diff --git a/.github/workflows/coverage-badge.yaml b/.github/workflows/coverage-badge.yaml index 0d2d41f6..2c3b40fa 100644 --- a/.github/workflows/coverage-badge.yaml +++ b/.github/workflows/coverage-badge.yaml @@ -4,7 +4,7 @@ name: Coverage Badge on: push: - branches: [ main ] + branches: [ main, ray-jobs-feature ] jobs: report: diff --git a/.github/workflows/e2e_tests.yaml b/.github/workflows/e2e_tests.yaml index fc80af56..d66e4b34 100644 --- a/.github/workflows/e2e_tests.yaml +++ b/.github/workflows/e2e_tests.yaml @@ -6,6 +6,7 @@ on: branches: - main - 'release-*' + - ray-jobs-feature paths-ignore: - 'docs/**' - '**.adoc' diff --git a/.github/workflows/unit-tests.yml b/.github/workflows/unit-tests.yml index 6697fc80..e38e6973 100755 --- a/.github/workflows/unit-tests.yml +++ b/.github/workflows/unit-tests.yml @@ -2,9 +2,9 @@ name: Python Tests on: pull_request: - branches: [ main ] + branches: [ main, ray-jobs-feature ] push: - branches: [ main ] + branches: [ main, ray-jobs-feature ] jobs: unit-tests: diff --git a/codecov.yml b/codecov.yml new file mode 100644 index 00000000..803ac581 --- /dev/null +++ b/codecov.yml @@ -0,0 +1,15 @@ +coverage: + precision: 2 + round: down + status: + project: + default: + target: auto + threshold: 2.5% + patch: + default: + target: 85% + threshold: 2.5% + +ignore: + - "**/__init__.py" 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..5348099c --- /dev/null +++ b/demo-notebooks/guided-demos/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/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/docs/sphinx/user-docs/cluster-configuration.rst b/docs/sphinx/user-docs/cluster-configuration.rst index c810148b..f8212823 100644 --- a/docs/sphinx/user-docs/cluster-configuration.rst +++ b/docs/sphinx/user-docs/cluster-configuration.rst @@ -155,20 +155,3 @@ Example configuration: .. note:: You need to have a Redis instance deployed in your Kubernetes cluster before using this feature. - -Deprecating Parameters ----------------------- - -The following parameters of the ``ClusterConfiguration`` are being -deprecated. - -.. list-table:: - :header-rows: 1 - :widths: auto - - * - Deprecated Parameter - - Replaced By - * - ``head_cpus`` - - ``head_cpu_requests``, ``head_cpu_limits`` - * - ``head_memory`` - - ``head_memory_requests``, ``head_memory_limits`` diff --git a/poetry.lock b/poetry.lock index 89bca284..381383d4 100644 --- a/poetry.lock +++ b/poetry.lock @@ -14,103 +14,103 @@ files = [ [[package]] name = "aiohttp" -version = "3.12.12" +version = "3.12.14" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.9" groups = ["main"] files = [ - {file = "aiohttp-3.12.12-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6f25e9d274d6abbb15254f76f100c3984d6b9ad6e66263cc60a465dd5c7e48f5"}, - {file = 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"https://github.com/ray-project/kuberay.git", subdirectory = "clients/python-client", rev = "d1e750d9beac612ad455b951c1a789f971409ab3" } + +[[tool.poetry.source]] +name = "pypi" + +[[tool.poetry.source]] +name = "testpypi" +url = "https://test.pypi.org/simple/" [tool.poetry.group.docs] optional = true @@ -59,4 +67,3 @@ markers = [ ] addopts = "--timeout=900" testpaths = ["src/codeflare_sdk"] -collect_ignore = ["src/codeflare_sdk/common/utils/unit_test_support.py"] 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/k8s_utils.py b/src/codeflare_sdk/common/utils/k8s_utils.py new file mode 100644 index 00000000..57eccf2d --- /dev/null +++ b/src/codeflare_sdk/common/utils/k8s_utils.py @@ -0,0 +1,37 @@ +""" +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(): + """ + Retrieves the current Kubernetes namespace. + + This function attempts to detect the current namespace by: + 1. First checking if running inside a pod (reading from service account namespace file) + 2. Falling back to reading from the current kubeconfig context + + 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/widgets/test_widgets.py b/src/codeflare_sdk/common/widgets/test_widgets.py index f88d8eb2..33beca5c 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.utils.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..91295fa9 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 @@ -353,7 +353,7 @@ def view_clusters(namespace: str = None): ) return # Exit function if not in Jupyter Notebook - from ...ray.cluster.cluster import get_current_namespace + from ...common.utils 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 92cefef4..9d7ed10a 100644 --- a/src/codeflare_sdk/ray/cluster/build_ray_cluster.py +++ b/src/codeflare_sdk/ray/cluster/build_ray_cluster.py @@ -136,6 +136,7 @@ def build_ray_cluster(cluster: "codeflare_sdk.ray.cluster.Cluster"): "enableIngress": False, "rayStartParams": { "dashboard-host": "0.0.0.0", + "dashboard-port": "8265", "block": "true", "num-gpus": str(head_gpu_count), "resources": head_resources, @@ -245,6 +246,7 @@ 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) diff --git a/src/codeflare_sdk/ray/cluster/cluster.py b/src/codeflare_sdk/ray/cluster/cluster.py index 4eaa2000..5c378efd 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" @@ -635,32 +640,6 @@ 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", @@ -760,6 +739,7 @@ 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( diff --git a/src/codeflare_sdk/ray/cluster/config.py b/src/codeflare_sdk/ray/cluster/config.py index ec89924a..dc61de2a 100644 --- a/src/codeflare_sdk/ray/cluster/config.py +++ b/src/codeflare_sdk/ray/cluster/config.py @@ -50,10 +50,6 @@ class ClusterConfiguration: The name of the cluster. namespace: The namespace in which the cluster should be