any need to write __metaclass__ stuff.

Interesting question. I learned a lot while thinking about that.

- Dirk
Jul 18 '05 #10
It may be useful to separate the code into version-independent part and
version-dependent part. Also, one can try to implement the higher-level
logic directly in the class definition of A, B, etc., and then use the
version objects only as patches for the details. That is, one can use
place-holder calls. The place-holder calls do nothing if a feature is
not really implemented (either in a parent class, or in an older
version).

class World(object):

def __init__(w, version):

class A(object):
def ff(): pass # place holder for version-dependent code
def f(self): # version-independent code
return self.ff()

class B(A):
def gg(): pass
def g(self):
return self.gg()

for cls in (A, B):
setattr(w, cls.__name__, w.versionize(cls, version))

def versionize(w, cls, version):
import inspect
methods = inspect.getmembers(version, inspect.ismethod)
methods = [m[1] for m in methods if m[0].split('_')[0] ==
cls.__name__]
for m in methods:
m_name = '_'.join(m.__name__.split('_')[1:])
import new
im = new.instancemethod(m.im_func, None, cls)
setattr(cls, m_name, im)
return cls

class Version1(object):
def A_ff(self):
return 'A.ff: version 1'
def B_gg(self):
return 'B.gg: version 1'

class Version2(Version1):
def A_ff(self):
return 'A.ff: version 2'
def B_ff(self):
return 'B.ff: version 2'

w1, w2 = World(Version1), World(Version2)
a1, b1 = w1.A(), w1.B()
a2, b2 = w2.A(), w2.B()

print a1.f() # prints 'A.ff: version 1'
print b1.f() # prints 'A.ff: version 1'
print b1.g() # prints 'B.gg: version 1'
print '------------'
print a2.f() # prints 'A.ff: version 2'
print b2.f() # prints 'B.ff: version 2'
print b2.g() # prints 'B.gg: version 1'

Jul 18 '05 #11
> On second thought, I had doubts. Consider the following scenario:

A2 | f <- A3
^ ^
| |
B2 | f <- B3
^ ^
| |
C2 <- C3 | g

Assume g calls f. Since f is defined in B version 2, it should taken
over unchanged into B version 3, and that should be the version g
calls. However, with multiple inheritance doing depth-first search,
giving the "upper" class priority over the "left", the first path
searched is B3 - A3 - A2, and hence it finds f at A2. A quick test
confirms this for old-style classes, which failed in exactly that
way. But with new-style classes, it works, and finds f at B2 instead.

So I dug through the documentation and found that new-style classes
compute a monotonic linearization of the inheritance graph, observing
local precedence order, using the algorithm also used in Dylan
described here:

http://www.webcom.com/haahr/dylan/li...-oopsla96.html
That's right; you can actually access this linearization for new-style
classes by the '__mro__' class atrribute. See my example in the main
subthread of this thread that uses __mro__ to illustrate the need for
the dummy intermediate classes.
And this algorithm will even work correctly if one leaves out B3
in the example above, inheriting directly as in C3(A3,C2), because
the ordering constraint that A2 comes before B2 will still be
valid in the linearization for C3.

However, in the following case (shortening the notation even more)
it will fail, if a method defined at C3 is looked up at D4:

A1 - A2 - A3 - A4 - ...
| | | |
B1 - B2 - + - B4 - ...
| | | |
C1 - + - C3 - + - ...
| | | |
D1 - D2 - + - D4 - ...
| | | |

The solution is simply to include C3 in the list of parents of D4, as
in D4(C3,B4,D2). So for every hole in a column, you have to include
the first class (or classes, if the hole spans multiple rows) to the
left of the hole as parents if the class just below the hole, in order from bottom to top. This adds the missing constraints, and should
solve the problem without any need to write __metaclass__ stuff.
Nice. I had taken for granted that you need to fill in the holes
(D3,B3,C2), either manually or automa[tg]ically, but if you allow a
class to inherit from more than two bases, you can pick a set of
parents that does the job, without any boilerplate code or
__metaclass__ magic. The downside of this approach is that it's even
harder to see the big picture, as in the schematic notation above;
remember that each column is a different version that resides in a
separate module, so it's not obvious which classes should be the
parents of each variation. Another drawback in the general case is ease
of maintenance: if a new hole appears in the future or an old hole is
filled, you have to go back and change the parents of the affected
classes. In my case this is not an issue though; old versions are
'frozen', so the only expected change in the lattice is the addition of
new columns (versions).
Interesting question. I learned a lot while thinking about that.

