diff --git a/.github/workflows/coverage-badge.yaml b/.github/workflows/coverage-badge.yaml
index 2c3b40fa..2a92010b 100644
--- a/.github/workflows/coverage-badge.yaml
+++ b/.github/workflows/coverage-badge.yaml
@@ -9,6 +9,9 @@ on:
jobs:
report:
+ permissions:
+ contents: write
+ pull-requests: write
runs-on: ubuntu-latest
steps:
@@ -47,7 +50,14 @@ jobs:
- name: Create Pull Request
if: steps.changed_files.outputs.files_changed == 'true'
- uses: peter-evans/create-pull-request@v4
+ uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.GITHUB_TOKEN }}
title: "[Automatic] Coverage Badge Update"
+ commit-message: "Updated coverage.svg"
+ branch: create-pull-request/coverage-badge-update
+ delete-branch: true
+ body: |
+ This is an automated pull request to update the coverage badge.
+
+ - Updated coverage.svg based on latest test results
diff --git a/.github/workflows/e2e_tests.yaml b/.github/workflows/e2e_tests.yaml
index ba59a9e1..44bf1214 100644
--- a/.github/workflows/e2e_tests.yaml
+++ b/.github/workflows/e2e_tests.yaml
@@ -5,13 +5,13 @@ on:
pull_request:
branches:
- main
- - 'release-*'
+ - "release-*"
- ray-jobs-feature
paths-ignore:
- - 'docs/**'
- - '**.adoc'
- - '**.md'
- - 'LICENSE'
+ - "docs/**"
+ - "**.adoc"
+ - "**.md"
+ - "LICENSE"
concurrency:
group: ${{ github.head_ref }}-${{ github.workflow }}
@@ -33,9 +33,9 @@ jobs:
- name: Checkout common repo code
uses: actions/checkout@v4
with:
- repository: 'project-codeflare/codeflare-common'
- ref: 'main'
- path: 'common'
+ repository: "project-codeflare/codeflare-common"
+ ref: "main"
+ path: "common"
- name: Checkout CodeFlare operator repository
uses: actions/checkout@v4
@@ -46,7 +46,7 @@ jobs:
- name: Set Go
uses: actions/setup-go@v5
with:
- go-version-file: './codeflare-operator/go.mod'
+ go-version-file: "./codeflare-operator/go.mod"
cache-dependency-path: "./codeflare-operator/go.sum"
- name: Set up gotestfmt
@@ -76,7 +76,7 @@ jobs:
run: |
cd codeflare-operator
echo Setting up CodeFlare stack
- make setup-e2e
+ make setup-e2e KUEUE_VERSION=v0.13.4 KUBERAY_VERSION=v1.4.0
echo Deploying CodeFlare operator
make deploy -e IMG="${CODEFLARE_OPERATOR_IMG}" -e ENV="e2e"
kubectl wait --timeout=120s --for=condition=Available=true deployment -n openshift-operators codeflare-operator-manager
@@ -95,6 +95,10 @@ jobs:
kubectl create clusterrolebinding sdk-user-namespace-creator --clusterrole=namespace-creator --user=sdk-user
kubectl create clusterrole raycluster-creator --verb=get,list,create,delete,patch --resource=rayclusters
kubectl create clusterrolebinding sdk-user-raycluster-creator --clusterrole=raycluster-creator --user=sdk-user
+ kubectl create clusterrole rayjob-creator --verb=get,list,create,delete,patch --resource=rayjobs
+ kubectl create clusterrolebinding sdk-user-rayjob-creator --clusterrole=rayjob-creator --user=sdk-user
+ kubectl create clusterrole rayjob-status-reader --verb=get,list,patch,update --resource=rayjobs/status
+ kubectl create clusterrolebinding sdk-user-rayjob-status-reader --clusterrole=rayjob-status-reader --user=sdk-user
kubectl create clusterrole appwrapper-creator --verb=get,list,create,delete,patch --resource=appwrappers
kubectl create clusterrolebinding sdk-user-appwrapper-creator --clusterrole=appwrapper-creator --user=sdk-user
kubectl create clusterrole resourceflavor-creator --verb=get,list,create,delete --resource=resourceflavors
@@ -122,7 +126,7 @@ jobs:
pip install poetry
poetry install --with test,docs
echo "Running e2e tests..."
- poetry run pytest -v -s ./tests/e2e -m 'kind and nvidia_gpu' > ${CODEFLARE_TEST_OUTPUT_DIR}/pytest_output.log 2>&1
+ poetry run pytest -v -s ./tests/e2e/ -m 'kind and nvidia_gpu' > ${CODEFLARE_TEST_OUTPUT_DIR}/pytest_output.log 2>&1
env:
GRPC_DNS_RESOLVER: "native"
@@ -146,7 +150,13 @@ jobs:
if: always() && steps.deploy.outcome == 'success'
run: |
echo "Printing KubeRay operator logs"
- kubectl logs -n ray-system --tail -1 -l app.kubernetes.io/name=kuberay | tee ${CODEFLARE_TEST_OUTPUT_DIR}/kuberay.log
+ kubectl logs -n default --tail -1 -l app.kubernetes.io/name=kuberay | tee ${CODEFLARE_TEST_OUTPUT_DIR}/kuberay.log
+
+ - name: Print Kueue controller logs
+ if: always() && steps.deploy.outcome == 'success'
+ run: |
+ echo "Printing Kueue controller logs"
+ kubectl logs -n kueue-system --tail -1 -l control-plane=controller-manager | tee ${CODEFLARE_TEST_OUTPUT_DIR}/kueue.log
- name: Export all KinD pod logs
uses: ./common/github-actions/kind-export-logs
diff --git a/.github/workflows/rayjob_e2e_tests.yaml b/.github/workflows/rayjob_e2e_tests.yaml
new file mode 100644
index 00000000..ba0659c0
--- /dev/null
+++ b/.github/workflows/rayjob_e2e_tests.yaml
@@ -0,0 +1,176 @@
+# rayjob e2e tests workflow for CodeFlare-SDK
+name: rayjob-e2e
+
+on:
+ pull_request:
+ branches:
+ - main
+ - "release-*"
+ - ray-jobs-feature
+ paths-ignore:
+ - "docs/**"
+ - "**.adoc"
+ - "**.md"
+ - "LICENSE"
+
+concurrency:
+ group: ${{ github.head_ref }}-${{ github.workflow }}
+ cancel-in-progress: true
+
+env:
+ CODEFLARE_OPERATOR_IMG: "quay.io/project-codeflare/codeflare-operator:dev"
+
+jobs:
+ kubernetes-rayjob:
+ runs-on: gpu-t4-4-core
+
+ steps:
+ - name: Checkout code
+ uses: actions/checkout@v4
+ with:
+ submodules: recursive
+
+ - name: Checkout common repo code
+ uses: actions/checkout@v4
+ with:
+ repository: "project-codeflare/codeflare-common"
+ ref: "main"
+ path: "common"
+
+ - name: Checkout CodeFlare operator repository
+ uses: actions/checkout@v4
+ with:
+ repository: project-codeflare/codeflare-operator
+ path: codeflare-operator
+
+ - name: Set Go
+ uses: actions/setup-go@v5
+ with:
+ go-version-file: "./codeflare-operator/go.mod"
+ cache-dependency-path: "./codeflare-operator/go.sum"
+
+ - name: Set up gotestfmt
+ uses: gotesttools/gotestfmt-action@v2
+ with:
+ token: ${{ secrets.GITHUB_TOKEN }}
+
+ - name: Set up specific Python version
+ uses: actions/setup-python@v5
+ with:
+ python-version: "3.11"
+ cache: "pip" # caching pip dependencies
+
+ - name: Setup NVidia GPU environment for KinD
+ uses: ./common/github-actions/nvidia-gpu-setup
+
+ - name: Setup and start KinD cluster
+ uses: ./common/github-actions/kind
+ with:
+ worker-nodes: 1
+
+ - name: Install NVidia GPU operator for KinD
+ uses: ./common/github-actions/nvidia-gpu-operator
+
+ - name: Deploy CodeFlare stack
+ id: deploy
+ run: |
+ cd codeflare-operator
+ echo Setting up CodeFlare stack
+ make setup-e2e KUEUE_VERSION=v0.13.4 KUBERAY_VERSION=v1.4.0
+ echo Deploying CodeFlare operator
+ make deploy -e IMG="${CODEFLARE_OPERATOR_IMG}" -e ENV="e2e"
+ kubectl wait --timeout=120s --for=condition=Available=true deployment -n openshift-operators codeflare-operator-manager
+ cd ..
+
+ - name: Add user to KinD
+ uses: ./common/github-actions/kind-add-user
+ with:
+ user-name: sdk-user
+
+ - name: Configure RBAC for sdk user with limited permissions
+ run: |
+ kubectl create clusterrole list-ingresses --verb=get,list --resource=ingresses
+ kubectl create clusterrolebinding sdk-user-list-ingresses --clusterrole=list-ingresses --user=sdk-user
+ kubectl create clusterrole namespace-creator --verb=get,list,create,delete,patch --resource=namespaces
+ kubectl create clusterrolebinding sdk-user-namespace-creator --clusterrole=namespace-creator --user=sdk-user
+ kubectl create clusterrole raycluster-creator --verb=get,list,create,delete,patch --resource=rayclusters
+ kubectl create clusterrolebinding sdk-user-raycluster-creator --clusterrole=raycluster-creator --user=sdk-user
+ kubectl create clusterrole rayjob-creator --verb=get,list,create,delete,patch --resource=rayjobs
+ kubectl create clusterrolebinding sdk-user-rayjob-creator --clusterrole=rayjob-creator --user=sdk-user
+ kubectl create clusterrole rayjob-status-reader --verb=get,list,patch,update --resource=rayjobs/status
+ kubectl create clusterrolebinding sdk-user-rayjob-status-reader --clusterrole=rayjob-status-reader --user=sdk-user
+ kubectl create clusterrole appwrapper-creator --verb=get,list,create,delete,patch --resource=appwrappers
+ kubectl create clusterrolebinding sdk-user-appwrapper-creator --clusterrole=appwrapper-creator --user=sdk-user
+ kubectl create clusterrole resourceflavor-creator --verb=get,list,create,delete --resource=resourceflavors
+ kubectl create clusterrolebinding sdk-user-resourceflavor-creator --clusterrole=resourceflavor-creator --user=sdk-user
+ kubectl create clusterrole clusterqueue-creator --verb=get,list,create,delete,patch --resource=clusterqueues
+ kubectl create clusterrolebinding sdk-user-clusterqueue-creator --clusterrole=clusterqueue-creator --user=sdk-user
+ kubectl create clusterrole localqueue-creator --verb=get,list,create,delete,patch --resource=localqueues
+ kubectl create clusterrolebinding sdk-user-localqueue-creator --clusterrole=localqueue-creator --user=sdk-user
+ kubectl create clusterrole list-secrets --verb=get,list --resource=secrets
+ kubectl create clusterrolebinding sdk-user-list-secrets --clusterrole=list-secrets --user=sdk-user
+ kubectl create clusterrole pod-creator --verb=get,list,watch --resource=pods
+ kubectl create clusterrolebinding sdk-user-pod-creator --clusterrole=pod-creator --user=sdk-user
+ kubectl create clusterrole service-reader --verb=get,list,watch --resource=services
+ kubectl create clusterrolebinding sdk-user-service-reader --clusterrole=service-reader --user=sdk-user
+ kubectl create clusterrole port-forward-pods --verb=create --resource=pods/portforward
+ kubectl create clusterrolebinding sdk-user-port-forward-pods-binding --clusterrole=port-forward-pods --user=sdk-user
+ kubectl create clusterrole secret-manager --verb=get,list,create,delete,update,patch --resource=secrets
+ kubectl create clusterrolebinding sdk-user-secret-manager --clusterrole=secret-manager --user=sdk-user
+ kubectl create clusterrole workload-reader --verb=get,list,watch --resource=workloads
+ kubectl create clusterrolebinding sdk-user-workload-reader --clusterrole=workload-reader --user=sdk-user
+ kubectl config use-context sdk-user
+
+ - name: Run RayJob E2E tests
+ run: |
+ export CODEFLARE_TEST_OUTPUT_DIR=${{ env.TEMP_DIR }}
+ echo "CODEFLARE_TEST_OUTPUT_DIR=${CODEFLARE_TEST_OUTPUT_DIR}" >> $GITHUB_ENV
+
+ set -euo pipefail
+ pip install poetry
+ poetry install --with test,docs
+ echo "Running RayJob e2e tests..."
+ poetry run pytest -v -s ./tests/e2e/rayjob/ > ${CODEFLARE_TEST_OUTPUT_DIR}/pytest_output_rayjob.log 2>&1
+
+ - name: Switch to kind-cluster context to print logs
+ if: always() && steps.deploy.outcome == 'success'
+ run: kubectl config use-context kind-cluster
+
+ - name: Print Pytest output log
+ if: always() && steps.deploy.outcome == 'success'
+ run: |
+ echo "Printing Pytest output logs"
+ cat ${CODEFLARE_TEST_OUTPUT_DIR}/pytest_output_rayjob.log
+
+ - name: Print CodeFlare operator logs
+ if: always() && steps.deploy.outcome == 'success'
+ run: |
+ echo "Printing CodeFlare operator logs"
+ kubectl logs -n openshift-operators --tail -1 -l app.kubernetes.io/name=codeflare-operator | tee ${CODEFLARE_TEST_OUTPUT_DIR}/codeflare-operator.log
+
+ - name: Print KubeRay operator logs
+ if: always() && steps.deploy.outcome == 'success'
+ run: |
+ echo "Printing KubeRay operator logs"
+ kubectl logs -n default --tail -1 -l app.kubernetes.io/name=kuberay | tee ${CODEFLARE_TEST_OUTPUT_DIR}/kuberay.log
+
+ - name: Print Kueue controller logs
+ if: always() && steps.deploy.outcome == 'success'
+ run: |
+ echo "Printing Kueue controller logs"
+ kubectl logs -n kueue-system --tail -1 -l control-plane=controller-manager | tee ${CODEFLARE_TEST_OUTPUT_DIR}/kueue.log
+
+ - name: Export all KinD pod logs
+ uses: ./common/github-actions/kind-export-logs
+ if: always() && steps.deploy.outcome == 'success'
+ with:
+ output-directory: ${CODEFLARE_TEST_OUTPUT_DIR}
+
+ - name: Upload logs
+ uses: actions/upload-artifact@v4
+ if: always() && steps.deploy.outcome == 'success'
+ with:
+ name: logs
+ retention-days: 10
+ path: |
+ ${{ env.CODEFLARE_TEST_OUTPUT_DIR }}/**/*.log
diff --git a/codecov.yml b/codecov.yml
index 550965e6..4494dcd4 100644
--- a/codecov.yml
+++ b/codecov.yml
@@ -1,3 +1,17 @@
ignore:
- "**/*.ipynb"
- "demo-notebooks/**"
+ - "**/__init__.py"
+
+coverage:
+ precision: 2
+ round: down
+ status:
+ project:
+ default:
+ target: auto
+ threshold: 2.5%
+ patch:
+ default:
+ target: 85%
+ threshold: 2.5%
diff --git a/coverage.svg b/coverage.svg
index a8c7e72a..59d64b37 100644
--- a/coverage.svg
+++ b/coverage.svg
@@ -15,7 +15,7 @@
coverage
coverage
- 92%
- 92%
+ 93%
+ 93%
diff --git a/demo-notebooks/guided-demos/4_rayjob_existing_cluster.ipynb b/demo-notebooks/guided-demos/4_rayjob_existing_cluster.ipynb
new file mode 100644
index 00000000..c0737db0
--- /dev/null
+++ b/demo-notebooks/guided-demos/4_rayjob_existing_cluster.ipynb
@@ -0,0 +1,207 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "9259e514",
+ "metadata": {},
+ "source": [
+ "# Submitting RayJobs against an existing RayCluster\n",
+ "\n",
+ "In this notebook, we will go through the basics of using the SDK to:\n",
+ " * Spin up a Ray cluster with our desired resources\n",
+ " * Verify the status of this cluster\n",
+ " * Submit a RayJob against that cluster\n",
+ " * Verify the status of this job"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "18136ea7",
+ "metadata": {},
+ "source": [
+ "## Creating the RayCluster"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a1c2545d",
+ "metadata": {},
+ "source": [
+ "First, we'll need to import the relevant CodeFlare SDK packages. You can do this by executing the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "51e18292",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from codeflare_sdk import Cluster, ClusterConfiguration, RayJob"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "649c5911",
+ "metadata": {},
+ "source": [
+ "Run the below `oc login` command using your Token and Server URL. Ensure the command is prepended by `!` and not `%`. This will work when running both locally and within RHOAI."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "dc364888",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!oc login --token= --server="
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5581eca9",
+ "metadata": {},
+ "source": [
+ "Next we'll need to initalize our RayCluster and apply it. You can do this be executing the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3094c60a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster = Cluster(ClusterConfiguration(\n",
+ " name='rayjob-cluster',\n",
+ " head_extended_resource_requests={'nvidia.com/gpu':0},\n",
+ " worker_extended_resource_requests={'nvidia.com/gpu':0},\n",
+ " num_workers=2,\n",
+ " worker_cpu_requests=1,\n",
+ " worker_cpu_limits=1,\n",
+ " worker_memory_requests=4,\n",
+ " worker_memory_limits=4,\n",
+ "\n",
+ "))\n",
+ "\n",
+ "cluster.apply()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f3612de2",
+ "metadata": {},
+ "source": [
+ "We can check the status of our cluster by executing the below cell. If it's not up immediately, run the cell a few more times until you see that it's in a 'running' state."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "96d92f93",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster.status()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a0e2a650",
+ "metadata": {},
+ "source": [
+ "## Submitting the RayJob"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4cf03419",
+ "metadata": {},
+ "source": [
+ "Now we can create the RayJob that we want to submit against the running cluster. The process is quite similar to how we initialize and apply the cluster. \n",
+ "In this context, we need to use the `cluster_name` variable to point it to our existing cluster.\n",
+ "\n",
+ "For the sake of demonstration, the job we'll submit via the `entrypoint` is a single python command. In standard practice this would be pointed to a python training script.\n",
+ "\n",
+ "We'll then call the `submit()` function to run the job against our cluster.\n",
+ "\n",
+ "You can run the below cell to achieve this."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "94edca70",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rayjob = RayJob(\n",
+ " job_name=\"sdk-test-job\",\n",
+ " cluster_name=\"rayjob-cluster\",\n",
+ " namespace=\"your-namespace\",\n",
+ " entrypoint=\"python -c 'import time; time.sleep(20)'\",\n",
+ ")\n",
+ "\n",
+ "rayjob.submit()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "30a8899a",
+ "metadata": {},
+ "source": [
+ "We can observe the status of the RayJob in the same way as the RayCluster by invoking the `status()` function via the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3283b09c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rayjob.status()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9f3c9c9f",
+ "metadata": {},
+ "source": [
+ "This function will output different tables based on the RayJob's current status. You can re-run the cell multiple times to observe the changes as you need to. Once you've observed that the job has been completed, you can shut down the cluster we created earlier by executing the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "5b11e379",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster.down()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.11"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/demo-notebooks/guided-demos/5_submit_rayjob_cr.ipynb b/demo-notebooks/guided-demos/5_submit_rayjob_cr.ipynb
new file mode 100644
index 00000000..1d9630b7
--- /dev/null
+++ b/demo-notebooks/guided-demos/5_submit_rayjob_cr.ipynb
@@ -0,0 +1,144 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "9259e514",
+ "metadata": {},
+ "source": [
+ "# Submitting a RayJob CR\n",
+ "\n",
+ "In this notebook, we will go through the basics of using the SDK to:\n",
+ " * Define a RayCluster configuration\n",
+ " * Use this configuration alongside a RayJob definition\n",
+ " * Submit the RayJob, and allow Kuberay Operator to lifecycle the RayCluster for the RayJob"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "18136ea7",
+ "metadata": {},
+ "source": [
+ "## Defining and Submitting the RayJob\n",
+ "First, we'll need to import the relevant CodeFlare SDK packages. You can do this by executing the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "51e18292",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from codeflare_sdk import RayJob, ManagedClusterConfig"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "649c5911",
+ "metadata": {},
+ "source": [
+ "Run the below `oc login` command using your Token and Server URL. Ensure the command is prepended by `!` and not `%`. This will work when running both locally and within RHOAI."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "dc364888",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!oc login --token= --server="
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5581eca9",
+ "metadata": {},
+ "source": [
+ "Next we'll need to define the ManagedClusterConfig. Kuberay will use this to spin up a short-lived RayCluster that will only exist as long as the job"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3094c60a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster_config = ManagedClusterConfig(\n",
+ " num_workers=2,\n",
+ " worker_cpu_requests=1,\n",
+ " worker_cpu_limits=1,\n",
+ " worker_memory_requests=4,\n",
+ " worker_memory_limits=4,\n",
+ " head_accelerators={'nvidia.com/gpu': 0},\n",
+ " worker_accelerators={'nvidia.com/gpu': 0},\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "02a2b32b",
+ "metadata": {},
+ "source": [
+ "Lastly we can pass the ManagedClusterConfig into the RayJob and submit it. You do not need to worry about tearing down the cluster when the job has completed, that is handled for you!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e905ccea",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "job = RayJob(\n",
+ " job_name=\"demo-rayjob\",\n",
+ " entrypoint=\"python -c 'print(\\\"Hello from RayJob!\\\")'\",\n",
+ " cluster_config=cluster_config,\n",
+ " namespace=\"your-namespace\"\n",
+ ")\n",
+ "\n",
+ "job.submit()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f3612de2",
+ "metadata": {},
+ "source": [
+ "We can check the status of our job by executing the below cell. The status may appear as `unknown` for a time while the RayCluster spins up."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "96d92f93",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "job.status()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.11"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/demo-notebooks/guided-demos/preview_nbs/4_rayjob_existing_cluster.ipynb b/demo-notebooks/guided-demos/preview_nbs/4_rayjob_existing_cluster.ipynb
new file mode 100644
index 00000000..5348099c
--- /dev/null
+++ b/demo-notebooks/guided-demos/preview_nbs/4_rayjob_existing_cluster.ipynb
@@ -0,0 +1,212 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "9259e514",
+ "metadata": {},
+ "source": [
+ "# Submitting RayJobs against an existing RayCluster\n",
+ "\n",
+ "In this notebook, we will go through the basics of using the SDK to:\n",
+ " * Spin up a Ray cluster with our desired resources\n",
+ " * Verify the status of this cluster\n",
+ " * Submit a RayJob against that cluster\n",
+ " * Verify the status of this job"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "18136ea7",
+ "metadata": {},
+ "source": [
+ "## Creating the RayCluster"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a1c2545d",
+ "metadata": {},
+ "source": [
+ "First, we'll need to import the relevant CodeFlare SDK packages. You can do this by executing the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "51e18292",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from codeflare_sdk import Cluster, ClusterConfiguration, RayJob, TokenAuthentication"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "649c5911",
+ "metadata": {},
+ "source": [
+ "Execute the below cell to authenticate the notebook via OpenShift."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "dc364888",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "auth = TokenAuthentication(\n",
+ " token = \"XXXXX\",\n",
+ " server = \"XXXXX\",\n",
+ " skip_tls=False\n",
+ ")\n",
+ "auth.login()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5581eca9",
+ "metadata": {},
+ "source": [
+ "Next we'll need to initalize our RayCluster and apply it. You can do this be executing the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3094c60a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster = Cluster(ClusterConfiguration(\n",
+ " name='rayjob-cluster',\n",
+ " head_extended_resource_requests={'nvidia.com/gpu':0},\n",
+ " worker_extended_resource_requests={'nvidia.com/gpu':0},\n",
+ " num_workers=2,\n",
+ " worker_cpu_requests=1,\n",
+ " worker_cpu_limits=1,\n",
+ " worker_memory_requests=4,\n",
+ " worker_memory_limits=4,\n",
+ "\n",
+ "))\n",
+ "\n",
+ "cluster.apply()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f3612de2",
+ "metadata": {},
+ "source": [
+ "We can check the status of our cluster by executing the below cell. If it's not up immediately, run the cell a few more times until you see that it's in a 'running' state."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "96d92f93",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster.status()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a0e2a650",
+ "metadata": {},
+ "source": [
+ "## Creating and Submitting the RayJob"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4cf03419",
+ "metadata": {},
+ "source": [
+ "Now we can create the RayJob that we want to submit against the running cluster. The process is quite similar to how we initialize and apply the cluster. \n",
+ "In this context, we need to use the `cluster_name` variable to point it to our existing cluster.\n",
+ "\n",
+ "For the sake of demonstration, the job we'll submit via the `entrypoint` is a single python command. In standard practice this would be pointed to a python training script.\n",
+ "\n",
+ "We'll then call the `submit()` function to run the job against our cluster.\n",
+ "\n",
+ "You can run the below cell to achieve this."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "94edca70",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rayjob = RayJob(\n",
+ " job_name=\"sdk-test-job\",\n",
+ " cluster_name=\"rayjob-cluster\",\n",
+ " namespace=\"rhods-notebooks\",\n",
+ " entrypoint=\"python -c 'import time; time.sleep(20)'\",\n",
+ ")\n",
+ "\n",
+ "rayjob.submit()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "30a8899a",
+ "metadata": {},
+ "source": [
+ "We can observe the status of the RayJob in the same way as the RayCluster by invoking the `submit()` function via the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3283b09c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rayjob.submit()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9f3c9c9f",
+ "metadata": {},
+ "source": [
+ "This function will output different tables based on the RayJob's current status. You can re-run the cell multiple times to observe the changes as you need to. Once you've observed that the job has been completed, you can shut down the cluster we created earlier by executing the below cell."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "5b11e379",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cluster.down()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.11"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/poetry.lock b/poetry.lock
index 49e45352..88ceb3cb 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
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+# This file is automatically @generated by Poetry 2.1.4 and should not be changed by hand.
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name = "aiohappyeyeballs"
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attrs = ">=17.3.0"
frozenlist = ">=1.1.1"
multidict = ">=4.5,<7.0"
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description = "aiosignal: a list of registered asynchronous callbacks"
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description = "Python package for providing Mozilla's CA Bundle."
optional = false
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[[package]]
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[[package]]
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+ {file = "rpds_py-0.26.0.tar.gz", hash = "sha256:20dae58a859b0906f0685642e591056f1e787f3a8b39c8e8749a45dc7d26bdb0"},
]
[[package]]
@@ -4020,27 +4093,27 @@ files = [
[[package]]
name = "smart-open"
-version = "7.1.0"
-description = "Utils for streaming large files (S3, HDFS, GCS, Azure Blob Storage, gzip, bz2...)"
+version = "7.3.0.post1"
+description = "Utils for streaming large files (S3, HDFS, GCS, SFTP, Azure Blob Storage, gzip, bz2, zst...)"
optional = false
-python-versions = "<4.0,>=3.7"
+python-versions = "<4.0,>=3.8"
groups = ["main"]
files = [
- {file = "smart_open-7.1.0-py3-none-any.whl", hash = "sha256:4b8489bb6058196258bafe901730c7db0dcf4f083f316e97269c66f45502055b"},
- {file = "smart_open-7.1.0.tar.gz", hash = "sha256:a4f09f84f0f6d3637c6543aca7b5487438877a21360e7368ccf1f704789752ba"},
+ {file = "smart_open-7.3.0.post1-py3-none-any.whl", hash = "sha256:c73661a2c24bf045c1e04e08fffc585b59af023fe783d57896f590489db66fb4"},
+ {file = "smart_open-7.3.0.post1.tar.gz", hash = "sha256:ce6a3d9bc1afbf6234ad13c010b77f8cd36d24636811e3c52c3b5160f5214d1e"},
]
[package.dependencies]
wrapt = "*"
[package.extras]
-all = ["azure-common", "azure-core", "azure-storage-blob", "boto3", "google-cloud-storage (>=2.6.0)", "paramiko", "requests", "zstandard"]
+all = ["smart_open[azure,gcs,http,s3,ssh,webhdfs,zst]"]
azure = ["azure-common", "azure-core", "azure-storage-blob"]
gcs = ["google-cloud-storage (>=2.6.0)"]
http = ["requests"]
s3 = ["boto3"]
ssh = ["paramiko"]
-test = ["awscli", "azure-common", "azure-core", "azure-storage-blob", "boto3", "google-cloud-storage (>=2.6.0)", "moto[server]", "numpy", "paramiko", "pyopenssl", "pytest", "pytest-benchmark", "pytest-rerunfailures", "requests", "responses", "zstandard"]
+test = ["awscli", "moto[server]", "numpy", "pyopenssl", "pytest", "pytest-rerunfailures", "pytest_benchmark", "responses", "smart_open[all]"]
webhdfs = ["requests"]
zst = ["zstandard"]
@@ -4351,26 +4424,26 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
[[package]]
name = "types-python-dateutil"
-version = "2.9.0.20250516"
+version = "2.9.0.20250708"
description = "Typing stubs for python-dateutil"
optional = false
python-versions = ">=3.9"
groups = ["test"]
files = [
- {file = "types_python_dateutil-2.9.0.20250516-py3-none-any.whl", hash = "sha256:2b2b3f57f9c6a61fba26a9c0ffb9ea5681c9b83e69cd897c6b5f668d9c0cab93"},
- {file = "types_python_dateutil-2.9.0.20250516.tar.gz", hash = "sha256:13e80d6c9c47df23ad773d54b2826bd52dbbb41be87c3f339381c1700ad21ee5"},
+ {file = "types_python_dateutil-2.9.0.20250708-py3-none-any.whl", hash = "sha256:4d6d0cc1cc4d24a2dc3816024e502564094497b713f7befda4d5bc7a8e3fd21f"},
+ {file = "types_python_dateutil-2.9.0.20250708.tar.gz", hash = "sha256:ccdbd75dab2d6c9696c350579f34cffe2c281e4c5f27a585b2a2438dd1d5c8ab"},
]
[[package]]
name = "typing-extensions"
-version = "4.14.0"
+version = "4.14.1"
description = "Backported and Experimental Type Hints for Python 3.9+"
optional = false
python-versions = ">=3.9"
groups = ["main", "test"]
files = [
- {file = "typing_extensions-4.14.0-py3-none-any.whl", hash = "sha256:a1514509136dd0b477638fc68d6a91497af5076466ad0fa6c338e44e359944af"},
- {file = "typing_extensions-4.14.0.tar.gz", hash = "sha256:8676b788e32f02ab42d9e7c61324048ae4c6d844a399eebace3d4979d75ceef4"},
+ {file = "typing_extensions-4.14.1-py3-none-any.whl", hash = "sha256:d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76"},
+ {file = "typing_extensions-4.14.1.tar.gz", hash = "sha256:38b39f4aeeab64884ce9f74c94263ef78f3c22467c8724005483154c26648d36"},
]
[[package]]
@@ -4417,14 +4490,14 @@ dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake
[[package]]
name = "urllib3"
-version = "2.4.0"
+version = "2.5.0"
description = "HTTP library with thread-safe connection pooling, file post, and more."
optional = false
python-versions = ">=3.9"
groups = ["main", "docs", "test"]
files = [
- {file = "urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813"},
- {file = "urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466"},
+ {file = "urllib3-2.5.0-py3-none-any.whl", hash = "sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc"},
+ {file = "urllib3-2.5.0.tar.gz", hash = "sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760"},
]
[package.extras]
@@ -4435,14 +4508,14 @@ zstd = ["zstandard (>=0.18.0)"]
[[package]]
name = "virtualenv"
-version = "20.31.2"
+version = "20.35.1"
description = "Virtual Python Environment builder"
optional = false
python-versions = ">=3.8"
groups = ["main"]
files = [
- {file = "virtualenv-20.31.2-py3-none-any.whl", hash = "sha256:36efd0d9650ee985f0cad72065001e66d49a6f24eb44d98980f630686243cf11"},
- {file = "virtualenv-20.31.2.tar.gz", hash = "sha256:e10c0a9d02835e592521be48b332b6caee6887f332c111aa79a09b9e79efc2af"},
+ {file = "virtualenv-20.35.1-py3-none-any.whl", hash = "sha256:1d9d93cd01d35b785476e2fa7af711a98d40d227a078941695bbae394f8737e2"},
+ {file = "virtualenv-20.35.1.tar.gz", hash = "sha256:041dac43b6899858a91838b616599e80000e545dee01a21172a6a46746472cb2"},
]
[package.dependencies]
@@ -4750,4 +4823,4 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.1"
python-versions = "^3.11"
-content-hash = "6720576cf9ff57c7bb15b97e268bb414218f6a053e7e0a5bdd45d022c0847111"
+content-hash = "9a052e3a816450844fa2cf3427e4660715977aca3b14561d1e9991899624b7c2"
diff --git a/pyproject.toml b/pyproject.toml
index 71610478..6d13354e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,6 +33,14 @@ cryptography = "43.0.3"
executing = "1.2.0"
pydantic = ">= 2.10.6"
ipywidgets = "8.1.2"
+python-client = { git = "https://github.com/ray-project/kuberay.git", subdirectory = "clients/python-client", rev = "b2fd91b58c2bbe22f9b4f730c5a8f3180c05e570" }
+
+[[tool.poetry.source]]
+name = "pypi"
+
+[[tool.poetry.source]]
+name = "testpypi"
+url = "https://test.pypi.org/simple/"
[tool.poetry.group.docs]
optional = true
@@ -51,6 +59,10 @@ pytest-mock = "3.11.1"
pytest-timeout = "2.3.1"
jupyterlab = "4.3.1"
+
+[tool.poetry.group.dev.dependencies]
+diff-cover = "^9.6.0"
+
[tool.pytest.ini_options]
filterwarnings = [
"ignore::DeprecationWarning:pkg_resources",
diff --git a/src/codeflare_sdk/__init__.py b/src/codeflare_sdk/__init__.py
index 9ab5c745..a27702e7 100644
--- a/src/codeflare_sdk/__init__.py
+++ b/src/codeflare_sdk/__init__.py
@@ -10,6 +10,8 @@
AWManager,
AppWrapperStatus,
RayJobClient,
+ RayJob,
+ ManagedClusterConfig,
)
from .common.widgets import view_clusters
diff --git a/src/codeflare_sdk/common/kueue/kueue.py b/src/codeflare_sdk/common/kueue/kueue.py
index 00f3364a..a721713e 100644
--- a/src/codeflare_sdk/common/kueue/kueue.py
+++ b/src/codeflare_sdk/common/kueue/kueue.py
@@ -18,6 +18,8 @@
from kubernetes import client
from kubernetes.client.exceptions import ApiException
+from ...common.utils import get_current_namespace
+
def get_default_kueue_name(namespace: str) -> Optional[str]:
"""
@@ -81,7 +83,6 @@ def list_local_queues(
List[dict]:
A list of dictionaries containing the name of the local queue and the available flavors
"""
- from ...ray.cluster.cluster import get_current_namespace
if namespace is None: # pragma: no cover
namespace = get_current_namespace()
diff --git a/src/codeflare_sdk/common/utils/__init__.py b/src/codeflare_sdk/common/utils/__init__.py
index e69de29b..e662bf5e 100644
--- a/src/codeflare_sdk/common/utils/__init__.py
+++ b/src/codeflare_sdk/common/utils/__init__.py
@@ -0,0 +1,7 @@
+"""
+Common utilities for the CodeFlare SDK.
+"""
+
+from .k8s_utils import get_current_namespace
+
+__all__ = ["get_current_namespace"]
diff --git a/src/codeflare_sdk/common/utils/constants.py b/src/codeflare_sdk/common/utils/constants.py
index fcd064d6..00559d2e 100644
--- a/src/codeflare_sdk/common/utils/constants.py
+++ b/src/codeflare_sdk/common/utils/constants.py
@@ -12,3 +12,4 @@
"3.11": CUDA_PY311_RUNTIME_IMAGE,
"3.12": CUDA_PY312_RUNTIME_IMAGE,
}
+MOUNT_PATH = "/home/ray/files"
diff --git a/src/codeflare_sdk/common/utils/k8s_utils.py b/src/codeflare_sdk/common/utils/k8s_utils.py
new file mode 100644
index 00000000..e2e03a5d
--- /dev/null
+++ b/src/codeflare_sdk/common/utils/k8s_utils.py
@@ -0,0 +1,33 @@
+"""
+Kubernetes utility functions for the CodeFlare SDK.
