Python

You can build and test a Python application using a Linux platform on Harness Cloud or a self-managed Kubernetes cluster build infrastructure.

This guide assumes you've created a Harness CI pipeline.

Install dependencies

Use Run steps to install dependencies in the build environment.

Harness Cloud

- step:
    type: Run
    identifier: dependencies
    name: Dependencies
    spec:
      shell: Sh
      command: |-
        python -m pip install --upgrade pip
        pip install -r requirements.txt
      envVariables:
        PIP_CACHE_DIR: "/root/.cache"

Self-managed

- step:
    type: Run
    identifier: dependencies
    name: Dependencies
    spec:
      connectorRef: YOUR_IMAGE_REGISTRY_CONNECTOR
      image: python:latest
      command: |-
        python -m pip install --upgrade pip
        pip install -r requirements.txt

tip

Background steps can be used to run dependent services that are needed by steps in the same stage.

Cache dependencies

Add caching to your stage.

Cache Intelligence

Cache your Python module dependencies with Cache Intelligence.

Add caching to your stage.spec:

- stage:
    spec:
      caching:
        enabled: true
        key: cache-{{ checksum "requirements.txt" }}
        paths:
          - "/root/.cache"
      sharedPaths:
        - /root/.cache

Save and Restore Cache steps

You can use built-in steps to:

• Save and Restore Cache from S3
• Save and Restore Cache from GCS

Python cache key and path requirements

Python pipelines typically reference requirements.txt in Save Cache and Restore Cache steps, for example:

spec:
  key: cache-{{ checksum "requirements.txt" }}

Additionally, spec.sourcePaths must include the python cache (typically /root/.cache) in the Save Cache step, for example:

spec:
  sourcePaths:
    - "/root/.cache"

YAML example: Save and restore cache steps

Here's an example of a pipeline with Save Cache to S3 and Restore Cache from S3 steps.

            steps:
              - step:
                  type: RestoreCacheS3
                  name: Restore Cache From S3
                  identifier: Restore_Cache_From_S3
                  spec:
                    connectorRef: AWS_Connector
                    region: us-east-1
                    bucket: your-s3-bucket
                    key: cache-{{ checksum "requirements.txt" }}
                    archiveFormat: Tar
              - step:
                  type: Run
                    envVariables:
                      PIP_CACHE_DIR: "/root/.cache"
                  ...
              - step:
                  type: SaveCacheS3
                  name: Save Cache to S3
                  identifier: Save_Cache_to_S3
                  spec:
                    connectorRef: AWS_Connector
                    region: us-east-1
                    bucket: your-s3-bucket
                    key: cache-{{ checksum "requirements.txt" }}
                    sourcePaths:
                      - "/root/.cache"
                    archiveFormat: Tar

Run tests

You can use Run and Test steps to run tests in Harness CI.

These examples run tests in a Run step.

Harness Cloud

- step:
    type: Run
    name: Test
    identifier: test
    spec:
      shell: Sh
      command: |-
        pip install pytest
        pytest tests.py --junit-xml=report.xml
      envVariables:
        PIP_CACHE_DIR: /root/.cache

Self-managed

- step:
    type: Run
    name: Test
    identifier: test
    spec:
      connectorRef: YOUR_IMAGE_REGISTRY_CONNECTOR
      image: python:latest
      shell: Sh
      command: |-
        python -m pip install --upgrade pip
        pip install -r requirements.txt
        pip install pytest
        pytest tests.py --junit-xml=report.xml

Visualize test results

If you want to view test results in Harness, make sure your test commands produce reports in JUnit XML format.

If you run tests in a Run step, your Run step must include the reports specification. The reports specification is not required for Test steps (Test Intelligence).

reports:
  type: JUnit
  spec:
    paths:
      - report.xml

Run tests with Test Intelligence

Test Intelligence is available for Python.

              - step:
                  type: Test
                  name: runTestsWithIntelligence
                  identifier: runTestsWithIntelligence
                  spec:
                    connectorRef: YOUR_IMAGE_REGISTRY_CONNECTOR
                    image: python:latest
                    command: |-
                      python3 -m venv .venv
                      . .venv/bin/activate

                      python3 -m pip install -r requirements/test.txt
                      python3 -m pip install -e .

                      pytest
                    shell: Python
                    intelligenceMode: true

Test splitting

Harness CI supports test splitting (parallelism) for both Run and Test steps.