created. - head_cpus: - The number of CPUs to allocate to the head node. - head_memory: - The amount of memory to allocate to the head node. head_extended_resource_requests: A dictionary of extended resource requests for the head node. ex: {"nvidia.com/gpu": 1} head_tolerations: @@ -104,10 +100,8 @@ class ClusterConfiguration: namespace: Optional[str] = None head_cpu_requests: Union[int, str] = 2 head_cpu_limits: Union[int, str] = 2 - head_cpus: Optional[Union[int, str]] = None # Deprecating head_memory_requests: Union[int, str] = 8 head_memory_limits: Union[int, str] = 8 - head_memory: Optional[Union[int, str]] = None # Deprecating head_extended_resource_requests: Dict[str, Union[str, int]] = field( default_factory=dict ) @@ -173,10 +167,8 @@ def __post_init__(self): ) self._validate_types() - self._memory_to_resource() self._memory_to_string() self._str_mem_no_unit_add_GB() - self._cpu_to_resource() self._combine_extended_resource_mapping() self._validate_extended_resource_requests(self.head_extended_resource_requests) self._validate_extended_resource_requests( @@ -209,8 +201,6 @@ def _validate_extended_resource_requests(self, extended_resources: Dict[str, int ) def _str_mem_no_unit_add_GB(self): - if isinstance(self.head_memory, str) and self.head_memory.isdecimal(): - self.head_memory = f"{self.head_memory}G" if ( isinstance(self.worker_memory_requests, str) and self.worker_memory_requests.isdecimal() @@ -232,20 +222,6 @@ def _memory_to_string(self): if isinstance(self.worker_memory_limits, int): self.worker_memory_limits = f"{self.worker_memory_limits}G" - def _cpu_to_resource(self): - if self.head_cpus: - warnings.warn( - "head_cpus is being deprecated, use head_cpu_requests and head_cpu_limits" - ) - self.head_cpu_requests = self.head_cpu_limits = self.head_cpus - - def _memory_to_resource(self): - if self.head_memory: - warnings.warn( - "head_memory is being deprecated, use head_memory_requests and head_memory_limits" - ) - self.head_memory_requests = self.head_memory_limits = self.head_memory - def _validate_types(self): """Validate the types of all fields in the ClusterConfiguration dataclass.""" errors = [] diff --git a/src/codeflare_sdk/ray/cluster/test_cluster.py b/src/codeflare_sdk/ray/cluster/test_cluster.py index ce684607..9b19e224 100644 --- a/src/codeflare_sdk/ray/cluster/test_cluster.py +++ b/src/codeflare_sdk/ray/cluster/test_cluster.py @@ -758,5 +758,11 @@ def custom_side_effect(group, version, namespace, plural, **kwargs): # 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/cluster/test_config.py b/src/codeflare_sdk/ray/cluster/test_config.py index 6f002df1..e405bc5b 100644 --- a/src/codeflare_sdk/ray/cluster/test_config.py +++ b/src/codeflare_sdk/ray/cluster/test_config.py @@ -135,23 +135,6 @@ def test_config_creation_wrong_type(): assert len(str(error_info.value).splitlines()) == 4 -@pytest.mark.filterwarnings("ignore::UserWarning") -def test_cluster_config_deprecation_conversion(mocker): - config = ClusterConfiguration( - name="test", - head_cpus=3, - head_memory=16, - ) - assert config.head_cpu_requests == 3 - assert config.head_cpu_limits == 3 - assert config.head_memory_requests == "16G" - assert config.head_memory_limits == "16G" - assert config.worker_memory_requests == "2G" - assert config.worker_memory_limits == "2G" - assert config.worker_cpu_requests == 1 - assert config.worker_cpu_limits == 1 - - def test_gcs_fault_tolerance_config_validation(): config = ClusterConfiguration( name="test", 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..08c352ee --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/config.py @@ -0,0 +1,517 @@ +# 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 +from kubernetes.client import ( + V1ConfigMapVolumeSource, + V1KeyToPath, + V1Toleration, + V1Volume, + V1VolumeMount, + V1ObjectMeta, + V1Container, + V1ContainerPort, + V1Lifecycle, + V1ExecAction, + V1LifecycleHandler, + V1EnvVar, + V1PodTemplateSpec, + V1PodSpec, + V1ResourceRequirements, +) + +import logging +from ...common.utils.constants import CUDA_RUNTIME_IMAGE, RAY_VERSION + +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", +} + +# Default volume mounts for CA certificates +DEFAULT_VOLUME_MOUNTS = [ + V1VolumeMount( + mount_path="/etc/pki/tls/certs/odh-trusted-ca-bundle.crt", + name="odh-trusted-ca-cert", + sub_path="odh-trusted-ca-bundle.crt", + ), + V1VolumeMount( + mount_path="/etc/ssl/certs/odh-trusted-ca-bundle.crt", + name="odh-trusted-ca-cert", + sub_path="odh-trusted-ca-bundle.crt", + ), + V1VolumeMount( + mount_path="/etc/pki/tls/certs/odh-ca-bundle.crt", + name="odh-ca-cert", + sub_path="odh-ca-bundle.crt", + ), + V1VolumeMount( + mount_path="/etc/ssl/certs/odh-ca-bundle.crt", + name="odh-ca-cert", + sub_path="odh-ca-bundle.crt", + ), +] + +# Default volumes for CA certificates +DEFAULT_VOLUMES = [ + V1Volume( + name="odh-trusted-ca-cert", + config_map=V1ConfigMapVolumeSource( + name="odh-trusted-ca-bundle", + items=[V1KeyToPath(key="ca-bundle.crt", path="odh-trusted-ca-bundle.crt")], + optional=True, + ), + ), + V1Volume( + name="odh-ca-cert", + config_map=V1ConfigMapVolumeSource( + name="odh-trusted-ca-bundle", + items=[V1KeyToPath(key="odh-ca-bundle.crt", path="odh-ca-bundle.crt")], + optional=True, + ), + ), +] + + +@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. + local_queue: + The name of the queue to use for the cluster. + annotations: + A dictionary of annotations to apply to the cluster. + volumes: + A list of V1Volume objects to add to the Cluster + volume_mounts: + A list of V1VolumeMount objects to add to the Cluster + enable_gcs_ft: + A boolean indicating