+"""
+
+import os
+from kubernetes import config
+from ..kubernetes_cluster import config_check, _kube_api_error_handling
+
+
+def get_current_namespace(): # pragma: no cover
+ """
+ Retrieves the current Kubernetes namespace.
+
+ Returns:
+ str:
+ The current namespace or None if not found.
+ """
+ if os.path.isfile("/var/run/secrets/kubernetes.io/serviceaccount/namespace"):
+ try:
+ file = open("/var/run/secrets/kubernetes.io/serviceaccount/namespace", "r")
+ active_context = file.readline().strip("\n")
+ return active_context
+ except Exception as e:
+ print("Unable to find current namespace")
+ print("trying to gather from current context")
+ try:
+ _, active_context = config.list_kube_config_contexts(config_check())
+ except Exception as e:
+ return _kube_api_error_handling(e)
+ try:
+ return active_context["context"]["namespace"]
+ except KeyError:
+ return None
diff --git a/src/codeflare_sdk/common/utils/test_demos.py b/src/codeflare_sdk/common/utils/test_demos.py
new file mode 100644
index 00000000..9124cbec
--- /dev/null
+++ b/src/codeflare_sdk/common/utils/test_demos.py
@@ -0,0 +1,57 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Tests for demos module.
+"""
+
+import pytest
+import tempfile
+from pathlib import Path
+from unittest.mock import patch, MagicMock
+from codeflare_sdk.common.utils.demos import copy_demo_nbs
+
+
+class TestCopyDemoNbs:
+ """Test cases for copy_demo_nbs function."""
+
+ def test_copy_demo_nbs_directory_exists_error(self):
+ """Test that FileExistsError is raised when directory exists and overwrite=False."""
+ with tempfile.TemporaryDirectory() as temp_dir:
+ # Create a subdirectory that will conflict
+ conflict_dir = Path(temp_dir) / "demo-notebooks"
+ conflict_dir.mkdir()
+
+ with pytest.raises(FileExistsError, match="Directory.*already exists"):
+ copy_demo_nbs(dir=str(conflict_dir), overwrite=False)
+
+ def test_copy_demo_nbs_overwrite_true(self):
+ """Test that overwrite=True allows copying to existing directory."""
+ with tempfile.TemporaryDirectory() as temp_dir:
+ # Create a subdirectory that will conflict
+ conflict_dir = Path(temp_dir) / "demo-notebooks"
+ conflict_dir.mkdir()
+
+ # Mock the demo_dir to point to a real directory
+ with patch("codeflare_sdk.common.utils.demos.demo_dir", temp_dir):
+ # Should not raise an error with overwrite=True
+ copy_demo_nbs(dir=str(conflict_dir), overwrite=True)
+
+ def test_copy_demo_nbs_default_parameters(self):
+ """Test copy_demo_nbs with default parameters."""
+ with tempfile.TemporaryDirectory() as temp_dir:
+ # Mock the demo_dir to point to a real directory
+ with patch("codeflare_sdk.common.utils.demos.demo_dir", temp_dir):
+ # Should work with default parameters
+ copy_demo_nbs(dir=temp_dir, overwrite=True)
diff --git a/src/codeflare_sdk/common/utils/test_k8s_utils.py b/src/codeflare_sdk/common/utils/test_k8s_utils.py
new file mode 100644
index 00000000..fcd0623d
--- /dev/null
+++ b/src/codeflare_sdk/common/utils/test_k8s_utils.py
@@ -0,0 +1,255 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Tests for k8s_utils module.
+"""
+
+import pytest
+from unittest.mock import mock_open, patch, MagicMock
+from codeflare_sdk.common.utils.k8s_utils import get_current_namespace
+
+
+class TestGetCurrentNamespace:
+ """Test cases for get_current_namespace function."""
+
+ def test_get_current_namespace_incluster_success(self):
+ """Test successful namespace detection from in-cluster service account."""
+ mock_file_content = "test-namespace\n"
+
+ with patch("os.path.isfile", return_value=True):
+ with patch("builtins.open", mock_open(read_data=mock_file_content)):
+ result = get_current_namespace()
+
+ assert result == "test-namespace"
+
+ def test_get_current_namespace_incluster_file_read_error(self):
+ """Test handling of file read errors when reading service account namespace."""
+ with patch("os.path.isfile", return_value=True):
+ with patch("builtins.open", side_effect=IOError("File read error")):
+ with patch("builtins.print") as mock_print:
+ # Mock config_check to avoid kubeconfig fallback
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ side_effect=Exception("Config error"),
+ ):
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils._kube_api_error_handling",
+ return_value=None,
+ ):
+ result = get_current_namespace()
+
+ assert result is None
+ # Should see both error messages: in-cluster failure and kubeconfig fallback
+ mock_print.assert_any_call("Unable to find current namespace")
+ mock_print.assert_any_call("trying to gather from current context")
+
+ def test_get_current_namespace_incluster_file_open_error(self):
+ """Test handling of file open errors when reading service account namespace."""
+ with patch("os.path.isfile", return_value=True):
+ with patch(
+ "builtins.open", side_effect=PermissionError("Permission denied")
+ ):
+ with patch("builtins.print") as mock_print:
+ # Mock config_check to avoid kubeconfig fallback
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ side_effect=Exception("Config error"),
+ ):
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils._kube_api_error_handling",
+ return_value=None,
+ ):
+ result = get_current_namespace()
+
+ assert result is None
+ # Should see both error messages: in-cluster failure and kubeconfig fallback
+ mock_print.assert_any_call("Unable to find current namespace")
+ mock_print.assert_any_call("trying to gather from current context")
+
+ def test_get_current_namespace_kubeconfig_success(self):
+ """Test successful namespace detection from kubeconfig context."""
+ mock_contexts = [
+ {"name": "context1", "context": {"namespace": "default"}},
+ {"name": "context2", "context": {"namespace": "test-namespace"}},
+ ]
+ mock_active_context = {
+ "name": "context2",
+ "context": {"namespace": "test-namespace"},
+ }
+
+ with patch("os.path.isfile", return_value=False):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ return_value="~/.kube/config",
+ ):
+ with patch(
+ "kubernetes.config.list_kube_config_contexts",
+ return_value=(mock_contexts, mock_active_context),
+ ):
+ result = get_current_namespace()
+
+ assert result == "test-namespace"
+ mock_print.assert_called_with("trying to gather from current context")
+
+ def test_get_current_namespace_kubeconfig_no_namespace_in_context(self):
+ """Test handling when kubeconfig context has no namespace field."""
+ mock_contexts = [
+ {"name": "context1", "context": {}},
+ {"name": "context2", "context": {"cluster": "test-cluster"}},
+ ]
+ mock_active_context = {
+ "name": "context2",
+ "context": {"cluster": "test-cluster"},
+ }
+
+ with patch("os.path.isfile", return_value=False):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ return_value="~/.kube/config",
+ ):
+ with patch(
+ "kubernetes.config.list_kube_config_contexts",
+ return_value=(mock_contexts, mock_active_context),
+ ):
+ result = get_current_namespace()
+
+ assert result is None
+ mock_print.assert_called_with("trying to gather from current context")
+
+ def test_get_current_namespace_kubeconfig_config_check_error(self):
+ """Test handling when config_check raises an exception."""
+ with patch("os.path.isfile", return_value=False):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ side_effect=Exception("Config error"),
+ ):
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils._kube_api_error_handling",
+ return_value=None,
+ ) as mock_error_handler:
+ result = get_current_namespace()
+
+ assert result is None
+ mock_print.assert_called_with("trying to gather from current context")
+ mock_error_handler.assert_called_once()
+
+ def test_get_current_namespace_kubeconfig_list_contexts_error(self):
+ """Test handling when list_kube_config_contexts raises an exception."""
+ with patch("os.path.isfile", return_value=False):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ return_value="~/.kube/config",
+ ):
+ with patch(
+ "kubernetes.config.list_kube_config_contexts",
+ side_effect=Exception("Context error"),
+ ):
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils._kube_api_error_handling",
+ return_value=None,
+ ) as mock_error_handler:
+ result = get_current_namespace()
+
+ assert result is None
+ mock_print.assert_called_with("trying to gather from current context")
+ mock_error_handler.assert_called_once()
+
+ def test_get_current_namespace_kubeconfig_key_error(self):
+ """Test handling when accessing context namespace raises KeyError."""
+ mock_contexts = [{"name": "context1", "context": {"namespace": "default"}}]
+ mock_active_context = {"name": "context1"} # Missing 'context' key
+
+ with patch("os.path.isfile", return_value=False):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ return_value="~/.kube/config",
+ ):
+ with patch(
+ "kubernetes.config.list_kube_config_contexts",
+ return_value=(mock_contexts, mock_active_context),
+ ):
+ result = get_current_namespace()
+
+ assert result is None
+ mock_print.assert_called_with("trying to gather from current context")
+
+ def test_get_current_namespace_fallback_flow(self):
+ """Test the complete fallback flow from in-cluster to kubeconfig."""
+ # First attempt: in-cluster file doesn't exist
+ # Second attempt: kubeconfig context has namespace
+ mock_contexts = [
+ {"name": "context1", "context": {"namespace": "fallback-namespace"}}
+ ]
+ mock_active_context = {
+ "name": "context1",
+ "context": {"namespace": "fallback-namespace"},
+ }
+
+ with patch("os.path.isfile", return_value=False):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ return_value="~/.kube/config",
+ ):
+ with patch(
+ "kubernetes.config.list_kube_config_contexts",
+ return_value=(mock_contexts, mock_active_context),
+ ):
+ result = get_current_namespace()
+
+ assert result == "fallback-namespace"
+ mock_print.assert_called_with("trying to gather from current context")
+
+ def test_get_current_namespace_complete_failure(self):
+ """Test complete failure scenario where no namespace can be detected."""
+ with patch("os.path.isfile", return_value=False):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ side_effect=Exception("Config error"),
+ ):
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils._kube_api_error_handling",
+ return_value=None,
+ ):
+ result = get_current_namespace()
+
+ assert result is None
+ mock_print.assert_called_with("trying to gather from current context")
+
+ def test_get_current_namespace_mixed_errors(self):
+ """Test scenario with mixed error conditions."""
+ # In-cluster file exists but read fails, then kubeconfig also fails
+ with patch("os.path.isfile", return_value=True):
+ with patch("builtins.open", side_effect=IOError("File read error")):
+ with patch("builtins.print") as mock_print:
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils.config_check",
+ side_effect=Exception("Config error"),
+ ):
+ with patch(
+ "codeflare_sdk.common.utils.k8s_utils._kube_api_error_handling",
+ return_value=None,
+ ):
+ result = get_current_namespace()
+
+ assert result is None
+ # Should see both error messages
+ assert mock_print.call_count >= 2
diff --git a/src/codeflare_sdk/common/utils/test_utils.py b/src/codeflare_sdk/common/utils/test_utils.py
new file mode 100644
index 00000000..d330bc4d
--- /dev/null
+++ b/src/codeflare_sdk/common/utils/test_utils.py
@@ -0,0 +1,209 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Tests for common/utils/utils.py
+"""
+
+import pytest
+from collections import namedtuple
+from codeflare_sdk.common.utils.utils import (
+ update_image,
+ get_ray_image_for_python_version,
+)
+from codeflare_sdk.common.utils.constants import (
+ SUPPORTED_PYTHON_VERSIONS,
+ CUDA_PY311_RUNTIME_IMAGE,
+ CUDA_PY312_RUNTIME_IMAGE,
+)
+
+
+def test_update_image_with_empty_string_python_311(mocker):
+ """Test that update_image() with empty string returns default image for Python 3.11."""
+ # Mock sys.version_info to simulate Python 3.11
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 11, 0, "final", 0))
+
+ # Test with empty image (should use default for Python 3.11)
+ image = update_image("")
+ assert image == CUDA_PY311_RUNTIME_IMAGE
+ assert image == SUPPORTED_PYTHON_VERSIONS["3.11"]
+
+
+def test_update_image_with_empty_string_python_312(mocker):
+ """Test that update_image() with empty string returns default image for Python 3.12."""
+ # Mock sys.version_info to simulate Python 3.12
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 12, 0, "final", 0))
+
+ # Test with empty image (should use default for Python 3.12)
+ image = update_image("")
+ assert image == CUDA_PY312_RUNTIME_IMAGE
+ assert image == SUPPORTED_PYTHON_VERSIONS["3.12"]
+
+
+def test_update_image_with_none_python_311(mocker):
+ """Test that update_image() with None returns default image for Python 3.11."""
+ # Mock sys.version_info to simulate Python 3.11
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 11, 0, "final", 0))
+
+ # Test with None image (should use default for Python 3.11)
+ image = update_image(None)
+ assert image == CUDA_PY311_RUNTIME_IMAGE
+
+
+def test_update_image_with_none_python_312(mocker):
+ """Test that update_image() with None returns default image for Python 3.12."""
+ # Mock sys.version_info to simulate Python 3.12
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 12, 0, "final", 0))
+
+ # Test with None image (should use default for Python 3.12)
+ image = update_image(None)
+ assert image == CUDA_PY312_RUNTIME_IMAGE
+
+
+def test_update_image_with_unsupported_python_version(mocker):
+ """Test update_image() warning for unsupported Python versions."""
+ # Mock sys.version_info to simulate Python 3.8 (unsupported)
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 8, 0, "final", 0))
+
+ # Mock warnings.warn to check if it gets called
+ warn_mock = mocker.patch("warnings.warn")
+
+ # Call update_image with empty image
+ image = update_image("")
+
+ # Assert that the warning was called with the expected message
+ warn_mock.assert_called_once()
+ assert "No default Ray image defined for 3.8" in warn_mock.call_args[0][0]
+ assert "3.11, 3.12" in warn_mock.call_args[0][0]
+
+ # Assert that no image was set since the Python version is not supported
+ assert image is None
+
+
+def test_update_image_with_provided_custom_image():
+ """Test that providing a custom image bypasses auto-detection."""
+ custom_image = "my-custom-ray:latest"
+ image = update_image(custom_image)
+
+ # Should return the provided image unchanged
+ assert image == custom_image
+
+
+def test_update_image_with_provided_image_empty_string():
+ """Test update_image() with provided custom image as a non-empty string."""
+ custom_image = "docker.io/rayproject/ray:2.40.0"
+ image = update_image(custom_image)
+
+ # Should return the provided image unchanged
+ assert image == custom_image
+
+
+def test_get_ray_image_for_python_version_explicit_311():
+ """Test get_ray_image_for_python_version() with explicit Python 3.11."""
+ image = get_ray_image_for_python_version("3.11")
+ assert image == CUDA_PY311_RUNTIME_IMAGE
+
+
+def test_get_ray_image_for_python_version_explicit_312():
+ """Test get_ray_image_for_python_version() with explicit Python 3.12."""
+ image = get_ray_image_for_python_version("3.12")
+ assert image == CUDA_PY312_RUNTIME_IMAGE
+
+
+def test_get_ray_image_for_python_version_auto_detect_311(mocker):
+ """Test get_ray_image_for_python_version() auto-detects Python 3.11."""
+ # Mock sys.version_info to simulate Python 3.11
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 11, 0, "final", 0))
+
+ # Test with None (should auto-detect)
+ image = get_ray_image_for_python_version()
+ assert image == CUDA_PY311_RUNTIME_IMAGE
+
+
+def test_get_ray_image_for_python_version_auto_detect_312(mocker):
+ """Test get_ray_image_for_python_version() auto-detects Python 3.12."""
+ # Mock sys.version_info to simulate Python 3.12
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 12, 0, "final", 0))
+
+ # Test with None (should auto-detect)
+ image = get_ray_image_for_python_version()
+ assert image == CUDA_PY312_RUNTIME_IMAGE
+
+
+def test_get_ray_image_for_python_version_unsupported_with_warning(mocker):
+ """Test get_ray_image_for_python_version() warns for unsupported versions."""
+ warn_mock = mocker.patch("warnings.warn")
+
+ # Test with unsupported version and warn_on_unsupported=True (default)
+ image = get_ray_image_for_python_version("3.9", warn_on_unsupported=True)
+
+ # Should have warned
+ warn_mock.assert_called_once()
+ assert "No default Ray image defined for 3.9" in warn_mock.call_args[0][0]
+
+ # Should return None
+ assert image is None
+
+
+def test_get_ray_image_for_python_version_unsupported_without_warning():
+ """Test get_ray_image_for_python_version() falls back to 3.12 without warning."""
+ # Test with unsupported version and warn_on_unsupported=False
+ image = get_ray_image_for_python_version("3.10", warn_on_unsupported=False)
+
+ # Should fall back to Python 3.12 image
+ assert image == CUDA_PY312_RUNTIME_IMAGE
+
+
+def test_get_ray_image_for_python_version_unsupported_silent_fallback():
+ """Test get_ray_image_for_python_version() silently falls back for old versions."""
+ # Test with Python 3.8 and warn_on_unsupported=False
+ image = get_ray_image_for_python_version("3.8", warn_on_unsupported=False)
+
+ # Should fall back to Python 3.12 image without warning
+ assert image == CUDA_PY312_RUNTIME_IMAGE
+
+
+def test_get_ray_image_for_python_version_none_defaults_to_current(mocker):
+ """Test that passing None to get_ray_image_for_python_version() uses current Python."""
+ # Mock sys.version_info to simulate Python 3.11
+ VersionInfo = namedtuple(
+ "version_info", ["major", "minor", "micro", "releaselevel", "serial"]
+ )
+ mocker.patch("sys.version_info", VersionInfo(3, 11, 5, "final", 0))
+
+ # Passing None should detect the mocked version
+ image = get_ray_image_for_python_version(None, warn_on_unsupported=True)
+
+ assert image == CUDA_PY311_RUNTIME_IMAGE
diff --git a/src/codeflare_sdk/common/utils/test_validation.py b/src/codeflare_sdk/common/utils/test_validation.py
new file mode 100644
index 00000000..20416d00
--- /dev/null
+++ b/src/codeflare_sdk/common/utils/test_validation.py
@@ -0,0 +1,224 @@
+# Copyright 2022-2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from codeflare_sdk.common.utils.validation import (
+ extract_ray_version_from_image,
+ validate_ray_version_compatibility,
+)
+from codeflare_sdk.common.utils.constants import RAY_VERSION
+
+
+class TestRayVersionDetection:
+ """Test Ray version detection from container image names."""
+
+ def test_extract_ray_version_standard_format(self):
+ """Test extraction from standard Ray image formats."""
+ # Standard format
+ assert extract_ray_version_from_image("ray:2.47.1") == "2.47.1"
+ assert extract_ray_version_from_image("ray:2.46.0") == "2.46.0"
+ assert extract_ray_version_from_image("ray:1.13.0") == "1.13.0"
+
+ def test_extract_ray_version_with_registry(self):
+ """Test extraction from images with registry prefixes."""
+ assert extract_ray_version_from_image("quay.io/ray:2.47.1") == "2.47.1"
+ assert (
+ extract_ray_version_from_image("docker.io/rayproject/ray:2.47.1")
+ == "2.47.1"
+ )
+ assert (
+ extract_ray_version_from_image("gcr.io/my-project/ray:2.47.1") == "2.47.1"
+ )
+
+ def test_extract_ray_version_with_suffixes(self):
+ """Test extraction from images with version suffixes."""
+ assert (
+ extract_ray_version_from_image("quay.io/modh/ray:2.47.1-py311-cu121")
+ == "2.47.1"
+ )
+ assert extract_ray_version_from_image("ray:2.47.1-py311") == "2.47.1"
+ assert extract_ray_version_from_image("ray:2.47.1-gpu") == "2.47.1"
+ assert extract_ray_version_from_image("ray:2.47.1-rocm62") == "2.47.1"
+
+ def test_extract_ray_version_complex_registry_paths(self):
+ """Test extraction from complex registry paths."""
+ assert (
+ extract_ray_version_from_image("quay.io/modh/ray:2.47.1-py311-cu121")
+ == "2.47.1"
+ )
+ assert (
+ extract_ray_version_from_image("registry.company.com/team/ray:2.47.1")
+ == "2.47.1"
+ )
+
+ def test_extract_ray_version_no_version_found(self):
+ """Test cases where no version can be extracted."""
+ # SHA-based tags
+ assert (
+ extract_ray_version_from_image(
+ "quay.io/modh/ray@sha256:6d076aeb38ab3c34a6a2ef0f58dc667089aa15826fa08a73273c629333e12f1e"
+ )
+ is None
+ )
+
+ # Non-semantic versions
+ assert extract_ray_version_from_image("ray:latest") is None
+ assert extract_ray_version_from_image("ray:nightly") is None
+ assert (
+ extract_ray_version_from_image("ray:v2.47") is None
+ ) # Missing patch version
+
+ # Non-Ray images
+ assert extract_ray_version_from_image("python:3.11") is None
+ assert extract_ray_version_from_image("ubuntu:20.04") is None
+
+ # Empty or None
+ assert extract_ray_version_from_image("") is None
+ assert extract_ray_version_from_image(None) is None
+
+ def test_extract_ray_version_edge_cases(self):
+ """Test edge cases for version extraction."""
+ # Version with 'v' prefix should not match our pattern
+ assert extract_ray_version_from_image("ray:v2.47.1") is None
+
+ # Multiple version-like patterns - should match the first valid one
+ assert (
+ extract_ray_version_from_image("registry/ray:2.47.1-based-on-1.0.0")
+ == "2.47.1"
+ )
+
+
+class TestRayVersionValidation:
+ """Test Ray version compatibility validation."""
+
+ def test_validate_compatible_versions(self):
+ """Test validation with compatible Ray versions."""
+ # Exact match
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ f"ray:{RAY_VERSION}"
+ )
+ assert is_compatible is True
+ assert is_warning is False
+ assert "Ray versions match" in message
+
+ # With registry and suffixes
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ f"quay.io/modh/ray:{RAY_VERSION}-py311-cu121"
+ )
+ assert is_compatible is True
+ assert is_warning is False
+ assert "Ray versions match" in message
+
+ def test_validate_incompatible_versions(self):
+ """Test validation with incompatible Ray versions."""
+ # Different version
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "ray:2.46.0"
+ )
+ assert is_compatible is False
+ assert is_warning is False
+ assert "Ray version mismatch detected" in message
+ assert "CodeFlare SDK uses Ray" in message
+ assert "runtime image uses Ray" in message
+
+ # Older version
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "ray:1.13.0"
+ )
+ assert is_compatible is False
+ assert is_warning is False
+ assert "Ray version mismatch detected" in message
+
+ def test_validate_empty_image(self):
+ """Test validation with no custom image (should use default)."""
+ # Empty string
+ is_compatible, is_warning, message = validate_ray_version_compatibility("")
+ assert is_compatible is True
+ assert is_warning is False
+ assert "Using default Ray image compatible with SDK" in message
+
+ # None
+ is_compatible, is_warning, message = validate_ray_version_compatibility(None)
+ assert is_compatible is True
+ assert is_warning is False
+ assert "Using default Ray image compatible with SDK" in message
+
+ def test_validate_unknown_version(self):
+ """Test validation when version cannot be determined."""
+ # SHA-based image
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "quay.io/modh/ray@sha256:6d076aeb38ab3c34a6a2ef0f58dc667089aa15826fa08a73273c629333e12f1e"
+ )
+ assert is_compatible is True
+ assert is_warning is True
+ assert "Cannot determine Ray version" in message
+
+ # Custom image without version
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "my-custom-ray:latest"
+ )
+ assert is_compatible is True
+ assert is_warning is True
+ assert "Cannot determine Ray version" in message
+
+ def test_validate_custom_sdk_version(self):
+ """Test validation with custom SDK version."""
+ # Compatible with custom SDK version
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "ray:2.46.0", "2.46.0"
+ )
+ assert is_compatible is True
+ assert is_warning is False
+ assert "Ray versions match" in message
+
+ # Incompatible with custom SDK version
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "ray:2.47.1", "2.46.0"
+ )
+ assert is_compatible is False
+ assert is_warning is False
+ assert "CodeFlare SDK uses Ray 2.46.0" in message
+ assert "runtime image uses Ray 2.47.1" in message
+
+ def test_validate_message_content(self):
+ """Test that validation messages contain expected guidance."""
+ # Mismatch message should contain helpful guidance
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "ray:2.46.0"
+ )
+ assert is_compatible is False
+ assert is_warning is False
+ assert "compatibility issues" in message.lower()
+ assert "unexpected behavior" in message.lower()
+ assert "please use a runtime image" in message.lower()
+ assert "update your sdk version" in message.lower()
+
+ def test_semantic_version_comparison(self):
+ """Test that semantic version comparison works correctly."""
+ # Test that 2.10.0 > 2.9.1 (would fail with string comparison)
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "ray:2.10.0", "2.9.1"
+ )
+ assert is_compatible is False
+ assert is_warning is False
+ assert "CodeFlare SDK uses Ray 2.9.1" in message
+ assert "runtime image uses Ray 2.10.0" in message
+
+ # Test that 2.9.1 < 2.10.0 (would fail with string comparison)
+ is_compatible, is_warning, message = validate_ray_version_compatibility(
+ "ray:2.9.1", "2.10.0"
+ )
+ assert is_compatible is False
+ assert is_warning is False
+ assert "CodeFlare SDK uses Ray 2.10.0" in message
+ assert "runtime image uses Ray 2.9.1" in message
diff --git a/src/codeflare_sdk/common/utils/utils.py b/src/codeflare_sdk/common/utils/utils.py
index f876e924..7e30b994 100644
--- a/src/codeflare_sdk/common/utils/utils.py
+++ b/src/codeflare_sdk/common/utils/utils.py
@@ -19,6 +19,17 @@
)
+def update_image(image) -> str:
+ """
+ The update_image() function automatically sets the image config parameter to a preset image based on Python version if not specified.
+ This now points to the centralized function in utils.py.
+ """
+ if not image:
+ # Pull the image based on the matching Python version (or output a warning if not supported)
+ image = get_ray_image_for_python_version(warn_on_unsupported=True)
+ return image
+
+
def get_ray_image_for_python_version(python_version=None, warn_on_unsupported=True):
"""
Get the appropriate Ray image for a given Python version.
diff --git a/src/codeflare_sdk/common/utils/validation.py b/src/codeflare_sdk/common/utils/validation.py
new file mode 100644
index 00000000..ec749f7c
--- /dev/null
+++ b/src/codeflare_sdk/common/utils/validation.py
@@ -0,0 +1,134 @@
+# Copyright 2022-2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Validation utilities for the CodeFlare SDK.
+
+This module contains validation functions used across the SDK for ensuring
+configuration compatibility and correctness.
+"""
+
+import logging
+import re
+from typing import Optional, Tuple
+from packaging.version import Version, InvalidVersion
+from .constants import RAY_VERSION
+
+logger = logging.getLogger(__name__)
+
+
+def extract_ray_version_from_image(image_name: str) -> Optional[str]:
+ """
+ Extract Ray version from a container image name.
+
+ Supports various image naming patterns:
+ - quay.io/modh/ray:2.47.1-py311-cu121
+ - ray:2.47.1
+ - some-registry/ray:2.47.1-py311
+ - quay.io/modh/ray@sha256:... (falls back to None)
+
+ Args:
+ image_name: The container image name/tag
+
+ Returns:
+ The extracted Ray version, or None if not found
+ """
+ if not image_name:
+ return None
+
+ # Pattern to match semantic version after ray: or ray/
+ # Looks for patterns like ray:2.47.1, ray:2.47.1-py311, etc.
+ patterns = [
+ r"ray:(\d+\.\d+\.\d+)", # ray:2.47.1
+ r"ray/[^:]*:(\d+\.\d+\.\d+)", # registry/ray:2.47.1
+ r"/ray:(\d+\.\d+\.\d+)", # any-registry/ray:2.47.1
+ ]
+
+ for pattern in patterns:
+ match = re.search(pattern, image_name)
+ if match:
+ return match.group(1)
+
+ # If we can't extract version, return None to indicate unknown
+ return None
+
+
+def validate_ray_version_compatibility(
+ image_name: str, sdk_ray_version: str = RAY_VERSION
+) -> Tuple[bool, bool, str]:
+ """
+ Validate that the Ray version in the runtime image matches the SDK's Ray version.
+
+ Args:
+ image_name: The container image name/tag
+ sdk_ray_version: The Ray version used by the CodeFlare SDK
+
+ Returns:
+ tuple: (is_compatible, is_warning, message)
+ - is_compatible: True if versions match or cannot be determined, False if mismatch
+ - is_warning: True if this is a warning (non-fatal), False otherwise
+ - message: Descriptive message about the validation result
+ """
+ if not image_name:
+ # No custom image specified, will use default - this is compatible
+ logger.debug("Using default Ray image compatible with SDK")
+ return True, False, "Using default Ray image compatible with SDK"
+
+ image_ray_version = extract_ray_version_from_image(image_name)
+
+ if image_ray_version is None:
+ # Cannot determine version from image name, issue a warning but allow
+ return (
+ True,
+ True,
+ f"Cannot determine Ray version from image '{image_name}'. Please ensure it's compatible with Ray {sdk_ray_version}",
+ )
+
+ # Use semantic version comparison for robust version checking
+ try:
+ sdk_version = Version(sdk_ray_version)
+ image_version = Version(image_ray_version)
+
+ if image_version != sdk_version:
+ # Version mismatch detected
+ message = (
+ f"Ray version mismatch detected!\n"
+ f"CodeFlare SDK uses Ray {sdk_ray_version}, but runtime image uses Ray {image_ray_version}.\n"
+ f"This mismatch can cause compatibility issues and unexpected behavior.\n"
+ f"Please use a runtime image with Ray {sdk_ray_version} or update your SDK version."
+ )
+ return False, False, message
+ except InvalidVersion as e:
+ # If version parsing fails, fall back to string comparison with a warning
+ logger.warning(
+ f"Failed to parse version for comparison ({e}), falling back to string comparison"
+ )
+ if image_ray_version != sdk_ray_version:
+ message = (
+ f"Ray version mismatch detected!\n"
+ f"CodeFlare SDK uses Ray {sdk_ray_version}, but runtime image uses Ray {image_ray_version}.\n"
+ f"This mismatch can cause compatibility issues and unexpected behavior.\n"
+ f"Please use a runtime image with Ray {sdk_ray_version} or update your SDK version."
+ )
+ return False, False, message
+
+ # Versions match
+ logger.debug(
+ f"Ray version validation successful: SDK and runtime image both use Ray {sdk_ray_version}"
+ )
+ return (
+ True,
+ False,
+ f"Ray versions match: SDK and runtime image both use Ray {sdk_ray_version}",
+ )
diff --git a/src/codeflare_sdk/common/widgets/test_widgets.py b/src/codeflare_sdk/common/widgets/test_widgets.py
index f88d8eb2..55be2b75 100644
--- a/src/codeflare_sdk/common/widgets/test_widgets.py
+++ b/src/codeflare_sdk/common/widgets/test_widgets.py
@@ -106,7 +106,7 @@ def test_view_clusters(mocker, capsys):
# Prepare to run view_clusters when notebook environment is detected
mocker.patch("codeflare_sdk.common.widgets.widgets.is_notebook", return_value=True)
mock_get_current_namespace = mocker.patch(
- "codeflare_sdk.ray.cluster.cluster.get_current_namespace",
+ "codeflare_sdk.common.widgets.widgets.get_current_namespace",
return_value="default",
)
namespace = mock_get_current_namespace.return_value
@@ -250,7 +250,7 @@ def test_ray_cluster_manager_widgets_init(mocker, capsys):
return_value=test_ray_clusters_df,
)
mocker.patch(
- "codeflare_sdk.ray.cluster.cluster.get_current_namespace",
+ "codeflare_sdk.common.utils.get_current_namespace",
return_value=namespace,
)
mock_delete_cluster = mocker.patch(
diff --git a/src/codeflare_sdk/common/widgets/widgets.py b/src/codeflare_sdk/common/widgets/widgets.py
index 36d896e8..c813fabc 100644
--- a/src/codeflare_sdk/common/widgets/widgets.py
+++ b/src/codeflare_sdk/common/widgets/widgets.py
@@ -26,6 +26,8 @@
import ipywidgets as widgets
from IPython.display import display, HTML, Javascript
import pandas as pd
+
+from ...common.utils import get_current_namespace
from ...ray.cluster.config import ClusterConfiguration
from ...ray.cluster.status import RayClusterStatus
from ..kubernetes_cluster import _kube_api_error_handling
@@ -43,8 +45,6 @@ class RayClusterManagerWidgets:
"""
def __init__(self, ray_clusters_df: pd.DataFrame, namespace: str = None):
- from ...ray.cluster.cluster import get_current_namespace
-
# Data
self.ray_clusters_df = ray_clusters_df
self.namespace = get_current_namespace() if not namespace else namespace
@@ -353,8 +353,6 @@ def view_clusters(namespace: str = None):
)
return # Exit function if not in Jupyter Notebook
- from ...ray.cluster.cluster import get_current_namespace
-
if not namespace:
namespace = get_current_namespace()
diff --git a/src/codeflare_sdk/ray/__init__.py b/src/codeflare_sdk/ray/__init__.py
index ab55cc82..7bd0b2c8 100644
--- a/src/codeflare_sdk/ray/__init__.py
+++ b/src/codeflare_sdk/ray/__init__.py
@@ -4,6 +4,14 @@
RayJobClient,
)
+from .rayjobs import (
+ RayJob,
+ ManagedClusterConfig,
+ RayJobDeploymentStatus,
+ CodeflareRayJobStatus,
+ RayJobInfo,
+)
+
from .cluster import (
Cluster,
ClusterConfiguration,
diff --git a/src/codeflare_sdk/ray/cluster/build_ray_cluster.py b/src/codeflare_sdk/ray/cluster/build_ray_cluster.py
index e8b68919..6a3984b1 100644
--- a/src/codeflare_sdk/ray/cluster/build_ray_cluster.py
+++ b/src/codeflare_sdk/ray/cluster/build_ray_cluster.py
@@ -21,7 +21,7 @@
from ...common.kubernetes_cluster import get_api_client, config_check
from kubernetes.client.exceptions import ApiException
from ...common.utils.constants import RAY_VERSION
-from ...common.utils.utils import get_ray_image_for_python_version
+from ...common.utils.utils import update_image
import codeflare_sdk
import os
@@ -96,9 +96,6 @@
),
]
-# Use centralized mapping from constants (so that we only have to update constants.py)
-SUPPORTED_PYTHON_VERSIONS = constants.SUPPORTED_PYTHON_VERSIONS
-
# RayCluster/AppWrapper builder function
def build_ray_cluster(cluster: "codeflare_sdk.ray.cluster.Cluster"):
@@ -245,6 +242,7 @@ def get_labels(cluster: "codeflare_sdk.ray.cluster.Cluster"):
"""
labels = {
"controller-tools.k8s.io": "1.0",
+ "ray.io/cluster": cluster.config.name, # Enforced label always present
}
if cluster.config.labels != {}:
labels.update(cluster.config.labels)
@@ -269,17 +267,6 @@ def with_nb_annotations(annotations: dict):
# Head/Worker container related functions
-def update_image(image) -> str:
- """
- The update_image() function automatically sets the image config parameter to a preset image based on Python version if not specified.
- This now points to the centralized function in utils.py.
