For full documentation, see http://garywiz.github.io/pytracker.
If you're in a hurry, here's a quick overview:
The pytracker extension provides a small, efficient set of classes
for tracking object usage in production code. In order to track objects,
they must be subclasses of the pytracker.Trackable class, which
in most cases behaves exactly like the Python object class.
Unlike existing packages like
Heapy and
PySizer, pytracker is not designed for
profiling or debugging existing code, but is rather designed to allow
you instrument production systems for monitoring of object usage
during normal operation. It is especially useful for optimizing long-running
systems which may exhibit memory leaks or unusual usage patterns over time.
Though you can create your own tracker to collect more comprehensive information about live objects, there is a simple tracker provided which can be used quickly and easily. For example:
>>> from pytracker import Tracker, Trackable, set_global_tracker
>>> t = Tracker()
>>> set_global_tracker(t)
>>>
>>> class track_my_instances(Trackable):
... pass
...
>>> i1 = track_my_instances()
>>> i2 = track_my_instances()
>>> t.dump()
track_my_instances allocated: 2 retired: 0
>>> i1 = None
>>> t.dump()
track_my_instances allocated: 1 (-1) retired: 1 (+1)
>>>
The easiest way to install pytracker`` is using pip` from the https://pypi.python.org/pypi/pytracker package:
# Ubuntu or debian prerequisites...
apt-get install pip
apt-get install python-dev
apt-get install gcc
# pytracker installation (may be all you need)
pip install pytracker
This software is distributed under the BSD License.
Copyright (c) 2013, Gary J. Wisniewski, All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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