whether to enable GCS fault tolerance. + redis_address: + The address of the Redis server to use for GCS fault tolerance, required when enable_gcs_ft is True. + redis_password_secret: + Kubernetes secret reference containing Redis password. ex: {"name": "secret-name", "key": "password-key"} + external_storage_namespace: + The storage namespace to use for GCS fault tolerance. By default, KubeRay sets it to the UID of RayCluster. + """ + + 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() + ) + local_queue: Optional[str] = None + annotations: Dict[str, str] = field(default_factory=dict) + volumes: list[V1Volume] = field(default_factory=list) + volume_mounts: list[V1VolumeMount] = field(default_factory=list) + enable_gcs_ft: bool = False + redis_address: Optional[str] = None + redis_password_secret: Optional[Dict[str, str]] = None + external_storage_namespace: Optional[str] = None + + def __post_init__(self): + self.envs["RAY_USAGE_STATS_ENABLED"] = "0" + + if self.enable_gcs_ft: + if not self.redis_address: + raise ValueError( + "redis_address must be provided when enable_gcs_ft is True" + ) + + if self.redis_password_secret and not isinstance( + self.redis_password_secret, dict + ): + raise ValueError( + "redis_password_secret must be a dictionary with 'name' and 'key' fields" + ) + + if self.redis_password_secret and ( + "name" not in self.redis_password_secret + or "key" not in self.redis_password_secret + ): + raise ValueError( + "redis_password_secret must contain both 'name' and 'key' fields" + ) + + 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, + "headGroupSpec": self._build_head_group_spec(), + "workerGroupSpecs": [self._build_worker_group_spec(cluster_name)], + } + + # Add GCS fault tolerance if enabled + if self.enable_gcs_ft: + gcs_ft_options = self._build_gcs_ft_options() + ray_cluster_spec["gcsFaultToleranceOptions"] = gcs_ft_options + + 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", + "dashboard-port": "8265", + "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=self.image or CUDA_RUNTIME_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(), + ) + + # Add environment variables if specified + if hasattr(self, "envs") and self.envs: + container.env = self._build_env_vars() + + return container + + def _build_worker_container(self) -> V1Container: + """Build the worker container specification.""" + container = V1Container( + name="ray-worker", + image=self.image or CUDA_RUNTIME_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(), + ) + + # Add environment variables if specified + if hasattr(self, "envs") and self.envs: + container.env = self._build_env_vars() + + 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: + from kubernetes.client import V1LocalObjectReference + + 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 = DEFAULT_VOLUME_MOUNTS.copy() + + # 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 = DEFAULT_VOLUMES.copy() + + # 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 _build_gcs_ft_options(self) -> Dict[str, Any]: + """Build GCS fault tolerance options.""" + gcs_ft_options = {"redisAddress": self.redis_address} + + if ( + hasattr(self, "external_storage_namespace") + and self.external_storage_namespace + ): + gcs_ft_options["externalStorageNamespace"] = self.external_storage_namespace + + if hasattr(self, "redis_password_secret") and self.redis_password_secret: + gcs_ft_options["redisPassword"] = { + "valueFrom": { + "secretKeyRef": { + "name": self.redis_password_secret["name"], + "key": self.redis_password_secret["key"], + } + } + } + + return gcs_ft_options 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..a1577d91 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/rayjob.py @@ -0,0 +1,284 @@ +# 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. + +""" +RayJob client for submitting and managing Ray jobs using the kuberay python client. +""" + +import logging +from typing import Dict, Any, Optional, Tuple +from python_client.kuberay_job_api import RayjobApi + +from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + +from ...common.utils import get_current_namespace + +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[Dict[str, Any]] = None, + shutdown_after_job_finishes: Optional[bool] = None, + ttl_seconds_after_finished: int = 0, + active_deadline_seconds: Optional[int] = 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 (optional) + shutdown_after_job_finishes: Whether to shut down cluster after job finishes (optional) + 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) + + Note: + shutdown_after_job_finishes is automatically detected but can be overridden: + - 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 + self.runtime_env = runtime_env + self.ttl_seconds_after_finished = ttl_seconds_after_finished + self.active_deadline_seconds = active_deadline_seconds + + # Auto-set shutdown_after_job_finishes based on cluster_config presence + # If cluster_config is provided, we want to clean up the cluster after job finishes + # If using existing cluster, we don't want to shut it down + # User can override this behavior by explicitly setting shutdown_after_job_finishes + if shutdown_after_job_finishes is not None: + self.shutdown_after_job_finishes = shutdown_after_job_finishes + elif cluster_config is not None: + self.shutdown_after_job_finishes = True + else: + self.shutdown_after_job_finishes = False + + 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() + + logger.info(f"Initialized RayJob: {self.name} in namespace: {self.namespace}") + + def submit(self) -> str: + # Validate required parameters + if