import json
from dataclasses import dataclass
from datetime import datetime

from huggingface_hub import hf_hub_download
from huggingface_hub.utils._errors import EntryNotFoundError
from loguru import logger


@dataclass
class CompetitionInfo:
    competition_id: str
    autotrain_token: str

    def __post_init__(self):
        try:
            config_fname = hf_hub_download(
                repo_id=self.competition_id,
                filename="conf.json",
                use_auth_token=self.autotrain_token,
                repo_type="dataset",
            )
            competition_desc = hf_hub_download(
                repo_id=self.competition_id,
                filename="COMPETITION_DESC.md",
                use_auth_token=self.autotrain_token,
                repo_type="dataset",
            )
            dataset_desc = hf_hub_download(
                repo_id=self.competition_id,
                filename="DATASET_DESC.md",
                use_auth_token=self.autotrain_token,
                repo_type="dataset",
            )
        except EntryNotFoundError:
            raise Exception("Competition config not found. Please check the competition id.")
        except Exception as e:
            logger.error(e)
            raise Exception("Hugging Face Hub is unreachable, please try again later.")

        self.config = self.load_config(config_fname)
        self.competition_desc = self.load_md(competition_desc)
        self.dataset_desc = self.load_md(dataset_desc)
        try:
            submission_desc = hf_hub_download(
                repo_id=self.competition_id,
                filename="SUBMISSION_DESC.md",
                use_auth_token=self.autotrain_token,
                repo_type="dataset",
            )
            self.submission_desc = self.load_md(submission_desc)
        except Exception:
            self.submission_desc = None

    def load_md(self, md_path):
        with open(md_path) as f:
            md = f.read()
        return md

    def load_config(self, config_path):
        with open(config_path) as f:
            config = json.load(f)
        return config

    @property
    def submission_limit(self):
        return self.config["SUBMISSION_LIMIT"]

    @property
    def selection_limit(self):
        return self.config["SELECTION_LIMIT"]

    @property
    def end_date(self):
        e_d = self.config["END_DATE"]
        return datetime.strptime(e_d, "%Y-%m-%d")

    @property
    def eval_higher_is_better(self):
        hb = self.config["EVAL_HIGHER_IS_BETTER"]
        return True if int(hb) == 1 else False

    @property
    def competition_description(self):
        return self.competition_desc

    @property
    def submission_columns(self):
        return self.config["SUBMISSION_COLUMNS"].split(",")

    @property
    def submission_description(self):
        return self.submission_desc

    @property
    def dataset_description(self):
        return self.dataset_desc

    @property
    def logo_url(self):
        return self.config["LOGO"]

    @property
    def competition_type(self):
        return self.config["COMPETITION_TYPE"].lower().strip()

    @property
    def metric(self):
        return self.config["EVAL_METRIC"]

    @property
    def submission_id_col(self):
        return self.config["SUBMISSION_ID_COLUMN"]

    @property
    def submission_cols(self):
        cols = self.config["SUBMISSION_COLUMNS"].split(",")
        cols = [c.strip() for c in cols]
        return cols

    @property
    def submission_rows(self):
        return self.config["SUBMISSION_ROWS"]

    @property
    def time_limit(self):
        return self.config["TIME_LIMIT"]