If you encounter issues with Python's garbage collection, ensure that you're not creating circular references. Use the `gc` module to manually manage garbage collection and identify memory leaks.

Python uses automatic garbage collection to manage memory, which helps free up space when objects are no longer in use. However, issues can arise, particularly with circular references—where two or more objects reference each other, preventing them from being deallocated. To address this, you can use the gc module, which provides functions for interacting with the garbage collector. You can manually trigger garbage collection with gc.collect(), allowing you to test whether this resolves memory-related issues. Additionally, gc.get_objects() can help identify all objects currently tracked by the garbage collector, which can aid in debugging memory leaks. To further investigate, use gc.set_debug(gc.DEBUG_LEAK) to get detailed logs about objects that are not being collected. Regularly review your code to minimize circular references, and use weak references where appropriate to allow the garbage collector to reclaim memory. By implementing these strategies, you can effectively manage garbage collection issues in your Python applications.