padv.pipeline.GitHubOptions

Options for generating pipeline files for GitHub Actions

Description

Use the padv.pipeline.GitHubOptions object to specify options for generating GitHub^® pipeline files. To generate pipeline files, pass the object to the padv.pipeline.generatePipeline function.

Creation

Syntax

options = padv.pipeline.GitHubOptions(GeneratorVersion=version)

options = padv.pipeline.GitHubOptions(___,PropertyName=Value)

Description

options = padv.pipeline.GitHubOptions(GeneratorVersion=version) creates configuration options for generating a GitHub pipeline using the specified pipeline generator version.

• Use GeneratorVersion=1 if you need to maintain compatibility with existing pipelines.

• Use GeneratorVersion=2 for new pipelines or when upgrading your pipeline setup.

options = padv.pipeline.GitHubOptions(___,PropertyName=Value) sets properties using one or more name-value arguments.

Some properties are available in Both Versions, while other properties are specific to Version 1 Only or Version 2 Only.

Input Arguments

version — Pipeline generator version

1 (default) | 2

Pipeline generator version, specified as either:

• 1 — Pipeline Generator Version 1 provides compatibility with the original pipeline generator functionality. Use GeneratorVersion=1 if you need to maintain compatibility with existing pipelines. For more information, see Integrate Process into GitHub.

• 2 — Pipeline Generator Version 2 contains several improvements to pipeline file propagation, generated pipeline file size, and integration with artifact management systems. Use GeneratorVersion=2 for new pipelines or when upgrading your pipeline setup. For more information, see Process Integration and Artifact Management for GitHub.

Properties

Both Versions

RunnerLabels — GitHub runner labels

"self-hosted" (default) | string

GitHub runner labels, specified as a string.

The labels determine which GitHub runner can execute the job. For more information, see the GitHub documentation for Choosing the runner for a job.

Example: "Linux"

Data Types: string

UseMatlabPlugin — Specify whether GitHub uses MATLAB^® Actions to run tasks

1 (true) (default) | 0 (false)

Specify whether GitHub uses MATLAB Actions to run tasks, specified as either a numeric or logical:

• 0 (false) — The pipeline runs tasks using shell commands.

• 1 (true) — The pipeline runs tasks using the Run MATLAB Command action and the pipeline generator ignores the properties MatlabLaunchCmd and MatlabStartupOptions

Note

If you dry run tasks by setting DryRun to true in RunprocessCommandOptions, the pipeline does not use the plugin and runs tasks using shell commands.

Data Types: logical

MatlabLaunchCmd — Command to start MATLAB program

"matlab" (default) | string

Command to start MATLAB program, specified as a string.

If you use a custom command to launch MATLAB on your machine, make sure to set this property. The default value of this property is "matlab", which assumes MATLAB is available in the PATH environment variable for your system and runs the default MATLAB executable.

Example: "C:\Program Files\MATLAB\R2024b\bin\matlab.exe"

Data Types: string

MatlabStartupOptions — Command-line startup options for MATLAB

"-nodesktop -logfile output.log" (default) | string

Command-line startup options for MATLAB, specified as a string.

Use this property to specify the command-line startup options that the generated pipeline file uses when starting the MATLAB program. By default, the pipeline generator launches MATLAB using the -batch option. If you need to run MATLAB without the -batch option, specify the property AddBatchStartupOption as false.

Some MATLAB code, including some built-in tasks, can only run successfully if a display is available for your machine. For more information, see Set Up Virtual Display Machines Without Displays.

Example: "-nodesktop -logfile mylogfile.log"

Data Types: string

AddBatchStartupOption — Specify whether to open MATLAB using -batch startup option

1 (true) (default) | 0 (false)

Specify whether to open MATLAB using -batch startup option, specified as a numeric or logical 0 (false) or 1 (true).

If you need to launch MATLAB with options that are not compatible with -batch, specify AddBatchStartupOption as false.

Data Types: logical

CheckoutSubmodules — Checkout Git™ submodules

"false" (default) | "true" | "recursive"

Checkout Git submodules at the beginning of each pipeline stage, specified as either:

• "false"

• "true"

• "recursive"

This property uses the GitHub Action checkout@v4. For information about the submodule input values, see the GitHub documentation for Checkout submodules.

