slots

How is __slots__ implemented in Python? Is this exposed in the C interface ? How do I get __slots__ behaviour when defining a Python class in C via PyTypeObject ? When creating Python classes, they by default have a __dict__ and you can set any attribute on them. The point of slots is to not create a __dict__ to save space. In the C interface it's the other way around, an extension class has by default no __dict__ , and you would instead explicitly have to add one and add getattr/setattr support to handle it (although luckily there are methods for this already, PyObject_GenericGetAttr and

Say I have a class which defines __slots__ : class Foo(object): __slots__ = ['x'] def __init__(self, x=1): self.x = x # will the following work? def __setattr__(self, key, value): if key == 'x': object.__setattr__(self, name, -value) # Haha - let's set to minus x Can I define __setattr__() for it? Since Foo has no __dict__ , what will it update? All your code does, apart from negate the value, is call the parent class __setattr__ , which is exactly what would happen without your __setattr__ method. So the short answer is: Sure you can define a __setattr__ . What you cannot do is redefine _

I'm working with wavelets on a program and I'm used the package wavelets to create the DWT of a time series using the function dwt . This function returns an object of class dwt , which is a S4 object with many slots: W , V , levels , filter , and so on. How can I access the W 's as a vector? Ari B. Friedman @ will let you access the slots of an S4 object. So if your object is called wave , then wave@W should get you your vector. Note that often the best way to do this is to not access the slot directly but rather through an accessor function (e.g. coefs() rather than digging out the

I've heard that __slots__ makes objects faster by avoiding a dictionary lookup. My confusion comes from Python being a dynamic language. In a static language, we avoid a dictionary lookup for a.test by doing a compile-time optimisation to save the index in the instruction we run. Now, in Python, a could just as easily be another object that has a dictionary or a different set of attributes. It seems like we'll still have to do a dictionary lookup - the only difference seems to be that we only need one dictionary for the class, rather than a dictionary for each object. With this rational, How

A certain situation in Python recently alarmed me, and its reason is still not completely clear after a little research. The following class definitions appear to work flawlessly and will produce what is intended: class A: __slots__ = 'a', 'b' class B(A): __slots__ = () class C(A): __slots__ = () class D(B, C): __slots__ = () These are four classes arranged in a diamond inheritance pattern. However, a somewhat similar pattern is not allowed. The following class definitions seem as though they should function the same as the first: class B: __slots__ = 'a', 'b' class C: __slots__ = 'a', 'b'

I'm trying to pickle an object of a (new-style) class I defined. But I'm getting the following error: >>> with open('temp/connection.pickle','w') as f: ... pickle.dump(c,f) ... Traceback (most recent call last): File "<stdin>", line 2, in <module> File "/usr/lib/python2.5/pickle.py", line 1362, in dump Pickler(file, protocol).dump(obj) File "/usr/lib/python2.5/pickle.py", line 224, in dump self.save(obj) File "/usr/lib/python2.5/pickle.py", line 331, in save self.save_reduce(obj=obj, *rv) File "/usr/lib/python2.5/pickle.py", line 419, in save_reduce save(state) File "/usr/lib/python2.5/pickle