"""Признаки длины и структуры реплики."""

from __future__ import annotations

import pandas as pd

from .base import (
    as_list,
    finite,
    mean,
    median,
    safe_div,
    sentence_word_counts,
    std,
    word_lengths,
    word_tokens,
)


def extract(row: pd.Series) -> dict[str, float]:
    tokens = as_list(row, "tokens")
    words = word_tokens(tokens)
    lengths = word_lengths(words)
    sentence_lengths = sentence_word_counts(row)
    n_sentences = max(len(sentence_lengths), 1)
    text = str(row.get("text", ""))

    return {
        "len_tokens": float(len(tokens)),
        "len_words": float(len(words)),
        "len_chars": float(len(text)),
        "len_sentences": float(n_sentences),
        "len_mean_sentence_words": finite(mean(sentence_lengths)),
        "len_std_sentence_words": finite(std(sentence_lengths)),
        "len_min_sentence_words": float(min(sentence_lengths)) if sentence_lengths else 0.0,
        "len_max_sentence_words": float(max(sentence_lengths)) if sentence_lengths else 0.0,
        "len_median_sentence_words": finite(median(sentence_lengths)),
        "len_pct_sentences_lt5": safe_div(sum(1 for value in sentence_lengths if value < 5), n_sentences),
        "len_pct_sentences_gt20": safe_div(sum(1 for value in sentence_lengths if value > 20), n_sentences),
        "len_pct_one_word_sentences": safe_div(sum(1 for value in sentence_lengths if value == 1), n_sentences),
        "len_mean_word_chars": finite(mean(lengths)),
        "len_std_word_chars": finite(std(lengths)),
        "len_median_word_chars": finite(median(lengths)),
        "len_pct_words_ge7": safe_div(sum(1 for value in lengths if value >= 7), len(lengths)),
        "len_pct_words_ge10": safe_div(sum(1 for value in lengths if value >= 10), len(lengths)),
        "len_pct_words_ge13": safe_div(sum(1 for value in lengths if value >= 13), len(lengths)),
        "len_pct_single_letter_words": safe_div(sum(1 for value in lengths if value == 1), len(lengths)),
    }