다음 사항을 포함해 Pydantic 모델에 대한 편집기 지원을 향상시킵니다:

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

///

## 모델 사용하기 { #use-the-model }

함수 안에서 모델 객체의 모든 어트리뷰트에 직접 접근 가능합니다:

{* ../../docs_src/body/tutorial002_py310.py *}

以下により、Pydanticモデルに対するエディタサポートが改善されます:

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

///

## モデルを使用する { #use-the-model }

関数内では、モデルオブジェクトのすべての属性に直接アクセスできます:

{* ../../docs_src/body/tutorial002_py310.py *}

### SIG CLI

SIG CLI's main focus this release was on refactoring `kubectl` internals to improve composability, readability and testability of `kubectl` commands. Those refactors will allow the team to extract a mechanism for extensibility of kubectl -- that is, plugins -- in the next releases.

    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

work, being done in conjunction with SIG Cloud Provider, is focusing on moving internal APIs that the OpenStack (and other providers) depends upon to staging to guarantee API stability. This work also included abstracting the in-tree Cinder API and refactoring code to the external Cinder provider to remove additional Cinder volume provider code.

Additional work was also done to implement an OpenStack driver for the Cluster API effort lead by SIG Cluster Lifecycle. For the external Cloud-Provider-OpenStack...

* Refactoring reorganize taints function in kubectl to expose operations ([#43171](https://github.com/kubernetes/kubernetes/pull/43171), [@ravisantoshgudimetla](https://github.com/ravisantoshgudimetla))

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

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...

does not need solving. An up-front discussion often saves a good deal of wasted
time in these cases.

We normally immediately reject isolated PRs that only perform simple
refactorings or otherwise "tidy up" certain aspects of the code. We think the
benefits of this kind of change are very small, and in our experience it is not
worth investing the substantial effort needed to review them. This especially

   *
   * if (guardExpression) {
   *    throw new BadException(badMsg(...));
   * }
   *
   * The alternative natural refactorings into void or Exception-returning methods are much slower.
   * This is a big deal - we're talking factors of 2-8 in microbenchmarks, not just 10-20%. (This is