Calling del
on a variable in Python. Does this free the allocated memory immediately or still waiting for garbage collector to collect? Like in java, explicitly calling del
has no effect on when the memory will be freed.
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.
del reference
causes the memory to be freed, so garbage collection is getting called, and (though there are no time guarantees on this) the interpreter is giving that memory back to the system. If I instead read my table and don't assign it to a variable, then it is an island, and I have to call gc.collect()
explicitly to find it and free. –
Roncesvalles del x
doesn't do anything different for garbage collection than x = None
does. It just removes a reference from x's value. –
Dispend del x
would decrease the reference count by 1; x= None
would decrease the reference count to zero. Is this no true? –
Peasant "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.
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
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.
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