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chore: Set Python 3.9 as the Minimum Supported Version #120

chore: Set Python 3.9 as the Minimum Supported Version

chore: Set Python 3.9 as the Minimum Supported Version #120

Workflow file for this run

name: KFP e2e tests
on:
push:
branches: [master]
pull_request:
paths:
- '.github/workflows/e2e-test.yml'
- 'scripts/deploy/github/**'
- 'go.mod'
- 'go.sum'
- 'backend/**'
- 'frontend/**'
- 'proxy/**'
- 'manifests/kustomize/**'
- 'test/**'
jobs:
initialization-tests-v1:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.9
- name: Create KFP cluster
uses: ./.github/actions/kfp-cluster
- name: Forward API port
run: ./scripts/deploy/github/forward-port.sh "kubeflow" "ml-pipeline" 8888 8888
- name: Initialization tests v1
working-directory: ./backend/test/initialization
run: go test -v ./... -namespace kubeflow -args -runIntegrationTests=true
- name: Collect test results
if: always()
uses: actions/upload-artifact@v4
with:
name: kfp-initialization-tests-v1-artifacts
path: /tmp/tmp.*/*
initialization-tests-v2:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.9
- name: Create KFP cluster
uses: ./.github/actions/kfp-cluster
- name: Forward API port
run: ./scripts/deploy/github/forward-port.sh "kubeflow" "ml-pipeline" 8888 8888
- name: Initialization tests v2
working-directory: ./backend/test/v2/initialization
run: go test -v ./... -namespace kubeflow -args -runIntegrationTests=true
- name: Collect test results
if: always()
uses: actions/upload-artifact@v4
with:
name: kfp-initialization-tests-v2-artifacts
path: /tmp/tmp.*/*
api-integration-tests-v1:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.9
- name: Create KFP cluster
uses: ./.github/actions/kfp-cluster
- name: Forward API port
run: ./scripts/deploy/github/forward-port.sh "kubeflow" "ml-pipeline" 8888 8888
- name: API integration tests v1
working-directory: ./backend/test/integration
run: go test -v ./... -namespace ${NAMESPACE} -args -runIntegrationTests=true
- name: Collect test results
if: always()
uses: actions/upload-artifact@v4
with:
name: kfp-api-integration-tests-v1-artifacts
path: /tmp/tmp.*/*
api-integration-tests-v2:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.9
- name: Create KFP cluster
uses: ./.github/actions/kfp-cluster
- name: Forward API port
run: ./scripts/deploy/github/forward-port.sh "kubeflow" "ml-pipeline" 8888 8888
- name: API integration tests v2
working-directory: ./backend/test/v2/integration
run: go test -v ./... -namespace ${NAMESPACE} -args -runIntegrationTests=true
- name: Collect test results
if: always()
uses: actions/upload-artifact@v4
with:
name: kfp-api-integration-tests-v2-artifacts
path: /tmp/tmp.*/*
frontend-integration-test:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.9
- name: Create KFP cluster
uses: ./.github/actions/kfp-cluster
- name: Forward API port
run: ./scripts/deploy/github/forward-port.sh "kubeflow" "ml-pipeline" 8888 8888
- name: Forward Frontend port
run: ./scripts/deploy/github/forward-port.sh "kubeflow" "ml-pipeline-ui" 3000 3000
- name: Build frontend integration tests image
working-directory: ./test/frontend-integration-test
run: docker build . -t kfp-frontend-integration-test:local
- name: Frontend integration tests
run: docker run --net=host kfp-frontend-integration-test:local --remote-run true
- name: Collect test results
if: always()
uses: actions/upload-artifact@v4
with:
name: kfp-frontend-integration-test-artifacts
path: /tmp/tmp.*/*
basic-sample-tests:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.9
- name: Create KFP cluster
uses: ./.github/actions/kfp-cluster
- name: Forward API port
run: ./scripts/deploy/github/forward-port.sh "kubeflow" "ml-pipeline" 8888 8888
- name: Install prerequisites
run: pip3 install -r ./test/sample-test/requirements.txt
- name: Basic sample tests - sequential
run: python3 ./test/sample-test/sample_test_launcher.py sample_test run_test --namespace kubeflow --test-name sequential --results-gcs-dir output
- name: Basic sample tests - exit_handler
run: python3 ./test/sample-test/sample_test_launcher.py sample_test run_test --namespace kubeflow --test-name exit_handler --results-gcs-dir output
- name: Collect test results
if: always()
uses: actions/upload-artifact@v4
with:
name: kfp-basic-sample-tests-artifacts
path: /tmp/tmp.*/*