일반적인 선택은 Jinja2로, Flask와 다른 도구에서도 사용됩니다.

설정을 쉽게 할 수 있는 유틸리티가 있으며, 이를 **FastAPI** 애플리케이션에서 직접 사용할 수 있습니다(Starlette 제공).

## 의존성 설치 { #install-dependencies }

[가상 환경](../virtual-environments.md)을 생성하고, 활성화한 후 `jinja2`를 설치해야 합니다:

<div class="termy">

```console
$ pip install jinja2

---> 100%
```

</div>

## `Jinja2Templates` 사용하기 { #using-jinja2templates }

* `Jinja2Templates`를 가져옵니다.

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

https://www.elastic.co/cloud/as-a-service[Elasticsearch Service on Elastic
Cloud].

If you prefer to install and manage Elasticsearch yourself, you can download
the latest version from 
https://www.elastic.co/downloads/elasticsearch[elastic.co/downloads/elasticsearch].

For more installation options, see the
https://www.elastic.co/guide/en/elasticsearch/reference/current/install-elasticsearch.html[Elasticsearch installation
documentation].

[[upgrade]]

        with:
          distribution: 'temurin'
          java-version: 21

      - uses: actions/setup-python@v6
        with:
          python-version: 3.x

      - run: pip install mkdocs-material mkdocs-redirects

      - name: Generate Docs
        run: ./test_docs.sh

      - uses: actions/upload-artifact@v7
        with:
          name: docs

<div class="termy">

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

---> 100%
```

</div>

////

//// tab | `uv`

如果你有 [`uv`](https://github.com/astral-sh/uv):

<div class="termy">

```console
$ uv pip install "fastapi[standard]"
---> 100%
```

</div>

////

### 從 `requirements.txt` 安裝 { #install-from-requirements-txt }

<div class="termy">

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

---> 100%
```

</div>

////

//// tab | `uv`

如果你有 [`uv`](https://github.com/astral-sh/uv):

<div class="termy">

```console
$ uv pip install "fastapi[standard]"
---> 100%
```

</div>

////

### 从 `requirements.txt` 安装 { #install-from-requirements-txt }

      - name: Setup uv
        uses: astral-sh/setup-uv@v7
        with:
          enable-cache: true
          cache-dependency-glob: |
            pyproject.toml
            uv.lock
      - name: Install GitHub Actions dependencies
        run: uv sync --locked --no-dev --group github-actions
      - name: Update Topic Repos
        run: uv run ./scripts/topic_repos.py
        env:

    - name: Setup uv
      uses: astral-sh/setup-uv@v7
      with:
        enable-cache: true
        cache-dependency-glob: |
            pyproject.toml
            uv.lock
    - name: Install GitHub Actions dependencies
      run: uv sync --locked --no-dev --group github-actions
    - name: Label Approved
      run: uv run ./scripts/label_approved.py
      env:
        TOKEN: ${{ secrets.GITHUB_TOKEN }}

## 서버 프로그램 설치하기 { #install-the-server-program }

FastAPI를 설치하면 프로덕션 서버인 Uvicorn이 함께 설치되며, `fastapi run` 명령으로 시작할 수 있습니다.

하지만 ASGI 서버를 수동으로 설치할 수도 있습니다.

[가상 환경](../virtual-environments.md)을 만들고 활성화한 다음, 서버 애플리케이션을 설치하세요.

예를 들어 Uvicorn을 설치하려면:

<div class="termy">

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

---> 100%
```

</div>

## Встановіть залежності { #install-dependencies }

Переконайтеся, що ви створили [віртуальне оточення](../virtual-environments.md), активували його та встановили `jinja2`:

<div class="termy">

```console
$ pip install jinja2

---> 100%
```

</div>

## Використання `Jinja2Templates` { #using-jinja2templates }