How Does the Python Garbage Collector Automatically Manage Memory?

Python Garbage Collector Documentation

The Python garbage collector is a memory management system that automatically frees memory that is no longer in use by the program. This helps to improve performance by preventing memory leaks and ensuring that the program does not run out of memory.

The garbage collector works in a two-step process:

1. Reference counting: The interpreter keeps track of the number of references to each object. When the reference count reaches zero, the object is considered unreachable and is added to a list of objects to be deleted.
2. Garbage collection: A background thread runs periodically to delete unreachable objects from the list. The thread uses a Mark-and-Sweep algorithm to identify and delete unreachable objects.

The following resources provide more details on how the Python garbage collector works:

• [Python Garbage Collection](https://docs.python.org/3/library/gc.html)
• [gc module docs](https://docs.python.org/3/library/gc.html)
• [Details on Garbage Collection for Python](https://nedbatchelder.com/text/python-gc.html)

These resources can help you understand the process of garbage collection and how to predict when it will occur. This information can be useful for optimizing the performance of your program by reducing the frequency of garbage collection.

Update

The Python source code provides further insights into the garbage collection process. The comments in the collect() function provide a detailed explanation of how the algorithm works. This information can be helpful for developers who want to learn more about the technical details of garbage collection in Python.

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