Numba vs Pure Python: Which is Better for Performance?

What are the main differences between Numba and pure Python?

Numba is a just-in-time compiler that translates a subset of Python and NumPy code into fast machine code. Pure Python, on the other hand, is interpreted and generally slower for numerical computations.

When should I use Numba instead of pure Python?

You should consider using Numba when you need to optimize performance for numerical computations, especially in loops or when using NumPy arrays.

Are there any downsides to using Numba?

Yes, Numba has some limitations, such as not supporting all Python features and requiring specific types of functions to work effectively.

Can I use Numba with existing Python code?

Absolutely! You can apply Numba decorators to existing functions to speed them up without needing to rewrite your entire codebase.

How does Numba compare to other optimization tools?

Numba is often faster than pure Python and can be more straightforward than other tools like Cython, but it may not be as flexible.