From cfca96aa55436532183f539af45c2af4d0a9707f Mon Sep 17 00:00:00 2001 From: Laura Fitzgerald Date: Thu, 22 May 2025 11:05:23 +0100 Subject: [PATCH 1/7] define a ray job class --- src/codeflare_sdk/ray/job/job.py | 116 +++++++++++++++++++++++++++++++ 1 file changed, 116 insertions(+) create mode 100644 src/codeflare_sdk/ray/job/job.py diff --git a/src/codeflare_sdk/ray/job/job.py b/src/codeflare_sdk/ray/job/job.py new file mode 100644 index 00000000..f45863c6 --- /dev/null +++ b/src/codeflare_sdk/ray/job/job.py @@ -0,0 +1,116 @@ +from dataclasses import dataclass, field +from typing import Dict, Any, Optional, Union, List +from enum import Enum + +class RayJobStatus(str, Enum): + """Status of a RayJob""" + PENDING = "PENDING" + RUNNING = "RUNNING" + STOPPED = "STOPPED" + SUCCEEDED = "SUCCEEDED" + FAILED = "FAILED" + +@dataclass +class RayJobSpec: + """Specification for a RayJob Custom Resource""" + + # Required fields + entrypoint: str + """The command to execute for this job (e.g., "python script.py")""" + + # Optional fields + submission_id: Optional[str] = None + """Unique ID for the job submission. If not provided, one will be generated.""" + + runtime_env: Optional[Dict[str, Any]] = None + """Runtime environment configuration for the job, including: + - working_dir: Directory containing files that your job will run in + - pip: List of pip packages to install + - conda: Conda environment specification + - env_vars: Environment variables to set + - py_modules: Python modules to include + """ + + metadata: Optional[Dict[str, str]] = None + """Arbitrary metadata to store with the job""" + + entrypoint_num_cpus: Optional[Union[int, float]] = None + """Number of CPU cores to reserve for the entrypoint command""" + + entrypoint_num_gpus: Optional[Union[int, float]] = None + """Number of GPUs to reserve for the entrypoint command""" + + entrypoint_memory: Optional[int] = None + """Amount of memory to reserve for the entrypoint command""" + + entrypoint_resources: Optional[Dict[str, float]] = None + """Custom resources to reserve for the entrypoint command""" + + cluster_name: Optional[str] = None + """Name of the RayCluster to run this job on""" + + cluster_namespace: Optional[str] = None + """Namespace of the RayCluster to run this job on""" + + # Status fields (managed by the controller) + status: RayJobStatus = field(default=RayJobStatus.PENDING) + """Current status of the job""" + + message: Optional[str] = None + """Detailed status message""" + + start_time: Optional[str] = None + """Time when the job started""" + + end_time: Optional[str] = None + """Time when the job ended""" + + driver_info: Optional[Dict[str, str]] = None + """Information about the job driver, including: + - id: Driver ID + - node_ip_address: IP address of the node running the driver + - pid: Process ID of the driver + """ + +@dataclass +class RayJob: + """RayJob Custom Resource Definition""" + + api_version: str = "ray.io/v1" + kind: str = "RayJob" + + metadata: Dict[str, Any] + """Kubernetes metadata for the job""" + + spec: RayJobSpec + """Job specification""" + + status: Optional[Dict[str, Any]] = None + """Status of the job (managed by the controller)""" + + def to_dict(self) -> Dict[str, Any]: + """Convert the RayJob to a dictionary suitable for Kubernetes API""" + return { + "apiVersion": self.api_version, + "kind": self.kind, + "metadata": self.metadata, + "spec": { + "entrypoint": self.spec.entrypoint, + "submission_id": self.spec.submission_id, + "runtime_env": self.spec.runtime_env, + "metadata": self.spec.metadata, + "entrypoint_num_cpus": self.spec.entrypoint_num_cpus, + "entrypoint_num_gpus": self.spec.entrypoint_num_gpus, + "entrypoint_memory": self.spec.entrypoint_memory, + "entrypoint_resources": self.spec.entrypoint_resources, + "cluster_name": self.spec.cluster_name, + "cluster_namespace": self.spec.cluster_namespace, + }, + "status": { + "status": self.spec.status, + "message": self.spec.message, + "start_time": self.spec.start_time, + "end_time": self.spec.end_time, + "driver_info": self.spec.driver_info, + } if self.status is None else self.status + } From 353606e54458d42ca3bef2dddb31ec49da5bee82 Mon Sep 17 00:00:00 2001 From: Laura Fitzgerald Date: Thu, 22 May 2025 11:12:47 +0100 Subject: [PATCH 2/7] apply the job to a k8s cluster --- src/codeflare_sdk/ray/job/job.py | 51 ++++++++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) diff --git a/src/codeflare_sdk/ray/job/job.py b/src/codeflare_sdk/ray/job/job.py index f45863c6..f7a4aaba 100644 --- a/src/codeflare_sdk/ray/job/job.py +++ b/src/codeflare_sdk/ray/job/job.py @@ -114,3 +114,54 @@ def to_dict(self) -> Dict[str, Any]: "driver_info": self.spec.driver_info, } if self.status is None else self.status } + + def apply(self, force=False): + """ + Applies the RayJob using server-side apply. + If 'force' is set to True, conflicts will be forced. + + Args: + force (bool): If True, force conflicts during server-side apply. + """ + from kubernetes import client + from kubernetes.dynamic import DynamicClient + from ...common.kubernetes_cluster.auth import get_api_client, config_check + from ...common import _kube_api_error_handling + + CF_SDK_FIELD_MANAGER = "codeflare-sdk" + + try: + # Check Kubernetes configuration + config_check() + + # Get the dynamic client + crds = DynamicClient(get_api_client()).resources + + # Get the RayJob API instance + api_version = "ray.io/v1" + api_instance = crds.get(api_version=api_version, kind="RayJob") + + # Get namespace from metadata + namespace = self.metadata.get("namespace", "default") + name = self.metadata.get("name") + + # Convert job to dictionary + body = self.to_dict() + + # Apply the job using server-side apply + api_instance.server_side_apply( + field_manager=CF_SDK_FIELD_MANAGER, + group="ray.io", + version="v1", + namespace=namespace, + plural="rayjobs", + body=body, + force_conflicts=force, + ) + + print(f"RayJob: '{name}' has successfully been applied") + + except AttributeError as e: + raise RuntimeError(f"Failed to initialize DynamicClient: {e}") + except Exception as e: + return _kube_api_error_handling(e) From 5d1714df62a580be2f474aa3b56e0fe95a169518 Mon Sep 17 00:00:00 2001 From: kryanbeane Date: Thu, 22 May 2025 11:54:28 +0100 Subject: [PATCH 3/7] test ray job poc --- src/codeflare_sdk/ray/cluster/cluster.py | 248 ++++++++++++++++++++++- src/codeflare_sdk/ray/job/job.py | 6 +- 2 files changed, 248 insertions(+), 6 deletions(-) diff --git a/src/codeflare_sdk/ray/cluster/cluster.py b/src/codeflare_sdk/ray/cluster/cluster.py index 86ed7c4d..c68c17ed 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 ..job.job import RayJobSpec 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" @@ -604,6 +609,238 @@ def _component_resources_down( yamls = yaml.safe_load_all(self.resource_yaml) _delete_resources(yamls, namespace, api_instance, cluster_name) + @staticmethod + def run_job_with_managed_cluster( + cluster_config: ClusterConfiguration, + job_config: RayJobSpec, + job_cr_name: Optional[str] = None, + submission_mode: str = "K8sJobMode", + shutdown_after_job_finishes: bool = True, + ttl_seconds_after_finished: Optional[int] = None, + suspend_rayjob_creation: bool = False, + wait_for_completion: bool = True, + job_timeout_seconds: Optional[int] = 3600, + job_polling_interval_seconds: int = 10, + ): + """ + Manages the lifecycle of a Ray cluster and a job by creating a RayJob custom resource. + KubeRay operator will then create/delete the RayCluster based on the RayJob definition. + + This method will: + 1. Generate a RayCluster specification from the provided 'cluster_config'. + 2. Construct a RayJob custom resource definition using 'job_config' and embedding the RayCluster spec. + 3. Create the RayJob resource in Kubernetes. + 4. Optionally, wait for the RayJob to complete or timeout, monitoring its status. + 5. The RayCluster lifecycle (creation and deletion) is managed by KubeRay + based on the RayJob's 'shutdownAfterJobFinishes' field. + + Args: + cluster_config: Configuration for the Ray cluster to be created by RayJob. + job_config: RayJobSpec object containing job-specific details like entrypoint, runtime_env, etc. + job_cr_name: Name for the RayJob Custom Resource. If None, a unique name is generated. + submission_mode: How the job is submitted ("K8sJobMode" or "RayClientMode"). + shutdown_after_job_finishes: If True, RayCluster is deleted after job finishes. + ttl_seconds_after_finished: TTL for RayJob after it's finished. + suspend_rayjob_creation: If True, creates the RayJob in a suspended state. + wait_for_completion: If True, waits for the job to finish. + job_timeout_seconds: Timeout for waiting for job completion. + job_polling_interval_seconds: Interval for