Controlling Garbage Collection State

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Alright, garbage collection in Python! You know that magical process where the computer cleans up all those objects you don’t need anymore? Well, did you know there are ways to control this state of affairs? That’s right, you can be a boss and tell Python when it’s time for the big clean-up.

First off, how garbage collection works in Python by default. The automatic garbage collector runs periodically (usually every few seconds) to collect any objects that are no longer being used by your program. This is great because you don’t have to worry about manually freeing up memory the computer takes care of it for you!

But what if you want more control over this process? Maybe you need to conserve resources or optimize performance in a specific situation. Python provides two ways to do manual garbage collection: time-based and event-based.

Time-based garbage collection is pretty straightforward you set up a timer that calls the garbage collector at regular intervals. This can be useful if your program generates a lot of temporary data or uses resources in short bursts, but doesn’t need them for long periods of time. For example:

# Import the garbage collector module
import gc
# Import the sleep function from the time module
from time import sleep

# Set up a timer to call the garbage collector every 5 seconds
while True:
    # Do some work here...
    # ...
    # When you're done, trigger the garbage collection
    gc.collect()
    # Pause the program for 5 seconds
    sleep(5)

# The above script sets up a timer to call the garbage collector at regular intervals, which can be useful for managing temporary data and resources in short bursts. The while loop ensures that the garbage collector is called continuously, while the sleep function pauses the program for 5 seconds before repeating the process.

Event-based garbage collection is a bit more complex it involves setting up events that trigger the garbage collector when certain conditions are met (like when a user exits your program or when the computer enters an idle state). This can be useful if you have a resource-intensive application and want to conserve memory during periods of low activity.

But what about controlling the threshold for new objects?In Python, garbage collection schedules based on a threshold of object allocations and deallocations. When the number of allocations minus the number of deallocations is greater than the threshold number, the garbage collector is run. To inspect the threshold for new objects (objects in Python known as generation 0 objects), you can import the gc module:

# Import the gc module to access garbage collector functions
import gc

# Print a message to indicate what is being displayed
print("Garbage collection thresholds:")

# Use the get_threshold() function from the gc module to retrieve the current threshold values for garbage collection
# The get_threshold() function returns a tuple with three values: (threshold0, threshold1, threshold2)
# threshold0: number of objects that can be allocated before garbage collection is run
# threshold1: number of objects that can be allocated before the threshold for generation 1 objects is increased
# threshold2: number of objects that can be allocated before the threshold for generation 2 objects is increased
print(gc.get_threshold())

And that’s it! With these tools at your disposal, you can now control when and how often garbage collection occurs in Python.

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