import os
import tarfile
import zipfile
import gzip
import traceback
import requests
from os.path import join as p_join
from tqdm import tqdm
from multiprocessing import Pool
from typing import Optional
from urllib3.connection import ConnectionError

import pandas as pd


url_metadata_s2s = "https://dl.fbaipublicfiles.com/seamless/data/seamless_align_nov2023_extension/seamless.dataset.metadata.public.enA-jaA.tsv.gz"
url_metadata_s2t = "https://dl.fbaipublicfiles.com/seamless/data/seamless.dataset.metadata.public.enA-jpn.withduration.tsv.gz"
cache_dir_root = "./download"
n_pool = 8


def wget(url: str, cache_dir: str, filename: Optional[str] = None):
    os.makedirs(cache_dir, exist_ok=True)
    filename = os.path.basename(url) if not filename else filename
    output_file = p_join(cache_dir, filename)
    try:
        with open(output_file, "wb") as f:
            r = requests.get(url)
            f.write(r.content)
    except ConnectionError or KeyboardInterrupt:
        traceback.print_exc()
        os.remove(output_file)
        return False

    if output_file.endswith('.tar.gz') or output_file.endswith('.tgz') or output_file.endswith('.tar'):
        if output_file.endswith('.tar'):
            tar = tarfile.open(output_file)
        else:
            tar = tarfile.open(output_file, "r:gz")
        tar.extractall(cache_dir)
        tar.close()
        os.remove(output_file)
    elif output_file.endswith('.gz'):
        with gzip.open(output_file, 'rb') as f:
            with open(output_file.replace('.gz', ''), 'wb') as f_write:
                f_write.write(f.read())
        os.remove(output_file)
    elif output_file.endswith('.zip'):
        with zipfile.ZipFile(output_file, 'r') as zip_ref:
            zip_ref.extractall(cache_dir)
        os.remove(output_file)
    return True


def get_metadata(url: str):
    cache_dir = p_join(cache_dir_root, "meta")
    filename = os.path.basename(url).replace(".gz", "")
    if not os.path.exists(filename):
        assert wget(url, cache_dir=cache_dir)
    df = pd.read_csv(p_join(cache_dir, filename), sep=r'[\t\s]', header=None)[[0, 2, 6, 9, 10, 11, 12]]
    df.columns = ["id", "url", "text_lid_score", "laser_score", "direction", "side", "line_no"]
    return df


def get_audio(url: str, filename: str):
    cache_dir = p_join(cache_dir_root, "audio")
    if not os.path.exists(p_join(cache_dir, filename)):
        return wget(url, filename=filename, cache_dir=cache_dir)
    return False


def process_dataset(url_metadata):
    df_metadata = get_metadata(url_metadata)
    print(f"load metadata: {url_metadata}, ({len(df_metadata)} rows)")
    inputs = [(
        r['url'], f"{r['id']}.{r['direction']}.{r['side']}.{os.path.basename(r['url'])}"
    ) for _, r in df_metadata.iterrows()]
    inputs = [x for x in inputs if not os.path.exists(p_join(cache_dir_root, "audio", x[1]))]
    print(f"{len(inputs)} urls to download")
    with Pool(n_pool) as pool:
        pool.starmap(get_audio, tqdm(inputs, total=len(inputs)))


if __name__ == '__main__':
    process_dataset(url_metadata_s2s)
    process_dataset(url_metadata_s2t)