polling job status. + + Returns: + A dictionary containing details like RayJob CR name, reported job submission ID, + final job status, dashboard URL, and the RayCluster name. + + Raises: + TimeoutError: If the job doesn't complete within the specified timeout. + ApiException: For Kubernetes API errors. + ValueError: For configuration issues. + """ + config_check() + k8s_co_api = k8s_client.CustomObjectsApi(get_api_client()) + namespace = cluster_config.namespace + + if not job_config.entrypoint: + raise ValueError("job_config.entrypoint must be specified.") + + # Warn if Pydantic V1/V2 specific fields in RayJobSpec are set, as they are not used for RayJob CR. + if job_config.entrypoint_num_cpus is not None or \ + job_config.entrypoint_num_gpus is not None or \ + job_config.entrypoint_memory is not None: + warnings.warn( + "RayJobSpec fields 'entrypoint_num_cpus', 'entrypoint_num_gpus', 'entrypoint_memory' " + "are not directly used when creating a RayJob CR. They are primarily for the Ray Job Submission Client. " + "Resource requests for the job driver pod should be configured in the RayCluster head node spec via ClusterConfiguration.", + UserWarning + ) + + # Generate rayClusterSpec from ClusterConfiguration + temp_config_for_spec = copy.deepcopy(cluster_config) + temp_config_for_spec.appwrapper = False + + with warnings.catch_warnings(): + warnings.simplefilter("ignore", UserWarning) + dummy_cluster_for_spec = Cluster(temp_config_for_spec) + + ray_cluster_cr_dict = dummy_cluster_for_spec.resource_yaml + if not isinstance(ray_cluster_cr_dict, dict) or "spec" not in ray_cluster_cr_dict: + raise ValueError( + "Failed to generate RayCluster CR dictionary from ClusterConfiguration. " + f"Got: {type(ray_cluster_cr_dict)}" + ) + ray_cluster_spec = ray_cluster_cr_dict["spec"] + + # Prepare RayJob CR + actual_job_cr_name = job_cr_name or f"rayjob-{uuid.uuid4().hex[:10]}" + + runtime_env_yaml_str = "" + if job_config.runtime_env: + try: + runtime_env_yaml_str = yaml.dump(job_config.runtime_env) + except yaml.YAMLError as e: + raise ValueError(f"Invalid job_config.runtime_env, failed to dump to YAML: {e}") + + ray_job_cr_spec = { + "entrypoint": job_config.entrypoint, + "shutdownAfterJobFinishes": shutdown_after_job_finishes, + "rayClusterSpec": ray_cluster_spec, + "submissionMode": submission_mode, + } + + if runtime_env_yaml_str: + ray_job_cr_spec["runtimeEnvYAML"] = runtime_env_yaml_str + if job_config.submission_id: + ray_job_cr_spec["jobId"] = job_config.submission_id + if job_config.metadata: + ray_job_cr_spec["metadata"] = job_config.metadata + if ttl_seconds_after_finished is not None: + ray_job_cr_spec["ttlSecondsAfterFinished"] = ttl_seconds_after_finished + if suspend_rayjob_creation: + ray_job_cr_spec["suspend"] = True + if job_config.entrypoint_resources: + ray_job_cr_spec["entrypointResources"] = job_config.entrypoint_resources + + ray_job_cr = { + "apiVersion": "ray.io/v1", + "kind": "RayJob", + "metadata": { + "name": actual_job_cr_name, + "namespace": namespace, + }, + "spec": ray_job_cr_spec, + } + + returned_job_submission_id = None + final_job_status = "UNKNOWN" + dashboard_url = None + ray_cluster_name_actual = None + + try: + print(f"Submitting RayJob '{actual_job_cr_name}' to namespace '{namespace}'...") + k8s_co_api.create_namespaced_custom_object( + group="ray.io", + version="v1", + namespace=namespace, + plural="rayjobs", + body=ray_job_cr, + ) + print(f"RayJob '{actual_job_cr_name}' created successfully.") + + if wait_for_completion: + print(f"Waiting for RayJob '{actual_job_cr_name}' to complete...") + start_time = time.time() + while True: + try: + ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( + group="ray.io", + version="v1", + namespace=namespace, + plural="rayjobs", + name=actual_job_cr_name, + ) + except ApiException as e: + if e.status == 404: + print(f"RayJob '{actual_job_cr_name}' status not found yet, retrying...") + time.sleep(job_polling_interval_seconds) + continue + raise + + status_field = ray_job_status_cr.get("status", {}) + job_deployment_status = status_field.get("jobDeploymentStatus", "UNKNOWN") + current_job_status = status_field.get("jobStatus", "PENDING") + + dashboard_url = status_field.get("dashboardURL", dashboard_url) + ray_cluster_name_actual = status_field.get("rayClusterName", ray_cluster_name_actual) + returned_job_submission_id = status_field.get("jobId", job_config.submission_id) + + final_job_status = current_job_status + print( + f"RayJob '{actual_job_cr_name}' status: JobDeployment='{job_deployment_status}', Job='{current_job_status}'" + ) + + if current_job_status in ["SUCCEEDED", "FAILED", "STOPPED"]: + break + + if job_timeout_seconds and (time.time() - start_time) > job_timeout_seconds: + try: + ray_job_status_cr_final = k8s_co_api.get_namespaced_custom_object_status( + group="ray.io", version="v1", namespace=namespace, plural="rayjobs", name=actual_job_cr_name + ) + status_field_final = ray_job_status_cr_final.get("status", {}) + final_job_status = status_field_final.get("jobStatus", final_job_status) + returned_job_submission_id = status_field_final.get("jobId", returned_job_submission_id) + dashboard_url = status_field_final.get("dashboardURL", dashboard_url) + ray_cluster_name_actual = status_field_final.get("rayClusterName", ray_cluster_name_actual) + except Exception: + pass + raise TimeoutError( + f"RayJob '{actual_job_cr_name}' timed out after {job_timeout_seconds} seconds. Last status: {final_job_status}" + ) + + time.sleep(job_polling_interval_seconds) + + print(f"RayJob '{actual_job_cr_name}' finished with status: {final_job_status}") + else: + try: + ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( + group="ray.io", version="v1", namespace=namespace, plural="rayjobs", name=actual_job_cr_name + ) + status_field = ray_job_status_cr.get("status", {}) + final_job_status = status_field.get("jobStatus", "SUBMITTED") + returned_job_submission_id = status_field.get("jobId", job_config.submission_id) + dashboard_url = status_field.get("dashboardURL", dashboard_url) + ray_cluster_name_actual = status_field.get("rayClusterName", ray_cluster_name_actual) + except ApiException as e: + if e.status == 404: + final_job_status = "SUBMITTED_NOT_FOUND" + else: + print(f"Warning: Could not fetch initial status for RayJob '{actual_job_cr_name}': {e}") + final_job_status = "UNKNOWN_API_ERROR" + + return { + "job_cr_name": actual_job_cr_name, + "job_submission_id": returned_job_submission_id, + "job_status": final_job_status, + "dashboard_url": dashboard_url, + "ray_cluster_name": ray_cluster_name_actual, + } + + except ApiException as e: + print(f"Kubernetes API error during RayJob '{actual_job_cr_name}' management: {e.reason} (status: {e.status})") + final_status_on_error = "ERROR_BEFORE_SUBMISSION" + if actual_job_cr_name: + try: + ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( + group="ray.io", version="v1", namespace=namespace, plural="rayjobs", name=actual_job_cr_name + ) + status_field = ray_job_status_cr.get("status", {}) + final_status_on_error = status_field.get("jobStatus", "UNKNOWN_AFTER_K8S_ERROR") + except Exception: + final_status_on_error = "UNKNOWN_FINAL_STATUS_FETCH_FAILED" + raise + except Exception as e: + print(f"An unexpected error occurred during managed RayJob execution for '{actual_job_cr_name}': {e}") + raise + def list_all_clusters(namespace: str, print_to_console: bool = True): """ @@ -760,6 +997,11 @@ def get_cluster( head_extended_resource_requests=head_extended_resources, worker_extended_resource_requests=worker_extended_resources, ) + # 1. Prepare RayClusterSpec from ClusterConfiguration + # Create a temporary config with appwrapper=False to ensure build_ray_cluster returns RayCluster YAML + temp_cluster_config_dict = cluster_config.dict(exclude_none=True) # Assuming Pydantic V1 or similar .dict() method + temp_cluster_config_dict['appwrapper'] = False + temp_cluster_config_for_spec = ClusterConfiguration(**temp_cluster_config_dict) # Ignore the warning here for the lack of a ClusterConfiguration with warnings.catch_warnings(): warnings.filterwarnings( @@ -767,7 +1009,7 @@ def get_cluster( message="Please provide a ClusterConfiguration to initialise the Cluster object", ) cluster = Cluster(None) - cluster.config = cluster_config + cluster.config = temp_cluster_config_for_spec # Remove auto-generated fields like creationTimestamp, uid and etc. remove_autogenerated_fields(resource) diff --git a/src/codeflare_sdk/ray/job/job.py b/src/codeflare_sdk/ray/job/job.py index f7a4aaba..66bd50ff 100644 --- a/src/codeflare_sdk/ray/job/job.py +++ b/src/codeflare_sdk/ray/job/job.py @@ -76,14 +76,14 @@ class RayJobSpec: class RayJob: """RayJob Custom Resource Definition""" - api_version: