To debug memory leaks in Python, use tools like `tracemalloc` and `objgraph`. They help track memory allocation and identify objects that are not being freed.

Memory leaks in Python can be particularly challenging to diagnose, especially in complex applications. While Python's garbage collector typically manages memory well, certain patterns, like circular references or retaining unnecessary references, can prevent the garbage collector from reclaiming memory. To debug memory leaks, you can start by using the built-in tracemalloc module, which tracks memory allocations in your application. By calling tracemalloc.start() at the beginning of your script, you can later use tracemalloc.get_traced_memory() to analyze memory usage at various points. Additionally, objgraph is another powerful tool that allows you to visualize object references and track down objects that are consuming memory. You can generate graphs of object types, which can help identify which objects are growing in number over time. Combining these tools with careful code review and profiling can help you effectively debug memory leaks in your Python applications.