from functools import reduce
from typing import Dict, List

import pandas as pd
from tqdm import tqdm

from src.feature_extractors.base_extractor import BaseExtractor
from src.feature_extractors.text_statistics_utils import (
    count_how_many_words_are_repeating, count_misspelled_words,
    count_punctuation, count_words, preprocess_test)
from src.spell_checker import SmartSpellChecker


class HandcraftedTextFeatureExtractor(BaseExtractor):
    def __init__(self, spellcheck: SmartSpellChecker):
        self._spellcheck = spellcheck

    def _generate_features(self, raw_text: str) -> Dict[str, int]:
        preprocessed_text = preprocess_test(raw_text)
        cleaned_text = self._spellcheck.correct_text(preprocessed_text)

        features: List[Dict] = [
            count_punctuation(raw_text),
            count_misspelled_words(preprocessed_text, self._spellcheck),
            count_words(cleaned_text),
            count_how_many_words_are_repeating(cleaned_text)
        ]

        return reduce(lambda x, y: {**x, **y}, features)

    def generate_features(self, data: pd.Series) -> pd.DataFrame:
        features = [self._generate_features(text) for text in tqdm(data, desc="Gen. handcraft text features...")]
        return pd.DataFrame(features, index=data.index)