str = "ray.io/v1" - kind: str = "RayJob" - metadata: Dict[str, Any] """Kubernetes metadata for the job""" spec: RayJobSpec """Job specification""" + + api_version: str = "ray.io/v1" + kind: str = "RayJob" status: Optional[Dict[str, Any]] = None """Status of the job (managed by the controller)""" From b3251fcbdd68f967e673fc6fda917bbb2af57616 Mon Sep 17 00:00:00 2001 From: kryanbeane Date: Fri, 11 Jul 2025 18:34:10 +0100 Subject: [PATCH 4/7] checkpoint: RayJob works when not using our modh runtime images --- poetry.lock | 1362 +++++++++-------- pyproject.toml | 8 + src/codeflare_sdk/__init__.py | 1 + src/codeflare_sdk/ray/__init__.py | 4 + .../ray/cluster/build_ray_cluster.py | 2 + src/codeflare_sdk/ray/cluster/cluster.py | 144 +- src/codeflare_sdk/ray/job/job.py | 62 +- src/codeflare_sdk/ray/rayjobs/__init__.py | 1 + src/codeflare_sdk/ray/rayjobs/rayjob.py | 111 ++ src/codeflare_sdk/ray/rayjobs/test_rayjob.py | 60 + test.ipynb | 169 ++ 11 files changed, 1194 insertions(+), 730 deletions(-) create mode 100644 src/codeflare_sdk/ray/rayjobs/__init__.py create mode 100644 src/codeflare_sdk/ray/rayjobs/rayjob.py create mode 100644 src/codeflare_sdk/ray/rayjobs/test_rayjob.py create mode 100644 test.ipynb diff --git a/poetry.lock b/poetry.lock index 89bca284..fca55833 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 = "aiohttp-3.12.12-cp310-cp310-macosx_10_9_x86_64.whl", hash 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ab55cc82..7c8e84da 100644 --- a/src/codeflare_sdk/ray/__init__.py +++ b/src/codeflare_sdk/ray/__init__.py @@ -4,6 +4,10 @@ RayJobClient, ) +from .rayjobs import ( + RayJob, +) + 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 c68c17ed..2e3d14dd 100644 --- a/src/codeflare_sdk/ray/cluster/cluster.py +++ b/src/codeflare_sdk/ray/cluster/cluster.py @@ -663,26 +663,31 @@ def run_job_with_managed_cluster( raise ValueError("job_config.entrypoint must be specified.") # Warn if Pydantic V1/V2 specific fields in RayJobSpec are set, as they are not used for RayJob CR. - if job_config.entrypoint_num_cpus is not None or \ - job_config.entrypoint_num_gpus is not None or \ - job_config.entrypoint_memory is not None: + if ( + job_config.entrypoint_num_cpus is not None + or job_config.entrypoint_num_gpus is not None + or job_config.entrypoint_memory is not None + ): warnings.warn( "RayJobSpec fields 'entrypoint_num_cpus', 'entrypoint_num_gpus', 'entrypoint_memory' " "are not directly used when creating a RayJob CR. They are primarily for the Ray Job Submission Client. " "Resource requests for the job driver pod should be configured in the RayCluster head node spec via ClusterConfiguration.", - UserWarning + UserWarning, ) # Generate rayClusterSpec from ClusterConfiguration temp_config_for_spec = copy.deepcopy(cluster_config) temp_config_for_spec.appwrapper = False - + with warnings.catch_warnings(): warnings.simplefilter("ignore", UserWarning) dummy_cluster_for_spec = Cluster(temp_config_for_spec) ray_cluster_cr_dict = dummy_cluster_for_spec.resource_yaml - if not isinstance(ray_cluster_cr_dict, dict) or "spec" not in ray_cluster_cr_dict: + if ( + not isinstance(ray_cluster_cr_dict, dict) + or "spec" not in ray_cluster_cr_dict + ): raise ValueError( "Failed to generate RayCluster CR dictionary from ClusterConfiguration. " f"Got: {type(ray_cluster_cr_dict)}" @@ -691,13 +696,15 @@ def run_job_with_managed_cluster( # Prepare RayJob CR actual_job_cr_name = job_cr_name or f"rayjob-{uuid.uuid4().hex[:10]}" - + runtime_env_yaml_str = "" if job_config.runtime_env: try: runtime_env_yaml_str = yaml.dump(job_config.runtime_env) except yaml.YAMLError as e: - raise ValueError(f"Invalid job_config.runtime_env, failed to dump to YAML: {e}") + raise ValueError( + f"Invalid job_config.runtime_env, failed to dump to YAML: {e}" + ) ray_job_cr_spec = { "entrypoint": job_config.entrypoint, @@ -735,7 +742,9 @@ def run_job_with_managed_cluster( ray_cluster_name_actual = None try: - print(f"Submitting RayJob '{actual_job_cr_name}' to namespace '{namespace}'...") + print( + f"Submitting RayJob '{actual_job_cr_name}' to namespace '{namespace}'..." + ) k8s_co_api.create_namespaced_custom_object( group="ray.io", version="v1", @@ -750,27 +759,37 @@ def run_job_with_managed_cluster( start_time = time.time() while True: try: - ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", - version="v1", - namespace=namespace, - plural="rayjobs", - name=actual_job_cr_name, + ray_job_status_cr = ( + k8s_co_api.get_namespaced_custom_object_status( + group="ray.io", + version="v1", + namespace=namespace, + plural="rayjobs", + name=actual_job_cr_name, + ) ) except ApiException as e: if e.status == 404: - print(f"RayJob '{actual_job_cr_name}' status not found yet, retrying...") + print( + f"RayJob '{actual_job_cr_name}' status not found yet, retrying..." + ) time.sleep(job_polling_interval_seconds) continue raise status_field = ray_job_status_cr.get("status", {}) - job_deployment_status = status_field.get("jobDeploymentStatus", "UNKNOWN") + job_deployment_status = status_field.get( + "jobDeploymentStatus", "UNKNOWN" + ) current_job_status = status_field.get("jobStatus", "PENDING") - + dashboard_url = status_field.get("dashboardURL", dashboard_url) - ray_cluster_name_actual = status_field.get("rayClusterName", ray_cluster_name_actual) - returned_job_submission_id = status_field.get("jobId", job_config.submission_id) + ray_cluster_name_actual = status_field.get( + "rayClusterName", ray_cluster_name_actual + ) + returned_job_submission_id = status_field.get( + "jobId", job_config.submission_id + ) final_job_status = current_job_status print( @@ -779,17 +798,36 @@ def run_job_with_managed_cluster( if current_job_status in ["SUCCEEDED", "FAILED", "STOPPED"]: break - - if job_timeout_seconds and (time.time() - start_time) > job_timeout_seconds: + + if ( + job_timeout_seconds + and (time.time() - start_time) > job_timeout_seconds + ): try: - ray_job_status_cr_final = k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", version="v1", namespace=namespace, plural="rayjobs", name=actual_job_cr_name + ray_job_status_cr_final = ( + k8s_co_api.get_namespaced_custom_object_status( + group="ray.io", + version="v1", + namespace=namespace, + plural="rayjobs", + name=actual_job_cr_name, + ) + ) + status_field_final = ray_job_status_cr_final.get( + "status", {} + ) + final_job_status = status_field_final.get( + "jobStatus", final_job_status + ) + returned_job_submission_id = status_field_final.get( + "jobId", returned_job_submission_id + ) + dashboard_url = status_field_final.get( + "dashboardURL", dashboard_url + ) + ray_cluster_name_actual = status_field_final.get( + "rayClusterName", ray_cluster_name_actual ) - status_field_final = ray_job_status_cr_final.get("status", {}) - final_job_status = status_field_final.get("jobStatus", final_job_status) - returned_job_submission_id = status_field_final.get("jobId", returned_job_submission_id) - dashboard_url = status_field_final.get("dashboardURL", dashboard_url) - ray_cluster_name_actual = status_field_final.get("rayClusterName", ray_cluster_name_actual) except Exception: pass raise TimeoutError( @@ -797,23 +835,35 @@ def run_job_with_managed_cluster( ) time.sleep(job_polling_interval_seconds) - - print(f"RayJob '{actual_job_cr_name}' finished with status: {final_job_status}") + + print( + f"RayJob '{actual_job_cr_name}' finished with status: {final_job_status}" + ) else: try: ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", version="v1", namespace=namespace, plural="rayjobs", name=actual_job_cr_name + group="ray.io", + version="v1", + namespace=namespace, + plural="rayjobs", + name=actual_job_cr_name, ) status_field = ray_job_status_cr.get("status", {}) final_job_status = status_field.get("jobStatus", "SUBMITTED") - returned_job_submission_id = status_field.get("jobId", job_config.submission_id) + returned_job_submission_id = status_field.get( + "jobId", job_config.submission_id + ) dashboard_url = status_field.get("dashboardURL", dashboard_url) - ray_cluster_name_actual = status_field.get("rayClusterName", ray_cluster_name_actual) + ray_cluster_name_actual = status_field.get( + "rayClusterName", ray_cluster_name_actual + ) except ApiException as e: if e.status == 404: final_job_status = "SUBMITTED_NOT_FOUND" else: - print(f"Warning: Could not fetch initial status for RayJob '{actual_job_cr_name}': {e}") + print( + f"Warning: Could not fetch initial status for RayJob '{actual_job_cr_name}': {e}" + ) final_job_status = "UNKNOWN_API_ERROR" return { @@ -825,20 +875,30 @@ def run_job_with_managed_cluster( } except ApiException as e: - print(f"Kubernetes API error during RayJob '{actual_job_cr_name}' management: {e.reason} (status: {e.status})") + print( + f"Kubernetes