Why Doesn\'t Python Immediately Release Memory After `del`?

Memory Release in Python

In Python, the release of memory is handled by the garbage collector (GC), which automatically deallocates objects that are no longer referenced. However, in certain situations, memory usage may not be released promptly after objects are deleted.

Initial Memory Usage

When you assign a large list to a variable, such as foo, Python allocates memory to store the list and its elements. In your example, creating a list of 10 million 'bar' strings consumes approximately 80.9 MB of memory.

Delayed Memory Release

After deleting foo with del foo, you may notice that the real memory usage only decreases to 30.4 MB instead of returning to the baseline of 4.4 MB. This is because the GC has not yet collected and released the memory associated with the list.

Amount of Memory Released

The amount of memory released after garbage collection is not a fixed value. It depends on various factors, including the size of the deleted objects, the current state of the memory manager, and the frequency of GC runs. In your case, approximately 50.5 MB of memory was released.

Enforced Memory Release

Python does not provide a direct mechanism to force immediate memory release. However, a workaround exists:

Using Child Processes

If you know that you will not need a large amount of memory in the near future, you can create a child process to handle the memory-intensive task. When the child process terminates, all its allocated memory is automatically released.

To create a child process, you can use the multiprocessing module:

import multiprocessing

def memory_intensive_task(args):
    # Perform memory-intensive operations here

process = multiprocessing.Process(target=memory_intensive_task, args=(args,))
process.start()
process.join()  # Wait for the child process to finish

By using child processes, you can ensure that memory allocated for temporary tasks is released as soon as possible.

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