Data Types: string

PipelineArchitecture — Number of stages and grouping of tasks in CI pipeline

padv.pipeline.Architecture.SingleStage (default) | padv.pipeline.Architecture.SerialStages | padv.pipeline.Architecture.SerialStagesGroupPerTask | padv.pipeline.Architecture.IndependentModelPipelines

Number of stages and grouping of tasks in CI pipeline, specified as either:

• padv.pipeline.Architecture.SingleStage — The pipeline has a single stage, named Runprocess, that runs each of the tasks in the process.

  

• padv.pipeline.Architecture.SerialStages — The pipeline has one stage for each task iteration in the process.

  

• padv.pipeline.Architecture.SerialStagesGroupPerTask — The pipeline has one stage for each task in the process.

  

• padv.pipeline.Architecture.IndependentModelPipelines— The pipeline contains parallel, downstream pipelines for each model. Each downstream pipeline independently runs the tasks associated with that model. To make sure the jobs run in parallel, make sure that you either have multiple build agents available or configure your build agent to run parallel jobs.

  

Note

For Pipeline Generator Version 2, if you decide to use the IndependentModelPipelines architecture to generate code and perform code analysis tasks in parallel, you must either switch to using the template parallel process model or update your existing process as shown in Considerations for Parallel Code Generation. These updates allow the tasks in your pipeline to properly handle shared utilities and code generated across parallel jobs.

Example: padv.pipeline.Architecture.IndependentModelPipelines

Example: "IndependentModelPipelines"

RunprocessCommandOptions — Options for runprocess command

padv.pipeline.RunProcessOptions (default) | padv.pipeline.RunProcessOptions object

Options for runprocess command, specified as a padv.pipeline.RunProcessOptions object.

The object padv.pipeline.RunProcessOptions has properties for each of the name-value arguments in the runprocess function, except for the Scope arguments Tasks, Process, Subprocesses, and FilterArtifact.

Note

• The GitHub workflow automatically dry runs tasks using shell commands if you set DryRun to true in RunprocessCommandOptions.

• GenerateJUnitForProcess is set to false by default in padv.pipeline.RunProcessOptions. Previously, this property was true by default.

• The GenerateJUnitForProcess property in padv.pipeline.GitHubOptions will be removed in a future release. Make sure to specify the GenerateJUnitForProcess property in padv.pipeline.RunProcessOptions to the value that you want the pipeline to use.

Example: padv.pipeline.RunProcessOptions()

StopOnStageFailure — Stop running pipeline after stage fails

0 (false) (default) | 1 (true)

Stop running pipeline after stage fails, specified as either:

• 1 (true) — Stop the pipeline immediately when any stage fails.

• 0 (false) — Allow the pipeline to continue running subsequent stages, even if a previous stage fails.

If you use the built-in tasks padv.builtin.task.RunTestsPerModel or padv.builtin.task.RunTestsPerTestCase to run tests, keep StopOnStageFailure set to false. This prevents the pipeline from skipping the padv.builtin.task.MergeTestResults task if a test stage fails.

Data Types: logical

GeneratedYMLFileName — File name of generated pipeline file

"simulink_pipeline" (default) | string

File name of generated pipeline file, specified as a string.

By default, the generated pipeline file generates into the subfolder derived > pipeline, relative to the project root. To change where the pipeline file generates, specify GeneratedPipelineDirectory.

Example: "padv_generated_pipeline_file"

Data Types: string

GeneratedPipelineDirectory — Location where generated pipeline file generates

fullfile("derived","pipeline") (default) | string

Location where the generated pipeline file generates, specified as a string.

This property defines the directory where the generated pipeline file generates.

By default, the generated pipeline file is named "simulink_pipeline.yml". To change the name of the generated pipeline file, specify the GeneratedYMLFileName property.

Example: fullfile("derived","pipeline","test")

Data Types: string

EnableArtifactCollection — When to collect build artifacts

"always", 1, or true (default) | "never", 0, or false | "on_success" | "on_failure"

When to collect build artifacts, specified as:

• "never", 0, or false — Never collect artifacts

• "on_success" — Only collect artifacts when the pipeline succeeds

• "on_failure" — Only collect artifacts when the pipeline fails

• "always", 1, or true — Always collect artifacts

Data Types: logical | string

ArtifactZipFileName — Name of ZIP file for job artifacts

"padv_artifacts.zip" (default) | string

Name of ZIP file for job artifacts, specified as a string.