- """
- if not image:
- # Pull the image based on the matching Python version (or output a warning if not supported)
- image = get_ray_image_for_python_version(warn_on_unsupported=True)
- return image
-
-
def get_pod_spec(
cluster: "codeflare_sdk.ray.cluster.Cluster",
containers: List,
diff --git a/src/codeflare_sdk/ray/cluster/cluster.py b/src/codeflare_sdk/ray/cluster/cluster.py
index 31b80418..cd188816 100644
--- a/src/codeflare_sdk/ray/cluster/cluster.py
+++ b/src/codeflare_sdk/ray/cluster/cluster.py
@@ -20,8 +20,14 @@
from time import sleep
from typing import List, Optional, Tuple, Dict
+import copy
-from ray.job_submission import JobSubmissionClient
+from ray.job_submission import JobSubmissionClient, JobStatus
+import time
+import uuid
+import warnings
+
+from ...common.utils import get_current_namespace
from ...common.kubernetes_cluster.auth import (
config_check,
@@ -57,7 +63,6 @@
from kubernetes.client.rest import ApiException
from kubernetes.client.rest import ApiException
-import warnings
CF_SDK_FIELD_MANAGER = "codeflare-sdk"
@@ -203,6 +208,10 @@ def apply(self, force=False):
self._throw_for_no_raycluster()
namespace = self.config.namespace
name = self.config.name
+
+ # Regenerate resource_yaml to reflect any configuration changes
+ self.resource_yaml = self.create_resource()
+
try:
self.config_check()
api_instance = client.CustomObjectsApi(get_api_client())
@@ -384,9 +393,14 @@ def is_dashboard_ready(self) -> bool:
bool:
True if the dashboard is ready, False otherwise.
"""
+
+ dashboard_uri = self.cluster_dashboard_uri()
+ if dashboard_uri is None:
+ return False
+
try:
response = requests.get(
- self.cluster_dashboard_uri(),
+ dashboard_uri,
headers=self._client_headers,
timeout=5,
verify=self._client_verify_tls,
@@ -394,6 +408,10 @@ def is_dashboard_ready(self) -> bool:
except requests.exceptions.SSLError: # pragma no cover
# SSL exception occurs when oauth ingress has been created but cluster is not up
return False
+ except Exception: # pragma no cover
+ # Any other exception (connection errors, timeouts, etc.)
+ return False
+
if response.status_code == 200:
return True
else:
@@ -501,6 +519,8 @@ def cluster_dashboard_uri(self) -> str:
):
protocol = "https" if route["spec"].get("tls") else "http"
return f"{protocol}://{route['spec']['host']}"
+ # No route found for this cluster
+ return "Dashboard not available yet, have you run cluster.apply()?"
else:
try:
api_instance = client.NetworkingV1Api(get_api_client())
@@ -637,32 +657,6 @@ def list_all_queued(
return resources
-def get_current_namespace(): # pragma: no cover
- """
- Retrieves the current Kubernetes namespace.
-
- Returns:
- str:
- The current namespace or None if not found.
- """
- if os.path.isfile("/var/run/secrets/kubernetes.io/serviceaccount/namespace"):
- try:
- file = open("/var/run/secrets/kubernetes.io/serviceaccount/namespace", "r")
- active_context = file.readline().strip("\n")
- return active_context
- except Exception as e:
- print("Unable to find current namespace")
- print("trying to gather from current context")
- try:
- _, active_context = config.list_kube_config_contexts(config_check())
- except Exception as e:
- return _kube_api_error_handling(e)
- try:
- return active_context["context"]["namespace"]
- except KeyError:
- return None
-
-
def get_cluster(
cluster_name: str,
namespace: str = "default",
@@ -762,6 +756,7 @@ def get_cluster(
head_extended_resource_requests=head_extended_resources,
worker_extended_resource_requests=worker_extended_resources,
)
+
# Ignore the warning here for the lack of a ClusterConfiguration
with warnings.catch_warnings():
warnings.filterwarnings(
@@ -805,6 +800,7 @@ def remove_autogenerated_fields(resource):
del resource[key]
else:
remove_autogenerated_fields(resource[key])
+
elif isinstance(resource, list):
for item in resource:
remove_autogenerated_fields(item)
diff --git a/src/codeflare_sdk/ray/cluster/test_build_ray_cluster.py b/src/codeflare_sdk/ray/cluster/test_build_ray_cluster.py
index f970d945..3a7947d3 100644
--- a/src/codeflare_sdk/ray/cluster/test_build_ray_cluster.py
+++ b/src/codeflare_sdk/ray/cluster/test_build_ray_cluster.py
@@ -40,7 +40,7 @@ def test_gen_names_without_name(mocker):
def test_update_image_without_supported_python_version(mocker):
# Mock SUPPORTED_PYTHON_VERSIONS
mocker.patch.dict(
- "codeflare_sdk.ray.cluster.build_ray_cluster.SUPPORTED_PYTHON_VERSIONS",
+ "codeflare_sdk.common.utils.constants.SUPPORTED_PYTHON_VERSIONS",
{
"3.11": "ray-py3.11",
"3.12": "ray-py3.12",
diff --git a/src/codeflare_sdk/ray/cluster/test_cluster.py b/src/codeflare_sdk/ray/cluster/test_cluster.py
index 6475f7a8..164b3a81 100644
--- a/src/codeflare_sdk/ray/cluster/test_cluster.py
+++ b/src/codeflare_sdk/ray/cluster/test_cluster.py
@@ -956,5 +956,11 @@ def test_cluster_namespace_type_error(mocker):
# Make sure to always keep this function last
def test_cleanup():
- os.remove(f"{aw_dir}test-all-params.yaml")
- os.remove(f"{aw_dir}aw-all-params.yaml")
+ # Remove files only if they exist
+ test_file = f"{aw_dir}test-all-params.yaml"
+ if os.path.exists(test_file):
+ os.remove(test_file)
+
+ aw_file = f"{aw_dir}aw-all-params.yaml"
+ if os.path.exists(aw_file):
+ os.remove(aw_file)
diff --git a/src/codeflare_sdk/ray/rayjobs/__init__.py b/src/codeflare_sdk/ray/rayjobs/__init__.py
new file mode 100644
index 00000000..cd6b4123
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/__init__.py
@@ -0,0 +1,3 @@
+from .rayjob import RayJob, ManagedClusterConfig
+from .status import RayJobDeploymentStatus, CodeflareRayJobStatus, RayJobInfo
+from .config import ManagedClusterConfig
diff --git a/src/codeflare_sdk/ray/rayjobs/config.py b/src/codeflare_sdk/ray/rayjobs/config.py
new file mode 100644
index 00000000..5b724272
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/config.py
@@ -0,0 +1,502 @@
+# Copyright 2022 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+The config sub-module contains the definition of the ManagedClusterConfig dataclass,
+which is used to specify resource requirements and other details when creating a
+Cluster object.
+"""
+
+import pathlib
+from dataclasses import dataclass, field, fields
+from typing import Dict, List, Optional, Union, get_args, get_origin, Any, Tuple
+from kubernetes.client import (
+ V1LocalObjectReference,
+ V1SecretVolumeSource,
+ V1Toleration,
+ V1Volume,
+ V1VolumeMount,
+ V1ObjectMeta,
+ V1Container,
+ V1ContainerPort,
+ V1Lifecycle,
+ V1ExecAction,
+ V1LifecycleHandler,
+ V1EnvVar,
+ V1PodTemplateSpec,
+ V1PodSpec,
+ V1ResourceRequirements,
+)
+
+import logging
+
+from ...common.utils.constants import MOUNT_PATH, RAY_VERSION
+from ...common.utils.utils import update_image
+
+logger = logging.getLogger(__name__)
+
+dir = pathlib.Path(__file__).parent.parent.resolve()
+
+# https://docs.ray.io/en/latest/ray-core/scheduling/accelerators.html
+DEFAULT_ACCELERATORS = {
+ "nvidia.com/gpu": "GPU",
+ "intel.com/gpu": "GPU",
+ "amd.com/gpu": "GPU",
+ "aws.amazon.com/neuroncore": "neuron_cores",
+ "google.com/tpu": "TPU",
+ "habana.ai/gaudi": "HPU",
+ "huawei.com/Ascend910": "NPU",
+ "huawei.com/Ascend310": "NPU",
+}
+
+
+@dataclass
+class ManagedClusterConfig:
+ """
+ This dataclass is used to specify resource requirements and other details for RayJobs.
+ The cluster name and namespace are automatically derived from the RayJob configuration.
+
+ Args:
+ head_accelerators:
+ A dictionary of extended resource requests for the head node. ex: {"nvidia.com/gpu": 1}
+ head_tolerations:
+ List of tolerations for head nodes.
+ num_workers:
+ The number of workers to create.
+ worker_tolerations:
+ List of tolerations for worker nodes.
+ envs:
+ A dictionary of environment variables to set for the cluster.
+ image:
+ The image to use for the cluster.
+ image_pull_secrets:
+ A list of image pull secrets to use for the cluster.
+ labels:
+ A dictionary of labels to apply to the cluster.
+ worker_accelerators:
+ A dictionary of extended resource requests for each worker. ex: {"nvidia.com/gpu": 1}
+ accelerator_configs:
+ A dictionary of custom resource mappings to map extended resource requests to RayCluster resource names.
+ Defaults to DEFAULT_ACCELERATORS but can be overridden with custom mappings.
+ annotations:
+ A dictionary of annotations to apply to the Job.
+ volumes:
+ A list of V1Volume objects to add to the Cluster
+ volume_mounts:
+ A list of V1VolumeMount objects to add to the Cluster
+ """
+
+ head_cpu_requests: Union[int, str] = 2
+ head_cpu_limits: Union[int, str] = 2
+ head_memory_requests: Union[int, str] = 8
+ head_memory_limits: Union[int, str] = 8
+ head_accelerators: Dict[str, Union[str, int]] = field(default_factory=dict)
+ head_tolerations: Optional[List[V1Toleration]] = None
+ worker_cpu_requests: Union[int, str] = 1
+ worker_cpu_limits: Union[int, str] = 1
+ num_workers: int = 1
+ worker_memory_requests: Union[int, str] = 2
+ worker_memory_limits: Union[int, str] = 2
+ worker_tolerations: Optional[List[V1Toleration]] = None
+ envs: Dict[str, str] = field(default_factory=dict)
+ image: str = ""
+ image_pull_secrets: List[str] = field(default_factory=list)
+ labels: Dict[str, str] = field(default_factory=dict)
+ worker_accelerators: Dict[str, Union[str, int]] = field(default_factory=dict)
+ accelerator_configs: Dict[str, str] = field(
+ default_factory=lambda: DEFAULT_ACCELERATORS.copy()
+ )
+ annotations: Dict[str, str] = field(default_factory=dict)
+ volumes: list[V1Volume] = field(default_factory=list)
+ volume_mounts: list[V1VolumeMount] = field(default_factory=list)
+
+ def __post_init__(self):
+ self.envs["RAY_USAGE_STATS_ENABLED"] = "0"
+
+ self._validate_types()
+ self._memory_to_string()
+ self._validate_gpu_config(self.head_accelerators)
+ self._validate_gpu_config(self.worker_accelerators)
+
+ def _validate_gpu_config(self, gpu_config: Dict[str, int]):
+ for k in gpu_config.keys():
+ if k not in self.accelerator_configs.keys():
+ raise ValueError(
+ f"GPU configuration '{k}' not found in accelerator_configs, available resources are {list(self.accelerator_configs.keys())}, to add more supported resources use accelerator_configs. i.e. accelerator_configs = {{'{k}': 'FOO_BAR'}}"
+ )
+
+ def _memory_to_string(self):
+ if isinstance(self.head_memory_requests, int):
+ self.head_memory_requests = f"{self.head_memory_requests}G"
+ if isinstance(self.head_memory_limits, int):
+ self.head_memory_limits = f"{self.head_memory_limits}G"
+ if isinstance(self.worker_memory_requests, int):
+ self.worker_memory_requests = f"{self.worker_memory_requests}G"
+ if isinstance(self.worker_memory_limits, int):
+ self.worker_memory_limits = f"{self.worker_memory_limits}G"
+
+ def _validate_types(self):
+ """Validate the types of all fields in the ManagedClusterConfig dataclass."""
+ errors = []
+ for field_info in fields(self):
+ value = getattr(self, field_info.name)
+ expected_type = field_info.type
+ if not self._is_type(value, expected_type):
+ errors.append(f"'{field_info.name}' should be of type {expected_type}.")
+
+ if errors:
+ raise TypeError("Type validation failed:\n" + "\n".join(errors))
+
+ @staticmethod
+ def _is_type(value, expected_type):
+ """Check if the value matches the expected type."""
+
+ def check_type(value, expected_type):
+ origin_type = get_origin(expected_type)
+ args = get_args(expected_type)
+ if origin_type is Union:
+ return any(check_type(value, union_type) for union_type in args)
+ if origin_type is list:
+ if value is not None:
+ return all(check_type(elem, args[0]) for elem in (value or []))
+ else:
+ return True
+ if origin_type is dict:
+ if value is not None:
+ return all(
+ check_type(k, args[0]) and check_type(v, args[1])
+ for k, v in value.items()
+ )
+ else:
+ return True
+ if origin_type is tuple:
+ return all(check_type(elem, etype) for elem, etype in zip(value, args))
+ if expected_type is int:
+ return isinstance(value, int) and not isinstance(value, bool)
+ if expected_type is bool:
+ return isinstance(value, bool)
+ return isinstance(value, expected_type)
+
+ return check_type(value, expected_type)
+
+ def build_ray_cluster_spec(self, cluster_name: str) -> Dict[str, Any]:
+ """
+ Build the RayCluster spec from ManagedClusterConfig for embedding in RayJob.
+
+ Args:
+ self: The cluster configuration object (ManagedClusterConfig)
+ cluster_name: The name for the cluster (derived from RayJob name)
+
+ Returns:
+ Dict containing the RayCluster spec for embedding in RayJob
+ """
+ ray_cluster_spec = {
+ "rayVersion": RAY_VERSION,
+ "enableInTreeAutoscaling": False, # Required for Kueue-managed jobs
+ "headGroupSpec": self._build_head_group_spec(),
+ "workerGroupSpecs": [self._build_worker_group_spec(cluster_name)],
+ }
+
+ return ray_cluster_spec
+
+ def _build_head_group_spec(self) -> Dict[str, Any]:
+ """Build the head group specification."""
+ return {
+ "serviceType": "ClusterIP",
+ "enableIngress": False,
+ "rayStartParams": self._build_head_ray_params(),
+ "template": V1PodTemplateSpec(
+ metadata=V1ObjectMeta(annotations=self.annotations),
+ spec=self._build_pod_spec(self._build_head_container(), is_head=True),
+ ),
+ }
+
+ def _build_worker_group_spec(self, cluster_name: str) -> Dict[str, Any]:
+ """Build the worker group specification."""
+ return {
+ "replicas": self.num_workers,
+ "minReplicas": self.num_workers,
+ "maxReplicas": self.num_workers,
+ "groupName": f"worker-group-{cluster_name}",
+ "rayStartParams": self._build_worker_ray_params(),
+ "template": V1PodTemplateSpec(
+ metadata=V1ObjectMeta(annotations=self.annotations),
+ spec=self._build_pod_spec(
+ self._build_worker_container(),
+ is_head=False,
+ ),
+ ),
+ }
+
+ def _build_head_ray_params(self) -> Dict[str, str]:
+ """Build Ray start parameters for head node."""
+ params = {
+ "dashboard-host": "0.0.0.0",
+ "block": "true",
+ }
+
+ # Add GPU count if specified
+ if self.head_accelerators:
+ gpu_count = sum(
+ count
+ for resource_type, count in self.head_accelerators.items()
+ if "gpu" in resource_type.lower()
+ )
+ if gpu_count > 0:
+ params["num-gpus"] = str(gpu_count)
+
+ return params
+
+ def _build_worker_ray_params(self) -> Dict[str, str]:
+ """Build Ray start parameters for worker nodes."""
+ params = {
+ "block": "true",
+ }
+
+ # Add GPU count if specified
+ if self.worker_accelerators:
+ gpu_count = sum(
+ count
+ for resource_type, count in self.worker_accelerators.items()
+ if "gpu" in resource_type.lower()
+ )
+ if gpu_count > 0:
+ params["num-gpus"] = str(gpu_count)
+
+ return params
+
+ def _build_head_container(self) -> V1Container:
+ """Build the head container specification."""
+ container = V1Container(
+ name="ray-head",
+ image=update_image(self.image),
+ image_pull_policy="IfNotPresent", # Always IfNotPresent for RayJobs
+ ports=[
+ V1ContainerPort(name="gcs", container_port=6379),
+ V1ContainerPort(name="dashboard", container_port=8265),
+ V1ContainerPort(name="client", container_port=10001),
+ ],
+ lifecycle=V1Lifecycle(
+ pre_stop=V1LifecycleHandler(
+ _exec=V1ExecAction(command=["/bin/sh", "-c", "ray stop"])
+ )
+ ),
+ resources=self._build_resource_requirements(
+ self.head_cpu_requests,
+ self.head_cpu_limits,
+ self.head_memory_requests,
+ self.head_memory_limits,
+ self.head_accelerators,
+ ),
+ volume_mounts=self._generate_volume_mounts(),
+ env=self._build_env_vars() if hasattr(self, "envs") and self.envs else None,
+ )
+
+ return container
+
+ def _build_worker_container(self) -> V1Container:
+ """Build the worker container specification."""
+ container = V1Container(
+ name="ray-worker",
+ image=update_image(self.image),
+ image_pull_policy="IfNotPresent", # Always IfNotPresent for RayJobs
+ lifecycle=V1Lifecycle(
+ pre_stop=V1LifecycleHandler(
+ _exec=V1ExecAction(command=["/bin/sh", "-c", "ray stop"])
+ )
+ ),
+ resources=self._build_resource_requirements(
+ self.worker_cpu_requests,
+ self.worker_cpu_limits,
+ self.worker_memory_requests,
+ self.worker_memory_limits,
+ self.worker_accelerators,
+ ),
+ volume_mounts=self._generate_volume_mounts(),
+ env=self._build_env_vars() if hasattr(self, "envs") and self.envs else None,
+ )
+
+ return container
+
+ def _build_resource_requirements(
+ self,
+ cpu_requests: Union[int, str],
+ cpu_limits: Union[int, str],
+ memory_requests: Union[int, str],
+ memory_limits: Union[int, str],
+ extended_resource_requests: Dict[str, Union[int, str]] = None,
+ ) -> V1ResourceRequirements:
+ """Build Kubernetes resource requirements."""
+ resource_requirements = V1ResourceRequirements(
+ requests={"cpu": cpu_requests, "memory": memory_requests},
+ limits={"cpu": cpu_limits, "memory": memory_limits},
+ )
+
+ # Add extended resources (e.g., GPUs)
+ if extended_resource_requests:
+ for resource_type, amount in extended_resource_requests.items():
+ resource_requirements.limits[resource_type] = amount
+ resource_requirements.requests[resource_type] = amount
+
+ return resource_requirements
+
+ def _build_pod_spec(self, container: V1Container, is_head: bool) -> V1PodSpec:
+ """Build the pod specification."""
+ pod_spec = V1PodSpec(
+ containers=[container],
+ volumes=self._generate_volumes(),
+ restart_policy="Never", # RayJobs should not restart
+ )
+
+ # Add tolerations if specified
+ if is_head and hasattr(self, "head_tolerations") and self.head_tolerations:
+ pod_spec.tolerations = self.head_tolerations
+ elif (
+ not is_head
+ and hasattr(self, "worker_tolerations")
+ and self.worker_tolerations
+ ):
+ pod_spec.tolerations = self.worker_tolerations
+
+ # Add image pull secrets if specified
+ if hasattr(self, "image_pull_secrets") and self.image_pull_secrets:
+ pod_spec.image_pull_secrets = [
+ V1LocalObjectReference(name=secret)
+ for secret in self.image_pull_secrets
+ ]
+
+ return pod_spec
+
+ def _generate_volume_mounts(self) -> list:
+ """Generate volume mounts for the container."""
+ volume_mounts = []
+
+ # Add custom volume mounts if specified
+ if hasattr(self, "volume_mounts") and self.volume_mounts:
+ volume_mounts.extend(self.volume_mounts)
+
+ return volume_mounts
+
+ def _generate_volumes(self) -> list:
+ """Generate volumes for the pod."""
+ volumes = []
+
+ # Add custom volumes if specified
+ if hasattr(self, "volumes") and self.volumes:
+ volumes.extend(self.volumes)
+
+ return volumes
+
+ def _build_env_vars(self) -> list:
+ """Build environment variables list."""
+ return [V1EnvVar(name=key, value=value) for key, value in self.envs.items()]
+
+ def add_file_volumes(self, secret_name: str, mount_path: str = MOUNT_PATH):
+ """
+ Add file volume and mount references to cluster configuration.
+
+ Args:
+ secret_name: Name of the Secret containing files
+ mount_path: Where to mount files in containers (default: /home/ray/scripts)
+ """
+ # Check if file volume already exists
+ volume_name = "ray-job-files"
+ existing_volume = next(
+ (v for v in self.volumes if getattr(v, "name", None) == volume_name), None
+ )
+ if existing_volume:
+ logger.debug(f"File volume '{volume_name}' already exists, skipping...")
+ return
+
+ # Check if file mount already exists
+ existing_mount = next(
+ (m for m in self.volume_mounts if getattr(m, "name", None) == volume_name),
+ None,
+ )
+ if existing_mount:
+ logger.debug(
+ f"File volume mount '{volume_name}' already exists, skipping..."
+ )
+ return
+
+ # Add file volume to cluster configuration
+ file_volume = V1Volume(
+ name=volume_name, secret=V1SecretVolumeSource(secret_name=secret_name)
+ )
+ self.volumes.append(file_volume)
+
+ # Add file volume mount to cluster configuration
+ file_mount = V1VolumeMount(name=volume_name, mount_path=mount_path)
+ self.volume_mounts.append(file_mount)
+
+ logger.info(
+ f"Added file volume '{secret_name}' to cluster config: mount_path={mount_path}"
+ )
+
+ def validate_secret_size(self, files: Dict[str, str]) -> None:
+ total_size = sum(len(content.encode("utf-8")) for content in files.values())
+ if total_size > 1024 * 1024: # 1MB
+ raise ValueError(
+ f"Secret size exceeds 1MB limit. Total size: {total_size} bytes"
+ )
+
+ def build_file_secret_spec(
+ self, job_name: str, namespace: str, files: Dict[str, str]
+ ) -> Dict[str, Any]:
+ """
+ Build Secret specification for files
+
+ Args:
+ job_name: Name of the RayJob (used for Secret naming)
+ namespace: Kubernetes namespace
+ files: Dictionary of file_name -> file_content
+
+ Returns:
+ Dict: Secret specification ready for Kubernetes API
+ """
+ secret_name = f"{job_name}-files"
+ return {
+ "apiVersion": "v1",
+ "kind": "Secret",
+ "type": "Opaque",
+ "metadata": {
+ "name": secret_name,
+ "namespace": namespace,
+ "labels": {
+ "ray.io/job-name": job_name,
+ "app.kubernetes.io/managed-by": "codeflare-sdk",
+ "app.kubernetes.io/component": "rayjob-files",
+ },
+ },
+ "data": files,
+ }
+
+ def build_file_volume_specs(
+ self, secret_name: str, mount_path: str = MOUNT_PATH
+ ) -> Tuple[Dict[str, Any], Dict[str, Any]]:
+ """
+ Build volume and mount specifications for files
+
+ Args:
+ secret_name: Name of the Secret containing files
+ mount_path: Where to mount files in containers
+
+ Returns:
+ Tuple of (volume_spec, mount_spec) as dictionaries
+ """
+ volume_spec = {"name": "ray-job-files", "secret": {"secretName": secret_name}}
+
+ mount_spec = {"name": "ray-job-files", "mountPath": mount_path}
+
+ return volume_spec, mount_spec
diff --git a/src/codeflare_sdk/ray/rayjobs/pretty_print.py b/src/codeflare_sdk/ray/rayjobs/pretty_print.py
new file mode 100644
index 00000000..34e8dfa1
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/pretty_print.py
@@ -0,0 +1,117 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+This sub-module exists primarily to be used internally by the RayJob object
+(in the rayjob sub-module) for pretty-printing job status and details.
+"""
+
+from rich.console import Console
+from rich.table import Table
+from rich.panel import Panel
+from typing import Tuple, Optional
+
+from .status import RayJobDeploymentStatus, RayJobInfo
+
+
+def print_job_status(job_info: RayJobInfo):
+ """
+ Pretty print the job status in a format similar to cluster status.
+ """
+ status_display, header_color = _get_status_display(job_info.status)
+
+ # Create main info table
+ table = _create_info_table(header_color, job_info.name, status_display)
+ table.add_row(f"[bold]Job ID:[/bold] {job_info.job_id}")
+ table.add_row(f"[bold]Status:[/bold] {job_info.status.value}")
+ table.add_row(f"[bold]RayCluster:[/bold] {job_info.cluster_name}")
+ table.add_row(f"[bold]Namespace:[/bold] {job_info.namespace}")
+
+ # Add timing information if available
+ if job_info.start_time:
+ table.add_row()
+ table.add_row(f"[bold]Started:[/bold] {job_info.start_time}")
+
+ # Add attempt counts if there are failures
+ if job_info.failed_attempts > 0:
+ table.add_row(f"[bold]Failed Attempts:[/bold] {job_info.failed_attempts}")
+
+ _print_table_in_panel(table)
+
+
+def print_no_job_found(job_name: str, namespace: str):
+ """
+ Print a message when no job is found.
+ """
+ # Create table with error message
+ table = _create_info_table(
+ "[white on red][bold]Name", job_name, "[bold red]No RayJob found"
+ )
+ table.add_row()
+ table.add_row("Please run rayjob.submit() to submit a job.")
+ table.add_row()
+ table.add_row(f"[bold]Namespace:[/bold] {namespace}")
+
+ _print_table_in_panel(table)
+
+
+def _get_status_display(status: RayJobDeploymentStatus) -> Tuple[str, str]:
+ """
+ Get the display string and header color for a given status.
+
+ Returns:
+ Tuple of (status_display, header_color)
+ """
+ status_mapping = {
+ RayJobDeploymentStatus.COMPLETE: (
+ "Complete :white_heavy_check_mark:",
+ "[white on green][bold]Name",
+ ),
+ RayJobDeploymentStatus.RUNNING: ("Running :gear:", "[white on blue][bold]Name"),
+ RayJobDeploymentStatus.FAILED: ("Failed :x:", "[white on red][bold]Name"),
+ RayJobDeploymentStatus.SUSPENDED: (
+ "Suspended :pause_button:",
+ "[white on yellow][bold]Name",
+ ),
+ }
+
+ return status_mapping.get(
+ status, ("Unknown :question:", "[white on red][bold]Name")
+ )
+
+
+def _create_info_table(header_color: str, name: str, status_display: str) -> Table:
+ """
+ Create a standardized info table with header and status.
+
+ Returns:
+ Table with header row, name/status row, and empty separator row
+ """
+ table = Table(box=None, show_header=False)
+ table.add_row(header_color)
+ table.add_row("[bold underline]" + name, status_display)
+ table.add_row() # Empty separator row
+ return table
+
+
+def _print_table_in_panel(table: Table):
+ """
+ Print a table wrapped in a consistent panel format.
+ """
+ console = Console()
+ main_table = Table(
+ box=None, title="[bold] :package: CodeFlare RayJob Status :package:"
+ )
+ main_table.add_row(Panel.fit(table))
+ console.print(main_table)
diff --git a/src/codeflare_sdk/ray/rayjobs/rayjob.py b/src/codeflare_sdk/ray/rayjobs/rayjob.py
new file mode 100644
index 00000000..65478087
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/rayjob.py
@@ -0,0 +1,615 @@
+# Copyright 2022-2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+RayJob client for submitting and managing Ray jobs using the kuberay python client.
+"""
+
+import logging
+import os
+import re
+import warnings
+from typing import Dict, Any, Optional, Tuple, Union
+
+from ray.runtime_env import RuntimeEnv
+from codeflare_sdk.common.kueue.kueue import get_default_kueue_name
+from codeflare_sdk.common.utils.constants import MOUNT_PATH
+
+from codeflare_sdk.common.utils.utils import get_ray_image_for_python_version
+from python_client.kuberay_job_api import RayjobApi
+from python_client.kuberay_cluster_api import RayClusterApi
+from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig
+from codeflare_sdk.ray.rayjobs.runtime_env import (
+ create_file_secret,
+ extract_all_local_files,
+ process_runtime_env,
+)
+
+from ...common.utils import get_current_namespace
+from ...common.utils.validation import validate_ray_version_compatibility
+
+from .status import (
+ RayJobDeploymentStatus,
+ CodeflareRayJobStatus,
+ RayJobInfo,
+)
+from . import pretty_print
+
+
+logger = logging.getLogger(__name__)
+
+
+class RayJob:
+ """
+ A client for managing Ray jobs using the KubeRay operator.
+
+ This class provides a simplified interface for submitting and managing
+ RayJob CRs (using the KubeRay RayJob python client).
+ """
+
+ def __init__(
+ self,
+ job_name: str,
+ entrypoint: str,
+ cluster_name: Optional[str] = None,
+ cluster_config: Optional[ManagedClusterConfig] = None,
+ namespace: Optional[str] = None,
+ runtime_env: Optional[Union[RuntimeEnv, Dict[str, Any]]] = None,
+ ttl_seconds_after_finished: int = 0,
+ active_deadline_seconds: Optional[int] = None,
+ local_queue: Optional[str] = None,
+ ):
+ """
+ Initialize a RayJob instance.
+
+ Args:
+ job_name: The name for the Ray job
+ entrypoint: The Python script or command to run (required)
+ cluster_name: The name of an existing Ray cluster (optional if cluster_config provided)
+ cluster_config: Configuration for creating a new cluster (optional if cluster_name provided)
+ namespace: The Kubernetes namespace (auto-detected if not specified)
+ runtime_env: Ray runtime environment configuration. Can be:
+ - RuntimeEnv object from ray.runtime_env
+ - Dict with keys like 'working_dir', 'pip', 'env_vars', etc.
+ Example: {"working_dir": "./my-scripts", "pip": ["requests"]}
+ ttl_seconds_after_finished: Seconds to wait before cleanup after job finishes (default: 0)
+ active_deadline_seconds: Maximum time the job can run before being terminated (optional)
+ local_queue: The Kueue LocalQueue to submit the job to (optional)
+
+ Note:
+ - True if cluster_config is provided (new cluster will be cleaned up)
+ - False if cluster_name is provided (existing cluster will not be shut down)
+ - User can explicitly set this value to override auto-detection
+ """
+ if cluster_name is None and cluster_config is None:
+ raise ValueError(
+ "❌ Configuration Error: You must provide either 'cluster_name' (for existing cluster) "
+ "or 'cluster_config' (to create new cluster), but not both."
+ )
+
+ if cluster_name is not None and cluster_config is not None:
+ raise ValueError(
+ "❌ Configuration Error: You cannot specify both 'cluster_name' and 'cluster_config'. "
+ "Choose one approach:\n"
+ "• Use 'cluster_name' to connect to an existing cluster\n"
+ "• Use 'cluster_config' to create a new cluster"
+ )
+
+ if cluster_config is None and cluster_name is None:
+ raise ValueError(
+ "❌ Configuration Error: When not providing 'cluster_config', 'cluster_name' is required "
+ "to specify which existing cluster to use."
+ )
+
+ self.name = job_name
+ self.entrypoint = entrypoint
+
+ # Convert dict to RuntimeEnv if needed for user convenience
+ if isinstance(runtime_env, dict):
+ self.runtime_env = RuntimeEnv(**runtime_env)
+ else:
+ self.runtime_env = runtime_env
+
+ self.ttl_seconds_after_finished = ttl_seconds_after_finished
+ self.active_deadline_seconds = active_deadline_seconds
+ self.local_queue = local_queue
+
+ if namespace is None:
+ detected_namespace = get_current_namespace()
+ if detected_namespace:
+ self.namespace = detected_namespace
+ logger.info(f"Auto-detected namespace: {self.namespace}")
+ else:
+ raise ValueError(
+ "❌ Configuration Error: Could not auto-detect Kubernetes namespace. "
+ "Please explicitly specify the 'namespace' parameter. "
+ )
+ else:
+ self.namespace = namespace
+
+ self._cluster_name = cluster_name
+ self._cluster_config = cluster_config
+
+ if cluster_config is not None:
+ self.cluster_name = f"{job_name}-cluster"
+ logger.info(f"Creating new cluster: {self.cluster_name}")
+ else:
+ # Using existing cluster: cluster_name must be provided
+ if cluster_name is None:
+ raise ValueError(
+ "❌ Configuration Error: a 'cluster_name' is required when not providing 'cluster_config'"
+ )
+ self.cluster_name = cluster_name
+ logger.info(f"Using existing cluster: {self.cluster_name}")
+
+ self._api = RayjobApi()
+ self._cluster_api = RayClusterApi()
+
+ logger.info(f"Initialized RayJob: {self.name} in namespace: {self.namespace}")
+
+ def submit(self) -> str:
+ if not self.entrypoint:
+ raise ValueError("Entrypoint must be provided to submit a RayJob")
+
+ # Validate configuration before submitting
+ self._validate_ray_version_compatibility()
+ self._validate_working_dir_entrypoint()
+
+ # Extract files from entrypoint and runtime_env working_dir
+ files = extract_all_local_files(self)
+
+ rayjob_cr = self._build_rayjob_cr()
+
+ logger.info(f"Submitting RayJob {self.name} to Kuberay operator")
+ result = self._api.submit_job(k8s_namespace=self.namespace, job=rayjob_cr)
+
+ if result:
+ logger.info(f"Successfully submitted RayJob {self.name}")
+
+ # Create Secret with owner reference after RayJob exists
+ if files:
+ create_file_secret(self, files, result)
+
+ return self.name
+ else:
+ raise RuntimeError(f"Failed to submit RayJob {self.name}")
+
+ def stop(self):
+ """
+ Suspend the Ray job.
+ """
+ stopped = self._api.suspend_job(name=self.name, k8s_namespace=self.namespace)
+ if stopped:
+ logger.info(f"Successfully stopped the RayJob {self.name}")
+ return True
+ else:
+ raise RuntimeError(f"Failed to stop the RayJob {self.name}")
+
+ def resubmit(self):
+ """
+ Resubmit the Ray job.
+ """
+ if self._api.resubmit_job(name=self.name, k8s_namespace=self.namespace):
+ logger.info(f"Successfully resubmitted the RayJob {self.name}")
+ return True
+ else:
+ raise RuntimeError(f"Failed to resubmit the RayJob {self.name}")
+
+ def delete(self):
+ """
+ Delete the Ray job.
+ Returns True if deleted successfully or if already deleted.
+ """
+ deleted = self._api.delete_job(name=self.name, k8s_namespace=self.namespace)
+ if deleted:
+ logger.info(f"Successfully deleted the RayJob {self.name}")
+ return True
+ else:
+ # The python client logs "rayjob custom resource already deleted"
+ # and returns False when the job doesn't exist.
+ # This is not an error - treat it as successful deletion.
+ logger.info(f"RayJob {self.name} already deleted or does not exist")
+ return True
+
+ def _build_rayjob_cr(self) -> Dict[str, Any]:
+ """
+ Build the RayJob custom resource specification using native RayJob capabilities.
+ """
+ rayjob_cr = {
+ "apiVersion": "ray.io/v1",
+ "kind": "RayJob",
+ "metadata": {
+ "name": self.name,
+ "namespace": self.namespace,
+ },
+ "spec": {
+ "entrypoint": self.entrypoint,
+ "ttlSecondsAfterFinished": self.ttl_seconds_after_finished,
+ "shutdownAfterJobFinishes": self._cluster_config is not None,
+ },
+ }
+
+ # Extract files once and use for both runtime_env and submitter pod
+ files = extract_all_local_files(self)
+
+ labels = {}
+ # If cluster_config is provided, use the local_queue from the cluster_config
+ if self._cluster_config is not None:
+ if self.local_queue:
+ labels["kueue.x-k8s.io/queue-name"] = self.local_queue
+ else:
+ default_queue = get_default_kueue_name(self.namespace)
+ if default_queue:
+ labels["kueue.x-k8s.io/queue-name"] = default_queue
+ else:
+ # No default queue found, use "default" as fallback
+ labels["kueue.x-k8s.io/queue-name"] = "default"
+ logger.warning(
+ f"No default Kueue LocalQueue found in namespace '{self.namespace}'. "
+ f"Using 'default' as the queue name. If a LocalQueue named 'default' "
+ f"does not exist, the RayJob submission will fail. "
+ f"To fix this, please explicitly specify the 'local_queue' parameter."
