python / python/cpython

Types with `mro()` unconditionally disables type attribute cache, causing performance regression for compatible MRO implementations, such as Zope

Ouverte
#156,096 1 commentaire 0 réactions 0 personnes assignées Voir sur GitHub

Personne n'a encore pris cette issue.

type-bug
Langage dominant
Python
Étoiles
77.2k
Forks
36k
Métriques de merge des PR
Métriques de PR en attente

Description

Bug report

Bug description:

Since https://github.com/python/cpython/issues/127773 / https://github.com/python/cpython/pull/127924, any type whose metaclass defines a custom mro() method has its type attribute cache permanently disabled. This was made initially to fix a problem with metaclasses defining mro() to inject new bases that are not in the class bases.

This affects Zope's ExtensionClass, used as base class for most classes the Zope ecosystem. This package has 5000 daily downloads on pypi ( https://pypistats.org/packages/extensionclass ). ExtensionClass defines a custom mro(), but only to reorganizes bases that are already bases of the class, which is different from the scenario from the issue and it looks like a case where the cache could still be used.

Compared to python3.11, this seems to causes a ~3x performance regression for attribute lookups on all zope classes:

$ uv run --python=3.11 --with Zope python -m timeit -s 'import OFS.Folder; f = OFS.Folder.Folder("f")' 'f.getId'
2000000 loops, best of 5: 116 nsec per loop
$ uv run --python=3.14 --with Zope python -m timeit -s 'import OFS.Folder; f = OFS.Folder.Folder("f")' 'f.getId'
500000 loops, best of 5: 399 nsec per loop

it's hard to tell how much this affect applications, this is just a micro benchmark, but we are also observing that running ERP5 test suites (a complex application based on zope) is slower on python3.13 than it was on python3.11.

Analysis

In type_mro_modified(), the check has_custom_mro(type) unconditionally jumps to clear:

https://github.com/python/cpython/blob/af49df919dafc3767ae956767dce0482f9cd6d4e/Objects/typeobject.c#L1261-L1262

which sets tp_versions_used = _Py_ATTR_CACHE_UNUSED, whenever the metaclass overrides mro():

https://github.com/python/cpython/blob/af49df919dafc3767ae956767dce0482f9cd6d4e/Objects/typeobject.c#L1279-L1283

This was introduced to fix https://github.com/python/cpython/issues/127773, where a custom mro() that injects a class not in tp_bases (e.g. Base) causes stale cache entries because PyType_Modified() only propagates through tp_subclasses, not through MRO-only relationships.

Although these are not much relevant here, ExtensionClass's mro is implemented in C as _ExtensionClass.c:569-626 and also has an equivalent pure-python implementation in ExtensionClass.__init__.py:181-200.

Suggested fix

Check whether the custom MRO actually contains non-base entries before disabling the cache. This requires an is_superclass() helper that walks tp_bases (not tp_mro) to determine reachability:

// Return true if `super` is reachable from `sub` through `tp_bases`,
// as opposed to a type merely injected into the MRO by a custom `mro()`
// implementation.  Only entries reachable through `tp_bases` are covered
// by the version-tag invalidation that _PyType_Modified_Unlocked()
// propagates through `tp_subclasses`.
static int
is_superclass(PyTypeObject *super, PyTypeObject *sub)
{
    PyObject *bases = lookup_tp_bases(sub);
    if (bases == NULL) {
        return 0;
    }
    Py_ssize_t n = PyTuple_GET_SIZE(bases);
    for (Py_ssize_t i = 0; i < n; i++) {
        PyTypeObject *base = _PyType_CAST(PyTuple_GET_ITEM(bases, i));
        if (base == super || is_superclass(super, base)) {
            return 1;
        }
    }
    return 0;
}

Then in type_mro_modified, replace the unconditional goto clear for custom MROs:

if (!Py_IS_TYPE(type, &PyType_Type) && has_custom_mro(type)) {
    // Only disable cache if the custom mro() injected an entry that
    // is not reachable through tp_bases;
    PyObject *mro = lookup_tp_mro(type);
    if (mro == NULL) {
        goto clear;
    }
    Py_ssize_t mro_size = PyTuple_GET_SIZE(mro);
    for (Py_ssize_t m = 0; m < mro_size; m++) {
        PyTypeObject *entry = _PyType_CAST(PyTuple_GET_ITEM(mro, m));
        if (entry != type && !is_superclass(entry, type)) {
            goto clear;
        }
    }
}

I'm not at all familiar with this, but it seems to me that this would preserve the correctness of https://github.com/python/cpython/pull/127924 for types that do inject non-base entries into their MRO (because cache would still be disabled for those), while restoring cache performance for compatible custom MRO implementations like Zope's ExtensionClass.

If this approach makes sense, I already have a draft commit implementing this: https://github.com/perrinjerome/cpython/commit/89af3385eb7e930466dcaef97b2d7b9286eb755e and I would be happy to clean it up and make a pull request.

CPython versions tested on:

3.13

Operating systems tested on:

Linux

Guide de contribution

Ouvrir le guide de contribution

Par où commencer

  1. Lisez l'issue en entier, puis le guide de contribution du projet.
  2. Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
  3. Forkez le dépôt et travaillez sur une branche.
  4. Ouvrez une pull request qui référence le numéro de l'issue.

Piste de recherche

Commencez dans Objects/typeobject.c, au niveau de type_mro_modified(), et lisez la logique environnante d’invalidation du cache. Comparez ensuite le comportement du MRO personnalisé lié avec le commit brouillon proposé. Le travail est terminé lorsque l’invalidation du cache est conservée pour les entrées de MRO injectées en dehors de tp_bases, tout en conservant le cache pour les MRO personnalisés compatibles, avec une couverture de régression pour les deux cas.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Évaluation

Stack technique
c, python
Domaine
backend, performance
Type d'issue
Bug
Difficulté
4/5
Temps estimé
3-5 jours
Activité
Active
Clarté
Plutôt claire
Accessibilité débutants
48/100

Recevez les nouvelles issues par e-mail

Un résumé court des issues GitHub adaptées aux débutants.