/**
     * Let the toolchain decide if it matches requirements defined
     * in the toolchain plugin configuration.
     *
     * @param requirements key value pair, may not be {@code null}
     * @return {@code true} if the requirements match, otherwise {@code false}
     */
    boolean matchesRequirements(Map<String, String> requirements);

    }
    TesterRequirements requirements;
    try {
      requirements = FeatureUtil.getTesterRequirements(method);
    } catch (ConflictingRequirementsException e) {
      throw new RuntimeException(e);
    }
    if (!features.containsAll(requirements.getPresentFeatures())) {
      if (logger.isLoggable(FINER)) {
        Set<Feature<?>> missingFeatures = copyToSet(requirements.getPresentFeatures());

# ==============================================================================
#
# setup.python.sh: Install a specific Python version and packages for it.
# Usage: setup.python.sh <pyversion> <requirements.txt>
set -xe

source ~/.bashrc
VERSION=$1
REQUIREMENTS=$2

# Install Python packages for this container's version
if [[ ${VERSION} == "python3.13" ]]; then
  cat >pythons.txt <<EOF
$VERSION
$VERSION-dev
$VERSION-venv
EOF

     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
   
   -----------------------------------------------------------------------------------------------
   
   **2. Installing **TensorFlow** (TF) CPU prebuilt binaries**
   
   

    }

fun Requirements.requiresOs(os: Os) {
    contains("teamcity.agent.jvm.os.name", os.agentRequirement)
}

fun Requirements.requiresArch(os: Os, arch: Arch) {
    if (os == Os.MACOS) {
        contains("teamcity.agent.jvm.os.arch", arch.nameOnMac)
    } else {
        contains("teamcity.agent.jvm.os.arch", arch.nameOnLinuxWindows)
    }
}

fun Requirements.requiresNotEc2Agent() {

# (2)
WORKDIR /code

# (3)
COPY ./requirements.txt /code/requirements.txt

# (4)
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# (5)
COPY ./app /code/app

# (6)
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]
```

1. 공식 파이썬 베이스 이미지에서 시작합니다.

2. 현재 워킹 디렉터리를 `/code`로 설정합니다.

    여기에 `requirements.txt` 파일과 `app` 디렉터리를 위치시킬 것입니다.

# (2)
WORKDIR /code

# (3)
COPY ./requirements.txt /code/requirements.txt

# (4)
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# (5)
COPY ./app /code/app

# (6)
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]
```

1. 公式のPythonベースイメージから始めます

2. 現在の作業ディレクトリを `/code` に設定します

    ここに `requirements.txt` ファイルと `app` ディレクトリを置きます。

    }
    TesterRequirements requirements;
    try {
      requirements = FeatureUtil.getTesterRequirements(method);
    } catch (ConflictingRequirementsException e) {
      throw new RuntimeException(e);
    }
    if (!features.containsAll(requirements.getPresentFeatures())) {
      if (logger.isLoggable(FINER)) {
        Set<Feature<?>> missingFeatures = copyToSet(requirements.getPresentFeatures());

  @MockWebServerInstance("server3") private val server3: MockWebServer
) {
  @Test
  fun test() {
    ...
  }
}
```

Requirements
------------

MockWebServer's JUnit 5 integration works on Android 7.0+ (API level 24+) and Java 8+. Note that

      uses: astral-sh/setup-uv@v3
      with:
        version: "0.4.15"
        enable-cache: true
        cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
    - name: Install GitHub Actions dependencies
      run: uv pip install -r requirements-github-actions.txt
    - name: Label Approved
      run: python ./scripts/label_approved.py
      env:
        TOKEN: ${{ secrets.GITHUB_TOKEN }}