#!/usr/bin/env python
# Copyright 2020 Kanari AI (Amir Hussein)
# Apache 2.0  (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import os
import pdb
import re
import string
import sys

import numpy as np
import pandas as pd
import pyarabic.number as number
from pyarabic import araby

_unicode = "\u0622\u0624\u0626\u0628\u062a\u062c\u06af\u062e\u0630\u0632\u0634\u0636\u0638\u063a\u0640\u0642\u0644\u0646\u0648\u064a\u064c\u064e\u0650\u0652\u0670\u067e\u0686\u0621\u0623\u0625\u06a4\u0627\u0629\u062b\u062d\u062f\u0631\u0633\u0635\u0637\u0639\u0641\u0643\u0645\u0647\u0649\u064b\u064d\u064f\u0651\u0671"
_buckwalter = "|&}btjGx*z$DZg_qlnwyNaio`PJ'><VApvHdrsSTEfkmhYFKu~{"
_backwardMap = {ord(b): a for a, b in zip(_buckwalter, _unicode)}


# def number2text(anumber):
#     """
#     Convert number to arabic words, for example convert 25 --> خمسة و عشرون
#     Example:
#         >>> number2text(523)
#         خمسمئة وثلاث وعشرون
#     @param anumber: input number
#     @type anumber: int
#     @return: number words
#     @rtype: unicode
#     """
#     # test if the given type is numeric(float or int
#     # if ok, convert it to string
#     if type(anumber) is int or type(anumber) is float:
#         anumber = str(anumber)
#     # if the given type is str/unicode, test if it's a valid number
#     elif type(anumber) is str or type(anumber) is unicode:
#         try:
#             a = float(anumber);
#         except ValueError:
#             return u"صفر"
#     # if the given number not a valid return 0
#     else:
#         return u"صفر"
#     arbn = number.ArNumbers()
#     arbn.set_feminine(2)
#     return arbn.int2str(anumber)

#     return total


def fromBuckWalter(s):
    return s.translate(_backwardMap)


def read_tsv(data_file):
    text_data = list()
    infile = open(data_file, encoding="utf-8")
    for line in infile:
        if not line.strip():
            continue
        text = line.split("\t")
        text_data.append(text)

    return text_data


words_to_remove = [
    "#غير_واضح",
    "#تلعثم",
    "#آ",
    "#أ",
    "#ال",
    "#بال",
    "#وال",
    " #وب",
    "###تداخل",
    "FRN",
    "RFN",
    " #سي",
    "#يي",
    "#هـ",
    "#لل",
    "#بم",
    "#الش",
    "#آآ",
    " #يت",
    "#وو",
    "#ومش",
    "#ول",
    "#وسي",
    "#غير_معروف",
    "#العا",
    "#مطا",
    "#محم",
    " #ماث",
    "#متطو",
    " #نشا",
    "#أأ",
    "#آآآ",
    " #استج",
]


def normalizeArabic(text):
    # text = re.sub("[إأٱآا]", "ا", text)
    # text = re.sub("ى", "ي", text)
    # text = re.sub("ة", "ه", text)
    # text = re.sub("ئ", "ء", text)
    # text = re.sub("ؤ", "ء", text)
    text = re.sub(r"(ه){2,}", "ههه", text)
    text = re.sub(r"(أ){2,}", "ا", text)
    text = re.sub(r"(ا){2,}", "ا", text)
    text = re.sub(r"(آ){2,}", "ا", text)
    text = re.sub(r"(ص){2,}", "ص", text)
    text = re.sub(r"(و){2,}", "و", text)
    return text


def remove_special_words(text):
    # remove special words from the transcription text
    for word in words_to_remove:
        if word in text:
            text = text.replace(word, "")
    return text


def remove_hashes(text):
    return re.sub(r"#?", "", text)


def remove_english_characters(text):
    return re.sub(r"[^\u0600-\u06FF0-9\s]+", "", text)


def remove_diacritics(text):
    return re.sub(r"[\u064B-\u0652\u06D4\u0670\u0674\u06D5-\u06ED]+", "", text)


def remove_punctuations(text):
    """This function  removes all punctuations except the verbatim"""

    arabic_punctuations = """﴿﴾‘`÷×؛<>_()*&^%][ـ،/:"؟.,'{}~¦+|!”…“–ـ"""
    english_punctuations = string.punctuation
    all_punctuations = set(arabic_punctuations + english_punctuations) - {
        "@",
        "%",
        ".",
    }  # remove all non verbatim punctuations

