"""Вспомогательные функции для вычисления признаков."""

from __future__ import annotations

import math
import re
from collections import Counter
from typing import Iterable, Sequence

import numpy as np
import pandas as pd


def safe_div(numerator: float, denominator: float, default: float = 0.0) -> float:
    """Деление без исключения при нулевом знаменателе."""
    if denominator == 0:
        return default
    return float(numerator) / float(denominator)


def finite(value: float, default: float = 0.0) -> float:
    """Заменяет NaN и бесконечности на допустимое число."""
    try:
        result = float(value)
    except (TypeError, ValueError):
        return default
    return result if math.isfinite(result) else default


def as_list(row: pd.Series, column: str) -> list:
    value = row.get(column, [])
    if isinstance(value, list):
        return value
    if isinstance(value, tuple):
        return list(value)
    if value is None or (isinstance(value, float) and math.isnan(value)):
        return []
    return list(value)


def word_tokens(tokens: Sequence[str]) -> list[str]:
    """Токены, содержащие хотя бы одну букву или цифру."""
    return [token for token in tokens if re.search(r"[A-Za-z0-9]", token)]


def alphabetic_tokens(tokens: Sequence[str]) -> list[str]:
    return [token for token in tokens if re.search(r"[A-Za-z]", token)]


def lower_tokens(tokens: Sequence[str]) -> list[str]:
    return [token.lower() for token in tokens]


def sentence_word_counts(row: pd.Series) -> list[int]:
    sentences = as_list(row, "sentences")
    counts = [len(word_tokens(sentence)) for sentence in sentences]
    counts = [count for count in counts if count > 0]
    return counts or [len(word_tokens(as_list(row, "tokens")))]


def count_set(tokens: Iterable[str], vocabulary: set[str]) -> int:
    return sum(1 for token in tokens if token.lower() in vocabulary)


def rate_set(tokens: Sequence[str], vocabulary: set[str]) -> float:
    return safe_div(count_set(tokens, vocabulary), len(tokens))


def counter(tokens: Iterable[str]) -> Counter:
    return Counter(token.lower() for token in tokens)


def mean(values: Sequence[float]) -> float:
    return float(np.mean(values)) if values else 0.0


def std(values: Sequence[float]) -> float:
    return float(np.std(values, ddof=0)) if values else 0.0


def median(values: Sequence[float]) -> float:
    return float(np.median(values)) if values else 0.0


def percentile(values: Sequence[float], q: float) -> float:
    return float(np.percentile(values, q)) if values else 0.0


def word_lengths(tokens: Sequence[str]) -> list[int]:
    lengths: list[int] = []
    for token in tokens:
        letters = re.sub(r"[^A-Za-z]", "", token)
        if letters:
            lengths.append(len(letters))
    return lengths


def strip_punctuation(token: str) -> str:
    return re.sub(r"^[^A-Za-z0-9]+|[^A-Za-z0-9]+$", "", token)