Python Memory Error is Becoming a Concern for Developers Now

Are you facing an unexpected Python Memory Error? This article might help you to find a solution.

A Python memory error means your program has run out of working memory. Python memory errors can be a rare occurrence for many programmers but they do happen in several situations. A memory error means that your program has run out of working memory and cannot continue or proceed. As a result, the program execution stops, and your operating system or programming environment will indicate that the program has run out of memory. If you get an unexpected Python Memory Error and you think you should have plenty of rams available, it might be because you are using a 32-bit python installation. Here are a few reasons why memory errors take place:  

Python Memory Error Due to Dataset

Like the point, about 32-bit and 64-bit versions have already been covered, another possibility could be dataset size if you’re working with a large dataset. Loading a large dataset directly into memory and performing computations on it and saving intermediate results of those computations can quickly fill up your memory. Generator functions come in very handy if this is your problem. Many popular python libraries like Keras and TensorFlow have specific functions and classes for generators.  

Memory is limited by 32-bit Python

A second reason memory errors happen is because, even though your computer has ample memory, the version of Python you are running could be old and can address only 32-bit memory (as opposed to 64-bit memory). With 32 bits, your programs can address only 2^32 addresses which are about 4GB. Now, of the 4GB, your operating system and other essential services on your computer will use up memory as well leaving much less memory available to your Python environment. Reinstalling the latest Python packages will usually alleviate this issue.  

How to solve Python memory error? 

#1 Free memory in Python

With gc.collect(), you can force the garbage collector to release an unreferenced memory. Syntax: import gc gc.collect()  

#2 Set the memory usage for python programs

If you want to keep the memory usage of the Python to a minimum, try this:

• Use the ulimit command to set a memory limit for python.
• You can utilize the resource module to limit the amount of memory used by the program;

If you want to speed up your program by giving it extra memory, consider the following:

• Threading, multiprocessing
• Pypy
• Pysco on only python 2.5

 

#3 Put limits on Memory and CPU Usage

To limit a program’s memory or CPU usage while it is executing. Because we don’t have any memory problems. Thus, the Resource module can be used, and both tasks can be completed successfully, as shown in the code below:  Restrict CPU time: # importing libraries import signal import resource import os # checking time limit exceed def time_exceeded(signo, frame): print(“Time’s up !”) raise SystemExit(1) def set_max_runtime(seconds): # setting up the resource limit soft, hard = resource.getrlimit(resource.RLIMIT_CPU) resource.setrlimit(resource.RLIMIT_CPU, (seconds, hard)) signal.signal(signal.SIGXCPU, time_exceeded) # max run time of 15 millisecond if __name__ == ‘__main__’: set_max_runtime(15) while True: pass In order to restrict memory use, the code puts a limit on the total address space # using resource import resource def limit_memory(maxsize): soft, hard = resource.getrlimit(resource.RLIMIT_AS) resource.setrlimit(resource.RLIMIT_AS, (maxsize, hard))  

How do you set the memory usage for python programs?

Python uses garbage collection and built-in memory management to ensure the program only uses as much RAM as required. So unless you expressly write your program in such a way to bloat the memory usage, e.g. making a database in RAM, Python only uses what it needs. Which begs the question, why would you want to use more RAM? The idea for most programmers is to minimize resource usage. If you want to limit the python memory usage, you can try this: 1、Linux，ulimit command to limit the memory usage on python 2、you can use the resource module to limit the program memory usage;   If you want to speed up your program though giving more memory to your application, you could try this: 1\threading, multiprocessing 2\pypy 3\pysco on only python 2.5  

More Trending Stories