    for p in all_punctuations:
        if p in text:
            text = text.replace(p, "")
    text = re.sub(
        "\s+\.", "", text
    )  # keep only the "." that is part of a word: marsad@aljazeera.net . => marsad@aljazeera.net
    return text


def remove_extra_space(text):
    text = text.lower()
    text = re.sub("\s+", " ", text)
    text = re.sub("\s+\.\s+", ".", text)
    return text


def remove_dot(text):

    words = text.split()
    res = []
    for word in words:
        if word.replace(
            ".", ""
        ).isnumeric():  # remove the dot if it is not part of a number
            res.append(word)

        else:
            word = re.sub("\s+\.", "", word)
            res.append(word)

    return " ".join(res)


def east_to_west_num(text):
    eastern_to_western = {
        "٠": "0",
        "١": "1",
        "٢": "2",
        "٣": "3",
        "٤": "4",
        "٥": "5",
        "٦": "6",
        "٧": "7",
        "٨": "8",
        "٩": "9",
        "٪": "%",
        "_": " ",
        "ڤ": "ف",
        "|": " ",
    }
    trans_string = str.maketrans(eastern_to_western)
    return text.translate(trans_string)


def remove_repeating_char(text):
    return re.sub(r"(.)\1+", r"\1", text)


def remove_single_char_word(text):
    """
    Remove single character word from text
    Example: I am in a a home for two years => am in home for two years
    Args:
            text (str): text
    Returns:
            (str): text with single char removed
    """
    words = text.split()

    filter_words = [word for word in words if len(word) > 1 or word.isnumeric()]
    return " ".join(filter_words)


def seperate_english_characters(text):
    text = text.lower()
    res = re.findall(r"[a-z]+", text)  # search for english
    for match in res:
        if match not in {".", " "}:
            text = re.sub(match, " " + match + " ", text)
            text = re.sub("\s+", " ", text)
    return text


def digit2num(text, dig2num=False):

    """This function is used to clean numbers"""

    # search for numbers with spaces
    # 100 . 000 => 100.000

    res = re.search("[0-9]+\s\.\s[0-9]+", text)
    if res != None:
        t = re.sub(r"\s", "", res[0])
        text = re.sub(res[0], t, text)

    # seperate numbers glued with words
    # 3أشهر => 3 أشهر
    # من10الى15 => من 10 الى 15
    # pdb.set_trace()
    res = re.findall(r"[^\u0600-\u06FF\%\@a-z]+", text)  # search for digits
    for match in res:
        if match not in {".", " "}:
            text = re.sub(match, " " + match + " ", text)
            text = re.sub("\s+", " ", text)

    # transliterate numbers to digits
    # 13 =>  ثلاثة عشر

    if dig2num == True:
        words = araby.tokenize(text)
        for i in range(len(words)):
            digit = re.sub(r"[\u0600-\u06FF]+", "", words[i])
            if digit.isnumeric():
                sub_word = re.sub(r"[^\u0600-\u06FF]+", "", words[i])
                if number.number2text(digit) != "صفر":
                    words[i] = sub_word + number.number2text(digit)
            else:
                pass

        return " ".join(words)
    else:
        return text


def data_cleaning(text):
    # text = remove_special_words(text)
    text = remove_punctuations(text)
    text = remove_single_char_word(text)
    text = remove_diacritics(text)
    text = seperate_english_characters(text)
    text = remove_extra_space(text)
    text = remove_dot(text)
    text = east_to_west_num(text)
    text = digit2num(text, True)
    text = normalizeArabic(text)
    # text = re.sub(r'#\w{1,2}\b', '', text) #  text = re.sub(r'#\w{1,3}\b', '', text)
    # text = remove_hashes(text)
    # text = normalizeArabic(text)
    return text


def main():
    input_file = sys.argv[1]  # input transcription file with format <id> <text>
    to_BW = str(sys.argv[2])  # transform to BW True|False
    output_file = sys.argv[3]  # output file name
    data = read_tsv(input_file)
    new_data = []
    for i in range(len(data)):

        tokens = data[i][0].split()

        tokens[1:] = data_cleaning(" ".join(tokens[1:])).split()
        # tokens = data_cleaning(" ".join(tokens)).split()
        if to_BW == "True":
            for i in range(len(tokens[1:])):
                tokens[i + 1] = fromBuckWalter(tokens[i + 1])
            new_data.append(" ".join(tokens))
        else:
            new_data.append(" ".join(tokens))

    df = pd.DataFrame(data=new_data)
    df.to_csv(output_file, sep="\n", header=False, index=False)


if __name__ == "__main__":
    main()