Example: "my_job_artifacts.zip"

Data Types: string

GenerateReport — Generate Process Advisor build report

true or 1 (default) | false or 0

Generate Process Advisor build report, specified as a numeric or logical 1 (true) or 0 (false).

Data Types: logical

ReportFormat — File format for generated report

"pdf" (default) | "html" | "html-file" | "docx"

File format for the generated report, specified as one of these values:

• "pdf" — PDF file

• "html" — HTML report, packaged as a zipped file that contains the HTML file, images, style sheet, and JavaScript^® files of the report

• "html-file" — HTML report, consisting of a single HTML file that contains the text, style sheets, JavaScript, and base64-encoded images of the report

• "docx" — Microsoft^® Word document

ReportPath — Name and path of generated report

"ProcessAdvisorReport" (default) | string array

Name and path of generated report, specified as a string array.

By default, the report path uses a relative path to the project root and the pipeline generator generates a report ProcessAdvisorReport.pdf.

As a recommended practice, set the ReportPath to a sub-folder within the project root. CI pipelines cannot archive files located in the project root itself.

Example: "$PROJECTROOT$/PA_Results/Report/ProcessAdvisorReport"

Data Types: string

EnableOpenTelemetry — Enable integration with OpenTelemetry

false (0) (default) | true (1)

Enable integration with OpenTelemetry to view detailed pipeline timing and execution data, specified as a numeric or logical true (1) or false (0).

Before you enable the OpenTelemetry integration, you must install the OpenTelemetry-MATLAB package and set up OpenTelemetry, as shown in Collect Detailed Execution Data with OpenTelemetry Integration.

Data Types: logical

Version 1 Only

CheckOutdatedResultsAfterMerge — (unused) Check for outdated results after merge

1 (true) (default) | 0 (false)

The pipeline generator does not use this property.

Data Types: logical

EnablePipelineCaching — Enable pipeline caching to support incremental builds in CI

1 (true) (default) | 0 (false)

Enable pipeline caching to support incremental builds in CI, specified as a numeric or logical 0 (false) or 1 (true).

For Pipeline Generator Version 1, generated pipelines use caching by default to help the performance of incremental builds in CI. However, if a generated pipeline has persistent conflicts and generates errors when merging artifact information from parallel jobs, you can disable pipeline caching by specifying EnablePipelineCaching as 0 (false). Disabling pipeline caching increases build times, but can help avoid merge conflicts.

Pipeline Generator Version 2 ignores this property.

Data Types: logical

MatlabInstallationLocation — Path to MATLAB installation location

"PATH_TO_MATLAB" (default) | string

Path to MATLAB installation location, specified as a string.

For Pipeline Generator Version 1, make sure the path that you specify uses the MATLAB root folder location and file separators for the operating system of your build agent.

Pipeline Generator Version 2 ignores this property. For Pipeline Generator Version 2, make sure MATLAB is available on the system PATH so the build agent can access MATLAB.

Example: "C:\Program Files\MATLAB\R2025a\bin"

Example: "/usr/local/MATLAB/R2025a/bin"

Example: "/Applications/MATLAB_R2025a.app/bin"

Data Types: string

RetentionDays — How many days GitHub stores workflow artifacts

"30" (default) | string

How many days GitHub stores workflow artifacts, specified as a string.

This property corresponds to the job keyword "retention-days" in GitHub. After the specified number of retention days, the artifacts expire and GitHub deletes the artifacts. For more information, see the GitHub documentation for Configuring a custom artifact retention period.

Pipeline Generator Version 2 ignores this property and instead uses the default organization retention policy. For more information, see the GitHub documentation for Artifact and log retention policy.

Example: RetentionDays = "90"

Data Types: string

ShellEnvironment — Shell environment GitHub uses to launch MATLAB

"bash" (default) | "pwsh"

Shell environment GitHub uses to launch MATLAB, specified as one of these values:

• "bash" — UNIX^® shell script

• "pwsh" — PowerShell Core script

Pipeline Generator Version 2 ignores this property and instead:

• If the build agent is a UNIX machine, the GitHub pipeline uses a shell script.

• If the build agent is not a UNIX machine, the GitHub pipeline uses a Windows^® batch script.

Data Types: string

Version 2 Only

SupportPackageRoot — Path to root folder of support packages on build agent

string

Path to root folder of support packages on build agent, specified as a string.

