from datasets.utils.logging import disable_progress_bar
from constants import column_names, RANKING_COLUMN, ORDERED_COLUMN_NAMES
from utils_display import make_clickable_model
disable_progress_bar()
import json
import os

summary_file = "hardcorelogic.summary.json"
#result_dir = "HardcoreLogic-Eval/results_dirs"
results_by_model = {}

# Formats the columns
def formatter(x):
    if type(x) is str:
        x = x
    else: 
        x = round(x, 2)
    return x

def post_processing(df, column_names, rank_column=RANKING_COLUMN, ordered_columns=ORDERED_COLUMN_NAMES, click_url=True):
    df = df[[col for col in column_names.keys() if col in df.columns]].copy()
    for col in df.columns:
        if col == "model" and click_url:
            df[col] = df[col].apply(lambda x: x.replace(x, make_clickable_model(x)))
        else:
            df[col] = df[col].apply(formatter) # For numerical values
    list_columns = [col for col in ordered_columns if col in df.columns]
    df = df[list_columns]
    if rank_column in df.columns:
        df.sort_values(by=rank_column, inplace=True, ascending=False)
    df.rename(columns=column_names, inplace=True)
    return df