What I have:
I am creating a dataclass and I am stating the types of its elements:
class Task():
n_items: int
max_weight: int
max_size: int
items: numpy.array(Item) # incorrect way of doing it
What I want to do
I'd like to declare, that items will be a numpy array of obejcts of class "Item"
You can put ndarray:
import numpy as np
class Task():
n_items: int
max_weight: int
max_size: int
items: np.ndarray
numpy container, as per: docs.scipy.org/doc/numpy/user/basics.dispatch.html and force it to take only certain type of objects.numpy type with restricted dtypeobject means everything. So it could be either your custom class, or anything else. You can actually force it to take only one type, but that would mean exactly making custom numpy containerYou have to use ndarray class type:
import numpy as np
class Task():
n_items: int
max_weight: int
max_size: int
items: np.ndarray[<shapeType>, <convertedNumpyGenericType>]
Where <shapeType> is the type of values defining the shape of the array (probably int) and <convertedNumpyGenericType> defines the array data's type. Be careful that you have to "convert" numpy generic types into python ones. You may want to use np.dtype[<generic>] with <generic> the generic numpy type (e.g np.float64)
If you want to set a default value (inside the field dataclass function) you have to do as follows:
items: np.ndarray[_, _] = field(default_factory=lambda: np.zeros(shape=<int>, dtype=<type>))
You can use the nptyping package, which offers type hints specifically for Numpy data types.
Unless you want to create a custom Numpy container, the best you can do is to denote your array as a container of typing.Any objects, since support for types beyond the ones mentioned here is lacking.
from nptyping import NDArray, Shape
from typing import Any
import numpy as np
class Item:
pass
class Foo:
def __init__(self, bar: NDArray[Shape["1,2"], Any]):
self.bar = bar
if __name__ == '__main__':
item = Item()
foo = Foo(bar=np.array([Item(), Item()], dtype=Item))
print(foo.bar)
Running this will yield something like
[<__main__.Item object at 0x7f13f0dd9e80>
<__main__.Item object at 0x7f13f0dd9040>]