+ )
+
+ rayjob_cr["metadata"]["labels"] = labels
+
+ # When using Kueue (queue label present), start with suspend=true
+ # Kueue will unsuspend the job once the workload is admitted
+ if labels.get("kueue.x-k8s.io/queue-name"):
+ rayjob_cr["spec"]["suspend"] = True
+
+ # Add active deadline if specified
+ if self.active_deadline_seconds:
+ rayjob_cr["spec"]["activeDeadlineSeconds"] = self.active_deadline_seconds
+
+ # Add runtime environment (can be inferred even if not explicitly specified)
+ processed_runtime_env = process_runtime_env(self, files)
+ if processed_runtime_env:
+ rayjob_cr["spec"]["runtimeEnvYAML"] = processed_runtime_env
+
+ # Add submitterPodTemplate if we have files to mount
+ if files:
+ secret_name = f"{self.name}-files"
+ rayjob_cr["spec"][
+ "submitterPodTemplate"
+ ] = self._build_submitter_pod_template(files, secret_name)
+
+ # Configure cluster: either use existing or create new
+ if self._cluster_config is not None:
+ ray_cluster_spec = self._cluster_config.build_ray_cluster_spec(
+ cluster_name=self.cluster_name
+ )
+
+ logger.info(
+ f"Built RayCluster spec using RayJob-specific builder for cluster: {self.cluster_name}"
+ )
+
+ rayjob_cr["spec"]["rayClusterSpec"] = ray_cluster_spec
+
+ logger.info(f"RayJob will create new cluster: {self.cluster_name}")
+ else:
+ # Use clusterSelector to reference existing cluster
+ rayjob_cr["spec"]["clusterSelector"] = {"ray.io/cluster": self.cluster_name}
+ logger.info(f"RayJob will use existing cluster: {self.cluster_name}")
+
+ return rayjob_cr
+
+ def _build_submitter_pod_template(
+ self, files: Dict[str, str], secret_name: str
+ ) -> Dict[str, Any]:
+ """
+ Build submitterPodTemplate with Secret volume mount for local files.
+
+ If files contain working_dir.zip, an init container will unzip it before
+ the main submitter container runs.
+
+ Args:
+ files: Dict of file_name -> file_content
+ secret_name: Name of the Secret containing the files
+
+ Returns:
+ submitterPodTemplate specification
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import UNZIP_PATH
+
+ # Image has to be hard coded for the job submitter
+ image = get_ray_image_for_python_version()
+ if (
+ self._cluster_config
+ and hasattr(self._cluster_config, "image")
+ and self._cluster_config.image
+ ):
+ image = self._cluster_config.image
+
+ # Build Secret items for each file
+ secret_items = []
+ entrypoint_path = files.get(
+ "__entrypoint_path__"
+ ) # Metadata for single file case
+
+ for file_name in files.keys():
+ if file_name == "__entrypoint_path__":
+ continue # Skip metadata key
+
+ # For single file case, use the preserved path structure
+ if entrypoint_path:
+ secret_items.append({"key": file_name, "path": entrypoint_path})
+ else:
+ secret_items.append({"key": file_name, "path": file_name})
+
+ # Check if we need to unzip working_dir
+ has_working_dir_zip = "working_dir.zip" in files
+
+ # Base volume mounts for main container
+ volume_mounts = [{"name": "ray-job-files", "mountPath": MOUNT_PATH}]
+
+ # If we have a zip file, we need shared volume for unzipped content
+ if has_working_dir_zip:
+ volume_mounts.append(
+ {"name": "unzipped-working-dir", "mountPath": UNZIP_PATH}
+ )
+
+ submitter_pod_template = {
+ "spec": {
+ "restartPolicy": "Never",
+ "containers": [
+ {
+ "name": "ray-job-submitter",
+ "image": image,
+ "volumeMounts": volume_mounts,
+ }
+ ],
+ "volumes": [
+ {
+ "name": "ray-job-files",
+ "secret": {
+ "secretName": secret_name,
+ "items": secret_items,
+ },
+ }
+ ],
+ }
+ }
+
+ # Add init container and volume for unzipping if needed
+ if has_working_dir_zip:
+ # Add emptyDir volume for unzipped content
+ submitter_pod_template["spec"]["volumes"].append(
+ {"name": "unzipped-working-dir", "emptyDir": {}}
+ )
+
+ # Add init container to unzip before KubeRay's submitter runs
+ submitter_pod_template["spec"]["initContainers"] = [
+ {
+ "name": "unzip-working-dir",
+ "image": image,
+ "command": ["/bin/sh", "-c"],
+ "args": [
+ # Decode base64 zip, save to temp file, extract, cleanup
+ f"mkdir -p {UNZIP_PATH} && "
+ f"python3 -m base64 -d {MOUNT_PATH}/working_dir.zip > /tmp/working_dir.zip && "
+ f"python3 -m zipfile -e /tmp/working_dir.zip {UNZIP_PATH}/ && "
+ f"rm /tmp/working_dir.zip && "
+ f"echo 'Successfully unzipped working_dir to {UNZIP_PATH}' && "
+ f"ls -la {UNZIP_PATH}"
+ ],
+ "volumeMounts": volume_mounts,
+ }
+ ]
+ logger.info(f"Added init container to unzip working_dir to {UNZIP_PATH}")
+
+ logger.info(
+ f"Built submitterPodTemplate with {len(files)} files mounted at {MOUNT_PATH}, using image: {image}"
+ )
+ return submitter_pod_template
+
+ def _validate_ray_version_compatibility(self):
+ """
+ Validate Ray version compatibility for cluster_config image.
+ Raises ValueError if there is a version mismatch.
+ """
+ # Validate cluster_config image if creating new cluster
+ if self._cluster_config is not None:
+ self._validate_cluster_config_image()
+
+ def _validate_cluster_config_image(self):
+ """
+ Validate that the Ray version in cluster_config image matches the SDK's Ray version.
+ """
+ if not hasattr(self._cluster_config, "image"):
+ logger.debug(
+ "No image attribute found in cluster config, skipping validation"
+ )
+ return
+
+ image = self._cluster_config.image
+ if not image:
+ logger.debug("Cluster config image is empty, skipping validation")
+ return
+
+ if not isinstance(image, str):
+ logger.warning(
+ f"Cluster config image should be a string, got {type(image).__name__}: {image}"
+ )
+ return # Skip validation for malformed image
+
+ is_compatible, is_warning, message = validate_ray_version_compatibility(image)
+ if not is_compatible:
+ raise ValueError(f"Cluster config image: {message}")
+ elif is_warning:
+ warnings.warn(f"Cluster config image: {message}")
+
+ def _validate_working_dir_entrypoint(self):
+ """
+ Validate entrypoint file configuration.
+
+ Checks:
+ 1. Entrypoint doesn't redundantly reference working_dir
+ 2. Local files exist before submission
+
+ Raises ValueError if validation fails.
+ """
+ # Skip validation for inline commands (python -c, etc.)
+ if re.search(r"\s+-c\s+", self.entrypoint):
+ return
+
+ # Match Python file references only
+ file_pattern = r"(?:python\d?\s+)?([./\w/-]+\.py)"
+ matches = re.findall(file_pattern, self.entrypoint)
+
+ if not matches:
+ return
+
+ entrypoint_path = matches[0]
+
+ # Get working_dir from runtime_env
+ runtime_env_dict = None
+ working_dir = None
+
+ if self.runtime_env:
+ runtime_env_dict = (
+ self.runtime_env.to_dict()
+ if hasattr(self.runtime_env, "to_dict")
+ else self.runtime_env
+ )
+ if runtime_env_dict and "working_dir" in runtime_env_dict:
+ working_dir = runtime_env_dict["working_dir"]
+
+ # Skip all validation for remote working_dir
+ if working_dir and not os.path.isdir(working_dir):
+ return
+
+ # Case 1: Local working_dir - check redundancy and file existence
+ if working_dir:
+ normalized_working_dir = os.path.normpath(working_dir)
+ normalized_entrypoint = os.path.normpath(entrypoint_path)
+
+ # Check for redundant directory reference
+ if normalized_entrypoint.startswith(normalized_working_dir + os.sep):
+ relative_to_working_dir = os.path.relpath(
+ normalized_entrypoint, normalized_working_dir
+ )
+ working_dir_basename = os.path.basename(normalized_working_dir)
+ redundant_nested_path = os.path.join(
+ normalized_working_dir,
+ working_dir_basename,
+ relative_to_working_dir,
+ )
+
+ if not os.path.exists(redundant_nested_path):
+ raise ValueError(
+ f"❌ Working directory conflict detected:\n"
+ f" working_dir: '{working_dir}'\n"
+ f" entrypoint references: '{entrypoint_path}'\n"
+ f"\n"
+ f"This will fail because the entrypoint runs from within working_dir.\n"
+ f"It would look for: '{redundant_nested_path}' (which doesn't exist)\n"
+ f"\n"
+ f"Fix: Remove the directory prefix from your entrypoint:\n"
+ f' entrypoint = "python {relative_to_working_dir}"'
+ )
+
+ # Check file exists within working_dir
+ if not normalized_entrypoint.startswith(normalized_working_dir + os.sep):
+ # Use normalized_working_dir (absolute path) for proper file existence check
+ full_entrypoint_path = os.path.join(
+ normalized_working_dir, entrypoint_path
+ )
+ if not os.path.isfile(full_entrypoint_path):
+ raise ValueError(
+ f"❌ Entrypoint file not found:\n"
+ f" Looking for: '{full_entrypoint_path}'\n"
+ f" (working_dir: '{working_dir}', entrypoint file: '{entrypoint_path}')\n"
+ f"\n"
+ f"Please ensure the file exists at the expected location."
+ )
+
+ # Case 2: No working_dir - validate local file exists
+ else:
+ if not os.path.isfile(entrypoint_path):
+ raise ValueError(
+ f"❌ Entrypoint file not found: '{entrypoint_path}'\n"
+ f"\n"
+ f"Please ensure the file exists at the specified path."
+ )
+
+ def status(
+ self, print_to_console: bool = True
+ ) -> Tuple[CodeflareRayJobStatus, bool]:
+ """
+ Get the status of the Ray job.
+
+ Args:
+ print_to_console (bool): Whether to print formatted status to console (default: True)
+
+ Returns:
+ Tuple of (CodeflareRayJobStatus, ready: bool) where ready indicates job completion
+ """
+ status_data = self._api.get_job_status(
+ name=self.name, k8s_namespace=self.namespace
+ )
+
+ if not status_data:
+ if print_to_console:
+ pretty_print.print_no_job_found(self.name, self.namespace)
+ return CodeflareRayJobStatus.UNKNOWN, False
+
+ # Map deployment status to our enums
+ deployment_status_str = status_data.get("jobDeploymentStatus", "Unknown")
+
+ try:
+ deployment_status = RayJobDeploymentStatus(deployment_status_str)
+ except ValueError:
+ deployment_status = RayJobDeploymentStatus.UNKNOWN
+
+ # Create RayJobInfo dataclass
+ job_info = RayJobInfo(
+ name=self.name,
+ job_id=status_data.get("jobId", ""),
+ status=deployment_status,
+ namespace=self.namespace,
+ cluster_name=self.cluster_name,
+ start_time=status_data.get("startTime"),
+ end_time=status_data.get("endTime"),
+ failed_attempts=status_data.get("failed", 0),
+ succeeded_attempts=status_data.get("succeeded", 0),
+ )
+
+ # Map to CodeFlare status and determine readiness
+ codeflare_status, ready = self._map_to_codeflare_status(deployment_status)
+
+ if print_to_console:
+ pretty_print.print_job_status(job_info)
+
+ return codeflare_status, ready
+
+ def _map_to_codeflare_status(
+ self, deployment_status: RayJobDeploymentStatus
+ ) -> Tuple[CodeflareRayJobStatus, bool]:
+ """
+ Map deployment status to CodeFlare status and determine readiness.
+
+ Returns:
+ Tuple of (CodeflareRayJobStatus, ready: bool)
+ """
+ status_mapping = {
+ RayJobDeploymentStatus.COMPLETE: (CodeflareRayJobStatus.COMPLETE, True),
+ RayJobDeploymentStatus.RUNNING: (CodeflareRayJobStatus.RUNNING, False),
+ RayJobDeploymentStatus.FAILED: (CodeflareRayJobStatus.FAILED, False),
+ RayJobDeploymentStatus.SUSPENDED: (CodeflareRayJobStatus.SUSPENDED, False),
+ }
+
+ return status_mapping.get(
+ deployment_status, (CodeflareRayJobStatus.UNKNOWN, False)
+ )
diff --git a/src/codeflare_sdk/ray/rayjobs/runtime_env.py b/src/codeflare_sdk/ray/rayjobs/runtime_env.py
new file mode 100644
index 00000000..93606d73
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/runtime_env.py
@@ -0,0 +1,405 @@
+from __future__ import annotations # Postpone evaluation of annotations
+
+import logging
+import os
+import re
+import yaml
+import zipfile
+import base64
+import io
+from typing import Dict, Any, Optional, List, TYPE_CHECKING
+from codeflare_sdk.common.utils.constants import MOUNT_PATH
+from kubernetes import client
+from ray.runtime_env import RuntimeEnv
+
+from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig
+from ...common.kubernetes_cluster.auth import get_api_client
+
+# Use TYPE_CHECKING to avoid circular import at runtime
+if TYPE_CHECKING:
+ from codeflare_sdk.ray.rayjobs.rayjob import RayJob
+
+logger = logging.getLogger(__name__)
+
+# Regex pattern for finding Python files in entrypoint commands
+# Matches paths like: test.py, ./test.py, dir/test.py, my-dir/test.py
+PYTHON_FILE_PATTERN = r"(?:python\s+)?([./\w/-]+\.py)"
+
+# Path where working_dir will be unzipped on submitter pod
+UNZIP_PATH = "/tmp/rayjob-working-dir"
+
+# Exclude Jupyter notebook and Markdown files from working directory zips
+JUPYTER_NOTEBOOK_PATTERN = r"\.ipynb$"
+MARKDOWN_FILE_PATTERN = r"\.md$"
+
+
+def _should_exclude_file(file_path: str) -> bool:
+ """
+ Check if file should be excluded from working directory zip.
+ Currently excludes:
+ - Jupyter notebook files (.ipynb)
+ - Markdown files (.md)
+
+ Args:
+ file_path: Relative file path within the working directory
+
+ Returns:
+ True if file should be excluded, False otherwise
+ """
+ return bool(
+ re.search(JUPYTER_NOTEBOOK_PATTERN, file_path, re.IGNORECASE)
+ or re.search(MARKDOWN_FILE_PATTERN, file_path, re.IGNORECASE)
+ )
+
+
+def _normalize_runtime_env(
+ runtime_env: Optional[RuntimeEnv],
+) -> Optional[Dict[str, Any]]:
+ if runtime_env is None:
+ return None
+ return runtime_env.to_dict()
+
+
+def extract_all_local_files(job: RayJob) -> Optional[Dict[str, str]]:
+ """
+ Prepare local files for Secret upload.
+
+ - If runtime_env has local working_dir: zip entire directory into single file
+ - If single entrypoint file (no working_dir): extract that file
+ - If remote working_dir URL: return None (pass through to Ray)
+
+ Returns:
+ Dict with either:
+ - {"working_dir.zip": } for zipped directories
+ - {"script.py": } for single files
+ - None for remote working_dir or no files
+ """
+ # Convert RuntimeEnv to dict for processing
+ runtime_env_dict = _normalize_runtime_env(job.runtime_env)
+
+ # If there's a remote working_dir, don't extract local files
+ if (
+ runtime_env_dict
+ and "working_dir" in runtime_env_dict
+ and not os.path.isdir(runtime_env_dict["working_dir"])
+ ):
+ logger.info(
+ f"Remote working_dir detected: {runtime_env_dict['working_dir']}. "
+ "Skipping local file extraction - using remote source."
+ )
+ return None
+
+ # If there's a local working_dir, zip it
+ if (
+ runtime_env_dict
+ and "working_dir" in runtime_env_dict
+ and os.path.isdir(runtime_env_dict["working_dir"])
+ ):
+ working_dir = runtime_env_dict["working_dir"]
+ logger.info(f"Zipping local working_dir: {working_dir}")
+ zip_data = _zip_directory(working_dir)
+ if zip_data:
+ # Encode zip as base64 for Secret storage
+ zip_base64 = base64.b64encode(zip_data).decode("utf-8")
+ return {"working_dir.zip": zip_base64}
+
+ # If no working_dir, check for single entrypoint file
+ entrypoint_file = _extract_single_entrypoint_file(job)
+ if entrypoint_file:
+ return entrypoint_file
+
+ return None
+
+
+def _zip_directory(directory_path: str) -> Optional[bytes]:
+ """
+ Zip entire directory preserving structure, excluding Jupyter notebook and markdown files.
+
+ Args:
+ directory_path: Path to directory to zip
+
+ Returns:
+ Bytes of zip file, or None on error
+ """
+ try:
+ # Create in-memory zip file
+ zip_buffer = io.BytesIO()
+ excluded_count = 0
+
+ with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED) as zipf:
+ # Walk through directory and add all files
+ for root, dirs, files in os.walk(directory_path):
+ for file in files:
+ file_path = os.path.join(root, file)
+ # Calculate relative path from directory_path
+ arcname = os.path.relpath(file_path, directory_path)
+
+ # Check if file should be excluded
+ if _should_exclude_file(arcname):
+ excluded_count += 1
+ logger.debug(f"Excluded from zip: {arcname}")
+ continue
+
+ zipf.write(file_path, arcname)
+ logger.debug(f"Added to zip: {arcname}")
+
+ zip_data = zip_buffer.getvalue()
+
+ # Log summary with exclusion count
+ log_message = (
+ f"Successfully zipped directory: {directory_path} ({len(zip_data)} bytes)"
+ )
+ if excluded_count > 0:
+ log_message += f" - Excluded {excluded_count} file(s) (.ipynb, .md)"
+ logger.info(log_message)
+
+ return zip_data
+
+ except (IOError, OSError) as e:
+ logger.error(f"Failed to zip directory {directory_path}: {e}")
+ return None
+
+
+def _extract_single_entrypoint_file(job: RayJob) -> Optional[Dict[str, str]]:
+ """
+ Extract single Python file from entrypoint if no working_dir specified.
+
+ Returns a dict with metadata about the file path structure so we can
+ preserve it when mounting via Secret.
+
+ Args:
+ job: RayJob instance
+
+ Returns:
+ Dict with special format: {"__entrypoint_path__": path, "filename": content}
+ This allows us to preserve directory structure when mounting
+ """
+ if not job.entrypoint:
+ return None
+
+ # Look for Python file in entrypoint
+ matches = re.findall(PYTHON_FILE_PATTERN, job.entrypoint)
+
+ for file_path in matches:
+ # Check if it's a local file
+ if os.path.isfile(file_path):
+ try:
+ with open(file_path, "r") as f:
+ content = f.read()
+
+ # Use basename as key (Secret keys can't have slashes)
+ # But store the full path for later use in Secret item.path
+ filename = os.path.basename(file_path)
+ relative_path = file_path.lstrip("./")
+
+ logger.info(f"Extracted single entrypoint file: {file_path}")
+
+ # Return special format with metadata
+ return {"__entrypoint_path__": relative_path, filename: content}
+
+ except (IOError, OSError) as e:
+ logger.warning(f"Could not read entrypoint file {file_path}: {e}")
+
+ return None
+
+
+def process_runtime_env(
+ job: RayJob, files: Optional[Dict[str, str]] = None
+) -> Optional[str]:
+ """
+ Process runtime_env field to handle env_vars, pip dependencies, and working_dir.
+
+ Returns:
+ Processed runtime environment as YAML string, or None if no processing needed
+ """
+ # Convert RuntimeEnv to dict for processing
+ runtime_env_dict = _normalize_runtime_env(job.runtime_env)
+
+ processed_env = {}
+
+ # Handle env_vars
+ if runtime_env_dict and "env_vars" in runtime_env_dict:
+ processed_env["env_vars"] = runtime_env_dict["env_vars"]
+ logger.info(
+ f"Added {len(runtime_env_dict['env_vars'])} environment variables to runtime_env"
+ )
+
+ # Handle pip dependencies
+ if runtime_env_dict and "pip" in runtime_env_dict:
+ pip_deps = process_pip_dependencies(job, runtime_env_dict["pip"])
+ if pip_deps:
+ processed_env["pip"] = pip_deps
+
+ # Handle working_dir
+ if runtime_env_dict and "working_dir" in runtime_env_dict:
+ working_dir = runtime_env_dict["working_dir"]
+ if os.path.isdir(working_dir):
+ # Local working directory - will be zipped and unzipped to UNZIP_PATH by submitter pod
+ processed_env["working_dir"] = UNZIP_PATH
+ logger.info(
+ f"Local working_dir will be zipped, mounted, and unzipped to: {UNZIP_PATH}"
+ )
+ else:
+ # Remote URI (e.g., GitHub, S3) - pass through as-is
+ processed_env["working_dir"] = working_dir
+ logger.info(f"Using remote working_dir: {working_dir}")
+
+ # If no working_dir specified but we have files (single file case)
+ elif not runtime_env_dict or "working_dir" not in runtime_env_dict:
+ if files and "working_dir.zip" not in files:
+ # Single file case - mount at MOUNT_PATH
+ processed_env["working_dir"] = MOUNT_PATH
+ logger.info(f"Single file will be mounted at: {MOUNT_PATH}")
+
+ # Convert to YAML string if we have any processed environment
+ if processed_env:
+ return yaml.dump(processed_env, default_flow_style=False)
+
+ return None
+
+
+def process_pip_dependencies(job: RayJob, pip_spec) -> Optional[List[str]]:
+ """
+ Process pip dependencies from runtime_env.
+
+ Args:
+ pip_spec: Can be a list of packages, a string path to requirements.txt, or dict
+
+ Returns:
+ List of pip dependencies
+ """
+ if isinstance(pip_spec, list):
+ # Already a list of dependencies
+ logger.info(f"Using provided pip dependencies: {len(pip_spec)} packages")
+ return pip_spec
+ elif isinstance(pip_spec, str):
+ # Assume it's a path to requirements.txt
+ return parse_requirements_file(pip_spec)
+ elif isinstance(pip_spec, dict):
+ # Handle dict format (e.g., {"packages": [...], "pip_check": False})
+ if "packages" in pip_spec:
+ logger.info(
+ f"Using pip dependencies from dict: {len(pip_spec['packages'])} packages"
+ )
+ return pip_spec["packages"]
+
+ logger.warning(f"Unsupported pip specification format: {type(pip_spec)}")
+ return None
+
+
+def parse_requirements_file(requirements_path: str) -> Optional[List[str]]:
+ """
+ Parse a requirements.txt file and return list of dependencies.
+
+ Args:
+ requirements_path: Path to requirements.txt file
+
+ Returns:
+ List of pip dependencies
+ """
+ if not os.path.isfile(requirements_path):
+ logger.warning(f"Requirements file not found: {requirements_path}")
+ return None
+
+ try:
+ with open(requirements_path, "r") as f:
+ lines = f.readlines()
+
+ # Parse requirements, filtering out comments and empty lines
+ requirements = []
+ for line in lines:
+ line = line.strip()
+ if line and not line.startswith("#"):
+ requirements.append(line)
+
+ logger.info(f"Parsed {len(requirements)} dependencies from {requirements_path}")
+ return requirements
+
+ except (IOError, OSError) as e:
+ logger.warning(f"Could not read requirements file {requirements_path}: {e}")
+ return None
+
+
+def create_secret_from_spec(
+ job: RayJob, secret_spec: Dict[str, Any], rayjob_result: Dict[str, Any] = None
+) -> str:
+ """
+ Create Secret from specification via Kubernetes API.
+
+ Args:
+ secret_spec: Secret specification dictionary
+ rayjob_result: The result from RayJob creation containing UID
+
+ Returns:
+ str: Name of the created Secret
+ """
+
+ secret_name = secret_spec["metadata"]["name"]
+
+ metadata = client.V1ObjectMeta(**secret_spec["metadata"])
+
+ # Add owner reference to ensure proper cleanup
+ # We can trust that rayjob_result contains UID since submit_job() only returns
+ # complete K8s resources or None, and we already validated result exists
+ logger.info(
+ f"Adding owner reference to Secret '{secret_name}' with RayJob UID: {rayjob_result['metadata']['uid']}"
+ )
+ metadata.owner_references = [
+ client.V1OwnerReference(
+ api_version="ray.io/v1",
+ kind="RayJob",
+ name=job.name,
+ uid=rayjob_result["metadata"]["uid"],
+ controller=True,
+ block_owner_deletion=True,
+ )
+ ]
+
+ # Convert dict spec to V1Secret
+ # Use stringData instead of data to avoid double base64 encoding
+ # Our zip files are already base64-encoded, so stringData will handle the final encoding
+ secret = client.V1Secret(
+ metadata=metadata,
+ type=secret_spec.get("type", "Opaque"),
+ string_data=secret_spec["data"],
+ )
+
+ # Create Secret via Kubernetes API
+ k8s_api = client.CoreV1Api(get_api_client())
+ try:
+ k8s_api.create_namespaced_secret(namespace=job.namespace, body=secret)
+ logger.info(
+ f"Created Secret '{secret_name}' with {len(secret_spec['data'])} files"
+ )
+ except client.ApiException as e:
+ if e.status == 409: # Already exists
+ logger.info(f"Secret '{secret_name}' already exists, updating...")
+ k8s_api.replace_namespaced_secret(
+ name=secret_name, namespace=job.namespace, body=secret
+ )
+ else:
+ raise RuntimeError(f"Failed to create Secret '{secret_name}': {e}")
+
+ return secret_name
+
+
+def create_file_secret(
+ job: RayJob, files: Dict[str, str], rayjob_result: Dict[str, Any]
+):
+ """
+ Create Secret with owner reference for local files.
+ """
+ # Use a basic config builder for Secret creation
+ config_builder = ManagedClusterConfig()
+
+ # Filter out metadata keys (like __entrypoint_path__) from Secret data
+ secret_files = {k: v for k, v in files.items() if not k.startswith("__")}
+
+ # Validate and build Secret spec
+ config_builder.validate_secret_size(secret_files)
+ secret_spec = config_builder.build_file_secret_spec(
+ job_name=job.name, namespace=job.namespace, files=secret_files
+ )
+
+ # Create Secret with owner reference
+ create_secret_from_spec(job, secret_spec, rayjob_result)
diff --git a/src/codeflare_sdk/ray/rayjobs/status.py b/src/codeflare_sdk/ray/rayjobs/status.py
new file mode 100644
index 00000000..027ed09c
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/status.py
@@ -0,0 +1,64 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+The status sub-module defines Enums containing information for Ray job
+deployment states and CodeFlare job states, as well as
+dataclasses to store information for Ray jobs.
+"""
+
+from dataclasses import dataclass
+from enum import Enum
+from typing import Optional
+
+
+class RayJobDeploymentStatus(Enum):
+ """
+ Defines the possible deployment states of a Ray job (from the KubeRay RayJob API).
+ """
+
+ COMPLETE = "Complete"
+ RUNNING = "Running"
+ FAILED = "Failed"
+ SUSPENDED = "Suspended"
+ UNKNOWN = "Unknown"
+
+
+class CodeflareRayJobStatus(Enum):
+ """
+ Defines the possible reportable states of a CodeFlare Ray job.
+ """
+
+ COMPLETE = 1
+ RUNNING = 2
+ FAILED = 3
+ SUSPENDED = 4
+ UNKNOWN = 5
+
+
+@dataclass
+class RayJobInfo:
+ """
+ For storing information about a Ray job.
+ """
+
+ name: str
+ job_id: str
+ status: RayJobDeploymentStatus
+ namespace: str
+ cluster_name: str
+ start_time: Optional[str] = None
+ end_time: Optional[str] = None
+ failed_attempts: int = 0
+ succeeded_attempts: int = 0
diff --git a/src/codeflare_sdk/ray/rayjobs/test/conftest.py b/src/codeflare_sdk/ray/rayjobs/test/conftest.py
new file mode 100644
index 00000000..bad195a7
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/test/conftest.py
@@ -0,0 +1,45 @@
+"""Shared pytest fixtures for rayjobs tests."""
+
+import pytest
+from unittest.mock import MagicMock
+
+
+# Global test setup that runs automatically for ALL tests
+@pytest.fixture(autouse=True)
+def auto_mock_setup(mocker):
+ """Automatically mock common dependencies for all tests."""
+ mocker.patch("kubernetes.config.load_kube_config")
+
+ # Always mock get_default_kueue_name to prevent K8s API calls
+ mocker.patch(
+ "codeflare_sdk.ray.rayjobs.rayjob.get_default_kueue_name",
+ return_value="default-queue",
+ )
+
+ mock_get_ns = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.rayjob.get_current_namespace",
+ return_value="test-namespace",
+ )
+
+ mock_rayjob_api = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mock_rayjob_instance = MagicMock()
+ mock_rayjob_api.return_value = mock_rayjob_instance
+
+ mock_cluster_api = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_cluster_instance = MagicMock()
+ mock_cluster_api.return_value = mock_cluster_instance
+
+ mock_k8s_api = mocker.patch("kubernetes.client.CoreV1Api")
+ mock_k8s_instance = MagicMock()
+ mock_k8s_api.return_value = mock_k8s_instance
+
+ # Mock get_api_client in runtime_env module where it's actually used
+ mocker.patch("codeflare_sdk.ray.rayjobs.runtime_env.get_api_client")
+
+ # Return the mocked instances so tests can configure them as needed
+ return {
+ "rayjob_api": mock_rayjob_instance,
+ "cluster_api": mock_cluster_instance,
+ "k8s_api": mock_k8s_instance,
+ "get_current_namespace": mock_get_ns,
+ }
diff --git a/src/codeflare_sdk/ray/rayjobs/test/test_config.py b/src/codeflare_sdk/ray/rayjobs/test/test_config.py
new file mode 100644
index 00000000..182ff90c
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/test/test_config.py
@@ -0,0 +1,346 @@
+"""
+Tests for the simplified ManagedClusterConfig accelerator_configs behavior.
+"""
+
+import pytest
+from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig, DEFAULT_ACCELERATORS
+from kubernetes.client import V1VolumeMount
+from kubernetes.client import V1Volume, V1SecretVolumeSource
+
+
+def test_accelerator_configs_defaults_to_default_accelerators():
+ """Test that accelerator_configs defaults to DEFAULT_ACCELERATORS.copy()"""
+ config = ManagedClusterConfig()
+
+ # Should have all the default accelerators
+ assert "nvidia.com/gpu" in config.accelerator_configs
+ assert "intel.com/gpu" in config.accelerator_configs
+ assert "google.com/tpu" in config.accelerator_configs
+
+ # Should be a copy, not the same object
+ assert config.accelerator_configs is not DEFAULT_ACCELERATORS
+ assert config.accelerator_configs == DEFAULT_ACCELERATORS
+
+
+def test_accelerator_configs_can_be_overridden():
+ """Test that users can override accelerator_configs with custom mappings"""
+ custom_configs = {
+ "nvidia.com/gpu": "GPU",
+ "custom.com/accelerator": "CUSTOM_ACCELERATOR",
+ }
+
+ config = ManagedClusterConfig(accelerator_configs=custom_configs)
+
+ # Should have custom configs
+ assert config.accelerator_configs == custom_configs
+ assert "custom.com/accelerator" in config.accelerator_configs
+ assert "nvidia.com/gpu" in config.accelerator_configs
+
+ # Should NOT have other defaults
+ assert "intel.com/gpu" not in config.accelerator_configs
+ assert "google.com/tpu" not in config.accelerator_configs
+
+
+def test_accelerator_configs_can_extend_defaults():
+ """Test that users can extend defaults by providing additional configs"""
+ extended_configs = {
+ **DEFAULT_ACCELERATORS,
+ "custom.com/accelerator": "CUSTOM_ACCEL",
+ }
+
+ config = ManagedClusterConfig(accelerator_configs=extended_configs)
+
+ # Should have all defaults plus custom
+ assert "nvidia.com/gpu" in config.accelerator_configs
+ assert "intel.com/gpu" in config.accelerator_configs
+ assert "custom.com/accelerator" in config.accelerator_configs
+ assert config.accelerator_configs["custom.com/accelerator"] == "CUSTOM_ACCEL"
+
+
+def test_gpu_validation_works_with_defaults():
+ """Test that GPU validation works with default accelerator configs"""
+ config = ManagedClusterConfig(head_accelerators={"nvidia.com/gpu": 1})
+
+ # Should not raise any errors
+ assert config.head_accelerators == {"nvidia.com/gpu": 1}
+
+
+def test_gpu_validation_works_with_custom_configs():
+ """Test that GPU validation works with custom accelerator configs"""
+ config = ManagedClusterConfig(
+ accelerator_configs={"custom.com/accelerator": "CUSTOM_ACCEL"},
+ head_accelerators={"custom.com/accelerator": 1},
+ )
+
+ # Should not raise any errors
+ assert config.head_accelerators == {"custom.com/accelerator": 1}
+
+
+def test_gpu_validation_fails_with_unsupported_accelerator():
+ """Test that GPU validation fails with unsupported accelerators"""
+ with pytest.raises(
+ ValueError, match="GPU configuration 'unsupported.com/accelerator' not found"
+ ):
+ ManagedClusterConfig(head_accelerators={"unsupported.com/accelerator": 1})
+
+
+def test_config_type_validation_errors(mocker):
+ """Test that type validation properly raises errors with incorrect types."""
+ # Mock the _is_type method to return False for type checking
+ mocker.patch.object(
+ ManagedClusterConfig,
+ "_is_type",
+ side_effect=lambda value, expected_type: False, # Always fail type check
+ )
+
+ # This should raise TypeError during initialization
+ with pytest.raises(TypeError, match="Type validation failed"):
+ ManagedClusterConfig()
+
+
+def test_config_is_type_method():
+ """Test the _is_type static method for type checking."""
