What are common memory leaks in Python and how can I avoid them?

What are common memory leaks in Python and how can I avoid them?

Common memory leaks in Python often occur due to circular references, large data structures, or unclosed resources. To avoid them, ensure you use weak references, manage your data structures carefully, and always close files and network connections.

Can you give me an example of a circular reference?

Sure! A circular reference occurs when two or more objects reference each other, preventing Python's garbage collector from reclaiming their memory. For example, if object A references object B and object B references object A, they create a cycle.

How can I detect memory leaks in my Python application?

You can use tools like objgraph, memory_profiler, or tracemalloc to detect memory leaks. These tools help you analyze memory usage and identify objects that are not being released.

What should I do if I find a memory leak?

If you find a memory leak, review your code to identify the source of the leak. Refactor your code to eliminate circular references, use weak references where appropriate, and ensure that all resources are properly closed.