from __future__ import annotations
from typing import List
from dataclasses import dataclass
from fuzzywuzzy import fuzz


CONF_THRESHOLD = 60
# word predictions with lower confidence will be filtered out


@dataclass
class PredictedWord:
    __slots__ = 'confidence', 'text'
    confidence: int
    text: str


class PredictedFrame:
    index: int  # 0-based index of the frame
    words: List[PredictedWord]
    confidence: int  # total confidence of all words
    text: str

    def __init__(self, index, pred_data: str):
        self.index = index
        self.words = []

        block = 0  # keep track of line breaks

        for l in pred_data.splitlines()[1:]:
            word_data = l.split()
            if len(word_data) < 12:
                # no word is predicted
                continue
            _, _, block_num, *_, conf, text = word_data
            block_num, conf = int(block_num), int(conf)

            # handle line breaks
            if block < block_num:
                block = block_num
                if self.words and self.words[-1].text != '\n':
                    self.words.append(PredictedWord(0, '\n'))

            if conf >= CONF_THRESHOLD:
                self.words.append(PredictedWord(conf, text))

        self.confidence = sum(word.confidence for word in self.words)

        self.text = ' '.join(word.text for word in self.words)
        # remove chars that are obviously ocr errors
        translate_table = {ord(c): None for c in '<>{};`@#$%^*_=\\'}
        translate_table[ord('|')] = 'I'
        self.text = self.text.translate(translate_table).strip()

    def is_similar_to(self, other: PredictedFrame, threshold=70) -> bool:
        return fuzz.partial_ratio(self.text, other.text) >= threshold


class PredictedSubtitle:
    frames: List[PredictedFrame]

    def __init__(self, frames: List[PredictedFrame]):
        self.frames = [f for f in frames if f.confidence > 0]

        if self.frames:
            conf_max = max(f.confidence for f in self.frames)
            self.text = next(f.text for f in self.frames 
                                    if f.confidence == conf_max)
        else:
            self.text = ''

    @property
    def index_start(self) -> int:
        if self.frames:
            return self.frames[0].index
        return 0

    @property
    def index_end(self) -> int:
        if self.frames:
            return self.frames[-1].index
        return 0

    def is_similar_to(self, other: PredictedSubtitle, threshold=70) -> bool:
        return fuzz.partial_ratio(self.text, other.text) >= threshold

    def __repr__(self):
        return '{} - {}. {}'.format(self.index_start, self.index_end, self.text)