+ # Test basic types
+ assert ManagedClusterConfig._is_type("test", str) is True
+ assert ManagedClusterConfig._is_type(123, int) is True
+ assert ManagedClusterConfig._is_type(123, str) is False
+
+ # Test optional types (Union with None)
+ from typing import Optional
+
+ assert ManagedClusterConfig._is_type(None, Optional[str]) is True
+ assert ManagedClusterConfig._is_type("test", Optional[str]) is True
+ assert ManagedClusterConfig._is_type(123, Optional[str]) is False
+
+ # Test dict types
+ assert ManagedClusterConfig._is_type({}, dict) is True
+ assert ManagedClusterConfig._is_type({"key": "value"}, dict) is True
+ assert ManagedClusterConfig._is_type([], dict) is False
+
+
+def test_ray_usage_stats_always_disabled_by_default():
+ """Test that RAY_USAGE_STATS_ENABLED is always set to '0' by default"""
+ config = ManagedClusterConfig()
+
+ # Should always have the environment variable set to "0"
+ assert "RAY_USAGE_STATS_ENABLED" in config.envs
+ assert config.envs["RAY_USAGE_STATS_ENABLED"] == "0"
+
+
+def test_ray_usage_stats_overwrites_user_env():
+ """Test that RAY_USAGE_STATS_ENABLED is always set to '0' even if user specifies it"""
+ # User tries to enable usage stats
+ config = ManagedClusterConfig(envs={"RAY_USAGE_STATS_ENABLED": "1"})
+
+ # Should still be disabled (our setting takes precedence)
+ assert "RAY_USAGE_STATS_ENABLED" in config.envs
+ assert config.envs["RAY_USAGE_STATS_ENABLED"] == "0"
+
+
+def test_ray_usage_stats_overwrites_user_env_string():
+ """Test that RAY_USAGE_STATS_ENABLED is always set to '0' even if user specifies it as string"""
+ # User tries to enable usage stats with string
+ config = ManagedClusterConfig(envs={"RAY_USAGE_STATS_ENABLED": "true"})
+
+ # Should still be disabled (our setting takes precedence)
+ assert "RAY_USAGE_STATS_ENABLED" in config.envs
+ assert config.envs["RAY_USAGE_STATS_ENABLED"] == "0"
+
+
+def test_ray_usage_stats_with_other_user_envs():
+ """Test that RAY_USAGE_STATS_ENABLED is set correctly while preserving other user envs"""
+ # User sets other environment variables
+ user_envs = {
+ "CUSTOM_VAR": "custom_value",
+ "ANOTHER_VAR": "another_value",
+ "RAY_USAGE_STATS_ENABLED": "1", # This should be overwritten
+ }
+
+ config = ManagedClusterConfig(envs=user_envs)
+
+ # Our setting should take precedence
+ assert config.envs["RAY_USAGE_STATS_ENABLED"] == "0"
+
+ # Other user envs should be preserved
+ assert config.envs["CUSTOM_VAR"] == "custom_value"
+ assert config.envs["ANOTHER_VAR"] == "another_value"
+
+ # Total count should be correct (3 user envs)
+ assert len(config.envs) == 3
+
+
+def test_add_file_volumes_existing_volume_early_return():
+ """Test add_file_volumes early return when volume already exists."""
+
+ config = ManagedClusterConfig()
+
+ # Pre-add a volume with same name
+ existing_volume = V1Volume(
+ name="ray-job-files",
+ secret=V1SecretVolumeSource(secret_name="existing-files"),
+ )
+ config.volumes.append(existing_volume)
+
+ # Should return early and not add duplicate
+ config.add_file_volumes(secret_name="new-files")
+
+ # Should still have only one volume, no mount added
+ assert len(config.volumes) == 1
+ assert len(config.volume_mounts) == 0
+
+
+def test_add_file_volumes_existing_mount_early_return():
+ """Test add_file_volumes early return when mount already exists."""
+
+ config = ManagedClusterConfig()
+
+ # Pre-add a mount with same name
+ existing_mount = V1VolumeMount(name="ray-job-files", mount_path="/existing/path")
+ config.volume_mounts.append(existing_mount)
+
+ # Should return early and not add duplicate
+ config.add_file_volumes(secret_name="new-files")
+
+ # Should still have only one mount, no volume added
+ assert len(config.volumes) == 0
+ assert len(config.volume_mounts) == 1
+
+
+def test_build_file_secret_spec_labels():
+ """Test that build_file_secret_spec creates Secret with correct labels."""
+ config = ManagedClusterConfig()
+
+ job_name = "test-job"
+ namespace = "test-namespace"
+ files = {"test.py": "print('hello')", "helper.py": "# helper code"}
+
+ secret_spec = config.build_file_secret_spec(job_name, namespace, files)
+
+ assert secret_spec["apiVersion"] == "v1"
+ assert secret_spec["kind"] == "Secret"
+ assert secret_spec["type"] == "Opaque"
+ assert secret_spec["metadata"]["name"] == f"{job_name}-files"
+ assert secret_spec["metadata"]["namespace"] == namespace
+
+ labels = secret_spec["metadata"]["labels"]
+ assert labels["ray.io/job-name"] == job_name
+ assert labels["app.kubernetes.io/managed-by"] == "codeflare-sdk"
+ assert labels["app.kubernetes.io/component"] == "rayjob-files"
+
+ assert secret_spec["data"] == files
+
+
+def test_managed_cluster_config_uses_update_image_for_head(mocker):
+ """Test that ManagedClusterConfig calls update_image() for head container."""
+ # Mock update_image where it's used (in config module), not where it's defined
+ mock_update_image = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.config.update_image",
+ return_value="mocked-image:latest",
+ )
+
+ config = ManagedClusterConfig(image="custom-image:v1")
+
+ # Build cluster spec (which should call update_image)
+ spec = config.build_ray_cluster_spec("test-cluster")
+
+ # Verify update_image was called for head container
+ assert mock_update_image.called
+ # Verify head container has the mocked image
+ head_container = spec["headGroupSpec"]["template"].spec.containers[0]
+ assert head_container.image == "mocked-image:latest"
+
+
+def test_managed_cluster_config_uses_update_image_for_worker(mocker):
+ """Test that ManagedClusterConfig calls update_image() for worker container."""
+ # Mock update_image where it's used (in config module), not where it's defined
+ mock_update_image = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.config.update_image",
+ return_value="mocked-image:latest",
+ )
+
+ config = ManagedClusterConfig(image="custom-image:v1")
+
+ # Build cluster spec (which should call update_image)
+ spec = config.build_ray_cluster_spec("test-cluster")
+
+ # Verify update_image was called for worker container
+ assert mock_update_image.called
+ # Verify worker container has the mocked image
+ worker_container = spec["workerGroupSpecs"][0]["template"].spec.containers[0]
+ assert worker_container.image == "mocked-image:latest"
+
+
+def test_managed_cluster_config_with_empty_image_uses_update_image(mocker):
+ """Test that empty image triggers update_image() to auto-detect."""
+ # Mock update_image where it's used (in config module), not where it's defined
+ mock_update_image = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.config.update_image",
+ return_value="auto-detected-image:py3.12",
+ )
+
+ config = ManagedClusterConfig(image="")
+
+ # Build cluster spec
+ spec = config.build_ray_cluster_spec("test-cluster")
+
+ # Verify update_image was called with empty string
+ mock_update_image.assert_called_with("")
+
+ # Verify containers have the auto-detected image
+ head_container = spec["headGroupSpec"]["template"].spec.containers[0]
+ assert head_container.image == "auto-detected-image:py3.12"
+
+ worker_container = spec["workerGroupSpecs"][0]["template"].spec.containers[0]
+ assert worker_container.image == "auto-detected-image:py3.12"
+
+
+def test_build_ray_cluster_spec_has_enable_in_tree_autoscaling_false():
+ """Test that build_ray_cluster_spec sets enableInTreeAutoscaling to False."""
+ config = ManagedClusterConfig()
+
+ spec = config.build_ray_cluster_spec("test-cluster")
+
+ # Verify enableInTreeAutoscaling is set to False (required for Kueue)
+ assert "enableInTreeAutoscaling" in spec
+ assert spec["enableInTreeAutoscaling"] is False
+
+
+def test_build_ray_cluster_spec_autoscaling_disabled_for_kueue():
+ """Test that autoscaling is explicitly disabled for Kueue-managed jobs."""
+ config = ManagedClusterConfig(num_workers=3)
+
+ spec = config.build_ray_cluster_spec("kueue-cluster")
+
+ # Verify enableInTreeAutoscaling is False
+ assert spec["enableInTreeAutoscaling"] is False
+
+ # Verify worker replicas are fixed (min == max == replicas)
+ worker_spec = spec["workerGroupSpecs"][0]
+ assert worker_spec["replicas"] == 3
+ assert worker_spec["minReplicas"] == 3
+ assert worker_spec["maxReplicas"] == 3
+
+
+def test_managed_cluster_config_default_image_integration():
+ """Test that ManagedClusterConfig works with default images (integration test)."""
+ # Create config without specifying an image (should auto-detect based on Python version)
+ config = ManagedClusterConfig()
+
+ # Build cluster spec
+ spec = config.build_ray_cluster_spec("test-cluster")
+
+ # Verify head container has an image (should be auto-detected)
+ head_container = spec["headGroupSpec"]["template"].spec.containers[0]
+ assert head_container.image is not None
+ assert len(head_container.image) > 0
+ # Should be one of the supported images
+ from codeflare_sdk.common.utils.constants import (
+ CUDA_PY311_RUNTIME_IMAGE,
+ CUDA_PY312_RUNTIME_IMAGE,
+ )
+
+ assert head_container.image in [CUDA_PY311_RUNTIME_IMAGE, CUDA_PY312_RUNTIME_IMAGE]
+
+ # Verify worker container has the same image
+ worker_container = spec["workerGroupSpecs"][0]["template"].spec.containers[0]
+ assert worker_container.image == head_container.image
diff --git a/src/codeflare_sdk/ray/rayjobs/test/test_pretty_print.py b/src/codeflare_sdk/ray/rayjobs/test/test_pretty_print.py
new file mode 100644
index 00000000..3bbe8bee
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/test/test_pretty_print.py
@@ -0,0 +1,265 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from codeflare_sdk.ray.rayjobs.pretty_print import (
+ _get_status_display,
+ print_job_status,
+ print_no_job_found,
+)
+from codeflare_sdk.ray.rayjobs.status import RayJobDeploymentStatus, RayJobInfo
+from unittest.mock import MagicMock, call
+
+
+def test_get_status_display():
+ """
+ Test the _get_status_display function.
+ """
+ # Test Complete status
+ display, color = _get_status_display(RayJobDeploymentStatus.COMPLETE)
+ assert display == "Complete :white_heavy_check_mark:"
+ assert color == "[white on green][bold]Name"
+
+ # Test Running status
+ display, color = _get_status_display(RayJobDeploymentStatus.RUNNING)
+ assert display == "Running :gear:"
+ assert color == "[white on blue][bold]Name"
+
+ # Test Failed status
+ display, color = _get_status_display(RayJobDeploymentStatus.FAILED)
+ assert display == "Failed :x:"
+ assert color == "[white on red][bold]Name"
+
+ # Test Suspended status
+ display, color = _get_status_display(RayJobDeploymentStatus.SUSPENDED)
+ assert display == "Suspended :pause_button:"
+ assert color == "[white on yellow][bold]Name"
+
+ # Test Unknown status
+ display, color = _get_status_display(RayJobDeploymentStatus.UNKNOWN)
+ assert display == "Unknown :question:"
+ assert color == "[white on red][bold]Name"
+
+
+def test_print_job_status_running_format(mocker):
+ """
+ Test the print_job_status function format for a running job.
+ """
+ # Mock Rich components to verify format
+ mock_console = MagicMock()
+ mock_inner_table = MagicMock()
+ mock_main_table = MagicMock()
+ mock_panel = MagicMock()
+
+ # Mock Table to return different instances for inner and main tables
+ table_instances = [mock_inner_table, mock_main_table]
+ mock_table_class = MagicMock(side_effect=table_instances)
+
+ mocker.patch(
+ "codeflare_sdk.ray.rayjobs.pretty_print.Console", return_value=mock_console
+ )
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Table", mock_table_class)
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Panel", mock_panel)
+
+ # Create test job info for running job
+ job_info = RayJobInfo(
+ name="test-job",
+ job_id="test-job-abc123",
+ status=RayJobDeploymentStatus.RUNNING,
+ namespace="test-ns",
+ cluster_name="test-cluster",
+ start_time="2025-07-28T11:37:07Z",
+ failed_attempts=0,
+ succeeded_attempts=0,
+ )
+
+ # Call the function
+ print_job_status(job_info)
+
+ # Verify both Table calls
+ expected_table_calls = [
+ call(box=None, show_header=False), # Inner content table
+ call(
+ box=None, title="[bold] :package: CodeFlare RayJob Status :package:"
+ ), # Main wrapper table
+ ]
+ mock_table_class.assert_has_calls(expected_table_calls)
+
+ # Verify inner table rows are added in correct order and format (versus our hard-coded version of this for cluster)
+ expected_calls = [
+ call("[white on blue][bold]Name"), # Header with blue color for running
+ call(
+ "[bold underline]test-job", "Running :gear:"
+ ), # Name and status with gear emoji
+ call(), # Empty separator row
+ call("[bold]Job ID:[/bold] test-job-abc123"),
+ call("[bold]Status:[/bold] Running"),
+ call("[bold]RayCluster:[/bold] test-cluster"),
+ call("[bold]Namespace:[/bold] test-ns"),
+ call(), # Empty row before timing info
+ call("[bold]Started:[/bold] 2025-07-28T11:37:07Z"),
+ ]
+ mock_inner_table.add_row.assert_has_calls(expected_calls)
+
+ # Verify Panel is created with inner table
+ mock_panel.fit.assert_called_once_with(mock_inner_table)
+
+ # Verify main table gets the panel
+ mock_main_table.add_row.assert_called_once_with(mock_panel.fit.return_value)
+
+ # Verify console prints the main table
+ mock_console.print.assert_called_once_with(mock_main_table)
+
+
+def test_print_job_status_complete_format(mocker):
+ """
+ Test the print_job_status function format for a completed job.
+ """
+ # Mock Rich components
+ mock_console = MagicMock()
+ mock_inner_table = MagicMock()
+ mock_main_table = MagicMock()
+ mock_panel = MagicMock()
+
+ # Mock Table to return different instances
+ table_instances = [mock_inner_table, mock_main_table]
+ mock_table_class = MagicMock(side_effect=table_instances)
+
+ mocker.patch(
+ "codeflare_sdk.ray.rayjobs.pretty_print.Console", return_value=mock_console
+ )
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Table", mock_table_class)
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Panel", mock_panel)
+
+ # Create test job info for completed job
+ job_info = RayJobInfo(
+ name="completed-job",
+ job_id="completed-job-xyz789",
+ status=RayJobDeploymentStatus.COMPLETE,
+ namespace="prod-ns",
+ cluster_name="prod-cluster",
+ start_time="2025-07-28T11:37:07Z",
+ failed_attempts=0,
+ succeeded_attempts=1,
+ )
+
+ # Call the function
+ print_job_status(job_info)
+
+ # Verify correct header color for completed job (green) (versus our hard-coded version of this for cluster)
+ expected_calls = [
+ call("[white on green][bold]Name"), # Green header for complete
+ call(
+ "[bold underline]completed-job", "Complete :white_heavy_check_mark:"
+ ), # Checkmark emoji
+ call(), # Empty separator
+ call("[bold]Job ID:[/bold] completed-job-xyz789"),
+ call("[bold]Status:[/bold] Complete"),
+ call("[bold]RayCluster:[/bold] prod-cluster"),
+ call("[bold]Namespace:[/bold] prod-ns"),
+ call(), # Empty row before timing info
+ call("[bold]Started:[/bold] 2025-07-28T11:37:07Z"),
+ ]
+ mock_inner_table.add_row.assert_has_calls(expected_calls)
+
+
+def test_print_job_status_failed_with_attempts_format(mocker):
+ """
+ Test the print_job_status function format for a failed job with attempts.
+ """
+ # Mock Rich components
+ mock_console = MagicMock()
+ mock_inner_table = MagicMock()
+ mock_main_table = MagicMock()
+ mock_panel = MagicMock()
+
+ # Mock Table to return different instances
+ table_instances = [mock_inner_table, mock_main_table]
+ mock_table_class = MagicMock(side_effect=table_instances)
+
+ mocker.patch(
+ "codeflare_sdk.ray.rayjobs.pretty_print.Console", return_value=mock_console
+ )
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Table", mock_table_class)
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Panel", mock_panel)
+
+ # Create test job info with failures
+ job_info = RayJobInfo(
+ name="failing-job",
+ job_id="failing-job-fail123",
+ status=RayJobDeploymentStatus.FAILED,
+ namespace="test-ns",
+ cluster_name="test-cluster",
+ start_time="2025-07-28T11:37:07Z",
+ failed_attempts=3, # Has failures
+ succeeded_attempts=0,
+ )
+
+ # Call the function
+ print_job_status(job_info)
+
+ # Verify correct formatting including failure attempts (versus our hard-coded version of this for cluster)
+ expected_calls = [
+ call("[white on red][bold]Name"), # Red header for failed
+ call("[bold underline]failing-job", "Failed :x:"), # X emoji for failed
+ call(), # Empty separator
+ call("[bold]Job ID:[/bold] failing-job-fail123"),
+ call("[bold]Status:[/bold] Failed"),
+ call("[bold]RayCluster:[/bold] test-cluster"),
+ call("[bold]Namespace:[/bold] test-ns"),
+ call(), # Empty row before timing info
+ call("[bold]Started:[/bold] 2025-07-28T11:37:07Z"),
+ call("[bold]Failed Attempts:[/bold] 3"), # Failed attempts should be shown
+ ]
+ mock_inner_table.add_row.assert_has_calls(expected_calls)
+
+
+def test_print_no_job_found_format(mocker):
+ """
+ Test the print_no_job_found function format.
+ """
+ # Mock Rich components
+ mock_console = MagicMock()
+ mock_inner_table = MagicMock()
+ mock_main_table = MagicMock()
+ mock_panel = MagicMock()
+
+ # Mock Table to return different instances
+ table_instances = [mock_inner_table, mock_main_table]
+ mock_table_class = MagicMock(side_effect=table_instances)
+
+ mocker.patch(
+ "codeflare_sdk.ray.rayjobs.pretty_print.Console", return_value=mock_console
+ )
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Table", mock_table_class)
+ mocker.patch("codeflare_sdk.ray.rayjobs.pretty_print.Panel", mock_panel)
+
+ # Call the function
+ print_no_job_found("missing-job", "test-namespace")
+
+ # Verify error message format (versus our hard-coded version of this for cluster)
+ expected_calls = [
+ call("[white on red][bold]Name"), # Red header for error
+ call(
+ "[bold underline]missing-job", "[bold red]No RayJob found"
+ ), # Error message in red
+ call(), # Empty separator
+ call(), # Another empty row
+ call("Please run rayjob.submit() to submit a job."), # Helpful hint
+ call(), # Empty separator
+ call("[bold]Namespace:[/bold] test-namespace"),
+ ]
+ mock_inner_table.add_row.assert_has_calls(expected_calls)
+
+ # Verify Panel is used
+ mock_panel.fit.assert_called_once_with(mock_inner_table)
diff --git a/src/codeflare_sdk/ray/rayjobs/test/test_rayjob.py b/src/codeflare_sdk/ray/rayjobs/test/test_rayjob.py
new file mode 100644
index 00000000..928cc1f8
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/test/test_rayjob.py
@@ -0,0 +1,1783 @@
+# Copyright 2022-2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import pytest
+from unittest.mock import MagicMock
+from codeflare_sdk.common.utils.constants import RAY_VERSION
+from ray.runtime_env import RuntimeEnv
+
+from codeflare_sdk.ray.rayjobs.rayjob import RayJob
+from codeflare_sdk.ray.cluster.config import ClusterConfiguration
+from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig
+from kubernetes.client import V1Volume, V1VolumeMount, V1Toleration
+
+
+def test_rayjob_submit_success(auto_mock_setup):
+ """
+ Test successful RayJob submission.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ mock_api_instance.submit.return_value = {"metadata": {"name": "test-rayjob"}}
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ cluster_name="test-ray-cluster",
+ namespace="test-namespace",
+ entrypoint="python -c 'print(\"hello world\")'",
+ runtime_env=RuntimeEnv(pip=["requests"]),
+ )
+
+ job_id = rayjob.submit()
+
+ assert job_id == "test-rayjob"
+
+ mock_api_instance.submit_job.assert_called_once()
+ call_args = mock_api_instance.submit_job.call_args
+
+ assert call_args.kwargs["k8s_namespace"] == "test-namespace"
+
+ job_cr = call_args.kwargs["job"]
+ assert job_cr["metadata"]["name"] == "test-rayjob"
+ assert job_cr["metadata"]["namespace"] == "test-namespace"
+ assert job_cr["spec"]["entrypoint"] == "python -c 'print(\"hello world\")'"
+ assert job_cr["spec"]["clusterSelector"]["ray.io/cluster"] == "test-ray-cluster"
+ assert job_cr["spec"]["runtimeEnvYAML"] == "pip:\n- requests\n"
+
+
+def test_rayjob_submit_failure(auto_mock_setup):
+ """
+ Test RayJob submission failure.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ mock_api_instance.submit_job.return_value = None
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ cluster_name="test-ray-cluster",
+ namespace="default",
+ entrypoint="python -c 'print()'",
+ runtime_env=RuntimeEnv(pip=["numpy"]),
+ )
+
+ with pytest.raises(RuntimeError, match="Failed to submit RayJob test-rayjob"):
+ rayjob.submit()
+
+
+def test_rayjob_init_validation_both_provided(auto_mock_setup):
+ """
+ Test that providing both cluster_name and cluster_config raises error.
+ """
+ cluster_config = ClusterConfiguration(name="test-cluster", namespace="test")
+
+ with pytest.raises(
+ ValueError,
+ match="❌ Configuration Error: You cannot specify both 'cluster_name' and 'cluster_config'",
+ ):
+ RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ )
+
+
+def test_rayjob_init_validation_neither_provided(auto_mock_setup):
+ """
+ Test that providing neither cluster_name nor cluster_config raises error.
+ """
+ with pytest.raises(
+ ValueError,
+ match="❌ Configuration Error: You must provide either 'cluster_name'",
+ ):
+ RayJob(job_name="test-job", entrypoint="python test.py")
+
+
+def test_rayjob_init_with_cluster_config(auto_mock_setup):
+ """
+ Test RayJob initialization with cluster configuration for auto-creation.
+ """
+ cluster_config = ClusterConfiguration(
+ name="auto-cluster", namespace="test-namespace", num_workers=2
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ assert rayjob.name == "test-job"
+ assert rayjob.cluster_name == "test-job-cluster" # Generated from job name
+ assert rayjob._cluster_config == cluster_config
+ assert rayjob._cluster_name is None
+
+
+def test_rayjob_cluster_name_generation(auto_mock_setup):
+ """
+ Test that cluster names are generated when config has empty name.
+ """
+ cluster_config = ClusterConfiguration(
+ name="", # Empty name should trigger generation
+ namespace="test-namespace",
+ num_workers=1,
+ )
+
+ rayjob = RayJob(
+ job_name="my-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ assert rayjob.cluster_name == "my-job-cluster"
+
+
+def test_rayjob_cluster_config_namespace_none(auto_mock_setup):
+ """
+ Test that cluster config namespace is set when None.
+ """
+ cluster_config = ClusterConfiguration(
+ name="test-cluster",
+ namespace=None, # This should be set to job namespace
+ num_workers=1,
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ namespace="job-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ assert rayjob.namespace == "job-namespace"
+
+
+def test_rayjob_with_active_deadline_seconds(auto_mock_setup):
+ """
+ Test RayJob CR generation with active deadline seconds.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-namespace",
+ entrypoint="python main.py",
+ active_deadline_seconds=30,
+ )
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+
+ assert rayjob_cr["spec"]["activeDeadlineSeconds"] == 30
+
+
+def test_build_ray_cluster_spec_no_config_error(auto_mock_setup):
+ """
+ Test _build_ray_cluster_spec raises error when no cluster config.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+
+ assert rayjob_cr["spec"]["clusterSelector"]["ray.io/cluster"] == "existing-cluster"
+ assert "rayClusterSpec" not in rayjob_cr["spec"]
+
+
+def test_build_ray_cluster_spec(mocker, auto_mock_setup):
+ """
+ Test _build_ray_cluster_spec method.
+ """
+
+ mock_ray_cluster = {
+ "apiVersion": "ray.io/v1",
+ "kind": "RayCluster",
+ "metadata": {"name": "test-cluster", "namespace": "test"},
+ "spec": {
+ "rayVersion": RAY_VERSION,
+ "headGroupSpec": {"replicas": 1},
+ "workerGroupSpecs": [{"replicas": 2}],
+ },
+ }
+ cluster_config = ManagedClusterConfig(num_workers=2)
+ mocker.patch.object(
+ cluster_config, "build_ray_cluster_spec", return_value=mock_ray_cluster["spec"]
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+
+ assert "rayClusterSpec" in rayjob_cr["spec"]
+ cluster_config.build_ray_cluster_spec.assert_called_once_with(
+ cluster_name="test-job-cluster"
+ )
+
+
+def test_build_rayjob_cr_with_existing_cluster(auto_mock_setup):
+ """
+ Test _build_rayjob_cr method with existing cluster.
+ """
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ namespace="test-namespace",
+ entrypoint="python main.py",
+ ttl_seconds_after_finished=300,
+ )
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+
+ assert rayjob_cr["apiVersion"] == "ray.io/v1"
+ assert rayjob_cr["kind"] == "RayJob"
+ assert rayjob_cr["metadata"]["name"] == "test-job"
+ spec = rayjob_cr["spec"]
+ assert spec["entrypoint"] == "python main.py"
+ assert spec["shutdownAfterJobFinishes"] is False
+ assert spec["ttlSecondsAfterFinished"] == 300
+
+ assert spec["clusterSelector"]["ray.io/cluster"] == "existing-cluster"
+ assert "rayClusterSpec" not in spec
+
+
+def test_build_rayjob_cr_with_auto_cluster(mocker, auto_mock_setup):
+ """
+ Test _build_rayjob_cr method with auto-created cluster.
+ """
+ mock_ray_cluster = {
+ "apiVersion": "ray.io/v1",
+ "kind": "RayCluster",
+ "metadata": {"name": "auto-cluster", "namespace": "test"},
+ "spec": {
+ "rayVersion": RAY_VERSION,
+ "headGroupSpec": {"replicas": 1},
+ "workerGroupSpecs": [{"replicas": 2}],
+ },
+ }
+ cluster_config = ManagedClusterConfig(num_workers=2)
+
+ mocker.patch.object(
+ cluster_config, "build_ray_cluster_spec", return_value=mock_ray_cluster["spec"]
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python main.py",
+ namespace="test-namespace",
+ )
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+ assert rayjob_cr["spec"]["rayClusterSpec"] == mock_ray_cluster["spec"]
+ assert "clusterSelector" not in rayjob_cr["spec"]
+
+
+def test_submit_validation_no_entrypoint(auto_mock_setup):
+ """
+ Test that submit() raises error when entrypoint is None.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=None, # No entrypoint provided
+ namespace="test-namespace",
+ )
+
+ with pytest.raises(
+ ValueError, match="Entrypoint must be provided to submit a RayJob"
+ ):
+ rayjob.submit()
+
+
+def test_submit_with_auto_cluster(mocker, auto_mock_setup):
+ """
+ Test successful submission with auto-created cluster.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ mock_ray_cluster = {
+ "apiVersion": "ray.io/v1",
+ "kind": "RayCluster",
+ "spec": {
+ "rayVersion": RAY_VERSION,
+ "headGroupSpec": {"replicas": 1},
+ "workerGroupSpecs": [{"replicas": 1}],
+ },
+ }
+ mock_api_instance.submit_job.return_value = True
+
+ cluster_config = ManagedClusterConfig(num_workers=1)
+ mocker.patch.object(
+ cluster_config, "build_ray_cluster_spec", return_value=mock_ray_cluster["spec"]
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ result = rayjob.submit()
+
+ assert result == "test-job"
+
+ mock_api_instance.submit_job.assert_called_once()
+ call_args = mock_api_instance.submit_job.call_args
+
+ job_cr = call_args.kwargs["job"]
+ assert "rayClusterSpec" in job_cr["spec"]
+ assert job_cr["spec"]["rayClusterSpec"] == mock_ray_cluster["spec"]
+
+
+def test_namespace_auto_detection_success(auto_mock_setup):
+ """
+ Test successful namespace auto-detection.
+ """
+ auto_mock_setup["get_current_namespace"].return_value = "detected-ns"
+
+ rayjob = RayJob(
+ job_name="test-job", entrypoint="python test.py", cluster_name="test-cluster"
+ )
+
+ assert rayjob.namespace == "detected-ns"
+
+
+def test_namespace_auto_detection_fallback(auto_mock_setup):
+ """
+ Test that namespace auto-detection failure raises an error.
+ """
+ auto_mock_setup["get_current_namespace"].return_value = None
+
+ with pytest.raises(ValueError, match="Could not auto-detect Kubernetes namespace"):
+ RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ )
+
+
+def test_namespace_explicit_override(auto_mock_setup):
+ """
+ Test that explicit namespace overrides auto-detection.
+ """
+ auto_mock_setup["get_current_namespace"].return_value = "detected-ns"
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ namespace="explicit-ns",
+ )
+
+ assert rayjob.namespace == "explicit-ns"
+
+
+def test_rayjob_with_rayjob_cluster_config(auto_mock_setup):
+ """
+ Test RayJob with the new ManagedClusterConfig.
+ """
+ cluster_config = ManagedClusterConfig(
+ num_workers=2,
+ head_cpu_requests="500m",
+ head_memory_requests="512Mi",
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_config=cluster_config,
+ namespace="test-namespace",
+ )
+
+ assert rayjob._cluster_config == cluster_config
+ assert rayjob.cluster_name == "test-job-cluster" # Generated from job name
+
+
+def test_rayjob_cluster_config_validation(auto_mock_setup):
+ """
+ Test validation of ManagedClusterConfig parameters.
+ """
+ cluster_config = ManagedClusterConfig()
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_config=cluster_config,
+ namespace="test-namespace",
+ )
+
+ assert rayjob._cluster_config is not None
+
+
+def test_rayjob_missing_entrypoint_validation(auto_mock_setup):
+ """
+ Test that RayJob requires entrypoint for submission.
+ """
+ with pytest.raises(
+ TypeError, match="missing 1 required positional argument: 'entrypoint'"
+ ):
+ RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ )
+
+
+def test_build_ray_cluster_spec_integration(mocker, auto_mock_setup):
+ """
+ Test integration with the new build_ray_cluster_spec method.
+ """
+ cluster_config = ManagedClusterConfig()
+ mock_spec = {"spec": "test-spec"}
+ mocker.patch.object(
+ cluster_config, "build_ray_cluster_spec", return_value=mock_spec
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_config=cluster_config,
+ namespace="test-namespace",
+ )
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+
+ cluster_config.build_ray_cluster_spec.assert_called_once_with(
+ cluster_name="test-job-cluster"
+ )
+ assert "rayClusterSpec" in rayjob_cr["spec"]
+ assert rayjob_cr["spec"]["rayClusterSpec"] == mock_spec
+
+
+def test_rayjob_with_runtime_env(auto_mock_setup):
+ """
+ Test RayJob with runtime environment configuration.
+ """
+ runtime_env = RuntimeEnv(pip=["numpy", "pandas"])
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ runtime_env=runtime_env,
+ namespace="test-namespace",
+ )
+
+ assert rayjob.runtime_env == runtime_env
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+ assert rayjob_cr["spec"]["runtimeEnvYAML"] == "pip:\n- numpy\n- pandas\n"
+
+
+def test_rayjob_with_runtime_env_dict(auto_mock_setup):
+ """
+ Test RayJob with runtime environment as dict (user convenience).
+ Users can pass a dict instead of having to import RuntimeEnv.
+ """
+ # User can pass dict instead of RuntimeEnv object
+ runtime_env_dict = {
+ "pip": ["numpy", "pandas"],
+ "env_vars": {"TEST_VAR": "test_value"},
+ }
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ runtime_env=runtime_env_dict,
+ namespace="test-namespace",
+ )
+
+ # Should be converted to RuntimeEnv internally
+ assert isinstance(rayjob.runtime_env, RuntimeEnv)
+ assert rayjob.runtime_env["env_vars"] == {"TEST_VAR": "test_value"}
+
+ # Verify it generates proper YAML output
+ rayjob_cr = rayjob._build_rayjob_cr()
+ assert "runtimeEnvYAML" in rayjob_cr["spec"]
+ runtime_yaml = rayjob_cr["spec"]["runtimeEnvYAML"]
+ assert "pip:" in runtime_yaml or "pip_packages:" in runtime_yaml
+ assert "env_vars:" in runtime_yaml
+ assert "TEST_VAR" in runtime_yaml
+
+
+def test_rayjob_with_active_deadline_and_ttl(auto_mock_setup):
+ """
+ Test RayJob with both active deadline and TTL settings.
+ """
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ active_deadline_seconds=300,
+ ttl_seconds_after_finished=600,
+ namespace="test-namespace",
+ )
+
+ assert rayjob.active_deadline_seconds == 300
+ assert rayjob.ttl_seconds_after_finished == 600
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+ assert rayjob_cr["spec"]["activeDeadlineSeconds"] == 300
+ assert rayjob_cr["spec"]["ttlSecondsAfterFinished"] == 600
+
+
+def test_rayjob_cluster_name_generation_with_config(auto_mock_setup):
+ """
+ Test cluster name generation when using cluster_config.
+ """
+
+ cluster_config = ManagedClusterConfig()
+
+ rayjob = RayJob(
+ job_name="my-job",
+ entrypoint="python -c 'print()'",
+ cluster_config=cluster_config,
+ namespace="test-namespace", # Explicitly specify namespace
+ )
+
+ assert rayjob.cluster_name == "my-job-cluster"
+
+
+def test_rayjob_namespace_propagation_to_cluster_config(auto_mock_setup):
+ """
+ Test that job namespace is propagated to cluster config when None.
+ """
+ auto_mock_setup["get_current_namespace"].return_value = "detected-ns"
+
+ cluster_config = ManagedClusterConfig()
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_config=cluster_config,
+ )
+
+ assert rayjob.namespace == "detected-ns"
+
+
+def test_rayjob_error_handling_invalid_cluster_config(auto_mock_setup):
+ """
+ Test error handling with invalid cluster configuration.
+ """
+
+ with pytest.raises(ValueError):
+ RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ )
+
+
+def test_rayjob_constructor_parameter_validation(auto_mock_setup):
+ """
+ Test constructor parameter validation.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ runtime_env=RuntimeEnv(pip=["numpy"]),
+ ttl_seconds_after_finished=300,
+ active_deadline_seconds=600,
+ )
+
+ assert rayjob.name == "test-job"
+ assert rayjob.entrypoint == "python -c 'print()'"
+ assert rayjob.cluster_name == "test-cluster"
+ assert rayjob.namespace == "test-ns"
+ # Check that runtime_env is a RuntimeEnv object and contains pip dependencies
+ assert isinstance(rayjob.runtime_env, RuntimeEnv)
+ runtime_env_dict = rayjob.runtime_env.to_dict()
+ assert "pip" in runtime_env_dict
+ # Ray transforms pip to dict format with 'packages' key
+ assert runtime_env_dict["pip"]["packages"] == ["numpy"]
+ assert rayjob.ttl_seconds_after_finished == 300
+ assert rayjob.active_deadline_seconds == 600
+
+
+def test_build_ray_cluster_spec_function():
+ """
+ Test the build_ray_cluster_spec method directly.
+ """
+ cluster_config = ManagedClusterConfig(
+ num_workers=2,
+ head_cpu_requests="500m",
+ head_memory_requests="512Mi",
+ worker_cpu_requests="250m",
+ worker_memory_requests="256Mi",
+ )
+
+ spec = cluster_config.build_ray_cluster_spec("test-cluster")
+ assert "rayVersion" in spec
+ assert "enableInTreeAutoscaling" in spec
+ assert spec["enableInTreeAutoscaling"] is False # Required for Kueue
+ assert "headGroupSpec" in spec
+ assert "workerGroupSpecs" in spec
+
+ head_spec = spec["headGroupSpec"]
+ assert head_spec["serviceType"] == "ClusterIP"
+ assert head_spec["enableIngress"] is False
+ assert "rayStartParams" in head_spec
+ assert "template" in head_spec
+ worker_specs = spec["workerGroupSpecs"]
+ assert len(worker_specs) == 1
+ worker_spec = worker_specs[0]
+ assert worker_spec["replicas"] == 2
+ assert worker_spec["minReplicas"] == 2
+ assert worker_spec["maxReplicas"] == 2
+ assert worker_spec["groupName"] == "worker-group-test-cluster"
+
+
+def test_build_ray_cluster_spec_with_accelerators():
+ """
+ Test build_ray_cluster_spec with GPU accelerators.