not self.entrypoint: + raise ValueError("entrypoint must be provided to submit a RayJob") + + # Build the RayJob custom resource + rayjob_cr = self._build_rayjob_cr() + + # Submit the job - KubeRay operator handles everything else + 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}") + if self.shutdown_after_job_finishes: + logger.info( + f"Cluster will be automatically cleaned up {self.ttl_seconds_after_finished}s after job completion" + ) + return self.name + else: + raise RuntimeError(f"Failed to submit RayJob {self.name}") + + def _build_rayjob_cr(self) -> Dict[str, Any]: + """ + Build the RayJob custom resource specification using native RayJob capabilities. + """ + # Basic RayJob custom resource structure + rayjob_cr = { + "apiVersion": "ray.io/v1", + "kind": "RayJob", + "metadata": { + "name": self.name, + "namespace": self.namespace, + }, + "spec": { + "entrypoint": self.entrypoint, + "shutdownAfterJobFinishes": self.shutdown_after_job_finishes, + "ttlSecondsAfterFinished": self.ttl_seconds_after_finished, + }, + } + + # Add active deadline if specified + if self.active_deadline_seconds: + rayjob_cr["spec"]["activeDeadlineSeconds"] = self.active_deadline_seconds + + # Add runtime environment if specified + if self.runtime_env: + rayjob_cr["spec"]["runtimeEnvYAML"] = str(self.runtime_env) + + # 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 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/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_config.py b/src/codeflare_sdk/ray/rayjobs/test_config.py new file mode 100644 index 00000000..80736295 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/test_config.py @@ -0,0 +1,133 @@ +""" +Tests for the simplified ManagedClusterConfig accelerator_configs behavior. +""" + +import pytest +from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig, DEFAULT_ACCELERATORS + + +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_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 diff --git a/src/codeflare_sdk/ray/rayjobs/test_pretty_print.py b/src/codeflare_sdk/ray/rayjobs/test_pretty_print.py new file mode 100644 index 00000000..3bbe8bee --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/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_rayjob.py b/src/codeflare_sdk/ray/rayjobs/test_rayjob.py new file mode 100644 index 00000000..1ecd4b48 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/test_rayjob.py @@ -0,0 +1,994 @@ +# 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 +from unittest.mock import MagicMock, patch +from codeflare_sdk.common.utils.constants import CUDA_RUNTIME_IMAGE, RAY_VERSION + +from codeflare_sdk.ray.rayjobs.rayjob import RayJob +from codeflare_sdk.ray.cluster.config import ClusterConfiguration + + +def test_rayjob_submit_success(mocker): + """Test successful RayJob submission.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + mock_api_instance = MagicMock() + mock_api_class.return_value = mock_api_instance + + # Configure the mock to return success when submit is called + mock_api_instance.submit.return_value = {"metadata": {"name": "test-rayjob"}} + + # Create RayJob instance + rayjob = RayJob( + job_name="test-rayjob", + cluster_name="test-ray-cluster", + namespace="test-namespace", + entrypoint="python -c 'print(\"hello world\")'", + runtime_env={"pip": ["requests"]}, + ) + + # Submit the job + job_id = rayjob.submit() + + # Assertions + assert job_id == "test-rayjob" + + # Verify the API was called with correct parameters + mock_api_instance.submit_job.assert_called_once() + call_args = mock_api_instance.submit_job.call_args + + # Check the namespace parameter + assert call_args.kwargs["k8s_namespace"] == "test-namespace" + + # Check the job custom resource + 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': ['requests']}" + + +def test_rayjob_submit_failure(mocker): + """Test RayJob submission failure.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + mock_api_instance = MagicMock() + mock_api_class.return_value = mock_api_instance + + # Configure the mock to return failure (False/None) when submit_job is called + mock_api_instance.submit_job.return_value = None + + # Create a RayJob instance + rayjob = RayJob( + job_name="test-rayjob", + cluster_name="test-ray-cluster", + namespace="default", + entrypoint="python script.py", + runtime_env={"pip": ["numpy"]}, + ) + + # Test that RuntimeError is raised on failure + with pytest.raises(RuntimeError, match="Failed to submit RayJob test-rayjob"): + rayjob.submit() + + +def test_rayjob_init_validation_both_provided(mocker): + """Test that providing both cluster_name and cluster_config raises error.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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 script.py", + ) + + +def test_rayjob_init_validation_neither_provided(mocker): + """Test that providing neither cluster_name nor cluster_config raises error.""" + # Mock kubernetes config loading (though this should fail before reaching it) + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely (though this should fail before reaching it) + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + with pytest.raises( + ValueError, + match="❌ Configuration Error: You must provide either 'cluster_name'", + ): + RayJob(job_name="test-job", entrypoint="python script.py") + + +def test_rayjob_init_with_cluster_config(mocker): + """Test RayJob initialization with cluster configuration for auto-creation.