Here's the monte carlo example from the video.
import random @nb.njit() def monte_carlo_pi_fast(nsamples): acc = 0 for i in range(nsamples): x = random.random() y = random.random() if (x ** 2 + y ** 2) < 1.0: acc += 1 return 4.0 * acc / nsamples
For more information on supported types, see the docs here.
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