In this tutorial, I will tell you the reason for getting this warning and will try to solve it in every possible way.
Why this ResourceWarning occurs?
Hey there! So, when you see a ResourceWarning, it’s like a gentle reminder that you opened a file, did your thing with it, but forgot to close it afterward. No worries, Python usually takes care of closing it when it realizes the file isn’t needed anymore, but it might take a bit of time. To keep you in the loop, recent Python versions also kindly give you a heads-up with a friendly ResourceWarning message when this happens. Just a little nudge to make sure everything’s neat and tidy!
The tracemalloc module is like a detective for memory blocks in Python, helping you trace where they’re allocated.
Just so you know, it’s more of a friendly warning suggesting you enable tracemalloc rather than a full-blown error. Your test case should be just fine despite this little heads-up. No need to worry!
How to Enable Tracemalloc
Enabling tracemalloc in your Python code is a straightforward process. Follow these simple steps:
import tracemalloc tracemalloc.start()
Once you’ve called tracemalloc.start(), the tracemalloc module will initiate tracking of memory allocation in your code. To conclude tracemalloc tracking, you can use tracemalloc.stop().
Obtaining Object Allocation Traceback
With tracemalloc activated, you can leverage the tracemalloc.get_traced_memory() function to gather information about memory usage in your code. This function returns a tuple containing the current size of allocated memory and a list of traceback objects. Each traceback object provides details about an allocation, including filename, line number, and function name.
Here’s an example demonstrating the use of tracemalloc.get_traced_memory():
import tracemalloc
tracemalloc.start()
# Your code here
current, peak = tracemalloc.get_traced_memory()
print("Current memory usage is", current / 10**6, "MB")
print("Peak was", peak / 10**6, "MB")
traces = tracemalloc.get_traced_memory()[1]
for trace in traces[:3]:
print("File:", trace.filename)
print("Line:", trace.lineno)
print("Function:", trace.name)
print()
tracemalloc.stop()
Understanding the Runtime Warning
When do we Encounter the Warning?
When Python kindly nudges you with the “Runtime Warning: Enable tracemalloc to get the object allocation traceback” message, it’s basically saying, “Hey, I’d love to help you trace where your memory is going, but I need tracemalloc to be in action for that!”
In simpler terms, it’s like your Python interpreter saying, “I can’t provide details about where this memory is allocated unless you enable tracemalloc.” So, if you’re curious about your memory’s journey, just turn on tracemalloc, and Python will happily share the story of your object allocation
Example Scenario
Consider the following code snippet:
import sys x = [1, 2, 3, 4, 5] print(sys.getobjects(0))
In this case, sys.getobjects(0) attempts to provide information about the memory allocation of all objects in the program. Running this code triggers the warning, signaling that tracemalloc is not enabled, and memory allocation information is unavailable.
If you want to steer clear of that warning, just make sure to turn on tracemalloc before diving into functions like sys.getobjects(0) that need memory allocation info. It’s like putting on your memory-tracking superhero cape before tackling the task! 🦸♂️✨
import sys import tracemalloc tracemalloc.start() x = [1, 2, 3, 4, 5] print(sys.getobjects(0)) tracemalloc.stop()
The above code aims to print information about memory allocations using sys.getobjects(0) after enabling tracemalloc. However, there’s an issue with the usage of sys.getobjects(0). This function no longer exists in recent Python versions.
If you were to run this code, you might encounter an AttributeError because sys object has no attribute getobjects. To get information about memory allocations, especially when using tracemalloc, you should use the functions provided by the tracemalloc module.