Specify version

Harness Cloud

Python is pre-installed on Harness Cloud runners. For details about all available tools and versions, go to Platforms and image specifications.

If your application requires a specific Python version, add a Run or GitHub Action step to install it.

Use the setup-python action in a GitHub Action step to install the required Python version.

You will need a personal access token, stored as a secret, with read-only access for GitHub authentication.

Install one Python version

- step:
    type: Action
    name: Install python
    identifier: installpython
    spec:
      uses: actions/setup-python@v4
      with:
        python-version: 3.10.10
        token: <+ secrets.getValue("github_token") >

Install multiple Python versions

1. Add the matrix looping strategy configuration to your stage.

- stage:
    strategy:
      matrix:
        pythonVersion:
          - 3.11.2
          - 3.10.10

2. Reference the matrix variable in your steps.

- step:
    type: Action
    name: Install python
    identifier: installpython
    spec:
      uses: actions/setup-python@v4
      with:
        python-version: <+ stage.matrix.pythonVersion >
        token: <+ secrets.getValue("github_token") >

Self-managed

Specify the desired Python Docker image tag in your steps. There is no need for a separate install step when using Docker.

Use a specific Python version

- step:
    type: Run
    name: Python Version
    identifier: pythonversion
    spec:
      connectorRef: YOUR_IMAGE_REGISTRY_CONNECTOR
      image: python:3.10.10
      shell: Sh
      command: |-
        python --version

Use multiple Python versions

1. Add the matrix looping strategy configuration to your stage.

- stage:
    strategy:
      matrix:
        pythonVersion:
          - 3.11.2
          - 3.10.10

2. Reference the matrix variable in the image field of your steps.

- step:
    type: Run
    name: Python Version
    identifier: pythonversion
    spec:
      connectorRef: YOUR_IMAGE_REGISTRY_CONNECTOR
      image: python:<+ stage.matrix.pythonVersion >
      shell: Sh
      command: |-
        python --version

Full pipeline examples

The following full pipeline examples are based on the partial examples above.

Harness Cloud

This pipeline uses Harness Cloud build infrastructure and Cache Intelligence.

If you copy this example, replace the placeholder values with appropriate values for your code repo connector and repository name. Depending on your project and organization, you may also need to replace projectIdentifier and orgIdentifier.

Pipeline with default Python version

pipeline:
  name: Test a Python app
  identifier: Test_a_Python_app
  projectIdentifier: default
  orgIdentifier: default
  stages:
    - stage:
        name: Test
        identifier: test
        description: ""
        type: CI
        spec:
          cloneCodebase: true
          caching:
            enabled: true
            key: cache-{{ checksum "requirements.txt" }}
            paths:
              - "/root/.cache"
          execution:
            steps:
              - step:
                  type: Run
                  identifier: dependencies
                  name: Dependencies
                  spec:
                    shell: Sh
                    command: |-
                      python -m pip install --upgrade pip
                      pip install -r requirements.txt
                    envVariables:
                      PIP_CACHE_DIR: "/root/.cache"
              - step:
                  type: Run
                  name: Test
                  identifier: test
                  spec:
                    shell: Sh
                    command: |-
                      pip install pytest
                      pytest tests.py --junit-xml=report.xml
                    envVariables:
                      PIP_CACHE_DIR: /root/.cache
                    reports:
                      type: JUnit
                      spec:
                        paths:
                          - report.xml
          platform:
            os: Linux
            arch: Amd64
          runtime:
            type: Cloud
            spec: {}
          sharedPaths:
            - /root/.cache
  properties:
    ci:
      codebase:
        connectorRef: YOUR_CODE_REPO_CONNECTOR_ID
        repoName: YOUR_REPO_NAME
        build: <+input>

