from __future__ import annotations
from dataclasses import dataclass
import pandas as pd


class Reporting:
    def __init__(self):
        self.results: pd.DataFrame = pd.DataFrame() 
        self.all_predictions: pd.DataFrame = pd.DataFrame() 
        self.all_probabilities: pd.DataFrame = pd.DataFrame() 
        self.asset: Reporting.Asset
    
    def get_results(self) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame, Reporting.Asset]:
        return self.results, self.all_predictions, self.all_probabilities, self.asset
    
    @dataclass
    class Single_Model:
        model_name: str
        model_over_time: pd.Series
        transformations_over_time: list[pd.Series]


    class Training_Step: 
        def __init__(self, level: str):
            self.level: str = level
            self.base: list[Reporting.Single_Model] = []
            self.metalabeling: list[list[Reporting.Single_Model]] = []
            
        def get_base(self) -> list[tuple[str, pd.Series, list[pd.Series]]]:
            return [(x.model_name, x.model_over_time, x.transformations_over_time) for x in self.base ]

        def get_metalabeling(self) -> dict:
            structured_dict = dict()
            for i, model in enumerate(self.base):
                structured_dict[model.model_name] = [(x.model_name, x.model_over_time, x.transformations_over_time) for x in self.metalabeling[i]]
            return structured_dict

    @dataclass
    class Asset():
        name: str
        primary: Reporting.Training_Step
        secondary: Reporting.Training_Step