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How to not run init based on __new__ method

I have the following class, which acts as a collection of people:
class Person:
PERSONS = dict() # name ==> instance
def __new__(cls, *args, **kwargs):
name = kwargs.get('name') or '' if not args else args[0]
print ('Name: %s' % name)
if name in cls.PERSONS:
print ('Returning found person!')
return cls.PERSONS[name]
else:
print ('Initializing new person')
return super(Person, cls).__new__(cls)
def __init__(self, name):
print ("Running init")
self.name = name
Person.PERSONS[name] = self
If a person is found, it returns that person, otherwise it creates a new one. And when I run it it works:
>>> p1 = Person('Julia')
Name: Julia
Initializing new person
Running init
>>> p2 = Person('Julia')
Name: Julia
Returning found person!
Running init # <== how to get this not to run?
>>> p1 is p2
True
However, if the person is found, I don't want the __init__ method to run. How would I "skip" the init method based on the return of the __new__ ?
One option is to add a conditional in the __init__, such as:
def __init__(self, name):
if name in Person.PERSONS: return # don't double-initialize
print ("Running init")
self.name = name
Person.PERSONS[name] = self
But I was hoping there might be a cleaner approach.

#MadPhysicist's idea of using a metaclass with a custom __call__ method is correct but the implementation included in the answer is quite off. Instead, the custom __call__ method should use the name of the person, rather than a new Person object, to check if a given name has an existing entry in the PERSONS dict:
class PersonMeta(type):
def __call__(cls, name):
print ('Name: %s' % name)
if name in cls.PERSONS:
print ('Returning found person!')
return cls.PERSONS[name]
print('Initializing new person')
obj = cls.__new__(cls, name)
cls.__init__(obj, name)
cls.PERSONS[name] = obj
return obj
class Person(metaclass=PersonMeta):
PERSONS = dict() # name ==> instance
def __init__(self, name):
print ("Running init")
self.name=name
p1=Person('Julia')
p2=Person('Julia')
print(p1 is p2)
This outputs:
Name: Julia
Initializing new person
Running init
Name: Julia
Returning found person!
True

Instead of trying to skip __init__, put your initialization in __new__. In general, most classes should only implement one of __new__ and __init__, or things get messy.
Also, trying to have a class act as a collection of anything is usually a bad idea. Instead of trying to make your class itself manage its instances, it tends to be a better idea to give that role to a dedicated collection object. This makes it easier to manage object lifetimes, have multiple containers, avoid weird __new__ problems, etc.

The problem I find in your approach is that the __new__ dunder method is triggered just before the __init__. Once said that, it's not that easy to change that behavior.
Instead of handling the new Person's creation inside __new__, create a class method (e.g. create_person) and update the PERSONS dict if needed.
class Person:
def __init__(self, name):
print("Running init\n")
self.name = name
class PersonFactory:
PERSONS = dict()
#classmethod
def create_person(cls, name):
print('Name: %s' % name)
if name in cls.PERSONS:
print ('Returning found person!')
return cls.PERSONS[name]
print('Initializing new person')
cls.PERSONS[name] = Person(name)
return cls.PERSONS[name]
if __name__ == '__main__':
PersonFactory.create_person('Julia')
PersonFactory.create_person('Julia')

Create a class level decorator to automatically add a property

I would like to create a class level decorator that automatically adds a property to an object, including the appropriate getter and setter methods and a backing variable. For example:
#autoproperty("foo", can_get=True, can_set=True, allow_null=False, default_value=0)
#autoproperty("baz", can_get=True, can_set=False, allow_null=True, default_value=0)
#autoproperty("bar")
class SomeNonTrivialClass(object):
def __init__(self):
#lots of stuff going on here
def discombobulate(self):
#this is obviously a very trivial example
local_foo = self.foo;
if (local_foo > 10):
raise RuntimeError("Foo can never be more than 10")
else:
#do whatever with foo
if __name__ == '__main__':
test = SomeNonTrivialClass()
test.foo = 5
test.discombobulate()
test.foo = 11
test.discombobulate()
I often find myself creating lots of "semi-complex" getters/setters (they could be done with just a simple property but they need default values and null protection. I would like to just be able to specify a decorator that does the heavy lifting of creating the properties on new instances of the class.
If I am way off base in this approach, I am open to an equally viable approach.
Any help would be appreciated.
I am working with python 3.X and python 2.7 so something that works in either is preferred but not necessary.
Update: I have added a bit more variety in what I am looking for. In general I need to be able to create a lot of these simple automatic properties (ala C# auto-property, but with a bit more flexibility). I do not necessarily want to expose the backing store, but I do want to make sure that an inspection of the instantiated object (not necessarily the class) shows the properties which have been created.

