How can I improve the performance of my Python code using Numba?

How can I improve the performance of my Python code using Numba?

You can use Numba to compile your Python functions to machine code, which can significantly speed up execution. Just decorate your function with @jit.

What types of functions benefit the most from using Numba?

Numba works best with numerical functions, especially those involving loops and array operations. Functions that are computationally intensive will see the most benefit.

Are there any limitations I should be aware of when using Numba?

Yes, Numba has some limitations, such as not supporting all Python features and libraries. It works best with NumPy arrays and basic Python types.

Can you give me an example of a simple function optimized with Numba?

Sure! Here's a simple example:

from numba import jit

@jit
def sum_array(arr):
    total = 0
    for i in arr:
        total += i
    return total