- uses: actions/checkout@v5
      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Setup uv
        uses: astral-sh/setup-uv@v6
        with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
      - name: Install Dependencies

                }
            }
        }
    }

    steps {
        exec {
            name = "UPDATE_WRAPPER_AND_CREATE_PR"
            path = ".teamcity/scripts/update_wrapper_and_create_pr.sh"
            arguments = "%wrapperVersion%"
        }
    }

    dependencies {
        dependency(AbsoluteId("Gradle_${vcsBranch.branchName.toCapitalized()}_$FINAL_RELEASE_BUILD_CONFIGURATION_ID")) {

**가상 환경**은 몇몇 파일로 구성된 하나의 디렉터리입니다.

///

/// info | 정보

이 페이지에서는 **가상 환경**의 사용 방법과 작동 방식을 설명합니다.

만약 **모든 것을 관리해주는 도구** (Python 설치까지 포함)를 사용하고 싶다면 <a href="https://github.com/astral-sh/uv" class="external-link" target="_blank">uv</a>를 사용해보세요.

///

## 프로젝트 생성

먼저, 프로젝트를 위한 디렉터리를 하나 생성합니다.

보통 사용자 홈 디렉터리 안에 `code`라는 디렉터리를 만들고, 그 안에 프로젝트마다 하나씩 디렉터리를 만들어 관리합니다.

<div class="termy">

  stars: 1130
  owner_login: art049
  owner_html_url: https://github.com/art049
- name: restish
  html_url: https://github.com/rest-sh/restish
  stars: 1107
  owner_login: rest-sh
  owner_html_url: https://github.com/rest-sh
- name: fastapi-scaff
  html_url: https://github.com/atpuxiner/fastapi-scaff
  stars: 1052
  owner_login: atpuxiner
  owner_html_url: https://github.com/atpuxiner

-   type: markdown
    attributes:
      value: |
        You can collect some of this information using our environment capture [script](https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh)  You can also obtain the TensorFlow version with: <br> 1. TF 1.0: `python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"` <br>2. TF 2.0: `python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`

#### Running sanity check

If you have Docker installed on your system, you can perform a sanity check on
your changes by running the command:

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

### Hey API { #hey-api }

Once we have a FastAPI app with the models, we can use Hey API to generate a TypeScript client. The fastest way to do that is via npx.

```sh
npx @hey-api/openapi-ts -i http://localhost:8000/openapi.json -o src/client
```

This will generate a TypeScript SDK in `./src/client`.

## Example request and response

Sample request with `curl`:

```sh
curl -XPOST 'http://localhost:9001/?Action=AssumeRoleWithCustomToken&Version=2011-06-15&Token=aaa&RoleArn=arn:minio:iam:::role/idmp-vGxBdLkOc8mQPU1-UQbBh-yWWVQ'
```

Prettified Response:

```xml

- [Kubernetes Documentation](https://kubernetes.io/docs/home/)

			<outputDirectory>fess-${project.version}/bin</outputDirectory>
			<fileMode>0755</fileMode>
			<directoryMode>0755</directoryMode>
			<lineEnding>unix</lineEnding>
			<includes>
				<include>fess.in.sh</include>
				<include>fess</include>
				<include>generate-thumbnail</include>
			</includes>
		</fileSet>
		<fileSet>
			<filtered>false</filtered>
			<outputDirectory>fess-${project.version}/bin</outputDirectory>