"""Метрики читаемости.

Формулы адаптированы для коротких разговорных реплик, поэтому значения
следует рассматривать как относительные признаки, а не как точные оценки
сложности текста. Число слогов вычисляется эвристически.
"""

from __future__ import annotations

import re

import pandas as pd

from .base import as_list, finite, safe_div, sentence_word_counts, word_tokens


def count_syllables(word: str) -> int:
    """Эвристическая оценка числа слогов в английском слове."""
    word = re.sub(r"[^a-z]", "", word.lower())
    if not word:
        return 0
    if len(word) <= 3:
        return 1
    if word.endswith("e") and not word.endswith("le"):
        word = word[:-1]
    groups = re.findall(r"[aeiouy]+", word)
    return max(len(groups), 1)


def extract(row: pd.Series) -> dict[str, float]:
    tokens = word_tokens(as_list(row, "tokens"))
    words = [re.sub(r"[^A-Za-z]", "", token).lower() for token in tokens]
    words = [word for word in words if word]
    n_words = max(len(words), 1)
    sentence_lengths = sentence_word_counts(row)
    n_sentences = max(len(sentence_lengths), 1)
    syllables = [count_syllables(word) for word in words]
    n_syllables = sum(syllables)
    polysyllables = sum(1 for value in syllables if value >= 3)
    n_letters = sum(len(word) for word in words)

    words_per_sentence = safe_div(n_words, n_sentences)
    syllables_per_word = safe_div(n_syllables, n_words)
    polysyllable_rate = safe_div(polysyllables, n_words)
    letters_per_word = safe_div(n_letters, n_words)

    flesch = 206.835 - 1.015 * words_per_sentence - 84.6 * syllables_per_word
    fk_grade = 0.39 * words_per_sentence + 11.8 * syllables_per_word - 15.59
    gunning_fog = 0.4 * (words_per_sentence + 100.0 * polysyllable_rate)
    smog = 1.0430 * (30.0 * safe_div(polysyllables, n_sentences)) ** 0.5 + 3.1291
    coleman_liau = 0.0588 * (letters_per_word * 100.0) - 0.296 * (
        safe_div(n_sentences, n_words) * 100.0
    ) - 15.8
    ari = 4.71 * letters_per_word + 0.5 * words_per_sentence - 21.43

    return {
        "read_syllables_per_word": finite(syllables_per_word),
        "read_polysyllable_rate": finite(polysyllable_rate),
        "read_flesch": finite(flesch),
        "read_fk_grade": finite(fk_grade),
        "read_gunning_fog": finite(gunning_fog),
        "read_smog": finite(smog),
        "read_coleman_liau": finite(coleman_liau),
        "read_ari": finite(ari),
        "read_words_per_sentence": finite(words_per_sentence),
    }