from apiflask import Schema, fields
from apiflask.validators import OneOf, Range


class DecisionTreeParamsDto(Schema):
    splitter = fields.String(load_default="best", validate=OneOf(["best", "random"]))
    max_depth = fields.Integer(load_default=7)
    min_samples_split = fields.Integer(load_default=2, validate=Range(min=2))
    min_samples_leaf = fields.Integer(load_default=1, validate=Range(min=1))
    min_weight_fraction_leaf = fields.Float(load_default=0.0)
    # TODO: Add float values support
    max_features = fields.String(
        load_default=None,
        validate=OneOf(["auto", "sqrt", "log2", None]),
    )
    random_state = fields.Integer(load_default=None)
    max_leaf_nodes = fields.Integer(load_default=None)
    min_impurity_decrease = fields.Float(load_default=0.0)
    ccp_alpha = fields.Float(load_default=0.0)


class RuleAtomDto(Schema):
    variable = fields.String()
    type = fields.String()
    value = fields.Float()


class RuleDto(Schema):
    antecedent = fields.List(fields.Nested(RuleAtomDto()))
    consequent = fields.Field()


class TreeNodeDto(Schema):
    parent = fields.String()
    name = fields.String()
    level = fields.Integer()
    variable = fields.String()
    type = fields.String()
    value = fields.Field()