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understanding garbage collection in python
garbage collection in python is the automatic management of memory allocation and deallocation. it is a vital aspect of python's memory management, ensuring that memory occupied by objects that are no longer in use is reclaimed and made available for future allocations. python's garbage collection mechanism helps developers avoid memory leaks and improves the efficiency of memory usage in their programs.
in this tutorial, we will explore the basics of garbage collection in python, including how it works and how to utilize it effectively.
how garbage collection works in python:
python's garbage collector employs a technique called reference counting to determine when objects are no longer needed and can be safely deleted. reference counting involves keeping track of the number of references to each object. when an object's reference count drops to zero, meaning there are no more references pointing to it, the garbage collector frees the memory associated with that object.
however, reference counting alone cannot handle all scenarios, particularly cyclic references where objects reference each other in a loop, causing their reference counts to never reach zero. to address this, python utilizes a secondary garbage collection mechanism called cyclic garbage collection. this mechanism detects and breaks cyclic references, allowing the garbage collector to reclaim memory even in the presence of such reference cycles.
garbage collection example:
let's illustrate garbage collection in action with a simple python example:
in this example, we create two instances of the myclass class (obj1 and obj2) and establish a cyclic reference between them by setting attributes ref to point to each other. then, we delete the references to obj1 and obj2 to break the cycle. finally, we manually trigger garbage collection using gc.collect().
tips for effective garbage collection:
avoid circular references: be mindful of creating circular references ...

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