+ """
+ cluster_config = ManagedClusterConfig(
+ head_accelerators={"nvidia.com/gpu": 1},
+ worker_accelerators={"nvidia.com/gpu": 2},
+ )
+
+ spec = cluster_config.build_ray_cluster_spec("test-cluster")
+ head_spec = spec["headGroupSpec"]
+ head_params = head_spec["rayStartParams"]
+ assert "num-gpus" in head_params
+ assert head_params["num-gpus"] == "1"
+
+ worker_specs = spec["workerGroupSpecs"]
+ worker_spec = worker_specs[0]
+ worker_params = worker_spec["rayStartParams"]
+ assert "num-gpus" in worker_params
+ assert worker_params["num-gpus"] == "2"
+
+
+def test_build_ray_cluster_spec_with_custom_volumes():
+ """
+ Test build_ray_cluster_spec with custom volumes and volume mounts.
+ """
+ custom_volume = V1Volume(name="custom-data", empty_dir={})
+ custom_volume_mount = V1VolumeMount(name="custom-data", mount_path="/data")
+ cluster_config = ManagedClusterConfig(
+ volumes=[custom_volume],
+ volume_mounts=[custom_volume_mount],
+ )
+
+ spec = cluster_config.build_ray_cluster_spec("test-cluster")
+ head_spec = spec["headGroupSpec"]
+ head_pod_spec = head_spec["template"].spec
+ assert len(head_pod_spec.volumes) > 0
+
+ head_container = head_pod_spec.containers[0]
+ assert len(head_container.volume_mounts) > 0
+
+
+def test_build_ray_cluster_spec_with_environment_variables():
+ """
+ Test build_ray_cluster_spec with environment variables.
+ """
+ cluster_config = ManagedClusterConfig(
+ envs={"CUDA_VISIBLE_DEVICES": "0", "RAY_DISABLE_IMPORT_WARNING": "1"},
+ )
+
+ spec = cluster_config.build_ray_cluster_spec("test-cluster")
+
+ head_spec = spec["headGroupSpec"]
+ head_pod_spec = head_spec["template"].spec
+ head_container = head_pod_spec.containers[0]
+ assert hasattr(head_container, "env")
+ env_vars = {env.name: env.value for env in head_container.env}
+ assert env_vars["CUDA_VISIBLE_DEVICES"] == "0"
+ assert env_vars["RAY_DISABLE_IMPORT_WARNING"] == "1"
+ worker_specs = spec["workerGroupSpecs"]
+ worker_spec = worker_specs[0]
+ worker_pod_spec = worker_spec["template"].spec
+ worker_container = worker_pod_spec.containers[0]
+
+ assert hasattr(worker_container, "env")
+ worker_env_vars = {env.name: env.value for env in worker_container.env}
+ assert worker_env_vars["CUDA_VISIBLE_DEVICES"] == "0"
+ assert worker_env_vars["RAY_DISABLE_IMPORT_WARNING"] == "1"
+
+
+def test_build_ray_cluster_spec_with_tolerations():
+ """
+ Test build_ray_cluster_spec with tolerations.
+ """
+ head_toleration = V1Toleration(
+ key="node-role.kubernetes.io/master", operator="Exists", effect="NoSchedule"
+ )
+ worker_toleration = V1Toleration(
+ key="nvidia.com/gpu", operator="Exists", effect="NoSchedule"
+ )
+
+ cluster_config = ManagedClusterConfig(
+ head_tolerations=[head_toleration],
+ worker_tolerations=[worker_toleration],
+ )
+
+ spec = cluster_config.build_ray_cluster_spec("test-cluster")
+ head_spec = spec["headGroupSpec"]
+ head_pod_spec = head_spec["template"].spec
+ assert hasattr(head_pod_spec, "tolerations")
+ assert len(head_pod_spec.tolerations) == 1
+ assert head_pod_spec.tolerations[0].key == "node-role.kubernetes.io/master"
+
+ worker_specs = spec["workerGroupSpecs"]
+ worker_spec = worker_specs[0]
+ worker_pod_spec = worker_spec["template"].spec
+ assert hasattr(worker_pod_spec, "tolerations")
+ assert len(worker_pod_spec.tolerations) == 1
+ assert worker_pod_spec.tolerations[0].key == "nvidia.com/gpu"
+
+
+def test_build_ray_cluster_spec_with_image_pull_secrets():
+ """
+ Test build_ray_cluster_spec with image pull secrets.
+ """
+ cluster_config = ManagedClusterConfig(
+ image_pull_secrets=["my-registry-secret", "another-secret"]
+ )
+
+ spec = cluster_config.build_ray_cluster_spec("test-cluster")
+
+ head_spec = spec["headGroupSpec"]
+ head_pod_spec = head_spec["template"].spec
+ assert hasattr(head_pod_spec, "image_pull_secrets")
+
+ head_secrets = head_pod_spec.image_pull_secrets
+ assert len(head_secrets) == 2
+ assert head_secrets[0].name == "my-registry-secret"
+ assert head_secrets[1].name == "another-secret"
+
+ worker_specs = spec["workerGroupSpecs"]
+ worker_spec = worker_specs[0]
+ worker_pod_spec = worker_spec["template"].spec
+ assert hasattr(worker_pod_spec, "image_pull_secrets")
+
+ worker_secrets = worker_pod_spec.image_pull_secrets
+ assert len(worker_secrets) == 2
+ assert worker_secrets[0].name == "my-registry-secret"
+ assert worker_secrets[1].name == "another-secret"
+
+
+def test_submit_with_cluster_config_compatible_image_passes(auto_mock_setup):
+ """
+ Test that submission passes with compatible cluster_config image.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = True
+
+ cluster_config = ManagedClusterConfig(image=f"ray:{RAY_VERSION}")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ result = rayjob.submit()
+ assert result == "test-job"
+
+
+def test_submit_with_cluster_config_incompatible_image_fails(auto_mock_setup):
+ """
+ Test that submission fails with incompatible cluster_config image.
+ """
+
+ cluster_config = ManagedClusterConfig(image="ray:2.8.0") # Different version
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ with pytest.raises(
+ ValueError, match="Cluster config image: Ray version mismatch detected"
+ ):
+ rayjob.submit()
+
+
+def test_validate_ray_version_compatibility_method(auto_mock_setup):
+ """
+ Test the _validate_ray_version_compatibility method directly.
+ """
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ rayjob._validate_ray_version_compatibility()
+ rayjob._cluster_config = ManagedClusterConfig(image=f"ray:{RAY_VERSION}")
+ rayjob._validate_ray_version_compatibility()
+ rayjob._cluster_config = ManagedClusterConfig(image="ray:2.8.0")
+ with pytest.raises(
+ ValueError, match="Cluster config image: Ray version mismatch detected"
+ ):
+ rayjob._validate_ray_version_compatibility()
+
+ rayjob._cluster_config = ManagedClusterConfig(image="custom-image:latest")
+ with pytest.warns(
+ UserWarning, match="Cluster config image: Cannot determine Ray version"
+ ):
+ rayjob._validate_ray_version_compatibility()
+
+
+def test_validate_cluster_config_image_method(auto_mock_setup):
+ """
+ Test the _validate_cluster_config_image method directly.
+ """
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=ManagedClusterConfig(),
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ rayjob._validate_cluster_config_image()
+ rayjob._cluster_config.image = f"ray:{RAY_VERSION}"
+ rayjob._validate_cluster_config_image()
+ rayjob._cluster_config.image = "ray:2.8.0"
+ with pytest.raises(
+ ValueError, match="Cluster config image: Ray version mismatch detected"
+ ):
+ rayjob._validate_cluster_config_image()
+
+ rayjob._cluster_config.image = "custom-image:latest"
+ with pytest.warns(
+ UserWarning, match="Cluster config image: Cannot determine Ray version"
+ ):
+ rayjob._validate_cluster_config_image()
+
+
+def test_validate_cluster_config_image_edge_cases(auto_mock_setup):
+ """
+ Test edge cases in _validate_cluster_config_image method.
+ """
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=ManagedClusterConfig(),
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ rayjob._cluster_config.image = None
+ rayjob._validate_cluster_config_image()
+ rayjob._cluster_config.image = ""
+ rayjob._validate_cluster_config_image()
+ rayjob._cluster_config.image = 123
+ rayjob._validate_cluster_config_image()
+
+ class MockClusterConfig:
+ pass
+
+ rayjob._cluster_config = MockClusterConfig()
+ rayjob._validate_cluster_config_image()
+
+
+def test_rayjob_stop_success(auto_mock_setup, caplog):
+ """
+ Test successful RayJob stop operation.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ mock_api_instance.suspend_job.return_value = {
+ "metadata": {"name": "test-rayjob"},
+ "spec": {"suspend": True},
+ }
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ cluster_name="test-cluster",
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ with caplog.at_level("INFO"):
+ result = rayjob.stop()
+
+ assert result is True
+
+ mock_api_instance.suspend_job.assert_called_once_with(
+ name="test-rayjob", k8s_namespace="test-namespace"
+ )
+
+ # Verify success message was logged
+ assert "Successfully stopped the RayJob test-rayjob" in caplog.text
+
+
+def test_rayjob_stop_failure(auto_mock_setup):
+ """
+ Test RayJob stop operation when API call fails.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ mock_api_instance.suspend_job.return_value = None
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ cluster_name="test-cluster",
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ with pytest.raises(RuntimeError, match="Failed to stop the RayJob test-rayjob"):
+ rayjob.stop()
+
+ mock_api_instance.suspend_job.assert_called_once_with(
+ name="test-rayjob", k8s_namespace="test-namespace"
+ )
+
+
+def test_rayjob_resubmit_success(auto_mock_setup):
+ """
+ Test successful RayJob resubmit operation.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ mock_api_instance.resubmit_job.return_value = {
+ "metadata": {"name": "test-rayjob"},
+ "spec": {"suspend": False},
+ }
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ cluster_name="test-cluster",
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ result = rayjob.resubmit()
+
+ assert result is True
+
+ mock_api_instance.resubmit_job.assert_called_once_with(
+ name="test-rayjob", k8s_namespace="test-namespace"
+ )
+
+
+def test_rayjob_resubmit_failure(auto_mock_setup):
+ """
+ Test RayJob resubmit operation when API call fails.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ mock_api_instance.resubmit_job.return_value = None
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ cluster_name="test-cluster",
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ with pytest.raises(RuntimeError, match="Failed to resubmit the RayJob test-rayjob"):
+ rayjob.resubmit()
+
+ mock_api_instance.resubmit_job.assert_called_once_with(
+ name="test-rayjob", k8s_namespace="test-namespace"
+ )
+
+
+def test_rayjob_delete_success(auto_mock_setup):
+ """
+ Test successful RayJob deletion.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ )
+
+ mock_api_instance.delete_job.return_value = True
+
+ result = rayjob.delete()
+
+ assert result is True
+ mock_api_instance.delete_job.assert_called_once_with(
+ name="test-rayjob", k8s_namespace="test-namespace"
+ )
+
+
+def test_rayjob_delete_already_deleted(auto_mock_setup, caplog):
+ """
+ Test RayJob deletion when already deleted (should succeed gracefully).
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ entrypoint="python -c 'print()'",
+ cluster_name="test-cluster",
+ )
+
+ # Python client returns False when job doesn't exist/already deleted
+ mock_api_instance.delete_job.return_value = False
+
+ with caplog.at_level("INFO"):
+ result = rayjob.delete()
+
+ # Should succeed (not raise error) when already deleted
+ assert result is True
+ assert "already deleted or does not exist" in caplog.text
+
+ mock_api_instance.delete_job.assert_called_once_with(
+ name="test-rayjob", k8s_namespace="test-namespace"
+ )
+
+
+def test_rayjob_init_both_none_error(auto_mock_setup):
+ """
+ Test RayJob initialization error when both cluster_name and cluster_config are None.
+ """
+ with pytest.raises(
+ ValueError,
+ match="Configuration Error: You must provide either 'cluster_name' .* or 'cluster_config'",
+ ):
+ RayJob(
+ job_name="test-job",
+ entrypoint="python -c 'print()'",
+ cluster_name=None,
+ cluster_config=None,
+ )
+
+
+def test_rayjob_init_missing_cluster_name_with_no_config(auto_mock_setup):
+ """
+ Test RayJob initialization error when cluster_name is None without cluster_config.
+ """
+ with pytest.raises(
+ ValueError,
+ match="Configuration Error: a 'cluster_name' is required when not providing 'cluster_config'",
+ ):
+ rayjob = RayJob.__new__(RayJob)
+ rayjob.name = "test-job"
+ rayjob.entrypoint = "python test.py"
+ rayjob.runtime_env = None
+ rayjob.ttl_seconds_after_finished = 0
+ rayjob.active_deadline_seconds = None
+ rayjob.shutdown_after_job_finishes = True
+ rayjob.namespace = "test-namespace"
+ rayjob._cluster_name = None
+ rayjob._cluster_config = None
+ if rayjob._cluster_config is None and rayjob._cluster_name is None:
+ raise ValueError(
+ "❌ Configuration Error: a 'cluster_name' is required when not providing 'cluster_config'"
+ )
+
+
+def test_rayjob_kueue_label_no_default_queue(auto_mock_setup, mocker, caplog):
+ """
+ Test RayJob falls back to 'default' queue when no default queue exists.
+ """
+ mocker.patch(
+ "codeflare_sdk.ray.rayjobs.rayjob.get_default_kueue_name",
+ return_value=None,
+ )
+
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = {"metadata": {"name": "test-job"}}
+
+ cluster_config = ManagedClusterConfig()
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ )
+
+ with caplog.at_level("WARNING"):
+ rayjob.submit()
+
+ # Verify the submitted job has the fallback label
+ call_args = mock_api_instance.submit_job.call_args
+ submitted_job = call_args.kwargs["job"]
+ assert submitted_job["metadata"]["labels"]["kueue.x-k8s.io/queue-name"] == "default"
+
+ # Verify warning was logged
+ assert "No default Kueue LocalQueue found" in caplog.text
+
+
+def test_rayjob_kueue_explicit_local_queue(auto_mock_setup):
+ """
+ Test RayJob uses explicitly specified local queue.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = {"metadata": {"name": "test-job"}}
+
+ cluster_config = ManagedClusterConfig()
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ local_queue="custom-queue",
+ )
+
+ rayjob.submit()
+
+ # Verify the submitted job has the explicit queue label
+ call_args = mock_api_instance.submit_job.call_args
+ submitted_job = call_args.kwargs["job"]
+ assert (
+ submitted_job["metadata"]["labels"]["kueue.x-k8s.io/queue-name"]
+ == "custom-queue"
+ )
+
+
+def test_rayjob_no_kueue_label_for_existing_cluster(auto_mock_setup):
+ """
+ Test RayJob doesn't add Kueue label for existing clusters.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = {"metadata": {"name": "test-job"}}
+
+ # Using existing cluster (no cluster_config)
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python -c 'print()'",
+ )
+
+ rayjob.submit()
+
+ # Verify no Kueue label was added
+ call_args = mock_api_instance.submit_job.call_args
+ submitted_job = call_args.kwargs["job"]
+ assert "kueue.x-k8s.io/queue-name" not in submitted_job["metadata"]["labels"]
+
+
+def test_rayjob_with_ttl_and_deadline(auto_mock_setup):
+ """
+ Test RayJob with TTL and active deadline seconds.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = {"metadata": {"name": "test-job"}}
+
+ cluster_config = ManagedClusterConfig()
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ ttl_seconds_after_finished=300,
+ active_deadline_seconds=600,
+ )
+
+ rayjob.submit()
+
+ # Verify TTL and deadline were set
+ call_args = mock_api_instance.submit_job.call_args
+ submitted_job = call_args.kwargs["job"]
+ assert submitted_job["spec"]["ttlSecondsAfterFinished"] == 300
+ assert submitted_job["spec"]["activeDeadlineSeconds"] == 600
+
+
+def test_rayjob_shutdown_after_job_finishes(auto_mock_setup):
+ """
+ Test RayJob sets shutdownAfterJobFinishes correctly.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = {"metadata": {"name": "test-job"}}
+
+ # Test with managed cluster (should shutdown)
+ cluster_config = ManagedClusterConfig()
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ )
+
+ rayjob.submit()
+
+ call_args = mock_api_instance.submit_job.call_args
+ submitted_job = call_args.kwargs["job"]
+ assert submitted_job["spec"]["shutdownAfterJobFinishes"] is True
+
+ # Test with existing cluster (should not shutdown)
+ rayjob2 = RayJob(
+ job_name="test-job2",
+ cluster_name="existing-cluster",
+ entrypoint="python -c 'print()'",
+ )
+
+ rayjob2.submit()
+
+ call_args2 = mock_api_instance.submit_job.call_args
+ submitted_job2 = call_args2.kwargs["job"]
+ assert submitted_job2["spec"]["shutdownAfterJobFinishes"] is False
+
+
+def test_rayjob_stop_delete_resubmit_logging(auto_mock_setup, caplog):
+ """
+ Test logging for stop, delete, and resubmit operations.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+
+ # Test stop with logging
+ mock_api_instance.suspend_job.return_value = {
+ "metadata": {"name": "test-rayjob"},
+ "spec": {"suspend": True},
+ }
+
+ rayjob = RayJob(
+ job_name="test-rayjob",
+ cluster_name="test-cluster",
+ namespace="test-namespace",
+ entrypoint="python -c 'print()'",
+ )
+
+ with caplog.at_level("INFO"):
+ result = rayjob.stop()
+
+ assert result is True
+ assert "Successfully stopped the RayJob test-rayjob" in caplog.text
+
+ # Test delete with logging
+ caplog.clear()
+ mock_api_instance.delete_job.return_value = True
+
+ with caplog.at_level("INFO"):
+ result = rayjob.delete()
+
+ assert result is True
+ assert "Successfully deleted the RayJob test-rayjob" in caplog.text
+
+ # Test resubmit with logging
+ caplog.clear()
+ mock_api_instance.resubmit_job.return_value = {
+ "metadata": {"name": "test-rayjob"},
+ "spec": {"suspend": False},
+ }
+
+ with caplog.at_level("INFO"):
+ result = rayjob.resubmit()
+
+ assert result is True
+ assert "Successfully resubmitted the RayJob test-rayjob" in caplog.text
+
+
+def test_rayjob_initialization_logging(auto_mock_setup, caplog):
+ """
+ Test RayJob initialization logging.
+ """
+ with caplog.at_level("INFO"):
+ cluster_config = ManagedClusterConfig()
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ )
+
+ assert "Creating new cluster: test-job-cluster" in caplog.text
+ assert "Initialized RayJob: test-job in namespace: test-namespace" in caplog.text
+
+
+def test_build_submitter_pod_template_uses_default_image(auto_mock_setup, mocker):
+ """
+ Test that _build_submitter_pod_template() uses get_ray_image_for_python_version() for default image.
+ """
+ # Mock get_ray_image_for_python_version to verify it's called
+ mock_get_image = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.rayjob.get_ray_image_for_python_version",
+ return_value="auto-detected-image:py3.12",
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ files = {"test.py": "print('hello')"}
+ secret_name = "test-files"
+
+ # Call _build_submitter_pod_template
+ submitter_template = rayjob._build_submitter_pod_template(files, secret_name)
+
+ # Verify get_ray_image_for_python_version was called
+ mock_get_image.assert_called_once()
+
+ # Verify the submitter pod uses the auto-detected image
+ assert (
+ submitter_template["spec"]["containers"][0]["image"]
+ == "auto-detected-image:py3.12"
+ )
+
+
+def test_build_submitter_pod_template_uses_cluster_config_image(
+ auto_mock_setup, mocker
+):
+ """
+ Test that _build_submitter_pod_template() uses cluster_config image when provided.
+ """
+ # Mock get_ray_image_for_python_version (should be called but overridden)
+ mock_get_image = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.rayjob.get_ray_image_for_python_version",
+ return_value="auto-detected-image:py3.12",
+ )
+
+ cluster_config = ManagedClusterConfig(image="custom-cluster-image:v1")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ files = {"test.py": "print('hello')"}
+ secret_name = "test-files"
+
+ # Call _build_submitter_pod_template
+ submitter_template = rayjob._build_submitter_pod_template(files, secret_name)
+
+ # Verify get_ray_image_for_python_version was called
+ mock_get_image.assert_called_once()
+
+ # Verify the submitter pod uses the cluster config image (overrides default)
+ assert (
+ submitter_template["spec"]["containers"][0]["image"]
+ == "custom-cluster-image:v1"
+ )
+
+
+def test_build_submitter_pod_template_with_files(auto_mock_setup):
+ """
+ Test that _build_submitter_pod_template() correctly builds Secret items for files.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python -c 'print()'",
+ namespace="test-namespace",
+ )
+
+ files = {"main.py": "print('main')", "helper.py": "print('helper')"}
+ secret_name = "test-files"
+
+ # Call _build_submitter_pod_template
+ submitter_template = rayjob._build_submitter_pod_template(files, secret_name)
+
+ # Verify Secret items are created for each file
+ secret_items = submitter_template["spec"]["volumes"][0]["secret"]["items"]
+ assert len(secret_items) == 2
+
+ # Verify each file has a Secret item
+ file_names = [item["key"] for item in secret_items]
+ assert "main.py" in file_names
+ assert "helper.py" in file_names
+
+ # Verify paths match keys
+ for item in secret_items:
+ assert item["key"] == item["path"]
+
+
+def test_validate_working_dir_entrypoint_no_runtime_env(auto_mock_setup, tmp_path):
+ """
+ Test validation checks file exists even when no runtime_env is specified.
+ """
+ # Create the script file
+ script_file = tmp_path / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=f"python {script_file}",
+ namespace="test-namespace",
+ )
+
+ # Should not raise exception (file exists)
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_working_dir_entrypoint_no_working_dir(auto_mock_setup, tmp_path):
+ """
+ Test validation checks file when runtime_env has no working_dir.
+ """
+ # Create the script file
+ script_file = tmp_path / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=f"python {script_file}",
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(pip=["numpy"]),
+ )
+
+ # Should not raise exception (file exists)
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_working_dir_entrypoint_remote_working_dir(auto_mock_setup):
+ """
+ Test validation skips ALL checks for remote working_dir.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python nonexistent_script.py", # File doesn't exist, but should be ignored
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(
+ working_dir="https://github.com/user/repo/archive/main.zip"
+ ),
+ )
+
+ # Should not raise any exception (remote working_dir skips all validation)
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_working_dir_entrypoint_no_python_file(auto_mock_setup):
+ """
+ Test validation passes when entrypoint has no Python file reference.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="echo 'hello world'", # No Python file
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir="."),
+ )
+
+ # Should not raise any exception
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_working_dir_entrypoint_no_redundancy(auto_mock_setup, tmp_path):
+ """
+ Test validation passes when entrypoint doesn't reference working_dir.
+ """
+ # Create test directory and file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ script_file = test_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python script.py", # No directory prefix
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir=str(test_dir)),
+ )
+
+ # Should not raise any exception
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_working_dir_entrypoint_redundant_reference_error(
+ auto_mock_setup, tmp_path
+):
+ """
+ Test validation raises error when entrypoint redundantly references working_dir.
+ """
+ # Create test directory and file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ script_file = test_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=f"python {test_dir}/script.py", # Redundant reference
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir=str(test_dir)),
+ )
+
+ # Should raise ValueError with helpful message
+ with pytest.raises(ValueError, match="Working directory conflict detected"):
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_working_dir_entrypoint_with_dot_slash(auto_mock_setup, tmp_path):
+ """
+ Test validation handles paths with ./ prefix correctly.
+ """
+ # Create test directory and file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ script_file = test_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ # Change to temp directory so relative paths work
+ import os
+
+ original_cwd = os.getcwd()
+ try:
+ os.chdir(tmp_path)
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python ./testdir/script.py", # With ./ prefix
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir="./testdir"), # With ./ prefix
+ )
+
+ # Should raise ValueError (redundant reference)
+ with pytest.raises(ValueError, match="Working directory conflict detected"):
+ rayjob._validate_working_dir_entrypoint()
+ finally:
+ os.chdir(original_cwd)
+
+
+def test_validate_working_dir_entrypoint_submit_integration(auto_mock_setup, tmp_path):
+ """
+ Test that validation is called during submit() and blocks submission.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = {"metadata": {"name": "test-job"}}
+
+ # Create test directory and file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ script_file = test_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=f"python {test_dir}/script.py", # Redundant reference
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir=str(test_dir)),
+ )
+
+ # Should raise ValueError during submit() before API call
+ with pytest.raises(ValueError, match="Working directory conflict detected"):
+ rayjob.submit()
+
+ # Verify submit_job was never called (validation blocked it)
+ mock_api_instance.submit_job.assert_not_called()
+
+
+def test_validate_working_dir_entrypoint_error_message_format(
+ auto_mock_setup, tmp_path
+):
+ """
+ Test that error message contains helpful information.
+ """
+ # Create test directory and file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ script_file = test_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=f"python {test_dir}/script.py",
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir=str(test_dir)),
+ )
+
+ try:
+ rayjob._validate_working_dir_entrypoint()
+ assert False, "Should have raised ValueError"
+ except ValueError as e:
+ error_msg = str(e)
+ # Verify error message contains key information
+ assert "Working directory conflict detected" in error_msg
+ assert "working_dir:" in error_msg
+ assert "entrypoint references:" in error_msg
+ assert "Fix: Remove the directory prefix" in error_msg
+ assert "python script.py" in error_msg # Suggested fix
+
+
+def test_validate_working_dir_entrypoint_subdirectory_valid(auto_mock_setup, tmp_path):
+ """
+ Test validation passes when entrypoint references subdirectory within working_dir.
+ """
+ # Create test directory structure: testdir/subdir/script.py
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ sub_dir = test_dir / "subdir"
+ sub_dir.mkdir()
+ script_file = sub_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python subdir/script.py", # Correct: relative to working_dir
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir=str(test_dir)),
+ )
+
+ # Should not raise any exception
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_working_dir_entrypoint_runtime_env_as_dict(auto_mock_setup, tmp_path):
+ """
+ Test validation works when runtime_env is passed as dict (not RuntimeEnv object).
+ """
+ # Create test directory and file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ script_file = test_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=f"python {test_dir}/script.py", # Redundant reference
+ namespace="test-namespace",
+ runtime_env={"working_dir": str(test_dir)}, # Dict instead of RuntimeEnv
+ )
+
+ # Should raise ValueError even with dict runtime_env
+ with pytest.raises(ValueError, match="Working directory conflict detected"):
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_file_exists_with_working_dir(auto_mock_setup, tmp_path):
+ """
+ Test validation checks that entrypoint file exists within working_dir.
+ """
+ # Create working directory but NOT the script file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python script.py", # File doesn't exist
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir=str(test_dir)),
+ )
+
+ # Should raise ValueError about missing file
+ with pytest.raises(ValueError, match="Entrypoint file not found"):
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_file_exists_without_working_dir(auto_mock_setup, tmp_path):
+ """
+ Test validation checks that entrypoint file exists when no working_dir and using ./ prefix.
+ """
+ # Don't create the script file
+ script_path = "./missing_script.py"
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint=f"python {script_path}", # File doesn't exist (local path with ./)
+ namespace="test-namespace",
+ )
+
+ # Should raise ValueError about missing file
+ with pytest.raises(ValueError, match="Entrypoint file not found"):
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_existing_file_with_working_dir_passes(auto_mock_setup, tmp_path):
+ """
+ Test validation passes when file exists in working_dir.
+ """
+ # Create working directory AND the script file
+ test_dir = tmp_path / "testdir"
+ test_dir.mkdir()
+ script_file = test_dir / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python script.py", # File exists
+ namespace="test-namespace",
+ runtime_env=RuntimeEnv(working_dir=str(test_dir)),
+ )
+
+ # Should not raise any exception
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_inline_python_command_skipped(auto_mock_setup):
+ """
+ Test validation skips inline Python commands (no file reference).
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python -c 'print(\"hello world\")'", # No file reference
+ namespace="test-namespace",
+ )
+
+ # Should not raise any exception (no file to validate)
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_simple_filename_without_working_dir_missing(auto_mock_setup):
+ """
+ Test validation checks simple filenames without working_dir.
+ """
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python script.py", # File doesn't exist locally
+ namespace="test-namespace",
+ )
+
+ # Should raise ValueError (file will be extracted from local, so must exist)
+ with pytest.raises(ValueError, match="Entrypoint file not found"):
+ rayjob._validate_working_dir_entrypoint()
+
+
+def test_validate_simple_filename_without_working_dir_exists(auto_mock_setup, tmp_path):
+ """
+ Test validation passes when simple filename exists locally without working_dir.
+ """
+ import os
+
+ original_cwd = os.getcwd()
+ try:
+ os.chdir(tmp_path)
+ # Create the script file in current directory
+ script_file = tmp_path / "script.py"
+ script_file.write_text("print('hello')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ entrypoint="python script.py", # Simple filename exists locally
+ namespace="test-namespace",
+ )
+
+ # Should not raise exception (file exists)
+ rayjob._validate_working_dir_entrypoint()
+ finally:
+ os.chdir(original_cwd)
diff --git a/src/codeflare_sdk/ray/rayjobs/test/test_runtime_env.py b/src/codeflare_sdk/ray/rayjobs/test/test_runtime_env.py
new file mode 100644
index 00000000..e059a8d3
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/test/test_runtime_env.py
@@ -0,0 +1,1061 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import pytest
+import os
+import io
+from unittest.mock import MagicMock, patch
+from codeflare_sdk.common.utils.constants import MOUNT_PATH, RAY_VERSION
+from ray.runtime_env import RuntimeEnv
+
+from codeflare_sdk.ray.rayjobs.rayjob import RayJob
+from codeflare_sdk.ray.cluster.config import ClusterConfiguration
+from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig
+from kubernetes.client import (
+ V1Volume,
+ V1VolumeMount,
+ ApiException,
+)
+
+from codeflare_sdk.ray.rayjobs.runtime_env import (
+ create_secret_from_spec,
+ extract_all_local_files,
+)
+
+
+def test_rayjob_with_remote_working_dir(auto_mock_setup):
+ """
+ Test RayJob with remote working directory in runtime_env.
+ Should not extract local files and should pass through remote URL.
+ """
+ runtime_env = RuntimeEnv(
+ working_dir="https://github.com/org/repo/archive/refs/heads/main.zip",
+ pip=["numpy", "pandas"],
+ env_vars={"TEST_VAR": "test_value"},
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python test.py",
+ cluster_name="test-cluster",
+ runtime_env=runtime_env,
+ namespace="test-namespace",
+ )
+
+ assert rayjob.runtime_env == runtime_env
+
+ # Should not extract any local files due to remote working_dir
+ files = extract_all_local_files(rayjob)
+ assert files is None
+
+ rayjob_cr = rayjob._build_rayjob_cr()
+
+ # Should have runtimeEnvYAML with all fields
+ expected_runtime_env = (
+ "env_vars:\n"
+ " TEST_VAR: test_value\n"
+ "pip:\n"
+ "- numpy\n"
+ "- pandas\n"
+ "working_dir: https://github.com/org/repo/archive/refs/heads/main.zip\n"
+ )
+ assert rayjob_cr["spec"]["runtimeEnvYAML"] == expected_runtime_env
+
+ # Should not have submitterPodTemplate since no local files
+ assert "submitterPodTemplate" not in rayjob_cr["spec"]
+
+ # Entrypoint should be unchanged
+ assert rayjob_cr["spec"]["entrypoint"] == "python test.py"
+
+
+def test_build_file_secret_spec():
+ """
+ Test building Secret specification for files.
+ """
+ config = ManagedClusterConfig()
+ files = {"main.py": "print('main')", "helper.py": "print('helper')"}
+
+ spec = config.build_file_secret_spec(
+ job_name="test-job", namespace="test-namespace", files=files
+ )
+
+ assert spec["apiVersion"] == "v1"
+ assert spec["kind"] == "Secret"
+ assert spec["type"] == "Opaque"
+ assert spec["metadata"]["name"] == "test-job-files"
+ assert spec["metadata"]["namespace"] == "test-namespace"
+ assert spec["data"] == files
+
+
+def test_build_file_volume_specs():
+ """
+ Test building volume and mount specifications for files.
+ """
+ config = ManagedClusterConfig()
+
+ volume_spec, mount_spec = config.build_file_volume_specs(
+ secret_name="test-files", mount_path="/custom/path"
+ )
+
+ assert volume_spec["name"] == "ray-job-files"
+ assert volume_spec["secret"]["secretName"] == "test-files"
+
+ assert mount_spec["name"] == "ray-job-files"
+ assert mount_spec["mountPath"] == "/custom/path"
+
+
+def test_add_file_volumes():
+ """
+ Test adding file volumes to cluster configuration.
+ """
+ config = ManagedClusterConfig()
+
+ # Initially no volumes
+ assert len(config.volumes) == 0
+ assert len(config.volume_mounts) == 0
+
+ config.add_file_volumes(secret_name="test-files")
+
+ assert len(config.volumes) == 1
+ assert len(config.volume_mounts) == 1
+
+ volume = config.volumes[0]
+ mount = config.volume_mounts[0]
+
+ assert volume.name == "ray-job-files"
+ assert volume.secret.secret_name == "test-files"
+
+ assert mount.name == "ray-job-files"
+ assert mount.mount_path == MOUNT_PATH
+
+
+def test_add_file_volumes_duplicate_prevention():
+ """
+ Test that adding file volumes twice doesn't create duplicates.
+ """
+ config = ManagedClusterConfig()
+
+ # Add volumes twice
+ config.add_file_volumes(secret_name="test-files")
+ config.add_file_volumes(secret_name="test-files")
+
+ assert len(config.volumes) == 1
+ assert len(config.volume_mounts) == 1
+
+
+def test_create_secret_from_spec(auto_mock_setup):
+ """
+ Test creating Secret via Kubernetes API.
+ """
+ mock_api_instance = auto_mock_setup["k8s_api"]
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ )
+
+ secret_spec = {
+ "apiVersion": "v1",
+ "kind": "Secret",
+ "type": "Opaque",
+ "metadata": {"name": "test-files", "namespace": "test-namespace"},
+ "data": {"test.py": "print('test')"},
+ }
+
+ # Provide valid RayJob result with UID as KubeRay client would
+ rayjob_result = {
+ "metadata": {
+ "name": "test-job",
+ "namespace": "test-namespace",
+ "uid": "test-uid-12345",
+ }
+ }
+
+ result = create_secret_from_spec(rayjob, secret_spec, rayjob_result)
+
+ assert result == "test-files"
+ mock_api_instance.create_namespaced_secret.assert_called_once()
+
+
+def test_create_secret_already_exists(auto_mock_setup):
+ """
+ Test creating Secret when it already exists (409 conflict).
+ """
+ mock_api_instance = auto_mock_setup["k8s_api"]
+
+ mock_api_instance.create_namespaced_secret.side_effect = ApiException(status=409)
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ )
+
+ secret_spec = {
+ "apiVersion": "v1",
+ "kind": "Secret",
+ "type": "Opaque",
+ "metadata": {"name": "test-files", "namespace": "test-namespace"},
+ "data": {"test.py": "print('test')"},
+ }
+
+ # Provide valid RayJob result with UID as KubeRay client would
+ rayjob_result = {
+ "metadata": {
+ "name": "test-job",
+ "namespace": "test-namespace",
+ "uid": "test-uid-67890",
+ }
+ }
+
+ result = create_secret_from_spec(rayjob, secret_spec, rayjob_result)
+
+ assert result == "test-files"
+ mock_api_instance.create_namespaced_secret.assert_called_once()
+ mock_api_instance.replace_namespaced_secret.assert_called_once()
+
+
+def test_create_secret_with_owner_reference_basic(mocker, auto_mock_setup, caplog):
+ """
+ Test creating Secret with owner reference from valid RayJob result.