The following class decorator would do that:
def autoproperty(name, can_get=True, can_set=True, allow_null=False, default_value=0):
attribute_name = '_' + name
def getter(self):
return getattr(self, attribute_name, default_value)
def setter(self, value):
if not allow_null and value is None:
raise ValueError('Cannot set {} to None'.format(name))
setattr(self, attribute_name, value)
prop = property(getter if can_get else None, setter if can_set else None)
def decorator(cls):
setattr(cls, name, prop)
return cls
return decorator
but you could just as well create a property factory:
def autoproperty(attribute_name, can_get=True, can_set=True, allow_null=False, default_value=0):
def getter(self):
return getattr(self, attribute_name, default_value)
def setter(self, value):
if not allow_null and value is None:
raise ValueError('Cannot set {} to None'.format(name))
setattr(self, attribute_name, value)
return property(getter if can_get else None, setter if can_set else None)
then set that in the class with:
class SomeNonTrivialClass(object):
# ...
foo = autoproperty('_foo', can_get=True, can_set=True, allow_null=False, default_value=0)
The class decorator would make more sense if you needed to create multiple properties (perhaps with interdependencies) instead.

Here's a more direct approach, which avoids decorating the class.
class SomeNonTrivialClass(object):
def __init__(self):
#lots of stuff going on here
foo = autoproperty("foo", can_get=True, can_set=True, allow_null=False, default_value=0)
def discombobulate(self):
#this is obviously a very trivial example
local_foo = self.foo;
class autoproperty(property):
def __init__(self, name, can_get, can_set, allow_null, default_value):
...

Mapping obj.method({argument:value}) to obj.argument(value)

I don't know if this will make sense, but...
I'm trying to dynamically assign methods to an object.
#translate this
object.key(value)
#into this
object.method({key:value})
To be more specific in my example, I have an object (which I didn't write), lets call it motor, which has some generic methods set, status and a few others. Some take a dictionary as an argument and some take a list. To change the motor's speed, and see the result, I use:
motor.set({'move_at':10})
print motor.status('velocity')
The motor object, then formats this request into a JSON-RPC string, and sends it to an IO daemon. The python motor object doesn't care what the arguments are, it just handles JSON formatting and sockets. The strings move_at and velocity are just two of what might be hundreds of valid arguments.
What I'd like to do is the following instead:
motor.move_at(10)
print motor.velocity()
I'd like to do it in a generic way since I have so many different arguments I can pass. What I don't want to do is this:
# create a new function for every possible argument
def move_at(self,x)
return self.set({'move_at':x})
def velocity(self)
return self.status('velocity')
#and a hundred more...
I did some searching on this which suggested the solution lies with lambdas and meta programming, two subjects I haven't been able to get my head around.
UPDATE:
Based on the code from user470379 I've come up with the following...
# This is what I have now....
class Motor(object):
def set(self,a_dict):
print "Setting a value", a_dict
def status(self,a_list):
print "requesting the status of", a_list
return 10
# Now to extend it....
class MyMotor(Motor):
def __getattr__(self,name):
def special_fn(*value):
# What we return depends on how many arguments there are.
if len(value) == 0: return self.status((name))
if len(value) == 1: return self.set({name:value[0]})
return special_fn
def __setattr__(self,attr,value): # This is based on some other answers
self.set({attr:value})
x = MyMotor()
x.move_at = 20 # Uses __setattr__
x.move_at(10) # May remove this style from __getattr__ to simplify code.
print x.velocity()
output:
Setting a value {'move_at': 20}
Setting a value {'move_at': 10}
10
Thank you to everyone who helped!

