"""Safe, conservative Persian text normalization for human-authored fields."""

import re
from functools import lru_cache

from hazm import Normalizer


# Hazm's spacing rules are intended for prose and can add spaces inside URLs and
# technical identifiers.  Temporarily replace those spans before normalization.
_PROTECTED_SPAN = re.compile(
    r"https?://\S+|www\.\S+|[\w.+-]+@[\w.-]+\.\w+|"
    r"(?<![\w\u0600-\u06ff])[A-Za-z0-9][A-Za-z0-9._:/?#%+\\=@-]*"
)
_TOKEN_PREFIX = "HAZMPROTECTEDTOKEN"


@lru_cache(maxsize=1)
def _normalizer():
    return Normalizer(
        remove_diacritics=False,
        remove_specials_chars=False,
        decrease_repeated_chars=False,
        persian_numbers=False,
    )


def _alpha_index(index):
    """Return an ASCII-letter-only stable suffix (A, B, ..., AA)."""
    result = ""
    while True:
        index, remainder = divmod(index, 26)
        result = chr(65 + remainder) + result
        if index == 0:
            return result
        index -= 1


def normalize_persian_text(value, *, multiline=False):
    """Normalize Persian orthography without rewriting meaning or technical data.

    Multiline values retain paragraph boundaries. Empty/None values become an
    empty string, matching the project's non-null textual model fields.
    """
    if value is None:
        return ""
    text = str(value).replace("\r\n", "\n").replace("\r", "\n")
    protected = {}

    def protect(match):
        token = f"{_TOKEN_PREFIX}{_alpha_index(len(protected))}"
        protected[token] = match.group(0)
        return token

    text = _PROTECTED_SPAN.sub(protect, text)
    if multiline:
        normalized = "\n".join(
            _normalizer().normalize(line).strip() if line.strip() else ""
            for line in text.split("\n")
        ).strip()
    else:
        normalized = _normalizer().normalize(" ".join(text.splitlines())).strip()

    for token, original in protected.items():
        normalized = normalized.replace(token, original)
    return normalized