175 lines
7.8 KiB
Python
175 lines
7.8 KiB
Python
# core/summary.py
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import datetime
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import os
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from core.result import ComicResult
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_CORRUPT_PATTERNS = ("BadRarFile", "BadZipFile", "corrupto", "Failed to read")
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_BORDER = "═" * 42
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class SummaryCollector:
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def __init__(self):
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self._results: list[ComicResult] = []
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def add(self, result: ComicResult) -> None:
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self._results.append(result)
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def _is_corrupt(self, result: ComicResult) -> bool:
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all_errors = [e for s in result.steps for e in s.errors]
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return any(
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pattern in err
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for err in all_errors
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for pattern in _CORRUPT_PATTERNS
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)
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def render(self, _max=10) -> str:
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results = self._results
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total = len(results)
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if total == 0:
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return ""
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# Categorize
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errors = [r for r in results if not r.ok() or r.final_path is None]
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ok_results = [r for r in results if r.ok() and r.final_path is not None]
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modified = [r for r in ok_results if any(s.changed for s in r.steps)]
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warnings_only = [
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r for r in ok_results
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if not any(s.changed for s in r.steps) and r.has_issues()
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]
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no_changes = [
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r for r in ok_results
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if not any(s.changed for s in r.steps) and not r.has_issues()
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]
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corrupt = [r for r in errors if self._is_corrupt(r)]
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other_errors = [r for r in errors if not self._is_corrupt(r)]
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# Operation breakdown (among modified)
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def count_step(step_names: list[str]) -> int:
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return sum(
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1 for r in modified
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if any(s.step in step_names and s.changed for s in r.steps)
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)
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cleaned = count_step(["clean"])
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pages_normalized = count_step(["normalize_pages"])
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images_converted = count_step(["normalize_images", "convert_images"])
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format_converted = count_step(["convert"])
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case_normalized = count_step(["normalize_case", "normalize_case_outer"])
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lines = [
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_BORDER,
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" RESUMEN DEL PROCESAMIENTO",
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_BORDER,
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f" Total procesados : {total:>3}",
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f" Sin cambios : {len(no_changes):>3}",
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f" Modificados : {len(modified):>3}",
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]
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if modified:
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if cleaned:
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lines.append(f" · Limpiados : {cleaned:>3}")
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if pages_normalized:
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lines.append(f" · Páginas normalizadas : {pages_normalized:>3}")
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if images_converted:
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lines.append(f" · Imágenes convertidas : {images_converted:>3}")
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if format_converted:
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lines.append(f" · Formato convertido : {format_converted:>3}")
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if case_normalized:
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lines.append(f" · Case normalizado : {case_normalized:>3}")
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lines.append(f" Advertencias : {len(warnings_only):>3}")
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lines.append(f" Errores : {len(errors):>3}")
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if errors:
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lines.append(f" · Corruptos : {len(corrupt):>3}")
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lines.append(f" · Otros errores : {len(other_errors):>3}")
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lines.append(_BORDER)
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if corrupt:
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lines.append("")
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lines.append("Archivos corruptos:")
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for r in corrupt:
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lines.append(f" {r.original_path}")
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if other_errors:
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lines.append("")
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lines.append("Otros errores:")
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for r in other_errors:
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all_errs = [e for s in r.steps for e in s.errors]
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lines.append(f" {r.original_path} — {'; '.join(all_errs)}")
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warn_categories = self._warning_categories(results)
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if warn_categories:
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lines.append("")
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lines.append("Advertencias por categoría:")
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for label, entries in warn_categories:
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lines.append(f"\n {label} ({len(entries)}):")
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shown = entries[:_max] if _max is not None else entries
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for path, msg, annotation in shown:
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suffix = f" ({annotation})" if annotation else ""
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if msg:
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lines.append(f" {path} — {msg}{suffix}")
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else:
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lines.append(f" {path}{suffix}")
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if _max is not None and len(entries) > _max:
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lines.append(f" ... y {len(entries) - _max} más")
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return "\n".join(lines)
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def full_log(self) -> str:
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parts = [self.render(_max=None)]
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issues = [r for r in self._results if r.has_issues()]
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if issues:
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parts.append("")
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parts.append("")
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parts.append("Detalle por fichero:")
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parts.append(_BORDER)
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for r in issues:
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parts.append(r.full_report())
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parts.append("")
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return "\n".join(parts)
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def _warning_categories(self, results):
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categories = [
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("Extensión incorrecta", "validate", lambda w: "Extensión incorrecta" in w, ["convert"], "convertido"),
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("Basura detectada", "check_trash", lambda w: True, ["clean"], "limpiado"),
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("Ficheros extraños", "check_foreign", lambda w: True, ["clean"], "limpiado"),
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("Estructura anidada", "check_nested", lambda w: w.startswith("Imágenes en subdirectorio: "), ["clean"], "aplanado"),
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("Estructura compleja", "check_nested", lambda w: w.startswith("Múltiples subdirectorios"), [], None),
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("Numeración de páginas", "check_page_numbering", lambda w: True, ["normalize_pages"], "renumerado"),
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("Imágenes mezcladas", "check_image_extensions", lambda w: True, ["normalize_images", "convert_images"], "normalizado"),
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("Sin ComicInfo.xml", "check_comicinfo", lambda w: True, [], None),
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("Case de extensión", "check_extension_case", lambda w: True, ["normalize_case"], "normalizado"),
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]
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output = []
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for label, step_name, predicate, resolver_steps, fix_label in categories:
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entries = []
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for r in results:
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msgs = [
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w for s in r.steps
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if s.step == step_name
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for w in s.warnings
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if predicate(w)
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]
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if msgs:
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resolved = bool(resolver_steps) and any(
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s.step in resolver_steps and s.changed for s in r.steps
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)
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annotation = fix_label if resolved else ""
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if step_name == "check_comicinfo":
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entries.append((r.original_path, "", annotation))
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elif step_name == "check_trash":
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items = [w.removeprefix("Basura detectada: ") for w in msgs]
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entries.append((r.original_path, ", ".join(items), annotation))
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elif step_name == "check_foreign":
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items = [w.removeprefix("Fichero extraño: ") for w in msgs]
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entries.append((r.original_path, ", ".join(items), annotation))
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elif step_name == "check_nested":
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entries.append((r.original_path, msgs[0], annotation))
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else:
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entries.append((r.original_path, msgs[0], annotation))
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if entries:
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output.append((label, entries))
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return output
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