+ """
+ mock_api_instance = auto_mock_setup["k8s_api"]
+
+ # Mock client.V1ObjectMeta and V1Secret
+ mock_v1_metadata = mocker.patch("kubernetes.client.V1ObjectMeta")
+ mock_metadata_instance = MagicMock()
+ mock_v1_metadata.return_value = mock_metadata_instance
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ )
+
+ secret_spec = {
+ "apiVersion": "v1",
+ "kind": "Secret",
+ "type": "Opaque",
+ "metadata": {
+ "name": "test-files",
+ "namespace": "test-namespace",
+ "labels": {
+ "ray.io/job-name": "test-job",
+ "app.kubernetes.io/managed-by": "codeflare-sdk",
+ "app.kubernetes.io/component": "rayjob-files",
+ },
+ },
+ "data": {"test.py": "print('test')"},
+ }
+
+ # Valid RayJob result with UID
+ rayjob_result = {
+ "metadata": {
+ "name": "test-job",
+ "namespace": "test-namespace",
+ "uid": "a4dd4c5a-ab61-411d-b4d1-4abb5177422a",
+ }
+ }
+
+ with caplog.at_level("INFO"):
+ result = create_secret_from_spec(rayjob, secret_spec, rayjob_result)
+
+ assert result == "test-files"
+
+ # Verify owner reference was set
+ expected_owner_ref = mocker.ANY # We'll check via the logs
+ assert (
+ "Adding owner reference to Secret 'test-files' with RayJob UID: a4dd4c5a-ab61-411d-b4d1-4abb5177422a"
+ in caplog.text
+ )
+
+ assert mock_metadata_instance.owner_references is not None
+ mock_api_instance.create_namespaced_secret.assert_called_once()
+
+
+def test_file_handling_kubernetes_best_practice_flow(mocker, tmp_path):
+ """
+ Test the Kubernetes best practice flow: pre-declare volume, submit, create Secret.
+ """
+ mocker.patch("kubernetes.config.load_kube_config")
+
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mock_api_instance = MagicMock()
+ mock_api_class.return_value = mock_api_instance
+
+ submit_result = {
+ "metadata": {
+ "name": "test-job",
+ "namespace": "test-namespace",
+ "uid": "test-uid-12345",
+ }
+ }
+ mock_api_instance.submit_job.return_value = submit_result
+
+ # Mock create_file_secret where it's used (imported into rayjob module)
+ mock_create_secret = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.rayjob.create_file_secret"
+ )
+ mock_add_volumes = mocker.patch.object(ManagedClusterConfig, "add_file_volumes")
+
+ # RayClusterApi is already mocked by auto_mock_setup
+
+ test_file = tmp_path / "test.py"
+ test_file.write_text("print('test')")
+
+ call_order = []
+
+ def track_add_volumes(*args, **kwargs):
+ call_order.append("add_volumes")
+ # Should be called with Secret name
+ assert args[0] == "test-job-files"
+
+ def track_submit(*args, **kwargs):
+ call_order.append("submit_job")
+ return submit_result
+
+ def track_create_secret(*args, **kwargs):
+ call_order.append("create_secret")
+ # Args should be: (job, files, rayjob_result)
+ assert len(args) >= 3, f"Expected 3 args, got {len(args)}: {args}"
+ assert args[2] == submit_result # rayjob_result should be third arg
+
+ mock_add_volumes.side_effect = track_add_volumes
+ mock_api_instance.submit_job.side_effect = track_submit
+ mock_create_secret.side_effect = track_create_secret
+
+ original_cwd = os.getcwd()
+ try:
+ os.chdir(tmp_path)
+
+ cluster_config = ManagedClusterConfig()
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ )
+
+ rayjob.submit()
+ finally:
+ os.chdir(original_cwd)
+
+ # Verify the order: submit → create Secret
+ assert call_order == ["submit_job", "create_secret"]
+
+ mock_api_instance.submit_job.assert_called_once()
+ mock_create_secret.assert_called_once()
+
+ # Verify create_file_secret was called with: (job, files, rayjob_result)
+ # Files dict includes metadata key __entrypoint_path__ for single file case
+ call_args = mock_create_secret.call_args[0]
+ assert call_args[0] == rayjob
+ assert call_args[2] == submit_result
+ # Check that the actual file content is present
+ assert "test.py" in call_args[1]
+ assert call_args[1]["test.py"] == "print('test')"
+
+
+def test_rayjob_submit_with_files_new_cluster(auto_mock_setup, tmp_path):
+ """
+ Test RayJob submission with file detection for new cluster.
+ """
+ mock_api_instance = auto_mock_setup["rayjob_api"]
+ mock_api_instance.submit_job.return_value = {
+ "metadata": {
+ "name": "test-job",
+ "namespace": "test-namespace",
+ "uid": "test-uid-files-12345",
+ }
+ }
+
+ mock_k8s_instance = auto_mock_setup["k8s_api"]
+
+ # Create test file
+ test_file = tmp_path / "test.py"
+ test_file.write_text("print('Hello from the test file!')")
+
+ cluster_config = ManagedClusterConfig()
+
+ original_cwd = os.getcwd()
+ os.chdir(tmp_path)
+
+ try:
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_config=cluster_config,
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ )
+
+ # Submit should detect files and handle them
+ result = rayjob.submit()
+
+ assert result == "test-job"
+
+ mock_k8s_instance.create_namespaced_secret.assert_called_once()
+
+ assert len(cluster_config.volumes) == 0
+ assert len(cluster_config.volume_mounts) == 0
+ # Entrypoint should be adjusted to use just the filename
+ assert rayjob.entrypoint == "python test.py"
+
+ finally:
+ os.chdir(original_cwd)
+
+
+def test_create_secret_api_error_non_409(auto_mock_setup):
+ """
+ Test create_secret_from_spec handles non-409 API errors.
+ """
+ mock_api_instance = auto_mock_setup["k8s_api"]
+
+ # Configure to raise 500 error
+ mock_api_instance.create_namespaced_secret.side_effect = ApiException(status=500)
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ )
+
+ secret_spec = {
+ "apiVersion": "v1",
+ "kind": "Secret",
+ "type": "Opaque",
+ "metadata": {"name": "test-files", "namespace": "test-namespace"},
+ "data": {"test.py": "print('test')"},
+ }
+
+ # Provide valid RayJob result with UID as KubeRay client would
+ rayjob_result = {
+ "metadata": {
+ "name": "test-job",
+ "namespace": "test-namespace",
+ "uid": "test-uid-api-error",
+ }
+ }
+
+ with pytest.raises(RuntimeError, match="Failed to create Secret"):
+ create_secret_from_spec(rayjob, secret_spec, rayjob_result)
+
+
+def test_add_file_volumes_existing_volume_skip():
+ """
+ Test add_file_volumes skips when volume already exists (missing coverage).
+ """
+ from kubernetes.client import V1SecretVolumeSource
+
+ config = ManagedClusterConfig()
+
+ # Pre-add a volume with same name
+ existing_volume = V1Volume(
+ name="ray-job-files",
+ secret=V1SecretVolumeSource(secret_name="existing-files"),
+ )
+ config.volumes.append(existing_volume)
+
+ config.add_file_volumes(secret_name="new-files")
+ assert len(config.volumes) == 1
+ assert len(config.volume_mounts) == 0 # Mount not added due to volume skip
+
+
+def test_add_file_volumes_existing_mount_skip():
+ """
+ Test add_file_volumes skips when mount already exists (missing coverage).
+ """
+ config = ManagedClusterConfig()
+
+ # Pre-add a mount with same name
+ existing_mount = V1VolumeMount(name="ray-job-files", mount_path="/existing/path")
+ config.volume_mounts.append(existing_mount)
+
+ config.add_file_volumes(secret_name="new-files")
+ assert len(config.volumes) == 0 # Volume not added due to mount skip
+ assert len(config.volume_mounts) == 1
+
+
+def test_zip_directory_functionality(tmp_path):
+ """
+ Test _zip_directory with real directories and files.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _zip_directory
+
+ # Create test directory structure
+ test_dir = tmp_path / "working_dir"
+ test_dir.mkdir()
+
+ # Create some test files
+ (test_dir / "main.py").write_text("print('main script')")
+ (test_dir / "utils.py").write_text("def helper(): pass")
+
+ # Create subdirectory with file
+ sub_dir = test_dir / "subdir"
+ sub_dir.mkdir()
+ (sub_dir / "nested.py").write_text("print('nested file')")
+
+ # Test zipping
+ zip_data = _zip_directory(str(test_dir))
+
+ assert zip_data is not None
+ assert len(zip_data) > 0
+ assert isinstance(zip_data, bytes)
+
+
+def test_zip_directory_excludes_jupyter_notebooks(tmp_path, caplog):
+ """
+ Test that Jupyter notebook files (.ipynb) and markdown files (.md) are excluded from zip.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _zip_directory
+ import zipfile
+
+ # Create test directory with mixed file types
+ test_dir = tmp_path / "working_dir"
+ test_dir.mkdir()
+
+ # Create Python files (should be included)
+ (test_dir / "main.py").write_text("print('main script')")
+ (test_dir / "utils.py").write_text("def helper(): pass")
+
+ # Create Jupyter notebook files (should be excluded)
+ (test_dir / "analysis.ipynb").write_text('{"cells": [], "metadata": {}}')
+ (test_dir / "experiment.IPYNB").write_text(
+ '{"cells": [], "metadata": {}}'
+ ) # Test case insensitive
+
+ # Create markdown files (should be excluded)
+ (test_dir / "README.md").write_text("# Project Documentation\n")
+ (test_dir / "CHANGELOG.MD").write_text("# Changes\n") # Test case insensitive
+
+ # Create subdirectory with mixed files
+ sub_dir = test_dir / "notebooks"
+ sub_dir.mkdir()
+ (sub_dir / "data_exploration.ipynb").write_text('{"cells": [], "metadata": {}}')
+ (sub_dir / "helper.py").write_text("print('nested file')")
+ (sub_dir / "guide.md").write_text("# Guide\n")
+
+ # Test zipping
+ with caplog.at_level("INFO"):
+ zip_data = _zip_directory(str(test_dir))
+
+ assert zip_data is not None
+ assert len(zip_data) > 0
+
+ # Verify log message includes exclusion count (3 ipynb + 3 md = 6 total)
+ assert "Excluded 6 file(s) (.ipynb, .md)" in caplog.text
+
+ # Verify excluded files are not in the zip
+ zip_buffer = io.BytesIO(zip_data)
+ with zipfile.ZipFile(zip_buffer, "r") as zipf:
+ zip_contents = zipf.namelist()
+
+ # Python files should be present
+ assert "main.py" in zip_contents
+ assert "utils.py" in zip_contents
+ assert "notebooks/helper.py" in zip_contents
+
+ # Jupyter notebooks should be excluded
+ assert "analysis.ipynb" not in zip_contents
+ assert "experiment.IPYNB" not in zip_contents
+ assert "notebooks/data_exploration.ipynb" not in zip_contents
+
+ # Markdown files should be excluded
+ assert "README.md" not in zip_contents
+ assert "CHANGELOG.MD" not in zip_contents
+ assert "notebooks/guide.md" not in zip_contents
+
+
+def test_zip_directory_no_exclusions_when_no_notebooks(tmp_path, caplog):
+ """
+ Test that no exclusion message is logged when no notebook or markdown files exist.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _zip_directory
+
+ # Create test directory with only Python files
+ test_dir = tmp_path / "working_dir"
+ test_dir.mkdir()
+ (test_dir / "main.py").write_text("print('main script')")
+ (test_dir / "utils.py").write_text("def helper(): pass")
+
+ # Test zipping
+ with caplog.at_level("INFO"):
+ zip_data = _zip_directory(str(test_dir))
+
+ assert zip_data is not None
+
+ # Verify log message does NOT mention exclusions
+ assert "Excluded" not in caplog.text
+
+
+def test_should_exclude_file_function():
+ """
+ Test the _should_exclude_file helper function directly.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _should_exclude_file
+
+ # Should exclude .ipynb files (case insensitive)
+ assert _should_exclude_file("notebook.ipynb") is True
+ assert _should_exclude_file("analysis.IPYNB") is True
+ assert _should_exclude_file("data/exploration.ipynb") is True
+ assert _should_exclude_file("subdir/nested.Ipynb") is True
+
+ # Should exclude .md files (case insensitive)
+ assert _should_exclude_file("README.md") is True
+ assert _should_exclude_file("CHANGELOG.MD") is True
+ assert _should_exclude_file("docs/guide.md") is True
+ assert _should_exclude_file("subdir/notes.Md") is True
+
+ # Should NOT exclude other files
+ assert _should_exclude_file("script.py") is False
+ assert _should_exclude_file("data.json") is False
+ assert _should_exclude_file("requirements.txt") is False
+ assert _should_exclude_file("model.pkl") is False
+ assert _should_exclude_file("markdown_parser.py") is False # Not .md
+ assert _should_exclude_file("test.html") is False
+
+
+def test_zip_directory_error_handling():
+ """
+ Test _zip_directory error handling for IO errors during zipping.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _zip_directory
+
+ # Mock os.walk to raise an OSError
+ with patch("os.walk", side_effect=OSError("Permission denied")):
+ zip_data = _zip_directory("/some/path")
+ assert zip_data is None
+
+
+def test_extract_all_local_files_with_working_dir(tmp_path):
+ """
+ Test extract_all_local_files with local working directory.
+ """
+ # Create test working directory
+ working_dir = tmp_path / "working_dir"
+ working_dir.mkdir()
+ (working_dir / "script.py").write_text("print('working dir script')")
+
+ runtime_env = RuntimeEnv(working_dir=str(working_dir))
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python script.py",
+ runtime_env=runtime_env,
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ files = extract_all_local_files(rayjob)
+
+ assert files is not None
+ assert "working_dir.zip" in files
+ assert isinstance(files["working_dir.zip"], str) # base64 encoded
+
+ # Verify it's valid base64
+ import base64
+
+ try:
+ decoded = base64.b64decode(files["working_dir.zip"])
+ assert len(decoded) > 0
+ except Exception:
+ pytest.fail("Invalid base64 encoding")
+
+
+def test_extract_all_local_files_excludes_notebooks(tmp_path, caplog):
+ """
+ Test that extract_all_local_files excludes Jupyter notebooks and markdown files when zipping working directory.
+ """
+ import zipfile
+ import base64
+
+ # Create test working directory with mixed files
+ working_dir = tmp_path / "working_dir"
+ working_dir.mkdir()
+
+ # Python files that should be included
+ (working_dir / "main.py").write_text("print('main script')")
+ (working_dir / "helper.py").write_text("def helper_function(): pass")
+
+ # Jupyter notebooks that should be excluded
+ (working_dir / "analysis.ipynb").write_text(
+ '{"cells": [{"cell_type": "code", "source": ["print(\'hello\')"]}]}'
+ )
+ (working_dir / "data.ipynb").write_text('{"cells": [], "metadata": {}}')
+
+ # Markdown files that should be excluded
+ (working_dir / "README.md").write_text("# Project Documentation\n")
+ (working_dir / "CHANGELOG.md").write_text("# Changes\n")
+
+ runtime_env = RuntimeEnv(working_dir=str(working_dir))
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python main.py",
+ runtime_env=runtime_env,
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ # This should zip the directory and exclude notebooks and markdown files
+ with caplog.at_level("INFO"):
+ files = extract_all_local_files(rayjob)
+
+ assert files is not None
+ assert "working_dir.zip" in files
+
+ # Verify exclusion was logged (2 ipynb + 2 md = 4 total)
+ assert "Excluded 4 file(s) (.ipynb, .md)" in caplog.text
+
+ # Decode and verify zip contents
+ zip_data = base64.b64decode(files["working_dir.zip"])
+ zip_buffer = io.BytesIO(zip_data)
+
+ with zipfile.ZipFile(zip_buffer, "r") as zipf:
+ zip_contents = zipf.namelist()
+
+ # Python files should be present
+ assert "main.py" in zip_contents
+ assert "helper.py" in zip_contents
+
+ # Jupyter notebooks should be excluded
+ assert "analysis.ipynb" not in zip_contents
+ assert "data.ipynb" not in zip_contents
+
+ # Markdown files should be excluded
+ assert "README.md" not in zip_contents
+ assert "CHANGELOG.md" not in zip_contents
+
+
+def test_extract_single_entrypoint_file_error_handling(tmp_path):
+ """
+ Test _extract_single_entrypoint_file with file read errors.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _extract_single_entrypoint_file
+
+ # Create a file that exists but make it unreadable
+ test_file = tmp_path / "unreadable.py"
+ test_file.write_text("print('test')")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint=f"python {test_file}",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ # Mock open to raise IOError
+ with patch("builtins.open", side_effect=IOError("Permission denied")):
+ result = _extract_single_entrypoint_file(rayjob)
+ assert result is None
+
+
+def test_extract_single_entrypoint_file_no_match():
+ """
+ Test _extract_single_entrypoint_file with no Python file matches.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _extract_single_entrypoint_file
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="echo 'no python files here'",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ result = _extract_single_entrypoint_file(rayjob)
+ assert result is None
+
+
+def test_parse_requirements_file_valid(tmp_path):
+ """
+ Test parse_requirements_file with valid requirements.txt.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import parse_requirements_file
+
+ # Create test requirements file
+ req_file = tmp_path / "requirements.txt"
+ req_file.write_text(
+ """# This is a comment
+numpy==1.21.0
+pandas>=1.3.0
+
+# Another comment
+scikit-learn
+"""
+ )
+
+ result = parse_requirements_file(str(req_file))
+
+ assert result is not None
+ assert len(result) == 3
+ assert "numpy==1.21.0" in result
+ assert "pandas>=1.3.0" in result
+ assert "scikit-learn" in result
+ # Comments and empty lines should be filtered out
+ assert "# This is a comment" not in result
+
+
+def test_parse_requirements_file_missing():
+ """
+ Test parse_requirements_file with non-existent file.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import parse_requirements_file
+
+ result = parse_requirements_file("/non/existent/requirements.txt")
+ assert result is None
+
+
+def test_parse_requirements_file_read_error(tmp_path):
+ """
+ Test parse_requirements_file with file read error.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import parse_requirements_file
+
+ # Create a file
+ req_file = tmp_path / "requirements.txt"
+ req_file.write_text("numpy==1.21.0")
+
+ # Mock open to raise IOError
+ with patch("builtins.open", side_effect=IOError("Permission denied")):
+ result = parse_requirements_file(str(req_file))
+ assert result is None
+
+
+def test_process_pip_dependencies_list():
+ """
+ Test process_pip_dependencies with list input.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import process_pip_dependencies
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ pip_list = ["numpy", "pandas", "scikit-learn"]
+ result = process_pip_dependencies(rayjob, pip_list)
+
+ assert result == pip_list
+
+
+def test_process_pip_dependencies_requirements_file(tmp_path):
+ """
+ Test process_pip_dependencies with requirements.txt path.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import process_pip_dependencies
+
+ # Create test requirements file
+ req_file = tmp_path / "requirements.txt"
+ req_file.write_text("numpy==1.21.0\npandas>=1.3.0")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ result = process_pip_dependencies(rayjob, str(req_file))
+
+ assert result is not None
+ assert len(result) == 2
+ assert "numpy==1.21.0" in result
+ assert "pandas>=1.3.0" in result
+
+
+def test_process_pip_dependencies_dict_format():
+ """
+ Test process_pip_dependencies with dict format containing packages.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import process_pip_dependencies
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ pip_dict = {"packages": ["numpy", "pandas"], "pip_check": False}
+ result = process_pip_dependencies(rayjob, pip_dict)
+
+ assert result == ["numpy", "pandas"]
+
+
+def test_process_pip_dependencies_unsupported_format():
+ """
+ Test process_pip_dependencies with unsupported format.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import process_pip_dependencies
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ # Test with unsupported format (int)
+ result = process_pip_dependencies(rayjob, 12345)
+ assert result is None
+
+
+def test_process_runtime_env_local_working_dir(tmp_path):
+ """
+ Test process_runtime_env with local working directory.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import process_runtime_env, UNZIP_PATH
+
+ # Create test working directory
+ working_dir = tmp_path / "working_dir"
+ working_dir.mkdir()
+ (working_dir / "script.py").write_text("print('test')")
+
+ runtime_env = RuntimeEnv(
+ working_dir=str(working_dir),
+ env_vars={"TEST_VAR": "test_value"},
+ )
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python script.py",
+ runtime_env=runtime_env,
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ result = process_runtime_env(rayjob)
+
+ assert result is not None
+ assert f"working_dir: {UNZIP_PATH}" in result
+ assert "env_vars:" in result
+ assert "TEST_VAR: test_value" in result
+
+
+def test_process_runtime_env_single_file_case(tmp_path):
+ """
+ Test process_runtime_env with single file case (no working_dir in runtime_env).
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import process_runtime_env
+ from codeflare_sdk.common.utils.constants import MOUNT_PATH
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ # Files dict without working_dir.zip (single file case)
+ files = {"test.py": "print('test')"}
+
+ result = process_runtime_env(rayjob, files)
+
+ assert result is not None
+ assert f"working_dir: {MOUNT_PATH}" in result
+
+
+def test_process_runtime_env_no_processing_needed():
+ """
+ Test process_runtime_env returns None when no processing needed.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import process_runtime_env
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ # No runtime_env and no files
+ result = process_runtime_env(rayjob)
+ assert result is None
+
+
+def test_normalize_runtime_env_with_none():
+ """
+ Test _normalize_runtime_env with None input.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _normalize_runtime_env
+
+ result = _normalize_runtime_env(None)
+ assert result is None
+
+
+def test_extract_single_entrypoint_file_no_entrypoint():
+ """
+ Test _extract_single_entrypoint_file with no entrypoint.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import _extract_single_entrypoint_file
+
+ rayjob = RayJob(
+ job_name="test-job",
+ entrypoint=None, # No entrypoint
+ namespace="test-namespace",
+ cluster_name="test-cluster",
+ )
+
+ result = _extract_single_entrypoint_file(rayjob)
+ assert result is None
+
+
+def test_create_file_secret_filters_metadata_keys(auto_mock_setup, tmp_path):
+ """
+ Test create_file_secret filters out metadata keys from files dict.
+ """
+ from codeflare_sdk.ray.rayjobs.runtime_env import create_file_secret
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="existing-cluster",
+ entrypoint="python test.py",
+ namespace="test-namespace",
+ )
+
+ # Files dict with metadata key that should be filtered out
+ files = {
+ "__entrypoint_path__": "some/path/test.py", # Should be filtered
+ "test.py": "print('test')", # Should remain
+ }
+
+ rayjob_result = {
+ "metadata": {
+ "name": "test-job",
+ "namespace": "test-namespace",
+ "uid": "test-uid-12345",
+ }
+ }
+
+ # This should not raise an error and should filter out metadata keys
+ create_file_secret(rayjob, files, rayjob_result)
+
+ # Verify the Secret was created (mocked)
+ mock_api_instance = auto_mock_setup["k8s_api"]
+ mock_api_instance.create_namespaced_secret.assert_called_once()
+
+ # The call should have filtered data (only test.py, not __entrypoint_path__)
+ call_args = mock_api_instance.create_namespaced_secret.call_args
+ secret_data = call_args[1]["body"].string_data # Changed from data to string_data
+ assert "test.py" in secret_data
+ assert "__entrypoint_path__" not in secret_data
diff --git a/src/codeflare_sdk/ray/rayjobs/test/test_status.py b/src/codeflare_sdk/ray/rayjobs/test/test_status.py
new file mode 100644
index 00000000..2f2b9957
--- /dev/null
+++ b/src/codeflare_sdk/ray/rayjobs/test/test_status.py
@@ -0,0 +1,373 @@
+# Copyright 2025 IBM, Red Hat
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from codeflare_sdk.ray.rayjobs.rayjob import RayJob
+from codeflare_sdk.ray.rayjobs.status import (
+ CodeflareRayJobStatus,
+ RayJobDeploymentStatus,
+ RayJobInfo,
+)
+
+
+def test_rayjob_status(mocker):
+ """
+ Test the RayJob status method with different deployment statuses.
+ """
+ # Mock kubernetes config loading
+ mocker.patch("kubernetes.config.load_kube_config")
+ # Mock the RayjobApi to avoid actual Kubernetes calls
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_api_instance = mock_api_class.return_value
+
+ # Create a RayJob instance
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # Test case 1: No job found
+ mock_api_instance.get_job_status.return_value = None
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.UNKNOWN
+ assert ready == False
+
+ # Test case 2: Running job
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": "Running",
+ "startTime": "2025-07-28T11:37:07Z",
+ "failed": 0,
+ "succeeded": 0,
+ "rayClusterName": "test-cluster",
+ }
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.RUNNING
+ assert ready == False
+
+ # Test case 3: Complete job
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": "Complete",
+ "startTime": "2025-07-28T11:37:07Z",
+ "endTime": "2025-07-28T11:42:30Z",
+ "failed": 0,
+ "succeeded": 1,
+ "rayClusterName": "test-cluster",
+ }
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.COMPLETE
+ assert ready == True
+
+ # Test case 4: Failed job
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": "Failed",
+ "startTime": "2025-07-28T11:37:07Z",
+ "endTime": "2025-07-28T11:42:30Z",
+ "failed": 1,
+ "succeeded": 0,
+ "rayClusterName": "test-cluster",
+ }
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.FAILED
+ assert ready == False
+
+ # Test case 5: Suspended job
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": "Suspended",
+ "startTime": "2025-07-28T11:37:07Z",
+ "failed": 0,
+ "succeeded": 0,
+ "rayClusterName": "test-cluster",
+ }
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.SUSPENDED
+ assert ready == False
+
+
+def test_rayjob_status_unknown_deployment_status(mocker):
+ """
+ Test handling of unknown deployment status from the API.
+ """
+ mocker.patch("kubernetes.config.load_kube_config")
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_api_instance = mock_api_class.return_value
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # Test with unrecognized deployment status
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": "SomeNewStatus", # Unknown status
+ "startTime": "2025-07-28T11:37:07Z",
+ "failed": 0,
+ "succeeded": 0,
+ }
+
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.UNKNOWN
+ assert ready == False
+
+
+def test_rayjob_status_missing_fields(mocker):
+ """
+ Test handling of API response with missing fields.
+ """
+ mocker.patch("kubernetes.config.load_kube_config")
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_api_instance = mock_api_class.return_value
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # Test with minimal API response (missing some fields)
+ mock_api_instance.get_job_status.return_value = {
+ # Missing jobId, failed, succeeded, etc.
+ "jobDeploymentStatus": "Running",
+ }
+
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.RUNNING
+ assert ready == False
+
+
+def test_map_to_codeflare_status(mocker):
+ """
+ Test the _map_to_codeflare_status helper method directly.
+ """
+ # Mock kubernetes config loading
+ mocker.patch("kubernetes.config.load_kube_config")
+ # Mock the RayjobApi constructor to avoid authentication issues
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # Test all deployment status mappings
+ status, ready = rayjob._map_to_codeflare_status(RayJobDeploymentStatus.COMPLETE)
+ assert status == CodeflareRayJobStatus.COMPLETE
+ assert ready == True
+
+ status, ready = rayjob._map_to_codeflare_status(RayJobDeploymentStatus.RUNNING)
+ assert status == CodeflareRayJobStatus.RUNNING
+ assert ready == False
+
+ status, ready = rayjob._map_to_codeflare_status(RayJobDeploymentStatus.FAILED)
+ assert status == CodeflareRayJobStatus.FAILED
+ assert ready == False
+
+ status, ready = rayjob._map_to_codeflare_status(RayJobDeploymentStatus.SUSPENDED)
+ assert status == CodeflareRayJobStatus.SUSPENDED
+ assert ready == False
+
+ status, ready = rayjob._map_to_codeflare_status(RayJobDeploymentStatus.UNKNOWN)
+ assert status == CodeflareRayJobStatus.UNKNOWN
+ assert ready == False
+
+
+def test_rayjob_info_dataclass():
+ """
+ Test the RayJobInfo dataclass creation and field access.
+ """
+ job_info = RayJobInfo(
+ name="test-job",
+ job_id="test-job-abc123",
+ status=RayJobDeploymentStatus.RUNNING,
+ namespace="test-ns",
+ cluster_name="test-cluster",
+ start_time="2025-07-28T11:37:07Z",
+ failed_attempts=0,
+ succeeded_attempts=0,
+ )
+
+ # Test all fields are accessible
+ assert job_info.name == "test-job"
+ assert job_info.job_id == "test-job-abc123"
+ assert job_info.status == RayJobDeploymentStatus.RUNNING
+ assert job_info.namespace == "test-ns"
+ assert job_info.cluster_name == "test-cluster"
+ assert job_info.start_time == "2025-07-28T11:37:07Z"
+ assert job_info.end_time is None # Default value
+ assert job_info.failed_attempts == 0
+ assert job_info.succeeded_attempts == 0
+
+
+def test_rayjob_status_print_no_job_found(mocker):
+ """
+ Test that pretty_print.print_no_job_found is called when no job is found and print_to_console=True.
+ """
+ mocker.patch("kubernetes.config.load_kube_config")
+ # Mock the RayjobApi and pretty_print
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_api_instance = mock_api_class.return_value
+ mock_print_no_job_found = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.pretty_print.print_no_job_found"
+ )
+
+ # Create a RayJob instance
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # No job found scenario
+ mock_api_instance.get_job_status.return_value = None
+
+ # Call status with print_to_console=True
+ status, ready = rayjob.status(print_to_console=True)
+
+ # Verify the pretty print function was called
+ mock_print_no_job_found.assert_called_once_with("test-job", "test-ns")
+ assert status == CodeflareRayJobStatus.UNKNOWN
+ assert ready == False
+
+
+def test_rayjob_status_print_job_found(mocker):
+ """
+ Test that pretty_print.print_job_status is called when job is found and print_to_console=True.
+ """
+ mocker.patch("kubernetes.config.load_kube_config")
+ # Mock the RayjobApi and pretty_print
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_api_instance = mock_api_class.return_value
+ mock_print_job_status = mocker.patch(
+ "codeflare_sdk.ray.rayjobs.pretty_print.print_job_status"
+ )
+
+ # Create a RayJob instance
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # Job found scenario
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": "Running",
+ "startTime": "2025-07-28T11:37:07Z",
+ "failed": 0,
+ "succeeded": 0,
+ "rayClusterName": "test-cluster",
+ }
+
+ # Call status with print_to_console=True
+ status, ready = rayjob.status(print_to_console=True)
+
+ # Verify the pretty print function was called
+ mock_print_job_status.assert_called_once()
+ # Verify the RayJobInfo object passed to print_job_status
+ call_args = mock_print_job_status.call_args[0][0] # First positional argument
+ assert call_args.name == "test-job"
+ assert call_args.job_id == "test-job-abc123"
+ assert call_args.status == RayJobDeploymentStatus.RUNNING
+ assert call_args.namespace == "test-ns"
+ assert call_args.cluster_name == "test-cluster"
+
+ assert status == CodeflareRayJobStatus.RUNNING
+ assert ready == False
+
+
+def test_rayjob_status_all_deployment_states(mocker):
+ """Test RayJob status method with all deployment states."""
+ mocker.patch("kubernetes.config.load_kube_config")
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_api_instance = mock_api_class.return_value
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # Test mapping of deployment statuses to CodeflareRayJobStatus
+ test_cases = [
+ # (deployment_status_str, expected CodeflareRayJobStatus, expected ready)
+ ("Complete", CodeflareRayJobStatus.COMPLETE, True),
+ ("Running", CodeflareRayJobStatus.RUNNING, False),
+ ("Failed", CodeflareRayJobStatus.FAILED, False),
+ ("Suspended", CodeflareRayJobStatus.SUSPENDED, False),
+ ]
+
+ for deployment_status_str, expected_status, expected_ready in test_cases:
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": deployment_status_str,
+ "startTime": "2025-07-28T11:37:07Z",
+ "failed": 0,
+ "succeeded": 0,
+ "rayClusterName": "test-cluster",
+ }
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == expected_status, f"Failed for {deployment_status_str}"
+ assert (
+ ready == expected_ready
+ ), f"Failed ready check for {deployment_status_str}"
+
+
+def test_rayjob_status_with_end_time(mocker):
+ """Test RayJob status with end time field."""
+ mocker.patch("kubernetes.config.load_kube_config")
+ mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi")
+ mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayClusterApi")
+ mock_api_instance = mock_api_class.return_value
+
+ rayjob = RayJob(
+ job_name="test-job",
+ cluster_name="test-cluster",
+ namespace="test-ns",
+ entrypoint="python test.py",
+ )
+
+ # Test with end time field
+ mock_api_instance.get_job_status.return_value = {
+ "jobId": "test-job-abc123",
+ "jobDeploymentStatus": "Complete",
+ "startTime": "2025-07-28T11:37:07Z",
+ "endTime": "2025-07-28T11:47:07Z",
+ "failed": 0,
+ "succeeded": 1,
+ "rayClusterName": "test-cluster",
+ }
+
+ status, ready = rayjob.status(print_to_console=False)
+ assert status == CodeflareRayJobStatus.COMPLETE
+ assert ready == True
diff --git a/tests/e2e/cluster_apply_kind_test.py b/tests/e2e/cluster_apply_kind_test.py
index 398bf73b..e023e92d 100644
--- a/tests/e2e/cluster_apply_kind_test.py
+++ b/tests/e2e/cluster_apply_kind_test.py
@@ -1,6 +1,8 @@
from codeflare_sdk import Cluster, ClusterConfiguration
import pytest
+import time
from kubernetes import client
+from codeflare_sdk.common.utils import constants
from support import (
initialize_kubernetes_client,
@@ -38,6 +40,7 @@ def test_cluster_apply(self):
worker_cpu_limits="1",
worker_memory_requests="1Gi",
worker_memory_limits="2Gi",
+ image=f"rayproject/ray:{constants.RAY_VERSION}",
write_to_file=True,
verify_tls=False,
)
@@ -47,9 +50,9 @@ def test_cluster_apply(self):
cluster.apply()
# Wait for the cluster to be ready
- cluster.wait_ready()
- status = cluster.status()
- assert status["ready"], f"Cluster {cluster_name} is not ready: {status}"
+ cluster.wait_ready(dashboard_check=False)
+ status, ready = cluster.status()
+ assert ready, f"Cluster {cluster_name} is not ready: {status}"
# Verify the cluster is created
ray_cluster = get_ray_cluster(cluster_name, namespace)
@@ -58,7 +61,7 @@ def test_cluster_apply(self):
ray_cluster["spec"]["workerGroupSpecs"][0]["replicas"] == 1
), "Initial worker count does not match"
- # Update configuration with 3 workers
+ # Update configuration with 2 workers
updated_config = ClusterConfiguration(
name=cluster_name,
namespace=namespace,
@@ -71,6 +74,7 @@ def test_cluster_apply(self):
worker_cpu_limits="1",
worker_memory_requests="1Gi",
worker_memory_limits="2Gi",
+ image=f"rayproject/ray:{constants.RAY_VERSION}",
write_to_file=True,
verify_tls=False,
)
@@ -79,12 +83,15 @@ def test_cluster_apply(self):
cluster.config = updated_config
cluster.apply()
+ # Give Kubernetes a moment to process the update
+ time.sleep(5)
+
# Wait for the updated cluster to be ready
- cluster.wait_ready()
- updated_status = cluster.status()
- assert updated_status[
- "ready"
- ], f"Cluster {cluster_name} is not ready after update: {updated_status}"
+ cluster.wait_ready(dashboard_check=False)
+ updated_status, updated_ready = cluster.status()
+ assert (
+ updated_ready
+ ), f"Cluster {cluster_name} is not ready after update: {updated_status}"
# Verify the cluster is updated
updated_ray_cluster = get_ray_cluster(cluster_name, namespace)
@@ -94,63 +101,19 @@ def test_cluster_apply(self):
# Clean up
cluster.down()
- ray_cluster = get_ray_cluster(cluster_name, namespace)
- assert ray_cluster is None, "Cluster was not deleted successfully"
- def test_apply_invalid_update(self):
- self.setup_method()
- create_namespace(self)
+ # Wait for deletion to complete (finalizers may delay deletion)
+ max_wait = 30 # seconds
+ wait_interval = 2
+ elapsed = 0
- cluster_name = "test-cluster-apply-invalid"
- namespace = self.namespace
+ while elapsed < max_wait:
+ ray_cluster = get_ray_cluster(cluster_name, namespace)
+ if ray_cluster is None:
+ break
+ time.sleep(wait_interval)
+ elapsed += wait_interval
- # Initial configuration
- initial_config = ClusterConfiguration(
- name=cluster_name,
- namespace=namespace,
- num_workers=1,
- head_cpu_requests="500m",
- head_cpu_limits="1",
- head_memory_requests="1Gi",
- head_memory_limits="2Gi",
- worker_cpu_requests="500m",
- worker_cpu_limits="1",
- worker_memory_requests="1Gi",
- worker_memory_limits="2Gi",
- write_to_file=True,
- verify_tls=False,
- )
-
- # Create the cluster
- cluster = Cluster(initial_config)
- cluster.apply()
-
- # Wait for the cluster to be ready
- cluster.wait_ready()
- status = cluster.status()
- assert status["ready"], f"Cluster {cluster_name} is not ready: {status}"
-
- # Update with an invalid configuration (e.g., immutable field change)
- invalid_config = ClusterConfiguration(
- name=cluster_name,
- namespace=namespace,
- num_workers=2,
- head_cpu_requests="1",
- head_cpu_limits="2", # Changing CPU limits (immutable)
- head_memory_requests="1Gi",
- head_memory_limits="2Gi",
- worker_cpu_requests="500m",
- worker_cpu_limits="1",
- worker_memory_requests="1Gi",
- worker_memory_limits="2Gi",
- write_to_file=True,
- verify_tls=False,
- )
-
- # Try to apply the invalid configuration and expect failure
- cluster.config = invalid_config
- with pytest.raises(RuntimeError, match="Immutable fields detected"):
- cluster.apply()
-
- # Clean up
- cluster.down()
+ assert (
+ ray_cluster is None
+ ), f"Cluster was not deleted successfully after {max_wait}s"
diff --git a/tests/e2e/rayjob/__init__.py b/tests/e2e/rayjob/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tests/e2e/rayjob/ray_version_validation_oauth_test.py b/tests/e2e/rayjob/ray_version_validation_oauth_test.py
new file mode 100644
index 00000000..794d739a
--- /dev/null
+++ b/tests/e2e/rayjob/ray_version_validation_oauth_test.py
@@ -0,0 +1,127 @@
+import pytest
+import sys
+import os
+
+# Add the parent directory to the path to import support
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+from support import *
+
+from codeflare_sdk import (
+ RayJob,
+ ManagedClusterConfig,
+)
+
+
+class TestRayJobRayVersionValidationOauth:
+ def setup_method(self):
+ initialize_kubernetes_client(self)
+
+ def teardown_method(self):
+ delete_namespace(self)
+ delete_kueue_resources(self)
+
+ def _create_basic_managed_cluster_config(
+ self, ray_image: str
+ ) -> ManagedClusterConfig:
+ """Helper method to create basic managed cluster configuration."""
