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14.11 Tracking Instances of Particular Classes

Credit: David Ascher, Mark Hammond

14.11.1 Problem

You're trying to track down memory usage of specific classes in a large system, and Recipe 14.10 either gives too much data to be useful or fails to recognize cycles.

14.11.2 Solution

You can design the constructors of suspect classes to keep a list of weak references to the instances in a global cache:

tracked_classes = {}
import weakref
def logInstanceCreation(instance):
    name = instance._ _class_ _._ _name_ _
    if not tracked_classes.has_key(name):
        tracked_classes[name] = []

def reportLoggedInstances(classes): # "*" means all known instances
    if classes == '*':
        classes = tracked_classes.keys(  )
        classes = classes.split(  )
    classes.sort(  )
    for classname in classes:
        for ref in tracked_classes[classname]:
            ob = ref(  )
            if ob is not None:
                print ref(  )

To use this code, add a call to logInstanceCreation(self) to the _ _init_ _ calls of the classes whose instances you want to track. When you want to find out which instances are currently alive, call reportLoggedInstances( ) with the name of the classes in question (e.g., MyClass._ _name_ _).

14.11.3 Discussion

Tracking memory problems is a key skill for developers of large systems. The above code was dreamed up to deal with memory allocations in a system that involved three different garbage collectors; Python was only one of them. Due to the references between Python objects and non-Python objects, none of the individual garbage collectors could be expected to detect cycles between objects managed in different memory-management systems. Furthermore, being able to ask a class which of its instances are alive can be useful even in the absence of cycles (e.g., when making sure that the right numbers of instances are created following a particular user action in a GUI program).

The recipe hinges on a global dictionary called tracking_classes, which uses class names as keys, and a list of weak references to instances of that class in correspondence with each key. The logInstanceCreation function updates the dictionary (adding a new empty list if the name of specific class whose instance is being tracked is not a key in the dictionary, then appending the new weak reference in any case). The reportLoggedInstances function accepts a string argument that is either '*', meaning all classes, or all the names of the pertinent classes separated by whitespace. The function checks the dictionary entry for each of these class names, examining the list and printing out those instances of the class that still exist. It checks whether an instance still exists by calling the weak reference that was put in the list to it. When called, a weak reference returns None if the object it referred to does not exist; otherwise, it returns a normal (strong) reference to the object in question.

Something you may want to do when using this kind of code is make sure that the possibly expensive debugging calls are wrapped in a if _ _debug_ _: test, as in:

class TrackedClass:
    def _ _init_ _(self):
        if _ _debug_ _: logInstanceCreation(self)

The pattern if _ _debug_ _: is detected by the Python parser in Python 2.0 and later. The body of any such marked block is ignored in the byte code-generation phase if the -O command-line switch is specified. Consequently, you may write inefficient debug-time code, while not impacting the production code. In this case, this even avoids some unimportant byte-code generation. These byte-code savings can't amount to much, but the feature is worth noting.

Also note that the ignominiously named setdefault dictionary method can be used to compact the logInstanceCreation function into a logical one-liner:

def logInstanceCreation(instance):
    tracked_classes.setdefault(instance._ _class_ _._ _name_ _, []

But such space savings are hardly worth the obfuscation cost, at least in the eyes of these authors.

14.11.4 See Also

Documentation on the weakref standard library module in the Library Reference.

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