You can find this location by using the function matlabshared.supportpkg.getSupportPackageRoot on the build agent.

Note

If you specify this property, you must also specify the variable MW_SUPPORT_PACKAGE_ROOT in your CI system.

Pipeline Generator Version 1 does not support this property.

Example: "C:\\ProgramData\\MATLAB\\SupportPackages\\R2025a\\bin"

Data Types: string

RelativeProjectPath — Relative path from repository root to project

"" (default) | string

Relative path from repository root to project root folder, specified as a string.

If your project root folder is at the repository root, leave RelativeProjectPath as an empty string "".

If your project is located in a subfolder, set RelativeProjectPath to the subfolder path relative to the repository root. The value of RelativeProjectPath must be the portion of the project path after the repository root and must be a valid sub-path within the full path to the project root folder. The path must end with the file separator /.

For example:

Situation	Project Root Folder	Valid RelativeProjectPath
Project in repository repo	"/home/user/repo-root/"	""
Project in subfolder	"/home/user/repo-root/src/myproject/"	"src/myproject/"

Note

If you specify this property, you must also specify the variable MW_RELATIVE_PROJECT_PATH in your CI system. The path must end with the file separator /.

Pipeline Generator Version 1 does not support this property.

Example: "src/myproject/"

Example: "subfolder/src/myproject/"

Data Types: string

RemoteBuildCacheName — Name of remote build cache directory

"${{ github.workflow }}" (default) | string

Name of remote build cache directory, specified as a string.

The pipeline generator uses the directory to store pipeline artifact caches on the remote build cache service. The artifacts and sub-folders are inside a root folder. You can specify the name of the root folder by using the RemoteBuildCacheName property.

For example, inside your artifact storage location, the pipeline generator can generate a folder structure such as:

<RemoteBuildCacheName>/
└── branchName/
    └── folderForEachRunId/
        └── folderForEachTaskIteration/
            ├── Project/
                ├── PA_Results/
                ├── derived/
            │       └── artifacts.dmr
        ├── ir_dag.json
        ├── simulink_pipeline
└── __lastSuccessfulRunId__

As a best practice, use a unique name for each pipeline and project to avoid conflicts between different pipelines.

Pipeline Generator Version 1 does not support this property.

Example: "GitHub MATLAB Workflow"

Data Types: string

ArtifactServiceMode — Artifact storage approach

"network" (default) | "jfrog" | "s3" | "azure_blob"

Artifact storage approach, specified as one of the values in this table. The artifact service mode determines how the pipeline stores and retrieves artifact caches. Depending on which approach you choose, you must also specify the additional properties and credentials in the Requirements column.

Value	Description	Requirements
"network"	Store artifacts on a network drive	Set the NetworkStoragePath property.
"jfrog"	Store artifacts in a JFrog Artifactory repository	Set both the ArtifactoryUrl and ArtifactoryRepoName properties. In your CI system, save your JFrog API token as a secret with the ID ARTIFACTORY_API_TOKEN_SECRET.
"s3"	Store artifacts in an Amazon S3™ bucket	Set both the S3BucketName and S3AwsAccessKeyID properties. In your CI system, save your Amazon S3 access key as a secret with the ID S3_AWS_SECRET_ACCESS_KEY_SECRET.
"azure_blob"	Store artifacts in an Azure® Blob Storage container	Set the AzContainerName property. In your CI system, save your Azure storage account connection string as a secret with the ID AZ_CONNECTION_STRING_SECRET.

Pipeline Generator Version 1 does not support this property.

NetworkStoragePath — Path to network storage location

string

Path to network storage location for storing artifacts when ArtifactServiceMode is "network", specified as a string.

Specify the path to a shared network location that all agents running the pipeline can access.

Pipeline Generator Version 1 does not support this property.

Example: "/artifactManagement/cacheStorage"

Data Types: string

ArtifactoryUrl — URL of JFrog Artifactory server

string

URL of JFrog Artifactory server for storing artifacts when ArtifactServiceMode is "jfrog", specified as a string.

Pipeline Generator Version 1 does not support this property.

Example: "http://localhost:8082/artifactory"

Data Types: string

ArtifactoryRepoName — Name of JFrog Artifactory repository

string

Name of JFrog Artifactory repository for storing artifacts when ArtifactServiceMode is "jfrog", specified as a string.

Pipeline Generator Version 1 does not support this property.