+ return ManagedClusterConfig(
+ head_cpu_requests="500m",
+ head_cpu_limits="500m",
+ head_memory_requests=1,
+ head_memory_limits=2,
+ num_workers=1,
+ worker_cpu_requests="500m",
+ worker_cpu_limits="500m",
+ worker_memory_requests=1,
+ worker_memory_limits=2,
+ image=ray_image,
+ )
+
+ def test_rayjob_lifecycled_cluster_incompatible_ray_version_oauth(self):
+ """Test that RayJob creation fails when cluster config specifies incompatible Ray version."""
+ self.setup_method()
+ create_namespace(self)
+ create_kueue_resources(self)
+ self.run_rayjob_lifecycled_cluster_incompatible_version()
+
+ def run_rayjob_lifecycled_cluster_incompatible_version(self):
+ """Test Ray version validation with cluster lifecycling using incompatible image."""
+
+ job_name = "incompatible-lifecycle-rayjob"
+
+ # Create cluster configuration with incompatible Ray version (2.46.1 instead of expected 2.47.1)
+ incompatible_ray_image = "quay.io/modh/ray:2.46.1-py311-cu121"
+
+ print(
+ f"Creating RayJob with incompatible Ray image in cluster config: {incompatible_ray_image}"
+ )
+
+ cluster_config = self._create_basic_managed_cluster_config(
+ incompatible_ray_image
+ )
+
+ # Create RayJob with incompatible cluster config - this should fail during submission
+ rayjob = RayJob(
+ job_name=job_name,
+ cluster_config=cluster_config,
+ namespace=self.namespace,
+ entrypoint="python -c 'print(\"This should not run due to version mismatch\")'",
+ ttl_seconds_after_finished=30,
+ )
+
+ print(
+ f"Attempting to submit RayJob '{job_name}' with incompatible Ray version..."
+ )
+
+ # This should fail during submission due to Ray version validation
+ with pytest.raises(ValueError, match="Ray version mismatch detected"):
+ rayjob.submit()
+
+ print(
+ "✅ Ray version validation correctly prevented RayJob submission with incompatible cluster config!"
+ )
+
+ def test_rayjob_lifecycled_cluster_unknown_ray_version_oauth(self):
+ """Test that RayJob creation succeeds with warning when Ray version cannot be determined."""
+ self.setup_method()
+ create_namespace(self)
+ create_kueue_resources(self)
+ self.run_rayjob_lifecycled_cluster_unknown_version()
+
+ def run_rayjob_lifecycled_cluster_unknown_version(self):
+ """Test Ray version validation with unknown image (should warn but not fail)."""
+
+ job_name = "unknown-version-rayjob"
+
+ # Use an image where Ray version cannot be determined (SHA digest)
+ unknown_ray_image = "quay.io/modh/ray@sha256:6d076aeb38ab3c34a6a2ef0f58dc667089aa15826fa08a73273c629333e12f1e"
+
+ print(
+ f"Creating RayJob with image where Ray version cannot be determined: {unknown_ray_image}"
+ )
+
+ cluster_config = self._create_basic_managed_cluster_config(unknown_ray_image)
+
+ # Create RayJob with unknown version image - this should succeed with warning
+ rayjob = RayJob(
+ job_name=job_name,
+ cluster_config=cluster_config,
+ namespace=self.namespace,
+ entrypoint="python -c 'print(\"Testing unknown Ray version scenario\")'",
+ ttl_seconds_after_finished=30,
+ )
+
+ print(f"Attempting to submit RayJob '{job_name}' with unknown Ray version...")
+
+ # This should succeed but with a warning
+ with pytest.warns(UserWarning, match="Cannot determine Ray version"):
+ submission_result = rayjob.submit()
+
+ assert (
+ submission_result == job_name
+ ), f"Job submission failed, expected {job_name}, got {submission_result}"
+
+ print("✅ RayJob submission succeeded with warning for unknown Ray version!")
+ print(
+ f"Note: RayJob '{job_name}' was submitted successfully but may need manual cleanup."
+ )
diff --git a/tests/e2e/rayjob/rayjob_existing_cluster_test.py b/tests/e2e/rayjob/rayjob_existing_cluster_test.py
new file mode 100644
index 00000000..82858d28
--- /dev/null
+++ b/tests/e2e/rayjob/rayjob_existing_cluster_test.py
@@ -0,0 +1,119 @@
+import pytest
+import sys
+import os
+from time import sleep
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+from support import *
+
+from codeflare_sdk import (
+ Cluster,
+ ClusterConfiguration,
+)
+from codeflare_sdk import RayJob, TokenAuthentication
+from codeflare_sdk.ray.rayjobs.status import CodeflareRayJobStatus
+from python_client.kuberay_job_api import RayjobApi
+
+
+class TestRayJobExistingCluster:
+ """Test RayJob against existing Kueue-managed clusters."""
+
+ def setup_method(self):
+ initialize_kubernetes_client(self)
+
+ def teardown_method(self):
+ delete_namespace(self)
+ delete_kueue_resources(self)
+
+ def test_existing_kueue_cluster(self):
+ """Test RayJob against Kueue-managed RayCluster."""
+ self.setup_method()
+ create_namespace(self)
+ create_kueue_resources(self)
+
+ cluster_name = "kueue-cluster"
+
+ if is_openshift():
+ auth = TokenAuthentication(
+ token=run_oc_command(["whoami", "--show-token=true"]),
+ server=run_oc_command(["whoami", "--show-server=true"]),
+ skip_tls=True,
+ )
+ auth.login()
+
+ resources = get_platform_appropriate_resources()
+
+ cluster = Cluster(
+ ClusterConfiguration(
+ name=cluster_name,
+ namespace=self.namespace,
+ num_workers=1,
+ head_cpu_requests=resources["head_cpu_requests"],
+ head_cpu_limits=resources["head_cpu_limits"],
+ head_memory_requests=resources["head_memory_requests"],
+ head_memory_limits=resources["head_memory_limits"],
+ worker_cpu_requests=resources["worker_cpu_requests"],
+ worker_cpu_limits=resources["worker_cpu_limits"],
+ worker_memory_requests=resources["worker_memory_requests"],
+ worker_memory_limits=resources["worker_memory_limits"],
+ image=constants.CUDA_PY312_RUNTIME_IMAGE,
+ local_queue=self.local_queues[0],
+ write_to_file=True,
+ verify_tls=False,
+ )
+ )
+
+ cluster.apply()
+
+ # Wait for cluster to be ready (with Kueue admission)
+ print(f"Waiting for cluster '{cluster_name}' to be ready...")
+ cluster.wait_ready(timeout=600)
+ print(f"✓ Cluster '{cluster_name}' is ready")
+
+ # RayJob with explicit local_queue
+ rayjob_explicit = RayJob(
+ job_name="job-explicit-queue",
+ cluster_name=cluster_name,
+ namespace=self.namespace,
+ entrypoint="python -c \"import ray; ray.init(); print('Job with explicit queue')\"",
+ runtime_env={"env_vars": get_setup_env_variables(ACCELERATOR="cpu")},
+ local_queue=self.local_queues[0],
+ )
+
+ # RayJob using default queue
+ rayjob_default = RayJob(
+ job_name="job-default-queue",
+ cluster_name=cluster_name,
+ namespace=self.namespace,
+ entrypoint="python -c \"import ray; ray.init(); print('Job with default queue')\"",
+ runtime_env={"env_vars": get_setup_env_variables(ACCELERATOR="cpu")},
+ )
+
+ try:
+ # Test RayJob with explicit queue
+ assert rayjob_explicit.submit() == "job-explicit-queue"
+ self._wait_completion(rayjob_explicit)
+
+ # Test RayJob with default queue
+ assert rayjob_default.submit() == "job-default-queue"
+ self._wait_completion(rayjob_default)
+ finally:
+ rayjob_explicit.delete()
+ rayjob_default.delete()
+ cluster.down()
+
+ def _wait_completion(self, rayjob: RayJob, timeout: int = 600):
+ """Wait for RayJob completion."""
+ elapsed = 0
+ interval = 10
+
+ while elapsed < timeout:
+ status, _ = rayjob.status(print_to_console=False)
+ if status == CodeflareRayJobStatus.COMPLETE:
+ return
+ elif status == CodeflareRayJobStatus.FAILED:
+ raise AssertionError(f"RayJob '{rayjob.name}' failed")
+ sleep(interval)
+ elapsed += interval
+
+ raise TimeoutError(f"RayJob '{rayjob.name}' timeout after {timeout}s")
diff --git a/tests/e2e/rayjob/rayjob_lifecycled_cluster_test.py b/tests/e2e/rayjob/rayjob_lifecycled_cluster_test.py
new file mode 100644
index 00000000..10390011
--- /dev/null
+++ b/tests/e2e/rayjob/rayjob_lifecycled_cluster_test.py
@@ -0,0 +1,249 @@
+import pytest
+import sys
+import os
+from time import sleep
+import tempfile
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+from support import *
+
+from codeflare_sdk import RayJob, ManagedClusterConfig
+
+from kubernetes import client
+from python_client.kuberay_job_api import RayjobApi
+from python_client.kuberay_cluster_api import RayClusterApi
+
+
+class TestRayJobLifecycledCluster:
+ """Test RayJob with auto-created cluster lifecycle management."""
+
+ def setup_method(self):
+ initialize_kubernetes_client(self)
+
+ def teardown_method(self):
+ delete_namespace(self)
+ delete_kueue_resources(self)
+
+ def test_lifecycled_kueue_managed(self):
+ """Test RayJob with Kueue-managed lifecycled cluster with Secret validation."""
+ self.setup_method()
+ create_namespace(self)
+ create_kueue_resources(self)
+
+ self.job_api = RayjobApi()
+ cluster_api = RayClusterApi()
+ job_name = "kueue-lifecycled"
+
+ # Get platform-appropriate resource configurations
+ resources = get_platform_appropriate_resources()
+
+ cluster_config = ManagedClusterConfig(
+ head_cpu_requests=resources["head_cpu_requests"],
+ head_cpu_limits=resources["head_cpu_limits"],
+ head_memory_requests=resources["head_memory_requests"],
+ head_memory_limits=resources["head_memory_limits"],
+ num_workers=1,
+ worker_cpu_requests=resources["worker_cpu_requests"],
+ worker_cpu_limits=resources["worker_cpu_limits"],
+ worker_memory_requests=resources["worker_memory_requests"],
+ worker_memory_limits=resources["worker_memory_limits"],
+ )
+
+ # Create a temporary script file to test Secret functionality
+ with tempfile.NamedTemporaryFile(
+ mode="w", suffix=".py", delete=False, dir=os.getcwd()
+ ) as script_file:
+ script_file.write(
+ """
+ import ray
+ ray.init()
+ print('Kueue job with Secret done')
+ ray.shutdown()
+ """
+ )
+ script_file.flush()
+ script_filename = os.path.basename(script_file.name)
+
+ try:
+ rayjob = RayJob(
+ job_name=job_name,
+ namespace=self.namespace,
+ cluster_config=cluster_config,
+ entrypoint=f"python {script_filename}",
+ runtime_env={"env_vars": get_setup_env_variables(ACCELERATOR="cpu")},
+ local_queue=self.local_queues[0],
+ )
+
+ assert rayjob.submit() == job_name
+
+ # Verify Secret was created with owner reference
+ self.verify_secret_with_owner_reference(rayjob)
+
+ assert self.job_api.wait_until_job_running(
+ name=rayjob.name, k8s_namespace=rayjob.namespace, timeout=600
+ )
+
+ assert self.job_api.wait_until_job_finished(
+ name=rayjob.name, k8s_namespace=rayjob.namespace, timeout=300
+ )
+ finally:
+ try:
+ rayjob.delete()
+ except Exception:
+ pass # Job might already be deleted
+ verify_rayjob_cluster_cleanup(cluster_api, rayjob.name, rayjob.namespace)
+ # Clean up the temporary script file
+ if "script_filename" in locals():
+ try:
+ os.remove(script_filename)
+ except:
+ pass
+
+ def test_lifecycled_kueue_resource_queueing(self):
+ """Test Kueue resource queueing with lifecycled clusters."""
+ self.setup_method()
+ create_namespace(self)
+ create_limited_kueue_resources(self)
+
+ self.job_api = RayjobApi()
+ cluster_api = RayClusterApi()
+
+ # Get platform-appropriate resource configurations
+ resources = get_platform_appropriate_resources()
+
+ cluster_config = ManagedClusterConfig(
+ head_cpu_requests=resources["head_cpu_requests"],
+ head_cpu_limits=resources["head_cpu_limits"],
+ head_memory_requests=resources["head_memory_requests"],
+ head_memory_limits=resources["head_memory_limits"],
+ num_workers=0,
+ )
+
+ job1 = None
+ job2 = None
+ try:
+ job1 = RayJob(
+ job_name="holder",
+ namespace=self.namespace,
+ cluster_config=cluster_config,
+ entrypoint='python -c "import ray; import time; ray.init(); time.sleep(15)"',
+ runtime_env={"env_vars": get_setup_env_variables(ACCELERATOR="cpu")},
+ local_queue=self.local_queues[0],
+ )
+ assert job1.submit() == "holder"
+ assert self.job_api.wait_until_job_running(
+ name=job1.name, k8s_namespace=job1.namespace, timeout=60
+ )
+
+ job2 = RayJob(
+ job_name="waiter",
+ namespace=self.namespace,
+ cluster_config=cluster_config,
+ entrypoint='python -c "import ray; ray.init()"',
+ runtime_env={"env_vars": get_setup_env_variables(ACCELERATOR="cpu")},
+ local_queue=self.local_queues[0],
+ )
+ assert job2.submit() == "waiter"
+
+ # Wait for Kueue to process the job
+ sleep(5)
+ job2_cr = self.job_api.get_job(name=job2.name, k8s_namespace=job2.namespace)
+
+ # For RayJobs with managed clusters, check if Kueue is holding resources
+ job2_status = job2_cr.get("status", {})
+ ray_cluster_name = job2_status.get("rayClusterName", "")
+
+ # If RayCluster is not created yet, it means Kueue is holding the job
+ if not ray_cluster_name:
+ # This is the expected behavior
+ job_is_queued = True
+ else:
+ # Check RayCluster resources - if all are 0, it's queued
+ ray_cluster_status = job2_status.get("rayClusterStatus", {})
+ desired_cpu = ray_cluster_status.get("desiredCPU", "0")
+ desired_memory = ray_cluster_status.get("desiredMemory", "0")
+
+ # Kueue creates the RayCluster but with 0 resources when queued
+ job_is_queued = desired_cpu == "0" and desired_memory == "0"
+
+ assert job_is_queued, "Job2 should be queued by Kueue while Job1 is running"
+
+ assert self.job_api.wait_until_job_finished(
+ name=job1.name, k8s_namespace=job1.namespace, timeout=60
+ )
+
+ assert wait_for_kueue_admission(
+ self, self.job_api, job2.name, job2.namespace, timeout=30
+ )
+
+ assert self.job_api.wait_until_job_finished(
+ name=job2.name, k8s_namespace=job2.namespace, timeout=60
+ )
+ finally:
+ for job in [job1, job2]:
+ if job:
+ try:
+ job.delete()
+ verify_rayjob_cluster_cleanup(
+ cluster_api, job.name, job.namespace
+ )
+ except:
+ pass
+
+ def verify_secret_with_owner_reference(self, rayjob: RayJob):
+ """Verify that the Secret was created with proper owner reference to the RayJob."""
+ v1 = client.CoreV1Api()
+ secret_name = f"{rayjob.name}-files"
+
+ try:
+ # Get the Secret
+ secret = v1.read_namespaced_secret(
+ name=secret_name, namespace=rayjob.namespace
+ )
+
+ # Verify Secret exists
+ assert secret is not None, f"Secret {secret_name} not found"
+
+ # Verify it contains the script
+ assert secret.data is not None, "Secret has no data"
+ assert len(secret.data) > 0, "Secret data is empty"
+
+ # Verify owner reference
+ assert (
+ secret.metadata.owner_references is not None
+ ), "Secret has no owner references"
+ assert (
+ len(secret.metadata.owner_references) > 0
+ ), "Secret owner references list is empty"
+
+ owner_ref = secret.metadata.owner_references[0]
+ assert (
+ owner_ref.api_version == "ray.io/v1"
+ ), f"Wrong API version: {owner_ref.api_version}"
+ assert owner_ref.kind == "RayJob", f"Wrong kind: {owner_ref.kind}"
+ assert owner_ref.name == rayjob.name, f"Wrong owner name: {owner_ref.name}"
+ assert (
+ owner_ref.controller is True
+ ), "Owner reference controller not set to true"
+ assert (
+ owner_ref.block_owner_deletion is True
+ ), "Owner reference blockOwnerDeletion not set to true"
+
+ # Verify labels
+ assert secret.metadata.labels.get("ray.io/job-name") == rayjob.name
+ assert (
+ secret.metadata.labels.get("app.kubernetes.io/managed-by")
+ == "codeflare-sdk"
+ )
+ assert (
+ secret.metadata.labels.get("app.kubernetes.io/component")
+ == "rayjob-files"
+ )
+
+ print(f"✓ Secret {secret_name} verified with proper owner reference")
+
+ except client.rest.ApiException as e:
+ if e.status == 404:
+ raise AssertionError(f"Secret {secret_name} not found")
+ else:
+ raise e
diff --git a/tests/e2e/support.py b/tests/e2e/support.py
index fe9261a2..85b3dd35 100644
--- a/tests/e2e/support.py
+++ b/tests/e2e/support.py
@@ -2,6 +2,7 @@
import random
import string
import subprocess
+from time import sleep
from codeflare_sdk import get_cluster
from kubernetes import client, config
from codeflare_sdk.common.kubernetes_cluster.kube_api_helpers import (
@@ -27,11 +28,82 @@ def get_ray_cluster(cluster_name, namespace):
raise
+def is_openshift():
+ """Detect if running on OpenShift by checking for OpenShift-specific API resources."""
+ try:
+ api = client.ApiClient()
+ discovery = client.ApisApi(api)
+ # Check for OpenShift-specific API group
+ groups = discovery.get_api_versions().groups
+ for group in groups:
+ if group.name == "image.openshift.io":
+ return True
+ return False
+ except Exception:
+ # If we can't determine, assume it's not OpenShift
+ return False
+
+
def get_ray_image():
- return os.getenv(
- "RAY_IMAGE",
- get_ray_image_for_python_version(warn_on_unsupported=False),
- )
+ """
+ Get appropriate Ray image based on platform (OpenShift vs Kind/vanilla K8s).
+
+ The tests marked with @pytest.mark.openshift can run on both OpenShift and Kind clusters
+ with Kueue installed. This function automatically selects the appropriate image:
+ - OpenShift: Uses the CUDA runtime image (quay.io/modh/ray:...)
+ - Kind/K8s: Uses the standard Ray image (rayproject/ray:VERSION)
+
+ You can override this behavior by setting the RAY_IMAGE environment variable.
+ """
+ # Allow explicit override via environment variable
+ if "RAY_IMAGE" in os.environ:
+ return os.environ["RAY_IMAGE"]
+
+ # Auto-detect platform and return appropriate image
+ if is_openshift():
+ return get_ray_image_for_python_version()
+ else:
+ # Use standard Ray image for Kind/vanilla K8s
+ return f"rayproject/ray:{constants.RAY_VERSION}"
+
+
+def get_platform_appropriate_resources():
+ """
+ Get appropriate resource configurations based on platform.
+
+ OpenShift with MODH images requires more memory than Kind with standard Ray images.
+
+ Returns:
+ dict: Resource configurations with keys:
+ - head_cpu_requests, head_cpu_limits
+ - head_memory_requests, head_memory_limits
+ - worker_cpu_requests, worker_cpu_limits
+ - worker_memory_requests, worker_memory_limits
+ """
+ if is_openshift():
+ # MODH runtime images require more memory
+ return {
+ "head_cpu_requests": "1",
+ "head_cpu_limits": "1.5",
+ "head_memory_requests": 7,
+ "head_memory_limits": 8,
+ "worker_cpu_requests": "1",
+ "worker_cpu_limits": "1",
+ "worker_memory_requests": 5,
+ "worker_memory_limits": 6,
+ }
+ else:
+ # Standard Ray images require less memory
+ return {
+ "head_cpu_requests": "1",
+ "head_cpu_limits": "1.5",
+ "head_memory_requests": 7,
+ "head_memory_limits": 8,
+ "worker_cpu_requests": "1",
+ "worker_cpu_limits": "1",
+ "worker_memory_requests": 2,
+ "worker_memory_limits": 3,
+ }
def get_setup_env_variables(**kwargs):
@@ -147,6 +219,17 @@ def run_oc_command(args):
return None
+def run_kubectl_command(args):
+ try:
+ result = subprocess.run(
+ ["kubectl"] + args, capture_output=True, text=True, check=True
+ )
+ return result.stdout.strip()
+ except subprocess.CalledProcessError as e:
+ print(f"Error executing 'kubectl {' '.join(args)}': {e}")
+ return None
+
+
def create_cluster_queue(self, cluster_queue, flavor):
cluster_queue_json = {
"apiVersion": "kueue.x-k8s.io/v1beta1",
@@ -161,9 +244,9 @@ def create_cluster_queue(self, cluster_queue, flavor):
{
"name": flavor,
"resources": [
- {"name": "cpu", "nominalQuota": 9},
- {"name": "memory", "nominalQuota": "36Gi"},
- {"name": "nvidia.com/gpu", "nominalQuota": 1},
+ {"name": "cpu", "nominalQuota": 20},
+ {"name": "memory", "nominalQuota": "80Gi"},
+ {"name": "nvidia.com/gpu", "nominalQuota": 2},
],
},
],
@@ -301,7 +384,6 @@ def create_kueue_resources(
def delete_kueue_resources(self):
- # Delete if given cluster-queue exists
for cq in self.cluster_queues:
try:
self.custom_api.delete_cluster_custom_object(
@@ -409,3 +491,234 @@ def assert_get_cluster_and_jobsubmit(
assert job_list[0].submission_id == submission_id
cluster.down()
+
+
+def wait_for_kueue_admission(self, job_api, job_name, namespace, timeout=120):
+ print(f"Waiting for Kueue admission of job '{job_name}'...")
+ elapsed_time = 0
+ check_interval = 5
+
+ while elapsed_time < timeout:
+ try:
+ job_cr = job_api.get_job(name=job_name, k8s_namespace=namespace)
+
+ # Check if the job is no longer suspended
+ is_suspended = job_cr.get("spec", {}).get("suspend", False)
+
+ if not is_suspended:
+ print(f"✓ Job '{job_name}' admitted by Kueue (no longer suspended)")
+ return True
+
+ # Debug: Check workload status every 10 seconds
+ if elapsed_time % 10 == 0:
+ workload = get_kueue_workload_for_job(self, job_name, namespace)
+ if workload:
+ conditions = workload.get("status", {}).get("conditions", [])
+ print(f" DEBUG: Workload conditions for '{job_name}':")
+ for condition in conditions:
+ print(
+ f" - {condition.get('type')}: {condition.get('status')} - {condition.get('reason', '')} - {condition.get('message', '')}"
+ )
+
+ # Optional: Check status conditions for more details
+ conditions = job_cr.get("status", {}).get("conditions", [])
+ for condition in conditions:
+ if (
+ condition.get("type") == "Suspended"
+ and condition.get("status") == "False"
+ ):
+ print(
+ f"✓ Job '{job_name}' admitted by Kueue (Suspended=False condition)"
+ )
+ return True
+
+ except Exception as e:
+ print(f"Error checking job status: {e}")
+
+ sleep(check_interval)
+ elapsed_time += check_interval
+
+ print(f"✗ Timeout waiting for Kueue admission of job '{job_name}'")
+ return False
+
+
+def create_limited_kueue_resources(self):
+ print("Creating limited Kueue resources for preemption testing...")
+
+ # Create a resource flavor with default (no special labels/tolerations)
+ resource_flavor = f"limited-flavor-{random_choice()}"
+ create_resource_flavor(
+ self, resource_flavor, default=True, with_labels=False, with_tolerations=False
+ )
+ self.resource_flavors = [resource_flavor]
+
+ # Create a cluster queue with very limited resources
+ # Adjust quota based on platform - OpenShift needs more memory
+ if is_openshift():
+ # MODH images need more memory, so higher quota but still limited to allow only 1 job
+ cpu_quota = 3
+ memory_quota = "15Gi" # One job needs ~8Gi head, allow some buffer
+ else:
+ # Standard Ray images - one job needs ~8G head + 500m submitter
+ cpu_quota = 3
+ memory_quota = "10Gi" # Enough for one job (8G head + submitter), but not two
+
+ cluster_queue_name = f"limited-cq-{random_choice()}"
+ cluster_queue_json = {
+ "apiVersion": "kueue.x-k8s.io/v1beta1",
+ "kind": "ClusterQueue",
+ "metadata": {"name": cluster_queue_name},
+ "spec": {
+ "namespaceSelector": {},
+ "resourceGroups": [
+ {
+ "coveredResources": ["cpu", "memory"],
+ "flavors": [
+ {
+ "name": resource_flavor,
+ "resources": [
+ {
+ "name": "cpu",
+ "nominalQuota": cpu_quota,
+ },
+ {
+ "name": "memory",
+ "nominalQuota": memory_quota,
+ },
+ ],
+ }
+ ],
+ }
+ ],
+ },
+ }
+
+ try:
+ self.custom_api.create_cluster_custom_object(
+ group="kueue.x-k8s.io",
+ plural="clusterqueues",
+ version="v1beta1",
+ body=cluster_queue_json,
+ )
+ print(f"✓ Created limited ClusterQueue: {cluster_queue_name}")
+ except Exception as e:
+ print(f"Error creating limited ClusterQueue: {e}")
+ raise
+
+ self.cluster_queues = [cluster_queue_name]
+
+ # Create a local queue
+ local_queue_name = f"limited-lq-{random_choice()}"
+ create_local_queue(self, cluster_queue_name, local_queue_name, is_default=True)
+ self.local_queues = [local_queue_name]
+
+ print("✓ Limited Kueue resources created successfully")
+
+
+def get_kueue_workload_for_job(self, job_name, namespace):
+ try:
+ # List all workloads in the namespace
+ workloads = self.custom_api.list_namespaced_custom_object(
+ group="kueue.x-k8s.io",
+ version="v1beta1",
+ plural="workloads",
+ namespace=namespace,
+ )
+
+ # Find workload with matching RayJob owner reference
+ for workload in workloads.get("items", []):
+ owner_refs = workload.get("metadata", {}).get("ownerReferences", [])
+
+ for owner_ref in owner_refs:
+ if (
+ owner_ref.get("kind") == "RayJob"
+ and owner_ref.get("name") == job_name
+ ):
+ workload_name = workload.get("metadata", {}).get("name")
+ print(
+ f"✓ Found Kueue workload '{workload_name}' for RayJob '{job_name}'"
+ )
+ return workload
+
+ print(f"✗ No Kueue workload found for RayJob '{job_name}'")
+ return None
+
+ except Exception as e:
+ print(f"Error getting Kueue workload for job '{job_name}': {e}")
+ return None
+
+
+def wait_for_job_status(
+ job_api, rayjob_name: str, namespace: str, expected_status: str, timeout: int = 30
+) -> bool:
+ """
+ Wait for a RayJob to reach a specific deployment status.
+
+ Args:
+ job_api: RayjobApi instance
+ rayjob_name: Name of the RayJob
+ namespace: Namespace of the RayJob
+ expected_status: Expected jobDeploymentStatus value
+ timeout: Maximum time to wait in seconds
+
+ Returns:
+ bool: True if status reached, False if timeout
+ """
+ elapsed_time = 0
+ check_interval = 2
+
+ while elapsed_time < timeout:
+ status = job_api.get_job_status(name=rayjob_name, k8s_namespace=namespace)
+ if status and status.get("jobDeploymentStatus") == expected_status:
+ return True
+
+ sleep(check_interval)
+ elapsed_time += check_interval
+
+ return False
+
+
+def verify_rayjob_cluster_cleanup(
+ cluster_api, rayjob_name: str, namespace: str, timeout: int = 60
+):
+ """
+ Verify that the RayCluster created by a RayJob has been cleaned up.
+ Handles KubeRay's automatic suffix addition to cluster names.
+
+ Args:
+ cluster_api: RayClusterApi instance
+ rayjob_name: Name of the RayJob
+ namespace: Namespace to check
+ timeout: Maximum time to wait in seconds
+
+ Raises:
+ TimeoutError: If cluster is not cleaned up within timeout
+ """
+ elapsed_time = 0
+ check_interval = 5
+
+ while elapsed_time < timeout:
+ # List all RayClusters in the namespace
+ clusters = cluster_api.list_ray_clusters(
+ k8s_namespace=namespace, async_req=False
+ )
+
+ # Check if any cluster exists that starts with our job name
+ found = False
+ for cluster in clusters.get("items", []):
+ cluster_name = cluster.get("metadata", {}).get("name", "")
+ # KubeRay creates clusters with pattern: {job_name}-raycluster-{suffix}
+ if cluster_name.startswith(f"{rayjob_name}-raycluster"):
+ found = True
+ break
+
+ if not found:
+ # No cluster found, cleanup successful
+ return
+
+ sleep(check_interval)
+ elapsed_time += check_interval
+
+ raise TimeoutError(
+ f"RayCluster for job '{rayjob_name}' was not cleaned up within {timeout} seconds"
+ )
diff --git a/tests/test_cluster_yamls/appwrapper/unit-test-all-params.yaml b/tests/test_cluster_yamls/appwrapper/unit-test-all-params.yaml
index aa097dd9..fe07e331 100644
--- a/tests/test_cluster_yamls/appwrapper/unit-test-all-params.yaml
+++ b/tests/test_cluster_yamls/appwrapper/unit-test-all-params.yaml
@@ -19,6 +19,7 @@ spec:
controller-tools.k8s.io: '1.0'
key1: value1
key2: value2
+ ray.io/cluster: aw-all-params
name: aw-all-params
namespace: ns
spec:
diff --git a/tests/test_cluster_yamls/kueue/aw_kueue.yaml b/tests/test_cluster_yamls/kueue/aw_kueue.yaml
index f5f16406..92e5078d 100644
--- a/tests/test_cluster_yamls/kueue/aw_kueue.yaml
+++ b/tests/test_cluster_yamls/kueue/aw_kueue.yaml
@@ -13,6 +13,7 @@ spec:
metadata:
labels:
controller-tools.k8s.io: '1.0'
+ ray.io/cluster: unit-test-aw-kueue
name: unit-test-aw-kueue
namespace: ns
spec:
diff --git a/tests/test_cluster_yamls/kueue/ray_cluster_kueue.yaml b/tests/test_cluster_yamls/kueue/ray_cluster_kueue.yaml
index d6db4f4a..04331aed 100644
--- a/tests/test_cluster_yamls/kueue/ray_cluster_kueue.yaml
+++ b/tests/test_cluster_yamls/kueue/ray_cluster_kueue.yaml
@@ -13,6 +13,7 @@ spec:
metadata:
labels:
controller-tools.k8s.io: '1.0'
+ ray.io/cluster: unit-test-cluster-kueue
name: unit-test-cluster-kueue
namespace: ns
spec:
diff --git a/tests/test_cluster_yamls/ray/default-appwrapper.yaml b/tests/test_cluster_yamls/ray/default-appwrapper.yaml
index 27828163..1041f3b5 100644
--- a/tests/test_cluster_yamls/ray/default-appwrapper.yaml
+++ b/tests/test_cluster_yamls/ray/default-appwrapper.yaml
@@ -11,6 +11,7 @@ spec:
metadata:
labels:
controller-tools.k8s.io: '1.0'
+ ray.io/cluster: default-appwrapper
name: default-appwrapper
namespace: ns
spec:
diff --git a/tests/test_cluster_yamls/ray/default-ray-cluster.yaml b/tests/test_cluster_yamls/ray/default-ray-cluster.yaml
index d2e6b05a..213b22cf 100644
--- a/tests/test_cluster_yamls/ray/default-ray-cluster.yaml
+++ b/tests/test_cluster_yamls/ray/default-ray-cluster.yaml
@@ -3,6 +3,7 @@ kind: RayCluster
metadata:
labels:
controller-tools.k8s.io: '1.0'
+ ray.io/cluster: default-cluster
name: default-cluster
namespace: ns
spec:
diff --git a/tests/test_cluster_yamls/ray/unit-test-all-params.yaml b/tests/test_cluster_yamls/ray/unit-test-all-params.yaml
index ee0878c1..7c7d82d6 100644
--- a/tests/test_cluster_yamls/ray/unit-test-all-params.yaml
+++ b/tests/test_cluster_yamls/ray/unit-test-all-params.yaml
@@ -10,6 +10,7 @@ metadata:
key1: value1
key2: value2
kueue.x-k8s.io/queue-name: local-queue-default
+ ray.io/cluster: test-all-params
name: test-all-params
namespace: ns
spec: