import pandas as pd

import os
from typing import Union

import datasets


def save_and_compress(dataset: Union[datasets.Dataset, pd.DataFrame], name: str, idx=None):
    if idx:
        path = f"{name}_{idx}.jsonl"
    else:
        path = f"{name}.jsonl"

    print("Saving to", path)
    dataset.to_json(path, force_ascii=False, orient='records', lines=True)

    print("Compressing...")
    os.system(f'xz -zkf -T0 {path}')  # -TO to use multithreading

dfs = []
for num_classes in [3, 6, 9]:
    df = pd.read_csv(f"datasets/mietrecht_sentences_{num_classes}_classes.csv", sep=";")
    # remove columns that are not needed
    df = df[['Funktion', 'Text']]
    df.rename(columns={'Funktion': f'label_{num_classes}_classes', 'Text': f'text_{num_classes}_classes'}, inplace=True)
    dfs.append(df)

train = pd.concat(dfs, axis=1)
save_and_compress(train, f"data/train")