Example: "example-repo-local"

Data Types: string

S3BucketName — Name of Amazon S3 bucket

string

Name of Amazon S3 bucket for storing artifacts when ArtifactServiceMode is "s3", specified as a string.

Pipeline Generator Version 1 does not support this property.

Example: "my-artifacts-bucket"

Data Types: string

S3AwsAccessKeyID — AWS^® access key ID

string

AWS access key ID for storing artifacts in an Amazon S3 bucket when ArtifactServiceMode is "s3", specified as a string.

Pipeline Generator Version 1 does not support this property.

Example: "AKIAIOSFODNN7EXAMPLE"

Data Types: string

AzContainerName — Name of Azure Blob Storage container

string

Name of Azure Blob Storage container for storing artifacts when ArtifactServiceMode is "azure_blob", specified as a string.

You can only specify a single container name, not multiple container names.

Pipeline Generator Version 1 does not support this property.

Example: "mycontainer"

Data Types: string

RunnerType — Execution environment of runner

"default" (default) | "container"

Execution environment of runner, specified as either:

• "default" — Runs tasks directly on the host machine without containerization.

• "container" — Runs tasks inside a containerized environment, such as a Docker^® container. Specify the container by using the ImageTag property.

  The container does not use MATLAB actions. Make sure to specify the UseMatlabPlugin, MatlabLaunchCmd, MatlabStartupOptions, and AddBatchStartupOption properties as required by your setup. For example:

  op = padv.pipeline.GitHubOptions(GeneratorVersion=2);
  % Docker image settings
  op.UseMatlabPlugin = false;
  op.MatlabLaunchCmd = "xvfb-run -a matlab -batch"; 
  op.MatlabStartupOptions = "";
  op.AddBatchStartupOption = false;

Pipeline Generator Version 1 does not support this property.

ImageTag — Full name of container image

string

Full name of the container image that the generated pipeline uses when RunnerType is "container", specified as a string.

The image must be an OCI-compliant image, such as a Docker image.

Pipeline Generator Version 1 does not support this property.

Example: "mycompany/pipeline-runner:latest"

Data Types: string

TemplatePath — Path to pipeline template file

"./.github/workflows/generic-job.yml" (default) | string

Path to pipeline template file, specified as a string.

The generated pipeline files look for the required supporting template files at this path location.

Pipeline Generator Version 1 does not support this property.

Data Types: string

CacheFallbackBranches — Branches to check for cached build artifacts

["main"] (default) | string

Branches to check for cached build artifacts, specified as a string.

To support incremental builds, the pipeline generator attempts to restore the cache from the last successful run on the same branch. If no cache is available, the pipeline checks for cached build artifacts on the branches that you specify. By default, the fallback branch is main, but you can specify multiple fallback branches and the pipeline checks each one in order. If the pipeline generator does not find a cache on the specified branches, the pipeline runs a full build, executing each task in the process without skipping tasks. For more information, see How Pipeline Generation Works.

Pipeline Generator Version 1 does not support this property.

Example: ["develop"]

Example: ["main","develop"]

Data Types: string

Examples

Generate GitHub Pipeline File with Version 1

This example code shows how to generate a GitHub pipeline file in MATLAB using Pipeline Generator Version 1. For a complete example, see Integrate Process into GitHub.

Note

Pipeline Generator Version 1 is provided for compatibility with the original pipeline generator functionality. Pipeline Generator Version 2 is recommended for enhanced file propagation and artifact management, but requires you to update your setup and workflow.

Load a project. For this example, you can load a Process Advisor example project.

processAdvisorExampleStart

Represent your pipeline generator options by creating a padv.pipeline.GitHubOptions object for pipeline generator version 1.

op = padv.pipeline.GitHubOptions(GeneratorVersion=1);

Choose which GitHub runners can execute the pipeline by specifying your GitHub runner labels.

op.RunnerLabels = "Linux";

Generate a pipeline file.

padv.pipeline.generatePipeline(op)

The pipeline generator generates a GitHub CI pipeline file, simulink_pipeline.yml, for the current project, process model, and pipeline generator options.

Generate GitHub Pipeline File with Network Storage

This example code shows how to configure and generate a GitHub pipeline file using Pipeline Generator Version 2 and network artifact storage. For the complete example, see Process Integration and Artifact Management for GitHub.

