How make a python class jitclass compatible when it contains itself jitclass classes?

[ymmx2]

I'm trying to make a class that could be a part of jitclass but has some attribute that are themself jitclass objects.

for example, if I have two class with the decorator @jitclass, I would like instanced those in a third class (combined).

import numpy as np
from numba import jitclass
from numba import boolean, int32, float64,uint8

spec = [
    ('type' ,int32),
    ('val' ,float64[:]),
    ('result',float64)]

@jitclass(spec)
class First:
    def __init__(self):
        self.type = 1
        self.val = np.ones(100)
        self.result = 0.
    def sum(self):
        self.result = np.sum(self.val)

@jitclass(spec)
class Second:
    def __init__(self):
        self.type = 2
        self.val = np.ones(100)
        self.result = 0.
    def sum(self):
        self.result = np.sum(self.val)



@jitclass(spec)
class Combined:
    def __init__(self):
        self.List = []
        for i in range(10):
            self.List.append(First())
            self.List.append(Second())

    def sum(self):
        for i, c in enumerate(self.List):
            c.sum()
    def getresult(self):
        result = []
        for i, c in enumerate(self.List):
            result.append(c.result)
        return result


C = Combined()
C.sum()
result = C.getresult()
print(result)

In that example I get an error because numba cannot determine the type of self.List which is a combination of the two jitclasses.
How can I make the class Combined be jitclass compatible?

update

It tried Something I found elsewhere:

import numpy as np
from numba import jitclass, deferred_type
from numba import boolean, int32, float64,uint8
from numba.typed import List

spec = [
    ('type' ,int32),
    ('val' ,float64[:]),
    ('result',float64)]

@jitclass(spec)
class First:
    def __init__(self):
        self.type = 1
        self.val = np.ones(100)
        self.result = 0.
    def sum(self):
        self.result = np.sum(self.val)
 

 
spec1 = [('ListA',List.empty_list(First.class_type.instance_type)  )]

@jitclass(spec1)
class Combined:
    def __init__(self):
        self.ListA = [First(),First()] 

    def sum(self):
        for i, c in enumerate(self.ListA):
            c.sum()
    def getresult(self):
        result = []
        for i, c in enumerate(self.ListA):
            result.append(c.result)
        return result


C = Combined()
C.sum()
result = C.getresult()
print(result)

but I get this error

TypeError: spec values should be Numba type instances, got ListType[instance.jitclass.First#20b0cbcf5f8<type:int32,val:array(float64, 1d, A),result:float64>]([])

[github-actions]

This issue is marked as stale as it has had no activity in the past 30 days. Please close this issue if no further response or action is needed. Otherwise, please respond with any updates and confirm that this issue still needs to be addressed.

[gmarkall]

@ymmx2 apologies for the long delay in the response here. The problem is that List gives an instance of the list, not its type. You can instead use a ListType for the spec, like:

import numpy as np
from numba.experimental import jitclass
from numba import int32, float64
from numba.typed import List
from numba.types import ListType

spec = [("type", int32), ("val", float64[:]), ("result", float64)]


@jitclass(spec)
class First:
    def __init__(self):
        self.type = 1
        self.val = np.ones(100)
        self.result = 0.0

    def sum(self):
        self.result = np.sum(self.val)


spec1 = [("ListA", ListType(First.class_type.instance_type))]


@jitclass(spec1)
class Combined:
    def __init__(self):
        self.ListA = List((First(), First()))

    def sum(self):
        for i, c in enumerate(self.ListA):
            c.sum()

    def getresult(self):
        result = []
        for i, c in enumerate(self.ListA):
            result.append(c.result)
        return result


C = Combined()
C.sum()
result = C.getresult()
print(result)

which prints:

$ python repro.py 
[100.0, 100.0]

[github-actions]

This issue is marked as stale as it has had no activity in the past 30 days. Please close this issue if no further response or action is needed. Otherwise, please respond with any updates and confirm that this issue still needs to be addressed.

[gmarkall]

Closing this issue as no further feedback has been received.