What about creating your own __getattr__ for the class that returns a function created on the fly? IIRC, there's some tricky cases to watch out for between __getattr__ and __getattribute__ that I don't recall off the top of my head, I'm sure someone will post a comment to remind me:
def __getattr__(self, name):
def set_fn(self, value):
return self.set({name:value})
return set_fn
Then what should happen is that calling an attribute that doesn't exist (ie: move_at) will call the __getattr__ function and create a new function that will be returned (set_fn above). The name variable of that function will be bound to the name parameter passed into __getattr__ ("move_at" in this case). Then that new function will be called with the arguments you passed (10 in this case).
Edit
A more concise version using lambdas (untested):
def __getattr__(self, name):
return lambda value: self.set({name:value})

There are a lot of different potential answers to this, but many of them will probably involve subclassing the object and/or writing or overriding the __getattr__ function.
Essentially, the __getattr__ function is called whenever python can't find an attribute in the usual way.
Assuming you can subclass your object, here's a simple example of what you might do (it's a bit clumsy but it's a start):
class foo(object):
def __init__(self):
print "initting " + repr(self)
self.a = 5
def meth(self):
print self.a
class newfoo(foo):
def __init__(self):
super(newfoo, self).__init__()
def meth2(): # Or, use a lambda: ...
print "meth2: " + str(self.a) # but you don't have to
self.methdict = { "meth2":meth2 }
def __getattr__(self, name):
return self.methdict[name]
f = foo()
g = newfoo()
f.meth()
g.meth()
g.meth2()
Output:
initting <__main__.foo object at 0xb7701e4c>
initting <__main__.newfoo object at 0xb7701e8c>
5
5
meth2: 5

You seem to have certain "properties" of your object that can be set by
obj.set({"name": value})
and queried by
obj.status("name")
A common way to go in Python is to map this behaviour to what looks like simple attribute access. So we write
obj.name = value
to set the property, and we simply use
obj.name
to query it. This can easily be implemented using the __getattr__() and __setattr__() special methods:
class MyMotor(Motor):
def __init__(self, *args, **kw):
self._init_flag = True
Motor.__init__(self, *args, **kw)
self._init_flag = False
def __getattr__(self, name):
return self.status(name)
def __setattr__(self, name, value):
if self._init_flag or hasattr(self, name):
return Motor.__setattr__(self, name, value)
return self.set({name: value})
Note that this code disallows the dynamic creation of new "real" attributes of Motor instances after the initialisation. If this is needed, corresponding exceptions could be added to the __setattr__() implementation.

Instead of setting with function-call syntax, consider using assignment (with =). Similarly, just use attribute syntax to get a value, instead of function-call syntax. Then you can use __getattr__ and __setattr__:
class OtherType(object): # this is the one you didn't write
# dummy implementations for the example:
def set(self, D):
print "setting", D
def status(self, key):
return "<value of %s>" % key
class Blah(object):
def __init__(self, parent):
object.__setattr__(self, "_parent", parent)
def __getattr__(self, attr):
return self._parent.status(attr)
def __setattr__(self, attr, value):
self._parent.set({attr: value})
obj = Blah(OtherType())
obj.velocity = 42 # prints setting {'velocity': 42}
print obj.velocity # prints <value of velocity>

Prevent creating new attributes outside __init__

I want to be able to create a class (in Python) that once initialized with __init__, does not accept new attributes, but accepts modifications of existing attributes. There's several hack-ish ways I can see to do this, for example having a __setattr__ method such as
def __setattr__(self, attribute, value):
if not attribute in self.__dict__:
print "Cannot set %s" % attribute
else:
self.__dict__[attribute] = value
and then editing __dict__ directly inside __init__, but I was wondering if there is a 'proper' way to do this?

I wouldn't use __dict__ directly, but you can add a function to explicitly "freeze" a instance:
class FrozenClass(object):
__isfrozen = False
def __setattr__(self, key, value):
if self.__isfrozen and not hasattr(self, key):
raise TypeError( "%r is a frozen class" % self )
object.__setattr__(self, key, value)
def _freeze(self):
self.__isfrozen = True
class Test(FrozenClass):
def __init__(self):
self.x = 42#
self.y = 2**3
self._freeze() # no new attributes after this point.
a,b = Test(), Test()
a.x = 10
b.z = 10 # fails

