Cached Just-In-Time compilation

With Transonic, one can use the Ahead-Of-Time compiler Pythran in a Just-In-Time mode. It is really the easiest way to speedup a function with Pythran, just by adding a decorator! And it works also in notebooks!

import numpy as np

from transonic import jit

def func0(a, b):
    return a + b

def func1(a: int, b: int):
    print("b", b)
    return np.exp(a) * b * func0(a, b)

if __name__ == "__main__":

    from time import sleep

    a = b = np.zeros([2, 3])

    for i in range(20):
        print(f"{i}, call with arrays")
        func1(a, b)
        print(f"{i}, call with numbers")
        func1(1, 1.5)

Note that it can be very convenient to use type hints and @jit in order to avoid multiple warmup periods:

from transonic import jit, Type

T = Type(int, float)

def func(a: T, b: T):
    return a * b

if __name__ == "__main__":

    from time import sleep

    a_i = b_i = 1
    a_f = b_f = 1.0

    for _ in range(10):
        print(_, end=",", flush=True)
        func(a_i, b_i)


    for _ in range(10):
        print(_, end=",", flush=True)
        func(a_f, b_f)

If the environment variable TRANSONIC_COMPILE_AT_IMPORT is set, transonic compiles at import time the functions with type hints.