Represent your pipeline generator options by creating a padv.pipeline.GitHubOptions object for pipeline generator version 2.

op = padv.pipeline.GitHubOptions(GeneratorVersion=2);

Configure the pipeline generator to use your GitHub runner and support package installation by specifying the properties RunnerLabels and SupportPackageRoot. You can find the location of your support package root by using the function matlabshared.supportpkg.getSupportPackageRoot on your build agent.

op.RunnerLabels = "padv_demo_ci";
op.SupportPackageRoot = "C:\\ProgramData\\MATLAB\\SupportPackages\\R2025a\\bin";

Use a shared network location for your artifacts by specifying the NetworkStoragePath property. For this example, suppose you have a shared network location /artifactManagement/cacheStorage.

op.NetworkStoragePath = "/artifactManagement/cacheStorage"

Generate the pipeline file and supporting files.

padv.pipeline.generatePipeline(op);

The pipeline generator generates a pipeline file, simulink_pipeline.yml, and two supporting files, ir_dag.json and generic-job.yml, which define the pipeline for your specific project, process model, and pipeline generator options.

Generate GitHub Pipeline File with JFrog Artifactory Integration

This example code shows how to configure and generate a GitHub pipeline file using Pipeline Generator Version 2 and JFrog Artifactory. For the complete example, see Process Integration and Artifact Management for GitHub.

Represent your pipeline generator options by creating a padv.pipeline.GitHubOptions object for pipeline generator version 2.

op = padv.pipeline.GitHubOptions(GeneratorVersion=2);

Configure the pipeline generator to use your GitHub runner and support package installation by specifying the properties RunnerLabels and SupportPackageRoot. You can find the location of your support package root by using the function matlabshared.supportpkg.getSupportPackageRoot on your build agent.

op.RunnerLabels = "padv_demo_ci";
op.SupportPackageRoot = "C:\\ProgramData\\MATLAB\\SupportPackages\\R2025a\\bin";

Use a JFrog Artifactory repository for your artifacts by specifying the ArtifactServiceMode property as "jfrog" and specifying the properties ArtifactoryUrl and ArtifactoryRepoName.

op.ArtifactServiceMode = "jfrog";
op.ArtifactoryUrl = "http://localhost:8082/artifactory";
op.ArtifactoryRepoName = "example-repo-local";

Generate the pipeline file and supporting files.

padv.pipeline.generatePipeline(op);

The pipeline generator generates a pipeline file, simulink_pipeline.yml, and two supporting files, ir_dag.json and generic-job.yml, which define the pipeline for your specific project, process model, and pipeline generator options.

Generate GitHub Pipeline File with Amazon S3 Integration

This example code shows how to configure and generate a GitHub pipeline file using Pipeline Generator Version 2 and Amazon S3 storage. For the complete example, see Process Integration and Artifact Management for GitHub.

Represent your pipeline generator options by creating a padv.pipeline.GitHubOptions object for pipeline generator version 2.

op = padv.pipeline.GitHubOptions(GeneratorVersion=2);

Configure the pipeline generator to use your GitHub runner and support package installation by specifying the properties RunnerLabels and SupportPackageRoot. You can find the location of your support package root by using the function matlabshared.supportpkg.getSupportPackageRoot on your build agent.

op.RunnerLabels = "padv_demo_ci";
op.SupportPackageRoot = "C:\\ProgramData\\MATLAB\\SupportPackages\\R2025a\\bin";

Use Amazon S3 storage for your artifacts by specifying the ArtifactServiceMode property as "s3" and specifying the properties S3BucketName and S3AwsAccessKeyID.

op.ArtifactServiceMode = "s3";
op.S3BucketName = "my-artifacts-bucket";
op.S3AwsAccessKeyID = "AKIAIOSFODNN7EXAMPLE";

Generate the pipeline file and supporting files.

padv.pipeline.generatePipeline(op);

The pipeline generator generates a pipeline file, simulink_pipeline.yml, and two supporting files, ir_dag.json and generic-job.yml, which define the pipeline for your specific project, process model, and pipeline generator options.

Generate GitHub Pipeline File with Azure Blob Storage Integration

This example code shows how to configure and generate a GitHub pipeline file using Pipeline Generator Version 2 and Azure Blob Storage. For the complete example, see Process Integration and Artifact Management for GitHub.