Slots is the way to go:
The pythonic way is to use slots instead of playing around with the __setter__. While it may solve the problem, it does not give any performance improvement. The attributes of objects are stored in a dictionary "__dict__", this is the reason, why you can dynamically add attributes to objects of classes that we have created so far. Using a dictionary for attribute storage is very convenient, but it can mean a waste of space for objects, which have only a small amount of instance variables.
Slots are a nice way to work around this space consumption problem. Instead of having a dynamic dict that allows adding attributes to objects dynamically, slots provide a static structure which prohibits additions after the creation of an instance.
When we design a class, we can use slots to prevent the dynamic creation of attributes. To define slots, you have to define a list with the name __slots__. The list has to contain all the attributes, you want to use. We demonstrate this in the following class, in which the slots list contains only the name for an attribute "val".
class S(object):
__slots__ = ['val']
def __init__(self, v):
self.val = v
x = S(42)
print(x.val)
x.new = "not possible"
=> It fails to create an attribute "new":
42
Traceback (most recent call last):
File "slots_ex.py", line 12, in <module>
x.new = "not possible"
AttributeError: 'S' object has no attribute 'new'
Notes:
Since Python 3.3 the advantage optimizing the space consumption is not as impressive any more. With Python 3.3 Key-Sharing Dictionaries are used for the storage of objects. The attributes of the instances are capable of sharing part of their internal storage between each other, i.e. the part which stores the keys and their corresponding hashes. This helps to reduce the memory consumption of programs, which create many instances of non-builtin types. But still is the way to go to avoid dynamically created attributes.
Using slots come also with it's own cost. It will break serialization (e.g. pickle). It will also break multiple inheritance. A class can't inherit from more than one class that either defines slots or has an instance layout defined in C code (like list, tuple or int).

If someone is interested in doing that with a decorator, here is a working solution:
from functools import wraps
def froze_it(cls):
cls.__frozen = False
def frozensetattr(self, key, value):
if self.__frozen and not hasattr(self, key):
print("Class {} is frozen. Cannot set {} = {}"
.format(cls.__name__, key, value))
else:
object.__setattr__(self, key, value)
def init_decorator(func):
#wraps(func)
def wrapper(self, *args, **kwargs):
func(self, *args, **kwargs)
self.__frozen = True
return wrapper
cls.__setattr__ = frozensetattr
cls.__init__ = init_decorator(cls.__init__)
return cls
Pretty straightforward to use:
#froze_it
class Foo(object):
def __init__(self):
self.bar = 10
foo = Foo()
foo.bar = 42
foo.foobar = "no way"
Result:
>>> Class Foo is frozen. Cannot set foobar = no way

Actually, you don't want __setattr__, you want __slots__. Add __slots__ = ('foo', 'bar', 'baz') to the class body, and Python will make sure that there's only foo, bar and baz on any instance. But read the caveats the documentation lists!

The proper way is to override __setattr__. That's what it's there for.

I like very much the solution that uses a decorator, because it's easy to use it for many classes across a project, with minimum additions for each class. But it doesn't work well with inheritance.
So here is my version: It only overrides the __setattr__ function - if the attribute doesn't exist and the caller function is not __init__, it prints an error message.
import inspect
def froze_it(cls):
def frozensetattr(self, key, value):
if not hasattr(self, key) and inspect.stack()[1][3] != "__init__":
print("Class {} is frozen. Cannot set {} = {}"
.format(cls.__name__, key, value))
else:
self.__dict__[key] = value
cls.__setattr__ = frozensetattr
return cls
#froze_it
class A:
def __init__(self):
self._a = 0
a = A()
a._a = 1
a._b = 2 # error

What about this:
class A():
__allowed_attr=('_x', '_y')
def __init__(self,x=0,y=0):
self._x=x
self._y=y
def __setattr__(self,attribute,value):
if not attribute in self.__class__.__allowed_attr:
raise AttributeError
else:
super().__setattr__(attribute,value)

Here is approach i came up with that doesn't need a _frozen attribute or method to freeze() in init.
During init i just add all class attributes to the instance.
I like this because there is no _frozen, freeze(), and _frozen also does not show up in the vars(instance) output.
class MetaModel(type):
def __setattr__(self, name, value):
raise AttributeError("Model classes do not accept arbitrary attributes")
class Model(object):
__metaclass__ = MetaModel
# init will take all CLASS attributes, and add them as SELF/INSTANCE attributes
def __init__(self):
for k, v in self.__class__.__dict__.iteritems():
if not k.startswith("_"):
self.__setattr__(k, v)
# setattr, won't allow any attributes to be set on the SELF/INSTANCE that don't already exist
def __setattr__(self, name, value):
if not hasattr(self, name):
raise AttributeError("Model instances do not accept arbitrary attributes")
else:
object.__setattr__(self, name, value)
# Example using
class Dog(Model):
name = ''
kind = 'canine'
d, e = Dog(), Dog()
print vars(d)
print vars(e)
e.junk = 'stuff' # fails

