# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
from typing import List

from .char_convert import tranditional_to_simplified
from .chronology import (
    RE_DATE,
    RE_DATE2,
    RE_TIME,
    RE_TIME_RANGE,
    replace_date,
    replace_date2,
    replace_time,
)
from .constants import F2H_ASCII_LETTERS, F2H_DIGITS, F2H_SPACE
from .num import (
    RE_DECIMAL_NUM,
    RE_DEFAULT_NUM,
    RE_FRAC,
    RE_INTEGER,
    RE_NUMBER,
    RE_PERCENTAGE,
    RE_POSITIVE_QUANTIFIERS,
    RE_RANGE,
    replace_default_num,
    replace_frac,
    replace_negative_num,
    replace_number,
    replace_percentage,
    replace_positive_quantifier,
    replace_range,
)
from .phonecode import (
    RE_MOBILE_PHONE,
    RE_NATIONAL_UNIFORM_NUMBER,
    RE_TELEPHONE,
    replace_mobile,
    replace_phone,
)
from .quantifier import RE_TEMPERATURE, replace_measure, replace_temperature


class TextNormalizer:
    def __init__(self):
        self.SENTENCE_SPLITOR = re.compile(r"([：、，；。？！,;?!][”’]?)")

    def _split(self, text: str, lang="zh") -> List[str]:
        """Split long text into sentences with sentence-splitting punctuations.
        Args:
            text (str): The input text.
        Returns:
            List[str]: Sentences.
        """
        # Only for pure Chinese here
        if lang == "zh":
            text = text.replace(" ", "")
            # 过滤掉特殊字符
            text = re.sub(r"[——《》【】<=>{}()（）#&@“”^_|…\\]", "", text)
        text = self.SENTENCE_SPLITOR.sub(r"\1\n", text)
        text = text.strip()
        sentences = [sentence.strip() for sentence in re.split(r"\n+", text)]
        return sentences

    def _post_replace(self, sentence: str) -> str:
        # sentence = sentence.replace('/', '每')
        # sentence = sentence.replace('~', '至')
        # sentence = sentence.replace('～', '至')
        sentence = sentence.replace("①", "一")
        sentence = sentence.replace("②", "二")
        sentence = sentence.replace("③", "三")
        sentence = sentence.replace("④", "四")
        sentence = sentence.replace("⑤", "五")
        sentence = sentence.replace("⑥", "六")
        sentence = sentence.replace("⑦", "七")
        sentence = sentence.replace("⑧", "八")
        sentence = sentence.replace("⑨", "九")
        sentence = sentence.replace("⑩", "十")
        sentence = sentence.replace("α", "阿尔法")
        sentence = sentence.replace("β", "贝塔")
        sentence = sentence.replace("γ", "伽玛").replace("Γ", "伽玛")
        sentence = sentence.replace("δ", "德尔塔").replace("Δ", "德尔塔")
        sentence = sentence.replace("ε", "艾普西龙")
        sentence = sentence.replace("ζ", "捷塔")
        sentence = sentence.replace("η", "依塔")
        sentence = sentence.replace("θ", "西塔").replace("Θ", "西塔")
        sentence = sentence.replace("ι", "艾欧塔")
        sentence = sentence.replace("κ", "喀帕")
        sentence = sentence.replace("λ", "拉姆达").replace("Λ", "拉姆达")
        sentence = sentence.replace("μ", "缪")
        sentence = sentence.replace("ν", "拗")
        sentence = sentence.replace("ξ", "克西").replace("Ξ", "克西")
        sentence = sentence.replace("ο", "欧米克伦")
        sentence = sentence.replace("π", "派").replace("Π", "派")
        sentence = sentence.replace("ρ", "肉")
        sentence = (
            sentence.replace("ς", "西格玛")
            .replace("Σ", "西格玛")
            .replace("σ", "西格玛")
        )
        sentence = sentence.replace("τ", "套")
        sentence = sentence.replace("υ", "宇普西龙")
        sentence = sentence.replace("φ", "服艾").replace("Φ", "服艾")
        sentence = sentence.replace("χ", "器")
        sentence = sentence.replace("ψ", "普赛").replace("Ψ", "普赛")
        sentence = sentence.replace("ω", "欧米伽").replace("Ω", "欧米伽")
        # re filter special characters, have one more character "-" than line 68
        # sentence = re.sub(r'[-——《》【】<=>{}()（）#&@“”^_|…\\]', '', sentence)
        return sentence

    def normalize_sentence(self, sentence: str) -> str:
        # basic character conversions
        sentence = tranditional_to_simplified(sentence)
        sentence = (
            sentence.translate(F2H_ASCII_LETTERS)
            .translate(F2H_DIGITS)
            .translate(F2H_SPACE)
        )

        # number related NSW verbalization
        sentence = RE_DATE.sub(replace_date, sentence)
        sentence = RE_DATE2.sub(replace_date2, sentence)

        # range first
        sentence = RE_TIME_RANGE.sub(replace_time, sentence)
        sentence = RE_TIME.sub(replace_time, sentence)

        sentence = RE_TEMPERATURE.sub(replace_temperature, sentence)
        sentence = replace_measure(sentence)
        sentence = RE_FRAC.sub(replace_frac, sentence)
        sentence = RE_PERCENTAGE.sub(replace_percentage, sentence)
        sentence = RE_MOBILE_PHONE.sub(replace_mobile, sentence)

        sentence = RE_TELEPHONE.sub(replace_phone, sentence)
        sentence = RE_NATIONAL_UNIFORM_NUMBER.sub(replace_phone, sentence)

        sentence = RE_RANGE.sub(replace_range, sentence)
        sentence = RE_INTEGER.sub(replace_negative_num, sentence)
        sentence = RE_DECIMAL_NUM.sub(replace_number, sentence)
        sentence = RE_POSITIVE_QUANTIFIERS.sub(replace_positive_quantifier, sentence)
        sentence = RE_DEFAULT_NUM.sub(replace_default_num, sentence)
        sentence = RE_NUMBER.sub(replace_number, sentence)
        sentence = self._post_replace(sentence)

        return sentence

    def normalize(self, text: str, lang="") -> List[str]:
        sentences = self._split(text, lang)
        sentences = [self.normalize_sentence(sent) for sent in sentences]
        return sentences