"""
preprocessing.py  –  Clean & preprocess text for sentiment analysis.
Only contains utility functions; no Colab/notebook code.
"""
import re
import html as html_lib

from bs4 import BeautifulSoup

try:
    from Sastrawi.Stemmer.StemmerFactory import StemmerFactory
    from Sastrawi.StopWordRemover.StopWordRemoverFactory import StopWordRemoverFactory
    _sastrawi_available = True
except ImportError:
    _sastrawi_available = False

try:
    from stop_words import get_stop_words
    _stopwords_id = get_stop_words('indonesian')
except Exception:
    _stopwords_id = []

# ── Stopwords ──────────────────────────────────────────────────────────────────
_sastrawi_stopwords: list = []
_stemmer = None

if _sastrawi_available:
    _stemmer = StemmerFactory().create_stemmer()
    _sastrawi_stopwords = StopWordRemoverFactory().get_stop_words()

_ADDITIONAL_STOPWORDS = [
    'yg','ga','gak','nggak','aja','saja','nya','oke','ok','bgt','jg','utk',
    'deh','sih','kok','dong','udah','sdh','blm','bgmn','dgn','lgi',
    'ya','lbh','digunakan','semangat','dah','sangat','penting',
    'lancar','cepat','senang','makasih','bermanfaat','keren','baik',
    'terimakasih','bagus','semoga','aplikasi','transaksi','banget','pakai',
    'hp','tolong','gimana','iya','jadi','ambil','buka','butuh','masuk',
    'baru','jelas','yuk','mohon','punya','cara','hari','kota','berita',
    # HTML attributes
    'class','id','span','div','href','src','style','alt','aria','role',
    'tabindex','button','label','img','input','placeholder','form',
    'field','hidden','value','by','link','tags',
]

_NOISE_STOPWORDS = [
    'xd','xyri','yu','uobl','ypdohk','xt','pz','lziwak',
    'rp','xdj','xggy','xjbqb','xstzfhl','hfl','xat',
    'qhh','dhg','cr','tdsg','ct','etr','nq','oe','ejq','psk',
    'hl','hd','sy','amp','fbf',
]

_SINGLE_LETTERS = set('abcdefghijklmnopqrstuvwxyz')

FINAL_STOPWORDS: set = set(
    _stopwords_id + _sastrawi_stopwords + _ADDITIONAL_STOPWORDS + _NOISE_STOPWORDS
) | _SINGLE_LETTERS


# ── Individual text cleaners ───────────────────────────────────────────────────

_AUTHOR_COMMENT_PATTERN = re.compile(r"author\b.*?\bcomment", flags=re.IGNORECASE|re.DOTALL)

def clean_html(text: str) -> str:
    """Strip HTML tags and unescape HTML entities."""
    if not text:
        return ""
    try:
        soup = BeautifulSoup(str(text), "html.parser")
        for tag in soup(["script", "style"]):
            tag.decompose()
        cleaned = soup.get_text(separator=" ")
    except Exception:
        cleaned = str(text)
    cleaned = html_lib.unescape(cleaned)
    cleaned = re.sub(r"\s+", " ", cleaned).strip()
    return cleaned


def clean_text(text: str) -> str:
    """Basic single-string cleaner: lowercase, remove URLs, non-alpha chars."""
    if not text:
        return ""
    text = str(text).lower()
    text = _AUTHOR_COMMENT_PATTERN.sub("", text)
    text = re.sub(r'http\S+|www\S+|https\S+', '', text)
    text = re.sub(r'[^a-zA-Z0-9\s]', ' ', text)
    text = re.sub(r'\s+', ' ', text).strip()
    return text


def _preprocess_single(text: str) -> str:
    """Full pipeline for one text string."""
    # 1. Strip HTML
    text = clean_html(text)
    # 2. Lowercase + remove URLs/non-alpha
    text = clean_text(text)
    # 3. Stem (Sastrawi)
    if _stemmer:
        text = _stemmer.stem(text)
    # 4. Remove stopwords & noise
    tokens = [
        w for w in text.split()
        if w not in FINAL_STOPWORDS and len(w) > 1
    ]
    # 5. Keep only tokens with at least one letter
    tokens = [t for t in tokens if re.search(r'[a-z]', t)]
    return " ".join(tokens).strip()


# ── Public API ─────────────────────────────────────────────────────────────────

def preprocess_text(texts) -> list:
    """
    Accept either a single string or a list of strings.
    Returns a list of cleaned strings.
    """
    if isinstance(texts, str):
        texts = [texts]
    return [_preprocess_single(t) for t in texts if isinstance(t, str)]