I like the "Frozen" of Jochen Ritzel. The inconvenient is that the isfrozen variable then appears when printing a Class.__dict
I went around this problem this way by creating a list of authorized attributes (similar to slots):
class Frozen(object):
__List = []
def __setattr__(self, key, value):
setIsOK = False
for item in self.__List:
if key == item:
setIsOK = True
if setIsOK == True:
object.__setattr__(self, key, value)
else:
raise TypeError( "%r has no attributes %r" % (self, key) )
class Test(Frozen):
_Frozen__List = ["attr1","attr2"]
def __init__(self):
self.attr1 = 1
self.attr2 = 1

The FrozenClass by Jochen Ritzel is cool, but calling _frozen() when initialing a class every time is not so cool (and you need to take the risk of forgetting it). I added a __init_slots__ function:
class FrozenClass(object):
__isfrozen = False
def _freeze(self):
self.__isfrozen = True
def __init_slots__(self, slots):
for key in slots:
object.__setattr__(self, key, None)
self._freeze()
def __setattr__(self, key, value):
if self.__isfrozen and not hasattr(self, key):
raise TypeError( "%r is a frozen class" % self )
object.__setattr__(self, key, value)
class Test(FrozenClass):
def __init__(self):
self.__init_slots__(["x", "y"])
self.x = 42#
self.y = 2**3
a,b = Test(), Test()
a.x = 10
b.z = 10 # fails

None of the answers mention the performance impact of overriding __setattr__, which can be an issue when creating many small objects. (And __slots__ would be the performant solution but limits pickle/inheritance).
So I came up with this variant which installs our slower settatr after init:
class FrozenClass:
def freeze(self):
def frozen_setattr(self, key, value):
if not hasattr(self, key):
raise TypeError("Cannot set {}: {} is a frozen class".format(key, self))
object.__setattr__(self, key, value)
self.__setattr__ = frozen_setattr
class Foo(FrozenClass): ...
If you don't want to call freeze at the end of __init__, if inheritance is an issue, or if you don't want it in vars(), it can also be adapted: for example here is a decorator version based on the pystrict answer:
import functools
def strict(cls):
cls._x_setter = getattr(cls, "__setattr__", object.__setattr__)
cls._x_init = cls.__init__
#functools.wraps(cls.__init__)
def wrapper(self, *args, **kwargs):
cls._x_init(self, *args, **kwargs)
def frozen_setattr(self, key, value):
if not hasattr(self, key):
raise TypeError("Class %s is frozen. Cannot set '%s'." % (cls.__name__, key))
cls._x_setter(self, key, value)
cls.__setattr__ = frozen_setattr
cls.__init__ = wrapper
return cls
#strict
class Foo: ...

I wrote pystrict as a solution to this problem. It's too large to paste all of the code in stackoverflow.
pystrict is a pypi installable decorator that can be used with classes to freeze them. Many solutions here don't properly support inheritance.
If __slots__ doesn't work for you (because of inheritance issues), this is a good alternative.
There is an example to the README that shows why a decorator like this is needed even if you have mypy and pylint running on your project:
pip install pystrict
Then just use the #strict decorator:
from pystrict import strict
#strict
class Blah
def __init__(self):
self.attr = 1

#dataclass(slots=True) Nirvana (Python 3.10)
I'm in love with this #dataclass thing:
main.py
from dataclasses import dataclass
#dataclass(slots=True)
class C:
n: int
s: str
c = C(n=1, s='one')
assert c.n == 1
assert c.s == 'one'
c.n == 2
c.s == 'two'
c.asdf = 2
Outcome:
Traceback (most recent call last):
File "/home/ciro/main.py", line 15, in <module>
c.asdf = 2
AttributeError: 'C' object has no attribute 'asdf'
Note how #dataclass only requires use to define our attributes once with type annotations
n: int
s: str
and then, without any repetition we get for free:
def __init__(n, s):
self.n = n
self.s = s
__slots__ = ['n', 's']
Other free things not shown in this example:
__str__
__eq__: Compare object instances for equality by their attributes
__hash__ if you also use frozen=True: Object of custom type as dictionary key
Tested on Python 3.10.7, Ubuntu 22.10.

