python3 -m wheel pack "${pkg_name}"
done

# Switch back to the original working directory. This is needed to ensure that
# cleanup steps at the end of the script works as expected.
popd

echo "Following installer wheels were generated: "
ls "${TFCI_OUTPUT_DIR}"/*.whl

if [[ "$TFCI_ARTIFACT_STAGING_GCS_ENABLE" == 1 ]]; then
  # Note: -n disables overwriting previously created files.

      - 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 }}

def test_fastapi_cli_not_installed():
    with patch.object(fastapi.cli, "cli_main", None):
        with pytest.raises(RuntimeError) as exc_info:
            fastapi.cli.main()

![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).

        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

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

/// info

To use `EmailStr`, first install <a href="https://github.com/JoshData/python-email-validator" class="external-link" target="_blank">`email-validator`</a>.

Make sure you create a [virtual environment](../virtual-environments.md){.internal-link target=_blank}, activate it, and then install it, for example:

```console
$ pip install email-validator
```

or with:

```console

libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-headers-cuda-13=9.12.0.46-1
libcudnn9-static-cuda-13=9.12.0.46-1
libcudnn9-dev-cuda-13=9.12.0.46-1

<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。

                .desc("Alternate path for the project settings file")
                .hasArg()
                .build());
        options.addOption(Option.builder(ALTERNATE_INSTALLATION_SETTINGS)
                .longOpt("install-settings")
                .desc("Alternate path for the installation settings file")
                .hasArg()
                .build());