Python garbage collection

I think this is circular reference (though the question isn't explicit about this information.)

One way to solve this problem is to manually invoke garbage collection. When you manually run garbage collector, it will sweep circular referenced objects too.

import gcfor i in xrange(10000):    j = myObj()    processObj(j)    #assuming count reference is not zero but still    #object won't remain usable after the iteration    if !(i%100):        gc.collect()

Here don't run garbage collector too often because it has its own overhead, e.g. if you run garbage collector in every loop, interpretation will become extremely slow.

You haven't provided enough information - this depends on the specifics of the object you are creating and what else you're doing with it in the loop. If the object does not create circular references, it should be deallocated on the next iteration. For example, the code

for x in range(100000):  obj = " " * 10000000

will not result in ever-increasing memory allocation.

This is an old error that was corrected for some types in python 2.5. What was happening was that python was not so good at collecting things like empty lists/dictionaries/tupes/floats/ints. In python 2.5 this was fixed...mostly. However floats and ints are singletons for comparisons so once one of those is created it stays around as long as the interpreter is alive. I've been bitten by this worst when dealing with large amount of floats since they have a nasty habit of being unique. This was characterized for python 2.4 and updated about it being folded into python 2.5

The best way I've found around it is to upgrade to python 2.5 or newer to take care of the lists/dictionaries/tuples issue. For numbers the only solution is to not let large amounts of numbers get into python. I've done it with my own wrapper to a c++ object, but I have the impression that numpy.array will give similar results.

As a post script I have no idea what has happened to this in python 3, but I'm suspicious that numbers are still part of a singleton. So the memory leak is actually a feature of the language.