How does the `del` statement work in Python?

Question

Suppose I have a variable x and then try del x. Does this free the allocated memory immediately, or will it still wait for the garbage collector to collect the object at some later point (like in Java)?

Answer 1

The del statement doesn't reclaim memory. It removes a reference, which decrements the reference count on the value. If the count is zero, the memory can be reclaimed. CPython will reclaim the memory immediately, there's no need to wait for the garbage collector to run.

In fact, the garbage collector is only needed for reclaiming cyclic structures.

As Waleed Khan says in his comment, Python memory management just works, you don't have to worry about it.

Answer 2

"Deletion of a name removes the binding of that name from the local or global namespace". No more, no less. It does nothing to the object the name pointed to, except decrementing its refcount, and if refcount is not zero, the object will not be collected even when GC runs.

Answer 3

Also, the del statement seems to be a little bit faster than assigning None (similar to Java's style assigning null to a variable to free its memory ...).

To compare:

import time, math

def measure_del():
        start = time.time()
        for i in range(0,int(math.pow(10,8))):
                    a = "123"
                    del a # <--- !!!
        end = time.time()
        print(end-start)

def measure_none():
        start = time.time()
        for i in range(0,int(math.pow(10,8))):
                    a = "123"
                    a = None # <--- !!!
        end = time.time()
        print(end-start)

results in (running in idle3.4):

>>> measure_del()
3.9930295944213867
>>> measure_del()
3.7402305603027344
>>> measure_del()
3.8423104286193848
>>> measure_del()
3.753770351409912
>>> measure_del()
3.7772741317749023
>>> measure_del()
3.815058946609497

>>> measure_none()
4.052351236343384
>>> measure_none()
4.130320072174072
>>> measure_none()
4.082390069961548
>>> measure_none()
4.100180625915527
>>> measure_none()
4.071730375289917
>>> measure_none()
4.136169672012329

Answer 4

Regarding delete: Sometimes you have to work on large datasets where you have to compute memory-intensive operations and store a large amount of data into a variable in a recursive manner. To save RAM, when you finish your entire operation, you should delete the variable if you are no more using it outside the recursive loop. You can use the command

del varname followed by Python’s garbage collector gc.collect()

Regarding speed: Speed is the most important in applications such as financial applications with a regulatory requirement. You have to make sure that the speed of operation is completed within the expected timeframe.