import math
import re
from collections import Counter

import numpy as np


def shannon_entropy(s: str) -> float:
    if not s:
        return 0.0
    counts = Counter(s)
    length = len(s)
    return -sum((c / length) * math.log2(c / length) for c in counts.values())


def special_char_ratio(s: str) -> float:
    if not s:
        return 0.0
    specials = sum(1 for ch in s if not ch.isalnum() and not ch.isspace())
    return specials / len(s)


def digit_ratio(s: str) -> float:
    if not s:
        return 0.0
    return sum(ch.isdigit() for ch in s) / len(s)


def keyword_hit_count(s: str, keywords) -> int:
    low = s.lower()
    return sum(1 for kw in keywords if kw in low)


def handcrafted_feature_matrix(texts, keywords):
    rows = []
    for t in texts:
        rows.append([
            len(t),
            shannon_entropy(t),
            special_char_ratio(t),
            digit_ratio(t),
            keyword_hit_count(t, keywords),
        ])
    return np.array(rows, dtype=float)


FEATURE_NAMES = ["length", "entropy", "special_char_ratio", "digit_ratio", "keyword_hits"]