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + cluster_config = ClusterConfiguration( + name="auto-cluster", namespace="test-namespace", num_workers=2 + ) + + rayjob = RayJob( + job_name="test-job", + cluster_config=cluster_config, + entrypoint="python script.py", + 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(mocker): + """Test that cluster names are generated when config has empty name.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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 script.py", + namespace="test-namespace", + ) + + assert rayjob.cluster_name == "my-job-cluster" + + +def test_rayjob_cluster_config_namespace_none(mocker): + """Test that cluster config namespace is set when None.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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 script.py", + ) + + assert rayjob.namespace == "job-namespace" + + +def test_rayjob_with_active_deadline_seconds(mocker): + """Test RayJob CR generation with active deadline seconds.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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(mocker): + """Test _build_ray_cluster_spec raises error when no cluster config.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + # Create RayJob with cluster_name (no cluster_config) + rayjob = RayJob( + job_name="test-job", + cluster_name="existing-cluster", + entrypoint="python script.py", + namespace="test-namespace", + ) + + # Since we removed _build_ray_cluster_spec method, this test is no longer applicable + # The method is now called internally by _build_rayjob_cr when needed + # We can test this by calling _build_rayjob_cr instead + rayjob_cr = rayjob._build_rayjob_cr() + + # Should use clusterSelector for existing cluster + assert rayjob_cr["spec"]["clusterSelector"]["ray.io/cluster"] == "existing-cluster" + assert "rayClusterSpec" not in rayjob_cr["spec"] + + +def test_build_ray_cluster_spec(mocker): + """Test _build_ray_cluster_spec method.""" + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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}], + }, + } + # Use ManagedClusterConfig which has the build_ray_cluster_spec method + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig(num_workers=2) + + # Mock the method that will be called + 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 script.py", + namespace="test-namespace", + ) + + # Test the integration through _build_rayjob_cr + rayjob_cr = rayjob._build_rayjob_cr() + + # Should have rayClusterSpec + assert "rayClusterSpec" in rayjob_cr["spec"] + + # Verify build_ray_cluster_spec was called on the cluster config + cluster_config.build_ray_cluster_spec.assert_called_once_with( + cluster_name="test-job-cluster" + ) + + +def test_build_rayjob_cr_with_existing_cluster(mocker): + """Test _build_rayjob_cr method with existing cluster.""" + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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() + + # Check basic structure + assert rayjob_cr["apiVersion"] == "ray.io/v1" + assert rayjob_cr["kind"] == "RayJob" + assert rayjob_cr["metadata"]["name"] == "test-job" + + # Check lifecycle parameters + spec = rayjob_cr["spec"] + assert spec["entrypoint"] == "python main.py" + # shutdownAfterJobFinishes should be False when using existing cluster (auto-set) + assert spec["shutdownAfterJobFinishes"] is False + assert spec["ttlSecondsAfterFinished"] == 300 + + # Should use clusterSelector for existing cluster + assert spec["clusterSelector"]["ray.io/cluster"] == "existing-cluster" + assert "rayClusterSpec" not in spec + + +def test_build_rayjob_cr_with_auto_cluster(mocker): + """Test _build_rayjob_cr method with auto-created cluster.""" + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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}], + }, + } + # Use ManagedClusterConfig and mock its build_ray_cluster_spec method + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig(num_workers=2) + + # Mock the method that will be called + 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() + + # Should use rayClusterSpec for auto-created cluster + assert rayjob_cr["spec"]["rayClusterSpec"] == mock_ray_cluster["spec"] + assert "clusterSelector" not in rayjob_cr["spec"] + + +def test_submit_validation_no_entrypoint(mocker): + """Test that submit() raises error when entrypoint is None.""" + mocker.patch("kubernetes.config.load_kube_config") + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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): + """Test successful submission with auto-created cluster.""" + mocker.patch("kubernetes.config.load_kube_config") + + mock_ray_cluster = { + "apiVersion": "ray.io/v1", + "kind": "RayCluster", + "spec": { + "rayVersion": RAY_VERSION, + "headGroupSpec": {"replicas": 1}, + "workerGroupSpecs": [{"replicas": 1}], + }, + } + # Mock the RayjobApi + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + mock_api_instance = MagicMock() + mock_api_class.return_value = mock_api_instance + mock_api_instance.submit_job.return_value = True + + # Use ManagedClusterConfig and mock its build_ray_cluster_spec method + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig(num_workers=1) + + # Mock the method that will be called + 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 script.py", + namespace="test-namespace", + ) + + result = rayjob.submit() + + assert result == "test-job" + + # Verify the correct RayJob CR was submitted + 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(mocker): + """Test successful namespace auto-detection.""" + mocker.patch( + "codeflare_sdk.ray.rayjobs.rayjob.get_current_namespace", + return_value="detected-ns", + ) + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + rayjob = RayJob( + job_name="test-job", entrypoint="python script.py", cluster_name="test-cluster" + ) + + assert rayjob.namespace == "detected-ns" + + +def test_namespace_auto_detection_fallback(mocker): + """Test that namespace auto-detection failure raises an error.""" + mocker.patch( + "codeflare_sdk.ray.rayjobs.rayjob.get_current_namespace", return_value=None + ) + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + with pytest.raises(ValueError, match="Could not auto-detect Kubernetes namespace"): + RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_name="test-cluster", + ) + + +def test_namespace_explicit_override(mocker): + """Test that explicit namespace overrides auto-detection.""" + mocker.patch( + "codeflare_sdk.ray.rayjobs.rayjob.get_current_namespace", + return_value="detected-ns", + ) + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_name="test-cluster", + namespace="explicit-ns", + ) + + assert rayjob.namespace == "explicit-ns" + + +def test_shutdown_behavior_with_cluster_config(mocker): + """Test that shutdown_after_job_finishes is True when cluster_config is provided.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig() + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_config=cluster_config, + namespace="test-namespace", + ) + + assert rayjob.shutdown_after_job_finishes is True + + +def test_shutdown_behavior_with_existing_cluster(mocker): + """Test that shutdown_after_job_finishes is False when using existing cluster.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_name="existing-cluster", + namespace="test-namespace", + ) + + assert rayjob.shutdown_after_job_finishes is False + + +def test_rayjob_with_rayjob_cluster_config(mocker): + """Test RayJob with the new ManagedClusterConfig.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig( + num_workers=2, + head_cpu_requests="500m", + head_memory_requests="512Mi", + ) + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + 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(mocker): + """Test validation of ManagedClusterConfig parameters.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + # Test with minimal valid config + cluster_config = ManagedClusterConfig() + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_config=cluster_config, + namespace="test-namespace", + ) + + assert rayjob._cluster_config is not None + + +def test_rayjob_missing_entrypoint_validation(mocker): + """Test that RayJob requires entrypoint for submission.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + # Should raise an error during construction + with pytest.raises( + TypeError, match="missing 1 required positional argument: 'entrypoint'" + ): + RayJob( + job_name="test-job", + cluster_name="test-cluster", + # No entrypoint provided + ) + + +def test_build_ray_cluster_spec_integration(mocker): + """Test integration with the new build_ray_cluster_spec method.""" + # Mock kubernetes config loading + mocker.patch("kubernetes.config.load_kube_config") + + # Mock the RayjobApi class entirely + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig() + + # Mock the build_ray_cluster_spec method on the cluster config + 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 script.py", + cluster_config=cluster_config, + namespace="test-namespace", + ) + + # Build the RayJob CR + rayjob_cr = rayjob._build_rayjob_cr() + + # Verify the method was called correctly + cluster_config.build_ray_cluster_spec.assert_called_once_with( + cluster_name="test-job-cluster" + ) + + # Verify the spec is included in the RayJob CR + assert "rayClusterSpec" in rayjob_cr["spec"] + assert rayjob_cr["spec"]["rayClusterSpec"] == mock_spec + + +def test_rayjob_with_runtime_env(mocker): + """Test RayJob with runtime environment configuration.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + runtime_env = {"pip": ["numpy", "pandas"]} + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_name="test-cluster", + runtime_env=runtime_env, + namespace="test-namespace", + ) + + assert rayjob.runtime_env == runtime_env + + # Verify runtime env is included in the CR + rayjob_cr = rayjob._build_rayjob_cr() + assert rayjob_cr["spec"]["runtimeEnvYAML"] == str(runtime_env) + + +def test_rayjob_with_active_deadline_and_ttl(mocker): + """Test RayJob with both active deadline and TTL settings.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + 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 + + # Verify both are included in the CR + 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(mocker): + """Test cluster name generation when using cluster_config.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig() + + rayjob = RayJob( + job_name="my-job", + entrypoint="python script.py", + cluster_config=cluster_config, + namespace="test-namespace", # Explicitly specify namespace + ) + + assert rayjob.cluster_name == "my-job-cluster" + # Note: cluster_config.name is not set in RayJob (it's only for resource config) + # The cluster name is generated independently for the RayJob + + +def test_rayjob_namespace_propagation_to_cluster_config(mocker): + """Test that job namespace is propagated to cluster config when None.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + from codeflare_sdk.ray.rayjobs.rayjob import get_current_namespace + + mocker.patch( + "codeflare_sdk.ray.rayjobs.rayjob.get_current_namespace", + return_value="detected-ns", + ) + + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig() + + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_config=cluster_config, + ) + + assert rayjob.namespace == "detected-ns" + + +def test_rayjob_error_handling_invalid_cluster_config(mocker): + """Test error handling with invalid cluster configuration.