- Dirk


I learned too, and I'm glad for this learning side-effect :-) Thanks !

George

Jul 18 '05 #12
> Have you considered a 'macro' solution composing source? If I were
handling so
many versions, I would want a complete class definition for each version rather than having to scan many sources for each implementation.


Can you elaborate on this a little ? You mean something like a
template-based code generating script that creates all the boilerplate
code for each version before you start customising it ? This could be
an option, though you'd better be pretty sure that the template is
frozen; you don't want to go back and fill in the template more than
once !

George

Jul 18 '05 #13
Hi George,

it's a nice little puzzle and it is more fun to solve it if one is not
a student anymore :)

Filling the gaps in the lattice is somehow necessary but it is not
necessary to create all the classes.

Ansatz:

We can consider two matrices: one is filled with nodes ( class names )
the other is filled with arrows between the nodes representing the
inheritance relationships.

In symbolic notatation:

| A B C |
Nodes = | D 0 F |
| G H I |

| 0 l l |
Arrows = | u 0 u*l |
| u u*l u*l |
Remarks:
1 ) if a node or an arrow is empty a 0 is inserted into the matrix.

2 ) u is for uppermost, l is for leftmost. A multiplication between
arrows should read as a logical AND: u*l ~ upper AND left.

With this interpretation the above matrizes contains the same
information than the lattice:

A <- B <- C
^ ^ ^
| | |
D <- 0 <- F
^ ^ ^
| | |
G <- H <- I

Now we need an algorithm to create all the classes from the matrix
information using multiple inheritance when needed:
# arrows symbolized as primes. Only u and l are used in the impl.
# d and r are somewhat more complicated to implement

l = 2
r = 3
u = 5
d = 7

class ClassGridError(Exception):pass

class ClassGrid(object):
def __init__(self):
self.class_names = [] # rows of the class-name matrix
self.arrows = [] # rows of the arrow matrix
self.classes = {} # store the resulting classes

def add_names(self,names):
self.class_names.append(names)

def add_arrow(self,arrow):
self.arrows.append(arrow)

def __repr__(self):
if self.classes:
return self.classes.__repr__()
return object.__repr__(self)

def create_classes(self):
for i,class_row in enumerate(self.class_names):
for j,cls_name in enumerate(class_row):
if cls_name == 0:
continue
arrow = self.arrows[i][j]
if arrow == 0:
self.classes[cls_name] = type(cls_name,(),{})
else:
bases = []
name = 0
if arrow%u == 0: # search uppermost
k = i-1
while k>=0:
name = self.class_names[k][j]
if name:
break
k-=1
if not name:
raise ClassGridError,"Wrong arrow matrix"
bases.append(self.classes[name])
if arrow%l == 0: # search leftmost
k = j-1
while k>=0:
name = self.class_names[i][k]
if name:
break
k-=1
if not name:
raise ClassGridError,"Wrong arrow matrix"
bases.append(self.classes[name])
self.classes[cls_name] =
type(cls_name,tuple(bases),{})

cg = ClassGrid()

cg.add_names(("A","B","C"))
cg.add_names(("D", 0, "F"))
cg.add_names(("G","H","I"))

cg.add_arrow(( 0, l, l ))
cg.add_arrow(( u, 0, u*l))
cg.add_arrow(( u, u*l, u*l))

cg.create_classes()

Now You can checkout Your solution:
cg.classes["A"].__subclasses__() [<class '__main__.B'>, <class '__main__.D'>]
cg.classes["B"].__subclasses__() [<class '__main__.C'>, <class '__main__.H'>]
cg.classes["C"].__subclasses__() [<class '__main__.F'>]
cg.classes["D"].__subclasses__() [<class '__main__.F'>, <class '__main__.G'>]
cg.classes["F"].__subclasses__() [<class '__main__.I'>]
cg.classes["G"].__subclasses__() [<class '__main__.H'>]
cg.classes["H"].__subclasses__() [<class '__main__.I'>]
cg.classes["I"].__subclasses__()

[]

Ciao,
Kay

Jul 18 '05 #14
George Sakkis wrote:
Have you considered a 'macro' solution composing source?

