Is your Python code grinding to a halt when faced with computationally intensive tasks? Are you constantly battling performance bottlenecks, especially in multi-threaded applications? If so, you're not alone. While Python is renowned for its ease of use and rapid development, its interpreted nature and the infamous Global Interpreter Lock (GIL) can often cap performance. But what if there was a way to break through these limits, achieving a…