from __future__ import annotations

from dataclasses import dataclass, field
from pathlib import Path
import sys

PROJECT_ROOT = Path(__file__).resolve().parents[1]
if str(PROJECT_ROOT) not in sys.path:
    sys.path.insert(0, str(PROJECT_ROOT))

from scripts.config import CORE_FEATURE_NAMES, DataConfig


@dataclass
class TreeModelConfig:
    candidate_models: tuple[str, ...] = ("extra_trees", "random_forest", "gradient_boosting")
    random_state: int = 42


@dataclass
class TrainConfig:
    checkpoint_dir: str = "checkpoints_tree"
    summary_name: str = "model_selection.csv"
    best_model_name: str = "best_tr_tree.pkl"


@dataclass
class ExperimentConfig:
    data: DataConfig = field(default_factory=DataConfig)
    model: TreeModelConfig = field(default_factory=TreeModelConfig)
    train: TrainConfig = field(default_factory=TrainConfig)


def make_experiment_config() -> ExperimentConfig:
    return ExperimentConfig()


def checkpoint_dir(config: ExperimentConfig) -> Path:
    path = config.data.project_root / config.train.checkpoint_dir / "task1_tr_tree"
    path.mkdir(parents=True, exist_ok=True)
    return path


def evaluation_dir(config: ExperimentConfig) -> Path:
    path = config.data.project_root / "evaluation_outputs" / "task1_tr_tree"
    path.mkdir(parents=True, exist_ok=True)
    return path


FEATURE_NAMES = CORE_FEATURE_NAMES