Numba - @jitclass

https://numba.readthedocs.io/en/stable/user/jitclass.html

INTRODUCTION

Numba supports code generation for classes via the numba.experimental.jitclass() decorator. A class can be marked for optimization using this decorator along with a specification of the types of each field. We call the resulting class object a 'jitclass'. All methods of a jitclass are compiled into nopython functions.

@classmethod and special methods are not supported.

Numpy arrays with 'dtype=object' are not supported in 'nopython mode'.

import numpy as np
from numba import types    # import the types
from numba.experimental import jitclass

spec = [('value', types.int64),        # a simple scalar field
        ('array', types.float64[:]),   # an array field
]   # the order is in agreement with __init__

@jitclass(spec)
class Bag(object):

    def __init__(self, value):
        # the fields should be initialized
        self.value = value
        self.array = np.zeros(value, dtype=np.float64)

    @property
    def size(self):
        return self.array.size

    def increment(self, val):
        for i in range(self.size):
            self.array[i] += val
        return self.array

    @staticmethod
    def add(x, y):
        return x + y

n = 5
mybag = Bag(n)
print(mybag.array)   # [0. 0. 0. 0. 0.]
print(mybag.size)   # 5
print(Bag.add(1,2))   # 3

# Specifying 'numba.typed' containers as class members.
# (1) Using explicit Numba types and explicit construction.
# (2) Using numba.typeof(), pobieranie typu z istniejącej instancji.

from numba import types, typed
from numba.experimental import jitclass

spec = [('d', types.DictType(types.int64, types.unicode_type)),
        ('lst', types.ListType(types.float64)),
]   # the order is in agreement with __init__

@jitclass(spec)
class ContainerHolder(object):
    def __init__(self):
        # initialize the containers
        self.d = typed.Dict.empty(types.int64, types.unicode_type)
        self.lst = typed.List.empty_list(types.float64)

container = ContainerHolder()
container.d[1] = "apple"
container.lst.append(12.3)