"""Word normalisation: produce display + grid forms with prefix stripping."""

from __future__ import annotations

import re
import sys
from dataclasses import dataclass

PREFIXES = {
    "mr", "mrs", "ms", "miss",
    "dr", "sir", "dame", "lord", "lady", "master",
    "captain", "capt", "cpt",
    "professor", "prof",
    "saint", "st",
}


@dataclass
class Normalised:
    display: str
    grid: str
    stripped_prefixes: list[str]
    skipped: bool = False
    warning: str | None = None


def _strip_prefix_tokens(tokens: list[str]) -> tuple[list[str], list[str]]:
    """Remove leading prefix tokens. Returns (stripped_prefixes, remaining_tokens)."""
    stripped: list[str] = []
    i = 0
    while i < len(tokens):
        bare = tokens[i].rstrip(".").lower()
        if bare in PREFIXES:
            stripped.append(tokens[i])
            i += 1
        else:
            break
    return stripped, tokens[i:]


def normalise(word: str) -> Normalised:
    display = word
    tokens = word.split()
    if not tokens:
        return Normalised(display=display, grid="", stripped_prefixes=[],
                          skipped=True, warning="empty word")

    stripped, remainder = _strip_prefix_tokens(tokens)

    if not remainder:
        # Word is *only* prefix tokens — keep raw form, warn.
        joined = "".join(tokens)
        grid = re.sub(r"[^A-Za-z0-9]", "", joined).upper()
        warning = f"word {word!r} is only prefix tokens; keeping as {grid}"
        print(f"[normaliser] warning: {warning}", file=sys.stderr)
        return Normalised(display=display, grid=grid, stripped_prefixes=[],
                          warning=warning)

    joined = "".join(remainder)
    grid = re.sub(r"[^A-Za-z0-9]", "", joined).upper()

    if not grid:
        warning = f"word {word!r} normalises to empty after stripping; skipping"
        print(f"[normaliser] warning: {warning}", file=sys.stderr)
        return Normalised(display=display, grid="", stripped_prefixes=stripped,
                          skipped=True, warning=warning)

    return Normalised(display=display, grid=grid, stripped_prefixes=stripped)


def normalise_all(words: list[str]) -> list[Normalised]:
    return [normalise(w) for w in words]