I’ve been delving deeper into Python’s internals recently, particularly focusing on memory management. While I understand the basics of Python’s garbage collection mechanism, I’m eager to gain a more comprehensive understanding of how Python handles memory allocation and deallocation under the hood.

From what I’ve gathered so far, Python employs a combination of reference counting and a cyclic garbage collector to manage memory. However, I’m curious about the finer details:

1. How does Python's reference counting mechanism work in practice? Are there any scenarios where it may lead to memory leaks or inefficiencies?
2. When does Python resort to using its cyclic garbage collector? What types of objects are more likely to trigger its activation?
3. Are there any best practices or strategies for optimizing memory usage in Python applications? How can developers effectively minimize memory leaks and optimize performance?
4. How does Python handle memory management in multi-threaded or asynchronous environments? Are there any potential pitfalls or concurrency issues to be aware of?
5. Are there any notable differences in memory management between different Python implementations (e.g., CPython, PyPy, Jython)?

Overall, I’m eager to gain a more nuanced understanding of Python’s memory management mechanisms and how they impact the performance and scalability of Python applications. Any guidance or expertise on this topic would be immensely valuable.

Thanks in advance!