# core/summary.py

from core.result import ComicResult

_CORRUPT_PATTERNS = ("BadRarFile", "BadZipFile", "corrupto", "Failed to read")
_BORDER = "═" * 42


class SummaryCollector:
    def __init__(self):
        self._results: list[ComicResult] = []

    def add(self, result: ComicResult) -> None:
        self._results.append(result)

    def _is_corrupt(self, result: ComicResult) -> bool:
        all_errors = [e for s in result.steps for e in s.errors]
        return any(
            pattern in err
            for err in all_errors
            for pattern in _CORRUPT_PATTERNS
        )

    def render(self) -> str:
        results = self._results
        total = len(results)
        if total == 0:
            return ""

        # Categorize
        errors = [r for r in results if not r.ok() or r.final_path is None]
        ok_results = [r for r in results if r.ok() and r.final_path is not None]

        modified = [r for r in ok_results if any(s.changed for s in r.steps)]
        warnings_only = [
            r for r in ok_results
            if not any(s.changed for s in r.steps) and r.has_issues()
        ]
        no_changes = [
            r for r in ok_results
            if not any(s.changed for s in r.steps) and not r.has_issues()
        ]

        corrupt = [r for r in errors if self._is_corrupt(r)]
        other_errors = [r for r in errors if not self._is_corrupt(r)]

        # Operation breakdown (among modified)
        def count_step(step_names: list[str]) -> int:
            return sum(
                1 for r in modified
                if any(s.step in step_names and s.changed for s in r.steps)
            )

        cleaned = count_step(["clean"])
        pages_normalized = count_step(["normalize_pages"])
        images_converted = count_step(["normalize_images", "convert_images"])
        format_converted = count_step(["convert"])

        lines = [
            _BORDER,
            "  RESUMEN DEL PROCESAMIENTO",
            _BORDER,
            f"  Total procesados : {total:>3}",
            f"  Sin cambios      : {len(no_changes):>3}",
            f"  Modificados      : {len(modified):>3}",
        ]
        if modified:
            if cleaned:
                lines.append(f"    · Limpiados            : {cleaned:>3}")
            if pages_normalized:
                lines.append(f"    · Páginas normalizadas : {pages_normalized:>3}")
            if images_converted:
                lines.append(f"    · Imágenes convertidas : {images_converted:>3}")
            if format_converted:
                lines.append(f"    · Formato convertido   : {format_converted:>3}")
        lines.append(f"  Advertencias     : {len(warnings_only):>3}")
        lines.append(f"  Errores          : {len(errors):>3}")
        if errors:
            lines.append(f"    · Corruptos            : {len(corrupt):>3}")
            lines.append(f"    · Otros errores        : {len(other_errors):>3}")
        lines.append(_BORDER)

        if corrupt:
            lines.append("")
            lines.append("Archivos corruptos:")
            for r in corrupt:
                lines.append(f"  {r.original_path}")

        if other_errors:
            lines.append("")
            lines.append("Otros errores:")
            for r in other_errors:
                all_errs = [e for s in r.steps for e in s.errors]
                lines.append(f"  {r.original_path} — {'; '.join(all_errs)}")

        return "\n".join(lines)