Raising an exception on updating a 'constant' attribute in python

As python does not have concept of constants, would it be possible to raise an exception if an 'constant' attribute is updated? How?
class MyClass():
CLASS_CONSTANT = 'This is a constant'
var = 'This is a not a constant, can be updated'
#this should raise an exception
MyClass.CLASS_CONSTANT = 'No, this cannot be updated, will raise an exception'
#this should not raise an exception
MyClass.var = 'updating this is fine'
#this also should raise an exception
MyClass().CLASS_CONSTANT = 'No, this cannot be updated, will raise an exception'
#this should not raise an exception
MyClass().var = 'updating this is fine'
Any attempt to change CLASS_CONSTANT as a class attribute or as an instance attribute should raise an exception.
Changing var as a class attribute or as an instance attribute should not raise an exception.

Customizing __setattr__ in every class (e.g. as exemplified in my old recipe that #ainab's answer is pointing to, and other answers), only works to stop assignment to INSTANCE attributes and not to CLASS attributes. So, none of the existing answers would actually satisfy your requirement as stated.
If what you asked for IS actually exactly what you want, you could resort to some mix of custom metaclasses and descriptors, such as:
class const(object):
def __init__(self, val): self.val = val
def __get__(self, *_): return self.val
def __set__(self, *_): raise TypeError("Can't reset const!")
class mcl(type):
def __init__(cls, *a, **k):
mkl = cls.__class__
class spec(mkl): pass
for n, v in vars(cls).items():
if isinstance(v, const):
setattr(spec, n, v)
spec.__name__ = mkl.__name__
cls.__class__ = spec
class with_const:
__metaclass__ = mcl
class foo(with_const):
CLASS_CONSTANT = const('this is a constant')
print foo().CLASS_CONSTANT
print foo.CLASS_CONSTANT
foo.CLASS_CONSTANT = 'Oops!'
print foo.CLASS_CONSTANT
This is pretty advanced stuff, so you might prefer the simpler __setattr__ approach suggested in other answers, despite it NOT meeting your requirements as stated (i.e., you might reasonably choose to weaken your requirements in order to gain simplicity;-). But the techniques here might still be interesting: the custom descriptor type const is another way (IMHO far nicer than overriding __setattr__ in each and every class that needs some constants AND making all attributes constants rather than picking and choosing...) to block assignment to an instance attribute; the rest of the code is about a custom metaclass creating unique per-class sub-metaclasses of itself, in order to exploit said custom descriptor to the fullest and achieving the exact functionality you specifically asked for.

You could do something like this:
(from http://www.siafoo.net/snippet/108)
class Constants:
# A constant variable
foo = 1337
def __setattr__(self, attr, value):
if hasattr(self, attr):
raise ValueError, 'Attribute %s already has a value and so cannot be written to' % attr
self.__dict__[attr] = value
Then use it like this:
>>> const = Constants()
>>> const.test1 = 42
>>> const.test1
42
>>> const.test1 = 43
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 4, in __setattr__
ValueError: Attribute test1 already has a value and so cannot be written to
>>> const.test1
42

You can use a metaclass to achieve this:
class ImmutableConstants(type):
def __init__(cls, name, bases, dct):
type.__init__(cls, name, bases, dct)
old_setattr = cls.__setattr__
def __setattr__(self, key, value):
cls.assert_attribute_mutable(key)
old_setattr(self, key, value)
cls.__setattr__ = __setattr__
def __setattr__(self, key, value):
self.assert_attribute_mutable(key)
type.__setattr__(self, key, value)
def assert_attribute_mutable(self, name):
if name.isupper():
raise AttributeError('Attribute %s is constant' % name)
class Foo(object):
__metaclass__ = ImmutableConstants
CONST = 5
class_var = 'foobar'
Foo.class_var = 'new value'
Foo.CONST = 42 # raises
But are you sure this is a real issue? Are you really accidentally setting constants all over the place? You can find most of these pretty easily with a grep -r '\.[A-Z][A-Z0-9_]*\s*=' src/.

If you really want to have constant that can't be changed then look at this: http://code.activestate.com/recipes/65207/

Start reading this:
http://docs.python.org/reference/datamodel.html#customizing-attribute-access
You basically write your own version of __setattr__ that throws exceptions for some attributes, but not others.