Can you elaborate on this a little ? You mean something like a
template-based code generating script that creates all the boilerplate
code for each version before you start customising it ?


I was thinking more along the lines of repeatable code generation.
I started from this idea:
http://groups-beta.google.com/group/...ef889e9f99696c
which is a straightforward wrapping case, but illustrates source code
composition/generation.

Now given that you have:
#World1.py

class Field:
...
class Movable
...
etc...
#Then in World2Delta.py

class FieldDelta:
"""just the classes that have changed"""
def somemethod(self):
"""just the methods that are added or changed
you could even have nomenclature for method deletion, (a lack which
sometimes bugs me in OO schemes)"""
etc...
then you have a 'makefile' that generates a new module for each of your worlds

#makefile.py

def generateWorld(baseworld, delta, newworld):
"""reads two modules:
baseworld defines the 'superclasses'
delta defines any changes to these
writes module newworld, that contains complete
source for all the classes in the model, with no
external dependencies
"""

I haven't tried it, but I'm sure it is fairly straightforward to implement (and
very easy to test).
This could be an option, though you'd better be pretty sure that the template is
frozen; you don't want to go back and fill in the template more than
once !


I envisage something that could be regenerated at will, simply by re-running the
makefile.

The thing that would need to be frozen is the inheritance graph within each
world. If you want to change that between versions, that would make
generateWorld much more complex.

The general advantage that I see with this approach is that whatever the hoops
you have to jump through to get the makefile process working right - the result
is extremely simple to verify. You would also probably get better performance,
by avoiding so much subclassing (not that you mentioned that as factor, but...)

Michael




Jul 18 '05 #15
Dirk wrote:
So I dug through the documentation and found that new-style classes
compute a monotonic linearization of the inheritance graph, observing
local precedence order, using the algorithm also used in Dylan
described here: http://www.webcom.com/haahr/dylan/li...-oopsla96.html


<nitpick mode>
Actually Dylan authors invented the C3 algorithm but Dylan does not use
it:
for compatibility with Lisp, Dylan uses the CLOS algorithm. Languages
that
I know that use C3 are Python and Goo. Playing with the MOP you can get
lispy languages to follow C3 too.
</nitpick mode>

Jul 18 '05 #16
On 9 Apr 2005 03:49:19 -0700, "George Sakkis" <gs*****@rutgers.edu> wrote:
"Michael Spencer" <ma**@telcopartners.com> wrote:

George,

since you explicit allowed metaprogramming hacks :-), how about

something like
this (not tested beyond what you see):

[snipped]


Nice try, but ideally all boilerplate classes would rather be avoided
(at least being written explicitly). Also, it is not obvious in your
solution why and which placeholder classes have to be written (like
World2.Movable) and which do not. By the way, my current working
solution involves copying and pasting verbatim these classes :-) Below
is an abstracted example; note that the 'declaration string' of each
original class is exactly the same across all different versions after
the first (e.g. "class B(PreviousNamespace.B, A)").
#================================================ ======
# version_1.py

class Namespace:
class A(object):
def foo(self): return "version_1.foo()"
class B(A):
def bar(self): return "version_1.bar()"
class C(B):
def zen(self): return "version_1.zen()"
#================================================ ======
# version_2.py

from version_1 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
class A(PreviousNamespace.A):
def foo(self): return "version_2.foo()"
class B(PreviousNamespace.B, A):
pass
class C(PreviousNamespace.C, B):
pass
#================================================ ======
# version_3.py

from version_2 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
class A(PreviousNamespace.A):
pass
class B(PreviousNamespace.B, A):
def bar(self): return "version_3.bar()"
class C(PreviousNamespace.C, B):
pass

#================================================ ======
# test.py
# command: python test.py <#version>

def NamespaceFactory(version):
return __import__("version_%d" % version).Namespace

print NamespaceFactory(2).B().foo() # "version_2.foo()"
print NamespaceFactory(3).C().bar() # "version_3.bar()"

import sys, inspect
namespace = NamespaceFactory(int(sys.argv[1]))
# print the __mro__ of each 'inner' class
for name,cls in inspect.getmembers(namespace,
inspect.isclass):
print cls
for ancestor in cls.__mro__:
print "\t", ancestor