Pipeline with multiple Python versions

pipeline:
  name: Test a Python app
  identifier: Test_a_Python_app
  projectIdentifier: default
  orgIdentifier: default
  stages:
    - stage:
        name: Test
        identifier: test
        description: ""
        type: CI
        strategy:
          matrix:
            pythonVersion:
              - 3.11.2
              - 3.10.10
        spec:
          cloneCodebase: true
          caching:
            enabled: true
            key: cache-{{ checksum "requirements.txt" }}
            paths:
              - "/root/.cache"
          execution:
            steps:
              - step:
                  type: Action
                  name: Install python
                  identifier: installpython
                  spec:
                    uses: actions/setup-python@v4
                    with:
                      python-version: <+ stage.matrix.pythonVersion >
                      token: <+ secrets.getValue("github_token") >
              - step:
                  type: Run
                  identifier: dependencies
                  name: Dependencies
                  spec:
                    shell: Sh
                    command: |-
                      python -m pip install --upgrade pip
                      pip install -r requirements.txt
                    envVariables:
                      PIP_CACHE_DIR: "/root/.cache"
              - step:
                  type: Run
                  name: Test
                  identifier: test
                  spec:
                    shell: Sh
                    command: |-
                      pip install pytest
                      pytest tests.py --junit-xml=report.xml
                    envVariables:
                      PIP_CACHE_DIR: /root/.cache
                    reports:
                      type: JUnit
                      spec:
                        paths:
                          - report.xml
          platform:
            os: Linux
            arch: Amd64
          runtime:
            type: Cloud
            spec: {}
          sharedPaths:
            - /root/.cache
  properties:
    ci:
      codebase:
        connectorRef: YOUR_CODE_REPO_CONNECTOR_ID
        repoName: YOUR_REPO_NAME
        build: <+input>

Self-managed

If you copy this example, replace the placeholder values with appropriate values for your code repo connector, kubernetes cluster connector, kubernetes namespace, and repository name. Depending on your project and organization, you may also need to replace projectIdentifier and orgIdentifier.

Pipeline with one specific Python version

Here is a single-stage pipeline, with steps that use Python 3.10.10.

pipeline:
  identifier: Test a Python app
  name: Test_a_Python_app
  orgIdentifier: default
  projectIdentifier: default
  stages:
    - stage:
        identifier: default
        name: default
        spec:
          cloneCodebase: true
          execution:
            steps:
              - step:
                  type: Run
                  name: Test
                  identifier: test
                  spec:
                    connectorRef: YOUR_IMAGE_REGISTRY_CONNECTOR
                    image: python:3.10.10
                    shell: Sh
                    command: |-
                      pip install pytest
                      pytest tests.py --junit-xml=report.xml
                    reports:
                      type: JUnit
                      spec:
                        paths:
                          - "report.xml"
          infrastructure:
            type: KubernetesDirect
            spec:
              connectorRef: YOUR_KUBERNETES_CLUSTER_CONNECTOR_ID
              namespace: YOUR_KUBERNETES_NAMESPACE
              automountServiceAccountToken: true
              nodeSelector: {}
              os: Linux
        type: CI
  properties:
    ci:
      codebase:
        connectorRef: YOUR_CODE_REPO_CONNECTOR_ID
        repoName: YOUR_REPO_NAME
        build: <+input>

Pipeline with multiple Python versions

Here is a single-stage pipeline, with a matrix looping strategy for Python versions 3.11.2 and 3.10.10.

pipeline:
  identifier: Test a Python app
  name: Test_a_Python_app
  orgIdentifier: default
  projectIdentifier: default
  stages:
    - stage:
        strategy:
          matrix:
            pythonVersion:
              - 3.11.2
              - 3.10.10
        identifier: default
        name: default
        spec:
          cloneCodebase: true
          execution:
            steps:
              - step:
                  type: Run
                  name: Test
                  identifier: test
                  spec:
                    connectorRef: YOUR_IMAGE_REGISTRY_CONNECTOR
                    image: python:<+ stage.matrix.pythonVersion >
                    shell: Sh
                    command: |-
                      python -m pip install --upgrade pip
                      pip install -r requirements.txt
                      pip install pytest
                      pytest tests.py --junit-xml=report.xml
                    reports:
                      type: JUnit
                      spec:
                        paths:
                          - "report.xml"
          infrastructure:
            type: KubernetesDirect
            spec:
              connectorRef: YOUR_KUBERNETES_CLUSTER_CONNECTOR_ID
              namespace: YOUR_KUBERNETES_NAMESPACE
              automountServiceAccountToken: true
              nodeSelector: {}
              os: Linux
        type: CI
  properties:
    ci:
      codebase:
        connectorRef: YOUR_CODE_REPO_CONNECTOR_ID
        repoName: YOUR_REPO_NAME
        build: <+input>

Next steps

Now that you have created a pipeline that builds and tests a Python app, you could:

• Create triggers to automatically run your pipeline.
• Add steps to build and upload artifacts.
• Add a step to build and push an image to a Docker registry.