Improper resource allocation - Memory leak - Python

Improper resource allocation - Memory leak - Python

Need

Proper resource management and deallocation

Context

  • Usage of Python 3 for writing and executing Python code
  • Usage of Django for building web applications

Description

Non compliant code

        from django.http import HttpResponse
from django.views import View

class MemoryLeakView(View):
    def get(self, request, *args, **kwargs):
        file = open('file.txt', 'r')
        data = file.read()
        return HttpResponse(data)
        
        

In the above code snippet, we have a Django view MemoryLeakView that opens a file 'file.txt' and reads its content. However, there is a significant issue with this code
- the opened file is never closed.

When a file is opened in Python, a file descriptor is allocated by the operating system to track the file. When the file is closed, the file descriptor is freed up. If a file is not closed, the file descriptor remains allocated, leading to a memory leak. This is because the number of file descriptors that an operating system can allocate is limited. If a program frequently opens files (or other resources) without closing them, the system may eventually run out of file descriptors and be unable to open new files, leading to system instability or crashes.

In the context of a Django application, this could be a severe issue. If the view is hit frequently, the server could quickly run out of resources, leading to a denial of service.

Steps

  • Identify all the places in the code where resources such as files or network connections are opened.
  • Ensure that these resources are always closed after they are no longer needed. This can be done by calling the close method on the resource.
  • Consider using the 'with' statement when dealing with file operations. This ensures that the file is properly closed when the block of code is exited, even if an error occurs within the block.
  • Regularly check for memory leaks using profiling tools or libraries. This can help identify areas of the code that are causing memory leaks.
  • Implement error handling to ensure that resources are closed in case of an error. This can be done using try/finally blocks.

Compliant code

        from django.http import HttpResponse
from django.views import View

class MemoryLeakView(View):
    def get(self, request, *args, **kwargs):
        with open('file.txt', 'r') as file:
            data = file.read()
        return HttpResponse(data)
        
        

The original code had a memory leak vulnerability due to the improper handling of file resources. The file was opened using the open function, but it was never closed. This can lead to a memory leak as the system may not be able to release the file resource.

The fixed code uses the with statement to handle the file resource. The with statement in Python is used in exception handling to make the code cleaner and much more readable. It simplifies the management of common resources like file streams.

In the fixed code, with open('file.txt', 'r') as file: is used to open the file. This ensures that the file is properly closed after its suite finishes, even if an exception is raised on the way. It is done automatically and implicitly by with statement.

So, the file resource is properly managed and this prevents the memory leak vulnerability in the code.

References