Represent your pipeline generator options by creating a padv.pipeline.GitHubOptions object for pipeline generator version 2.

op = padv.pipeline.GitHubOptions(GeneratorVersion=2);

Configure the pipeline generator to use your GitHub runner and support package installation by specifying the properties RunnerLabels and SupportPackageRoot. You can find the location of your support package root by using the function matlabshared.supportpkg.getSupportPackageRoot on your build agent.

op.RunnerLabels = "padv_demo_ci";
op.SupportPackageRoot = "C:\\ProgramData\\MATLAB\\SupportPackages\\R2025a\\bin";

Use Azure Blob Storage storage for your artifacts by specifying the ArtifactServiceMode property as "azure_blob" and specifying the property AzContainerName.

ops.ArtifactServiceMode = "azure_blob";
ops.AzContainerName = "mycontainer";

Generate the pipeline file and supporting files.

padv.pipeline.generatePipeline(op);

The pipeline generator generates a pipeline file, simulink_pipeline.yml, and two supporting files, ir_dag.json and generic-job.yml, which define the pipeline for your specific project, process model, and pipeline generator options.

Version History

R2025a: Migrate from repository variables to GitHubOptions properties for Pipeline Generator Version 2

Starting in September 2025, the setup and requirements for pipeline generator 2 have changed. Update your setup and code as shown in Process Integration and Artifact Management for GitHub.

Previously, you provided configuration details using repository variables. Now, you must specify these details as properties of your pipeline generation options object, padv.pipeline.GitHubOptions.

Previous Repository Variable	Use This padv.pipeline.GitHubOptions Property Instead
ARTIFACT_SERVICE_MODE	ArtifactServiceMode
NETWORK_STORAGE_PATH	NetworkStoragePath
PATH_TO_MATLAB	No longer used. Make sure MATLAB is available on the system PATH for the build agent.
PYTHON_ALIAS	No longer used. The pipeline generator expects the alias python3.
RUNNER_LABEL	RunnerLabels
SUPPORT_PACKAGE_ROOT	SupportPackageRoot

R2025a: Generate pipelines that use a specific container image

Starting in September 2025, Pipeline Generator Version 2 supports generating pipelines that use a specific container image. For example:

options = padv.pipeline.GitHubOptions(GeneratorVersion=2);
options.RunnerType = "container";
options.ImageTag = "mycompany/docker-pipeline-runner:latest";

R2025a: Store artifacts in Amazon S3 buckets or Azure Blob Storage containers

Starting in September 2025, Pipeline Generator Version 2 supports storing artifacts in:

• Amazon S3 buckets. For example:

  options = padv.pipeline.GitHubOptions(GeneratorVersion=2);
  options.ArtifactServiceMode = "s3";
  options.S3AwsAccessKeyID = "AKIAIOSFODNN7EXAMPLE";
  options.S3BucketName = "my-artifacts-bucket";

• Azure Blob Storage containers. For example:

  options = padv.pipeline.GitHubOptions(GeneratorVersion=2);
  options.ArtifactServiceMode = "azure_blob";
  options.AzContainerName = "mycontainer";

R2025a: Support for projects in subfolders of the repository root

Starting in September 2025, Pipeline Generator Version 2 supports projects where the project root folder is in a subfolder of the repository root. Specify the relative path from the repository root to your project by using the RelativeProjectPath property.

options = padv.pipeline.GitHubOptions(GeneratorVersion=2);
% Suppose the full path to the project root is:
% "/home/user/repo-root/src/myproject"
options.RelativeProjectPath = "src/myproject";

R2024b: Pipeline Generator Version 2 introduced

Starting in April 2025, the CI Support Package for Simulink^® includes version 2 of the pipeline generator. Pipeline Generator Version 2 includes enhanced features like external artifact management with JFrog Artifactory.

To upgrade to version 2, see Process Integration and Artifact Management for GitHub. Otherwise, specify the GeneratorVersion property as 1 to keep the original pipeline generator functionality.

R2024a: Property GenerateJUnitForProcess will be removed

The property GenerateJUnitForProcess will be removed in a future release.

To control how generated pipelines invoke the runprocess function, use the RunprocessCommandOptions property instead.

Functionality	Use This Instead
op = padv.pipeline.GitHubOptions(GenerateJUnitForProcess=false)	rpo = padv.pipeline.RunProcessOptions; rpo.GenerateJUnitForProcess = false; op = padv.pipeline.GitHubOptions(RunprocessCommandOptions=rpo)