FROM ${BASE_DISTRIBUTION:-debug}

LABEL description="Istio CNI plugin installer."

ARG TARGETARCH
COPY ${TARGETARCH:-amd64}/istio-cni /opt/cni/bin/istio-cni
COPY ${TARGETARCH:-amd64}/install-cni /usr/local/bin/install-cni

ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/opt/cni/bin
WORKDIR /opt/cni/bin

	\
	Write-Host 'Removing ...'; \
	Remove-Item C:\tmp\pyinstall.exe -Force; \
	\
	Write-Host 'Complete.';

# Install pip packages.
RUN python -m pip install --ignore-installed --force-reinstall --upgrade \
    setuptools packaging

# Install JDK 21.
RUN \
  Add-Type -AssemblyName \"System.IO.Compression.FileSystem\"; \
  $zulu_pkg = \"zulu21.34.19-ca-jdk21.0.3-win_x64.zip\"; \

    /**
     * Install an artifact from a particular file.
     *
     * @param source the file to install
     * @param artifact the artifact definition
     * @param localRepository the local repository to install into
     * @throws ArtifactInstallationException if an error occurred installing the artifact
     */
    void install(File source, Artifact artifact, ArtifactRepository localRepository)

            pyproject.toml
      - name: Install docs extras
        run: uv pip install -r requirements-docs.txt
      # Install MkDocs Material Insiders here just to put it in the cache for the rest of the steps
      - name: Install Material for MkDocs Insiders
        if: ( github.event_name != 'pull_request' || github.secret_source == 'Actions' )
        run: uv pip install -r requirements-docs-insiders.txt
        env:

# This aims to maintain TF compatibility with NumPy 1.x until 2025 b/361369076.
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then
  # Uninstall tf nightly wheel built with numpy1.
  "$python" -m pip uninstall -y tf_nightly_numpy1
  # Install tf nightly cpu wheel built with numpy2.x from PyPI in numpy1.x env.
  "$python" -m pip install tf-nightly-cpu
  if [[ "$TFCI_WHL_IMPORT_TEST_ENABLE" == "1" ]]; then

	<property name="opensearch.version" value="2.17.1" />

	<target name="install.modules">
		<mkdir dir="${target.dir}" />
		<delete dir="${modules.dir}" />
		<mkdir dir="${modules.dir}" />

		<!-- analysis-common -->
		<antcall target="install.module">
			<param name="repo.url" value="${maven.release.repo.url}" />

      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.
         * It has an added advantage since you can you easily switch to different hardware accelerators (cpu, gpu, tpu) as per the task.

     * @throws IllegalArgumentException in case {@code request} is {@code null}
     */
    void install(@Nonnull ArtifactInstallerRequest request);

    /**
     * @param session the repository session
     * @param artifact the {@link ProducedArtifact} to install
     * @throws ArtifactInstallerException In case of an error which can be the a given artifact cannot be found or the

# Run go tool dist to install a command.
# The -v causes dist to print the name of each directory as it runs.
# The -vv causes dist to print each build command as it runs.
# go tool dist clean cleans all directories, not just this one,
# but it's as close as we can get.

# Default target (first).
install:
	go tool dist install -v

verbose:
	go tool dist install -vv

clean:

${packaging.scripts.header}

#
# This script is executed in the pre-installation phase
#
#   On Debian,
#       $1=install : indicates an new install
#       $1=upgrade : indicates an upgrade
#
#   On RedHat,
#       $1=1       : indicates an new install
#       $1=2       : indicates an upgrade



# Sets the default values for fess variables used in this script
FESS_USER="${packaging.fess.user}"
FESS_GROUP="${packaging.fess.group}"