#================================================ ======

See if this does what you want:
(Note that vermeta.py preliminarily writes out the three version_?.py files, so
you can just go to a temp directory and run python24 vermeta.py)

It makes the version files look a little more cluttered with the
open(..).write('''\ ... ''') wrapping. E.g., 2 & 3 are just
----< version_2.py >-----------
from version_1 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
__metaclass__ = vars(PreviousNamespace)['__metaclass__']

class A:
def foo(self): return "version_2.foo()"
-------------------------------

and

----< version_3.py >-----------
from version_2 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
__metaclass__ = vars(PreviousNamespace)['__metaclass__']

class B:
def bar(self): return "version_3.bar()"
-------------------------------

And you only have to change one digit in the 3-line boilerplate
and your class definitions don't have to specify inheritance,
but it could test for type classobj (classic class) and only
redefine if so ;-)

There are some limitations I think (;-) but the idea is you just have to
specify three lines of boilerplate for a new version, and then just
the classes and methods you are interested in overriding in the new
version, and you don't have to specify the class inheritance in the new versions,
as the lazystyle metaclass function takes care of that. I hope ;-)
Version_1 has to be hand made, but after that, see what you think.

----< vermeta.py >---------------------------------------------------------------
#================================================= =====
# version_1.py
open('version_1.py','w').write('''\
NAMESPACE_CLASSNAMES = ['A', 'B', 'C']
def metadeco(nsname, nsbases, nsdict):
# print '--- metadeco ---', nsbases, nsdict['__module__'], __name__
# print 'nsname = %r\\nnsbases = %r\\nnsdict = %s' %(
# nsname, nsbases, ',\\n '.join(str(nsdict).split(', ')))
if nsdict['__module__'] != __name__: # exclude this first-version module
# print '--- doing meta stuff for namespace of module %s ---'% nsdict['__module__']
for i, cname in enumerate(NAMESPACE_CLASSNAMES):
cbases = (vars(nsbases[0])[cname],) + (i and (nsdict[NAMESPACE_CLASSNAMES[i-1]],) or ())
if object not in cbases: cbases += (object,)
if cname in nsdict:
cdict = nsdict[cname].__dict__.copy()
#cdict['__module__'] = __name__
else:
cdict = {'__doc__': '(Generated by version_1.metadeco)'}
cdict['__module__'] = nsdict['__module__']
nsdict[cname] = type(cname, cbases, cdict)
return type(nsname, nsbases, nsdict)

class Namespace(object):
__metaclass__ = metadeco
class A(object):
def foo(self): return "version_1.foo()"
class B(A):
def bar(self): return "version_1.bar()"
class C(B):
def zen(self): return "version_1.zen()"
''')

#================================================= =====
# version_2.py
open('version_2.py','w').write('''\
from version_1 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
__metaclass__ = vars(PreviousNamespace)['__metaclass__']

class A:
def foo(self): return "version_2.foo()"
''')
#================================================= =====
# version_3.py
open('version_3.py','w').write('''\
from version_2 import Namespace as PreviousNamespace
class Namespace(PreviousNamespace):
__metaclass__ = vars(PreviousNamespace)['__metaclass__']

class B:
def bar(self): return "version_3.bar()"
''')

#================================================= =====
# test.py
# command: python test.py <#version>

def NamespaceFactory(version):
return __import__("version_%d" % version).Namespace

print NamespaceFactory(2).B().foo() # "version_2.foo()"
print NamespaceFactory(3).C().bar() # "version_3.bar()"

import sys, inspect
namespace = NamespaceFactory(int(sys.argv[1]))
# print the __mro__ of each 'inner' class
for name,cls in inspect.getmembers(namespace,
inspect.isclass):
#for name, cls in (t for t in namespace.__dict__.items() if isinstance(t[1], type)):
print cls
for ancestor in cls.__mro__:
print "\t", ancestor

#================================================= =====
---------------------------------------------------------------------------------

Run:

[ 5:33] C:\pywk\clp\sakkis\meta>py24 vermeta.py 3
version_2.foo()
version_3.bar()
<class 'version_3.A'>
<class 'version_3.A'>
<class 'version_2.A'>
<class 'version_1.A'>
<type 'object'>
<class 'version_3.B'>
<class 'version_3.B'>
<class 'version_2.B'>
<class 'version_1.B'>
<class 'version_3.A'>
<class 'version_2.A'>
<class 'version_1.A'>
<type 'object'>
<class 'version_3.C'>
<class 'version_3.C'>
<class 'version_2.C'>
<class 'version_1.C'>
<class 'version_3.B'>
<class 'version_2.B'>
<class 'version_1.B'>
<class 'version_3.A'>
<class 'version_2.A'>
<class 'version_1.A'>
<type 'object'>
<type 'type'>
<type 'type'>
<type 'object'>

Regards,
Bengt Richter
Jul 18 '05 #17
George Sakkis <gs*****@rutgers.edu> wrote:
A1 - A2 - A3 - A4 - ...
| | | |
B1 - B2 - + - B4 - ...
| | | |
C1 - + - C3 - + - ...
| | | |
D1 - D2 - + - D4 - ...
| | | | The solution is simply to include C3 in the list of parents of D4,
as in D4(C3,B4,D2). So for every hole in a column, you have to
include the first class (or classes, if the hole spans multiple
rows) to the left of the hole as parents if the class just below
the hole, in order from bottom to top.
Nice. I had taken for granted that you need to fill in the holes
(D3,B3,C2), either manually or automa[tg]ically, but if you allow a
class to inherit from more than two bases, you can pick a set of
parents that does the job, without any boilerplate code or
__metaclass__ magic. The downside of this approach is that it's even
harder to see the big picture, as in the schematic notation above;
remember that each column is a different version that resides in a
separate module, so it's not obvious which classes should be the
parents of each variation.


It's obvious if you know which versions are available, and which
aren't. If you don't have this information, and you're only looking at
each module locally, than it's probably even safer (i.e., less likely
to confuse a casual reader of the source) to just generate all the
dummy classes manually. But that sort of makes your original problem
irrelevant :-)

- Dirk
Jul 18 '05 #18
"Bengt Richter" <bo**@oz.net> wrote in message
news:42***************@news.oz.net...

See if this does what you want:

[snipped]


Yes, that's pretty much what I had in mind. I particularly liked the
idea of mirroring automagically the nested class inheritance in each
version. So I tried to refine this recipe a little and I pushed down
the boilerplate code from 3 lines to one word; laziness is a virtue :-)
Below is the test only; I posted the main module to
http://rafb.net/paste/results/Hweu3t19.html to avoid messing up the
indentation.

Cheers,
George

#=================================================
# test.py
from namespace import Namespace

class Era(object):
def __init__(self):
self.lumberjack = self.GameUnit()
self.warrior = self.CombatUnit()
self.shooter = self.RangedUnit()

class MedievalAge(Era):
__metaclass__ = Namespace()
class GameUnit(object):
def move(self): return "MedievalAge.GameUnit.move()"
class CombatUnit(GameUnit):
def fight(self): return "MedievalAge.CombatUnit.fight()"
class RangedUnit(CombatUnit):
def aim(self): return "MedievalAge.RangedUnit.aim()"

class ColonialAge(Era):
__metaclass__ = Namespace(MedievalAge)
class CombatUnit:
def fight(self): return "ColonialAge.CombatUnit.fight()"

class IndustrialAge(Era):
__metaclass__ = Namespace(ColonialAge)
class GameUnit:
def move(self): return "IndustrialAge.GameUnit.move()"
class RangedUnit:
def aim(self): return "IndustrialAge.RangedUnit.aim()"
if __name__ == '__main__':
for era in MedievalAge(), ColonialAge(), IndustrialAge():
for player in era.lumberjack, era.warrior, era.shooter:
for action in "move", "fight", "aim":
try: result = getattr(player,action)()
except AttributeError:
result = "N/A"
print "%s:%s.%s:\t%s" % (type(era).__name__,
type(player).__name__,
action, result)

Jul 18 '05 #19

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