from dataclasses import dataclass, make_dataclass
from enum import Enum

import pandas as pd

from src.about import Tasks

def fields(raw_class):
    return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"]


# These classes are for user facing column names,
# to avoid having to change them all around the code
# when a modif is needed
@dataclass
class ColumnContent:
    name: str
    type: str
    displayed_by_default: bool
    hidden: bool = False
    never_hidden: bool = False

## Leaderboard columns
auto_eval_column_dict = []
# Init
auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
auto_eval_column_dict.append(["org", ColumnContent, ColumnContent("Organization", "str", True)])
#Scores
auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Aiera Score ⬆️", "number", True)])
for task in Tasks:
    auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)])

auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", False)])
auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("License", "str", False)])


# We use make dataclass to dynamically fill the scores from Tasks
AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)

## For the queue columns in the submission tab
@dataclass(frozen=True)
class EvalQueueColumn:  # Queue column
    model = ColumnContent("model", "markdown", True)
    private = ColumnContent("private", "bool", False)
    status = ColumnContent("status", "str", True)

@dataclass(frozen=True)
class FailedEvalQueueColumn:  # Queue column
    model = ColumnContent("model", "markdown", True)
    private = ColumnContent("private", "bool", False)
    status = ColumnContent("status", "str", True)
    reason = ColumnContent("reason", "str", True)

## All the model information that we might need
@dataclass
class ModelDetails:
    name: str
    display_name: str = ""
    symbol: str = "" # emoji

# Column selection
COLS = [c.name for c in fields(AutoEvalColumn) if not c.hidden]

EVAL_COLS = [c.name for c in fields(EvalQueueColumn)]
EVAL_TYPES = [c.type for c in fields(EvalQueueColumn)]

FAILED_EVAL_COLS = [c.name for c in fields(FailedEvalQueueColumn)]
FAILED_EVAL_TYPES = [c.type for c in fields(FailedEvalQueueColumn)]

BENCHMARK_COLS = [t.value.col_name for t in Tasks]