It improves editor support for Pydantic models, with:

* auto-completion
* type checks
* refactoring
* searching
* inspections

///

## Use the model

Inside of the function, you can access all the attributes of the model object directly:

{!> ../../docs_src/body/tutorial002_py310.py!}

Ce qui améliore le support pour les modèles Pydantic avec :

* de l'auto-complétion
* des vérifications de type
* du "refactoring" (ou remaniement de code)
* de la recherche
* de l'inspection

///

## Utilisez le modèle

Dans la fonction, vous pouvez accéder à tous les attributs de l'objet du modèle directement :

          - "!**/operator/**"
          - "!**/istioctl/**"
          - "!**/tools/bug-report/**"
          # This should only really import operator API, but that is hard to express without a larger refactoring
          - "!**/pkg/kube/**"
          - "!**/pkg/url/**"
          - "!**/pkg/test/framework/**"
          - "!**/tests/fuzz/**"
        deny:
          - pkg: istio.io/istio/operator

      }

      return mapGenerator.create(entries.toArray()).keySet();
    }

    @Override
    public K[] createArray(int length) {
      // TODO: with appropriate refactoring of OneSizeGenerator, we can perhaps
      // tidy this up and get rid of the casts here and in
      // MapValueCollectionGenerator.

RELEASE_SIZE_TEST_BINARIES:=pilot-discovery pilot-agent istioctl envoy ztunnel client server

# agent: enables agent-specific files. Usually this is used to trim dependencies where they would be hard to trim through standard refactoring
# disable_pgv: disables protoc-gen-validation. This is not used buts adds many MB to Envoy protos
# not set vtprotobuf: this adds some performance improvement, but at a binary cost increase that is not worth it for the agent

modifier, use it as base\n        ...(Popper.Defaults.modifiers[name] || {}),\n        // If there are custom options, override and merge with default ones\n        ...(options.modifiers ? options.modifiers[name] : {}),\n      };\n    });\n\n    // Refactoring modifiers' list (Object => Array)\n    this.modifiers = Object.keys(this.options.modifiers)\n      .map(name => ({\n        name,\n        ...this.options.modifiers[name],\n      }))\n      // sort the modifiers by order\n      .sort((a, b) => a.order...

    on Ampere based GPUs. TensorFloat-32, or TF32 for short, is a math mode for
    NVIDIA Ampere based GPUs and is enabled by default.

*   A major refactoring of the internals of the Keras Functional API has been
    completed, that should improve the reliability, stability, and performance
    of constructing Functional models.

*   Keras mixed precision API

* vSphere cloud provider: vSphere cloud provider code refactoring ([#49164](https://github.com/kubernetes/kubernetes/pull/49164), [@BaluDontu](https://github.com/BaluDontu))

/// tip

Het feit dat dit **standaard Python** is, betekent dat je nog steeds de **best mogelijke ontwikkelaarservaring** krijgt in je editor, met de hulpmiddelen die je gebruikt om je code te analyseren en te refactoren, enz. ✨

Daarnaast betekent het ook dat je code zeer verenigbaar zal zijn met veel andere Python-hulpmiddelen en -pakketten. 🚀

///

## Type hints in **FastAPI**