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + with pytest.raises(ValueError): + RayJob( + job_name="test-job", + entrypoint="python script.py", + ) + + +def test_rayjob_constructor_parameter_validation(mocker): + """Test constructor parameter validation.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + # Test with valid parameters + rayjob = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_name="test-cluster", + namespace="test-ns", + runtime_env={"pip": ["numpy"]}, + ttl_seconds_after_finished=300, + active_deadline_seconds=600, + ) + + assert rayjob.name == "test-job" + assert rayjob.entrypoint == "python script.py" + assert rayjob.cluster_name == "test-cluster" + assert rayjob.namespace == "test-ns" + assert rayjob.runtime_env == {"pip": ["numpy"]} + assert rayjob.ttl_seconds_after_finished == 300 + assert rayjob.active_deadline_seconds == 600 + + +def test_build_ray_cluster_spec_function(mocker): + """Test the build_ray_cluster_spec method directly.""" + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + # Create a test cluster config + cluster_config = ManagedClusterConfig( + num_workers=2, + head_cpu_requests="500m", + head_memory_requests="512Mi", + worker_cpu_requests="250m", + worker_memory_requests="256Mi", + ) + + # Build the spec using the method on the cluster config + spec = cluster_config.build_ray_cluster_spec("test-cluster") + + # Verify basic structure + assert "rayVersion" in spec + assert "enableInTreeAutoscaling" in spec + assert "headGroupSpec" in spec + assert "workerGroupSpecs" in spec + + # Verify head group 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 + + # Verify worker group 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(mocker): + """Test build_ray_cluster_spec with GPU accelerators.""" + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + # Create a test cluster config with GPU accelerators + cluster_config = ManagedClusterConfig( + head_accelerators={"nvidia.com/gpu": 1}, + worker_accelerators={"nvidia.com/gpu": 2}, + ) + + # Build the spec using the method on the cluster config + spec = cluster_config.build_ray_cluster_spec("test-cluster") + + # Verify head group has GPU parameters + head_spec = spec["headGroupSpec"] + head_params = head_spec["rayStartParams"] + assert "num-gpus" in head_params + assert head_params["num-gpus"] == "1" + + # Verify worker group has GPU parameters + 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(mocker): + """Test build_ray_cluster_spec with custom volumes and volume mounts.""" + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + from kubernetes.client import V1Volume, V1VolumeMount + + # Create custom volumes and volume mounts + custom_volume = V1Volume(name="custom-data", empty_dir={}) + custom_volume_mount = V1VolumeMount(name="custom-data", mount_path="/data") + + # Create a test cluster config with custom volumes + cluster_config = ManagedClusterConfig( + volumes=[custom_volume], + volume_mounts=[custom_volume_mount], + ) + + # Build the spec using the method on the cluster config + spec = cluster_config.build_ray_cluster_spec("test-cluster") + + # Verify custom volumes are included + head_spec = spec["headGroupSpec"] + head_pod_spec = head_spec["template"].spec # Access the spec attribute + # Note: We can't easily check DEFAULT_VOLUMES length since they're now part of the class + assert len(head_pod_spec.volumes) > 0 + + # Verify custom volume mounts are included + head_container = head_pod_spec.containers[0] # Access the containers attribute + # Note: We can't easily check DEFAULT_VOLUME_MOUNTS length since they're now part of the class + assert len(head_container.volume_mounts) > 0 + + +def test_build_ray_cluster_spec_with_environment_variables(mocker): + """Test build_ray_cluster_spec with environment variables.""" + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + # Create a test cluster config 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") + + # Verify environment variables are included in head container + 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" + + # Verify environment variables are included in worker container + 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(mocker): + """Test build_ray_cluster_spec with tolerations.""" + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + from kubernetes.client import V1Toleration + + # Create test 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" + ) + + # Create a test cluster config with tolerations + cluster_config = ManagedClusterConfig( + head_tolerations=[head_toleration], + worker_tolerations=[worker_toleration], + ) + + spec = cluster_config.build_ray_cluster_spec("test-cluster") + + # Verify head tolerations + head_spec = spec["headGroupSpec"] + head_pod_spec = head_spec["template"].spec # Access the spec attribute + 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" + + # Verify worker tolerations + worker_specs = spec["workerGroupSpecs"] + worker_spec = worker_specs[0] + worker_pod_spec = worker_spec["template"].spec # Access the spec attribute + 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(mocker): + """Test build_ray_cluster_spec with image pull secrets.""" + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + # Create a test cluster config with image pull secrets + cluster_config = ManagedClusterConfig( + image_pull_secrets=["my-registry-secret", "another-secret"] + ) + + spec = cluster_config.build_ray_cluster_spec("test-cluster") + + # Verify image pull secrets are included in head pod + head_spec = spec["headGroupSpec"] + head_pod_spec = head_spec["template"].spec # Access the spec attribute + 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" + + # Verify image pull secrets are included in worker pod + 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_rayjob_user_override_shutdown_behavior(mocker): + """Test that user can override the auto-detected shutdown behavior.""" + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + # Test 1: User overrides shutdown to True even when using existing cluster + rayjob_existing_override = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_name="existing-cluster", + shutdown_after_job_finishes=True, # User override + namespace="test-namespace", # Explicitly specify namespace + ) + + assert rayjob_existing_override.shutdown_after_job_finishes is True + + # Test 2: User overrides shutdown to False even when creating new cluster + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + cluster_config = ManagedClusterConfig() + + rayjob_new_override = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_config=cluster_config, + shutdown_after_job_finishes=False, # User override + namespace="test-namespace", # Explicitly specify namespace + ) + + assert rayjob_new_override.shutdown_after_job_finishes is False + + # Test 3: User override takes precedence over auto-detection + rayjob_override_priority = RayJob( + job_name="test-job", + entrypoint="python script.py", + cluster_config=cluster_config, + shutdown_after_job_finishes=True, # Should override auto-detection + namespace="test-namespace", # Explicitly specify namespace + ) + + assert rayjob_override_priority.shutdown_after_job_finishes is True + + +def test_build_ray_cluster_spec_with_gcs_ft(mocker): + """Test build_ray_cluster_spec with GCS fault tolerance enabled.""" + from codeflare_sdk.ray.rayjobs.config import ManagedClusterConfig + + # Create a test cluster config with GCS FT enabled + cluster_config = ManagedClusterConfig( + enable_gcs_ft=True, + redis_address="redis://redis-service:6379", + external_storage_namespace="storage-ns", + ) + + # Build the spec using the method on the cluster config + spec = cluster_config.build_ray_cluster_spec("test-cluster") + + # Verify GCS fault tolerance options + assert "gcsFaultToleranceOptions" in spec + gcs_ft = spec["gcsFaultToleranceOptions"] + assert gcs_ft["redisAddress"] == "redis://redis-service:6379" + assert gcs_ft["externalStorageNamespace"] == "storage-ns" diff --git a/src/codeflare_sdk/ray/rayjobs/test_status.py b/src/codeflare_sdk/ray/rayjobs/test_status.py new file mode 100644 index 00000000..6d2ce946 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/test_status.py @@ -0,0 +1,290 @@ +# 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 the RayjobApi to avoid actual Kubernetes calls + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + 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. + """ + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + 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. + """ + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + 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 the RayjobApi constructor to avoid authentication issues + mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + + 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. + """ + # Mock the RayjobApi and pretty_print + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + 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. + """ + # Mock the RayjobApi and pretty_print + mock_api_class = mocker.patch("codeflare_sdk.ray.rayjobs.rayjob.RayjobApi") + 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 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..3d710bfc 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: @@ -38,6 +39,7 @@ spec: rayStartParams: block: 'true' dashboard-host: 0.0.0.0 + dashboard-port: '8265' num-gpus: '1' resources: '"{\"TPU\": 2}"' serviceType: ClusterIP diff --git a/tests/test_cluster_yamls/kueue/aw_kueue.yaml b/tests/test_cluster_yamls/kueue/aw_kueue.yaml index f5f16406..7f72d25b 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: @@ -32,6 +33,7 @@ spec: rayStartParams: block: 'true' dashboard-host: 0.0.0.0 + dashboard-port: '8265' num-gpus: '0' resources: '"{}"' serviceType: ClusterIP diff --git a/tests/test_cluster_yamls/kueue/ray_cluster_kueue.yaml b/tests/test_cluster_yamls/kueue/ray_cluster_kueue.yaml index d6db4f4a..7a5a62ba 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: @@ -32,6 +33,7 @@ spec: rayStartParams: block: 'true' dashboard-host: 0.0.0.0 + dashboard-port: '8265' num-gpus: '0' resources: '"{}"' serviceType: ClusterIP diff --git a/tests/test_cluster_yamls/ray/default-appwrapper.yaml b/tests/test_cluster_yamls/ray/default-appwrapper.yaml index 27828163..734f3d33 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: @@ -30,6 +31,7 @@ spec: rayStartParams: block: 'true' dashboard-host: 0.0.0.0 + dashboard-port: '8265' num-gpus: '0' resources: '"{}"' serviceType: ClusterIP diff --git a/tests/test_cluster_yamls/ray/default-ray-cluster.yaml b/tests/test_cluster_yamls/ray/default-ray-cluster.yaml index d2e6b05a..cc5f2ada 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: @@ -22,6 +23,7 @@ spec: rayStartParams: block: 'true' dashboard-host: 0.0.0.0 + dashboard-port: '8265' num-gpus: '0' resources: '"{}"' serviceType: ClusterIP 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..213a082a 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: @@ -29,6 +30,7 @@ spec: rayStartParams: block: 'true' dashboard-host: 0.0.0.0 + dashboard-port: '8265' num-gpus: '1' resources: '"{\"TPU\": 2}"' serviceType: ClusterIP