- name: Setup uv
        uses: astral-sh/setup-uv@v7
        with:
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
      - run: uv pip install -r requirements-github-actions.txt
      - uses: actions/download-artifact@v6
        with:
          name: coverage-html
          path: htmlcov
          github-token: ${{ secrets.GITHUB_TOKEN }}

## Instalar `PyJWT` { #install-pyjwt }

Nós precisamos instalar o `PyJWT` para criar e verificar os tokens JWT em Python.

Certifique-se de criar um [ambiente virtual](../../virtual-environments.md){.internal-link target=_blank}, ativá-lo e então instalar o `pyjwt`:

<div class="termy">

```console
$ pip install pyjwt

---> 100%
```

</div>

/// info | Informação

The drives should all be of approximately the same size.

## Get Started with MinIO in Erasure Code

### 1. Prerequisites

![quota](https://raw.githubusercontent.com/minio/minio/master/docs/bucket/quota/bucketquota.png)

Buckets can be configured to have `Hard` quota - it disallows writes to the bucket after configured quota limit is reached.

## Prerequisites

- Install MinIO - [MinIO Quickstart Guide](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-on-redhat-linux.html#procedure).

opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch

        uses: astral-sh/setup-uv@v7
        with:
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
            uv.lock
      - name: Install Dependencies
        run: |
          uv venv
          uv pip install -r requirements.txt
      - name: Run prek - pre-commit
        id: precommit
        run: uvx prek run --from-ref origin/${GITHUB_BASE_REF} --to-ref HEAD --show-diff-on-failure

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%
```

</div>

...これには、コードを実行するサーバーとして使用できる `uvicorn`も含まれます。

/// note | 備考

パーツ毎にインストールすることも可能です。

以下は、アプリケーションを本番環境にデプロイする際に行うであろうものです:

```
pip install fastapi
```

また、サーバーとして動作するように`uvicorn` をインストールします:

```
pip install "uvicorn[standard]"
```

そして、使用したい依存関係をそれぞれ同様にインストールします。

libcufft-12-8
libcurand-12-8
libcusolver-dev-12-8
libcusparse-dev-12-8
libcublas-12-8
libcublas-dev-12-8
libnccl-dev=2.25.1-1+cuda12.8
libnccl2=2.25.1-1+cuda12.8
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-12=9.8.0.87-1

Entretanto, se você usar o comando `pip install fastapi`, o pacote `python-multipart` não é incluído por padrão.

Para instalá-lo manualmente, certifique-se de criar um [ambiente virtual](../../virtual-environments.md){.internal-link target=_blank}, ativá-lo e então instalá-lo com:

```console
$ pip install python-multipart
```

Sin embargo, si usas el comando `pip install fastapi`, el paquete `python-multipart` no se incluye por defecto.

Para instalarlo manualmente, asegúrate de crear un [entorno virtual](../../virtual-environments.md){.internal-link target=_blank}, activarlo, y luego instalarlo con:

```console
$ pip install python-multipart
```