import re
import fasttext
from functools import reduce

FASTTEXT_MODEL_PATH = "/researchdisk/lid.176.bin"
fasttext_model = fasttext.load_model(FASTTEXT_MODEL_PATH)


def filter_stats(batch):
    filter_stats_funcs = [
        _count_alphabet,
        _count_numbers,
        _count_upper,
        _count_str_len,
        _predict_lang,
        _calculate_alphabet_ratio,
        _calculate_number_ratio,
        _calculate_upper_ratio,
    ]
    return reduce(lambda x, y: y(x), filter_stats_funcs, batch)


def _count_alphabet(batch):
    batch["alphabet_len"] = len(re.findall(r"[äÄöÖåÅa-zA-Z]", batch["text"]))
    return batch


def _count_numbers(batch):
    batch["number_len"] = len(re.findall(r"[0-9]", batch["text"]))
    return batch


def _count_upper(batch):
    batch["upper_len"] = len(re.findall(r"[ÄÖÅA-Z]", batch["text"]))
    return batch


def _count_str_len(batch):
    batch["total_len"] = len(batch["text"])
    return batch


def _predict_lang(batch):
    pred = fasttext_model.predict(batch["text"])
    batch["predicted_lang"] = pred[0][0]
    batch["predicted_lang_percentage"] = float(pred[1][0])
    return batch


def _calculate_alphabet_ratio(batch):
    batch["alphabet_ratio"] = int(batch["alphabet_len"]) / int(batch["total_len"])
    return batch


def _calculate_number_ratio(batch):
    batch["number_ratio"] = int(batch["number_len"]) / int(batch["total_len"])
    return batch


def _calculate_upper_ratio(batch):
    batch["upper_ratio"] = int(batch["upper_len"]) / int(batch["total_len"])
    return batch