How can I validate a list which contains floats in a specific range with Cerberus?

I would like to validate JSON objects that were parsed into Python dictionaries like the following:

# example with 2 elements
{
    'coordinates': [-20.3, 30.6]
}

# example with 3 elements
{
    'coordinates': [-20.3, 30.6, 0]
}

So far I was able to define the following schema:

schema = {
    'coordinates': {
        'required': True,
        'type': 'list',
        'minlength': 2,
        'maxlength': 3,
        'schema': {
            'type': 'float',
        },
    }
}

I would also like to check these constraints:

the first item of the coordinates field's value should be between -30.0 and 10.0
the second item should be between -10.0 and 50.0

But I was not able to come up with something useful. Does anyone have suggestions how to achieve this?

Update: Based on accepted answer the schema becomes the following

schema = {
    'coordinates': {
        'required': True,
        'type': 'list',
        "oneof_items": (
            ({"min": -30.0, "max": 10.0}, {"min": -10.0, "max": 50.0}),
            ({"min": -30.0, "max": 10.0}, {"min": -10.0, "max": 50.0}, {}),
        ),
    }
}

docs: https://docs.python-cerberus.org/en/stable/validation-rules.html#of-rules-typesaver

Solution

Add this rule:

{"oneof_items":
  (
    ({"min": -30.0, "max": 10.0}, {"min": -10.0, "max": 50.0}),
    ({"min": -30.0, "max": 10.0}, {"min": -10.0, "max": 50.0}, {}),
  )
}

That makes the length-related rules superfluous. To get rid of the redundancies Python object references or the rule set registry are feasible.