API error during RayJob '{actual_job_cr_name}' management: {e.reason} (status: {e.status})" + ) final_status_on_error = "ERROR_BEFORE_SUBMISSION" if actual_job_cr_name: try: ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", version="v1", namespace=namespace, plural="rayjobs", name=actual_job_cr_name + group="ray.io", + version="v1", + namespace=namespace, + plural="rayjobs", + name=actual_job_cr_name, ) status_field = ray_job_status_cr.get("status", {}) - final_status_on_error = status_field.get("jobStatus", "UNKNOWN_AFTER_K8S_ERROR") + final_status_on_error = status_field.get( + "jobStatus", "UNKNOWN_AFTER_K8S_ERROR" + ) except Exception: final_status_on_error = "UNKNOWN_FINAL_STATUS_FETCH_FAILED" raise except Exception as e: - print(f"An unexpected error occurred during managed RayJob execution for '{actual_job_cr_name}': {e}") + print( + f"An unexpected error occurred during managed RayJob execution for '{actual_job_cr_name}': {e}" + ) raise @@ -999,8 +1059,10 @@ def get_cluster( ) # 1. Prepare RayClusterSpec from ClusterConfiguration # Create a temporary config with appwrapper=False to ensure build_ray_cluster returns RayCluster YAML - temp_cluster_config_dict = cluster_config.dict(exclude_none=True) # Assuming Pydantic V1 or similar .dict() method - temp_cluster_config_dict['appwrapper'] = False + temp_cluster_config_dict = cluster_config.dict( + exclude_none=True + ) # Assuming Pydantic V1 or similar .dict() method + temp_cluster_config_dict["appwrapper"] = False temp_cluster_config_for_spec = ClusterConfiguration(**temp_cluster_config_dict) # Ignore the warning here for the lack of a ClusterConfiguration with warnings.catch_warnings(): diff --git a/src/codeflare_sdk/ray/job/job.py b/src/codeflare_sdk/ray/job/job.py index 66bd50ff..8a6962c8 100644 --- a/src/codeflare_sdk/ray/job/job.py +++ b/src/codeflare_sdk/ray/job/job.py @@ -2,26 +2,29 @@ from typing import Dict, Any, Optional, Union, List from enum import Enum + class RayJobStatus(str, Enum): """Status of a RayJob""" + PENDING = "PENDING" RUNNING = "RUNNING" STOPPED = "STOPPED" SUCCEEDED = "SUCCEEDED" FAILED = "FAILED" + @dataclass class RayJobSpec: """Specification for a RayJob Custom Resource""" - + # Required fields entrypoint: str """The command to execute for this job (e.g., "python script.py")""" - + # Optional fields submission_id: Optional[str] = None """Unique ID for the job submission. If not provided, one will be generated.""" - + runtime_env: Optional[Dict[str, Any]] = None """Runtime environment configuration for the job, including: - working_dir: Directory containing files that your job will run in @@ -30,41 +33,41 @@ class RayJobSpec: - env_vars: Environment variables to set - py_modules: Python modules to include """ - + metadata: Optional[Dict[str, str]] = None """Arbitrary metadata to store with the job""" - + entrypoint_num_cpus: Optional[Union[int, float]] = None """Number of CPU cores to reserve for the entrypoint command""" - + entrypoint_num_gpus: Optional[Union[int, float]] = None """Number of GPUs to reserve for the entrypoint command""" - + entrypoint_memory: Optional[int] = None """Amount of memory to reserve for the entrypoint command""" - + entrypoint_resources: Optional[Dict[str, float]] = None """Custom resources to reserve for the entrypoint command""" - + cluster_name: Optional[str] = None """Name of the RayCluster to run this job on""" - + cluster_namespace: Optional[str] = None """Namespace of the RayCluster to run this job on""" - + # Status fields (managed by the controller) status: RayJobStatus = field(default=RayJobStatus.PENDING) """Current status of the job""" - + message: Optional[str] = None """Detailed status message""" - + start_time: Optional[str] = None """Time when the job started""" - + end_time: Optional[str] = None """Time when the job ended""" - + driver_info: Optional[Dict[str, str]] = None """Information about the job driver, including: - id: Driver ID @@ -72,19 +75,20 @@ class RayJobSpec: - pid: Process ID of the driver """ + @dataclass class RayJob: """RayJob Custom Resource Definition""" - + metadata: Dict[str, Any] """Kubernetes metadata for the job""" - + spec: RayJobSpec """Job specification""" api_version: str = "ray.io/v1" kind: str = "RayJob" - + status: Optional[Dict[str, Any]] = None """Status of the job (managed by the controller)""" @@ -112,14 +116,16 @@ def to_dict(self) -> Dict[str, Any]: "start_time": self.spec.start_time, "end_time": self.spec.end_time, "driver_info": self.spec.driver_info, - } if self.status is None else self.status + } + if self.status is None + else self.status, } def apply(self, force=False): """ Applies the RayJob using server-side apply. If 'force' is set to True, conflicts will be forced. - + Args: force (bool): If True, force conflicts during server-side apply. """ @@ -129,25 +135,25 @@ def apply(self, force=False): from ...common import _kube_api_error_handling CF_SDK_FIELD_MANAGER = "codeflare-sdk" - + try: # Check Kubernetes configuration config_check() - + # Get the dynamic client crds = DynamicClient(get_api_client()).resources - + # Get the RayJob API instance api_version = "ray.io/v1" api_instance = crds.get(api_version=api_version, kind="RayJob") - + # Get namespace from metadata namespace = self.metadata.get("namespace", "default") name = self.metadata.get("name") - + # Convert job to dictionary body = self.to_dict() - + # Apply the job using server-side apply api_instance.server_side_apply( field_manager=CF_SDK_FIELD_MANAGER, @@ -158,9 +164,9 @@ def apply(self, force=False): body=body, force_conflicts=force, ) - + print(f"RayJob: '{name}' has successfully been applied") - + except AttributeError as e: raise RuntimeError(f"Failed to initialize DynamicClient: {e}") except Exception as e: diff --git a/src/codeflare_sdk/ray/rayjobs/__init__.py b/src/codeflare_sdk/ray/rayjobs/__init__.py new file mode 100644 index 00000000..d9cbae34 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/__init__.py @@ -0,0 +1 @@ +from .rayjob import RayJob diff --git a/src/codeflare_sdk/ray/rayjobs/rayjob.py b/src/codeflare_sdk/ray/rayjobs/rayjob.py new file mode 100644 index 00000000..e7a9a588 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/rayjob.py @@ -0,0 +1,111 @@ +""" +RayJob client for submitting and managing Ray jobs using the odh-kuberay-client. +""" + +import logging +from typing import Dict, Any, Optional +from odh_kuberay_client.kuberay_job_api import RayjobApi + +# Set up logging +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 + Ray jobs in a Kubernetes cluster with the KubeRay operator installed. + """ + + def __init__( + self, + job_name: str, + cluster_name: str, + namespace: str = "default", + entrypoint: str = "None", + runtime_env: Optional[Dict[str, Any]] = None, + ): + """ + Initialize a RayJob instance. + + Args: + name: The name for the Ray job + namespace: The Kubernetes namespace to submit the job to (default: "default") + cluster_name: The name of the Ray cluster to submit the job to + **kwargs: Additional configuration options + """ + self.name = job_name + self.namespace = namespace + self.cluster_name = cluster_name + self.entrypoint = entrypoint + self.runtime_env = runtime_env + + # Initialize the KubeRay job API client + self._api = RayjobApi() + + logger.info(f"Initialized RayJob: {self.name} in namespace: {self.namespace}") + + def submit( + self, + ) -> str: + """ + Submit the Ray job to the Kubernetes cluster. + + Args: + entrypoint: The Python script or command to run + runtime_env: Ray runtime environment configuration (optional) + + Returns: + The job ID/name if submission was successful + + Raises: + RuntimeError: If the job has already been submitted or submission fails + """ + # Build the RayJob custom resource + rayjob_cr = self._build_rayjob_cr( + entrypoint=self.entrypoint, + runtime_env=self.runtime_env, + ) + + # Submit the job + logger.info( + f"Submitting RayJob {self.name} to RayCluster {self.cluster_name} in namespace {self.namespace}" + ) + result = self._api.submit_job(k8s_namespace=self.namespace, job=rayjob_cr) + + if result: + logger.info(f"Successfully submitted RayJob {self.name}") + return self.name + else: + raise RuntimeError(f"Failed to submit RayJob {self.name}") + + def _build_rayjob_cr( + self, + entrypoint: str, + runtime_env: Optional[Dict[str, Any]] = None, + ) -> Dict[str, Any]: + """ + Build the RayJob custom resource specification. + + This creates a minimal RayJob CR that can be extended later. + """ + # Basic RayJob custom resource structure + rayjob_cr = { + "apiVersion": "ray.io/v1", + "kind": "RayJob", + "metadata": { + "name": self.name, + "namespace": self.namespace, + }, + "spec": { + "entrypoint": entrypoint, + "clusterSelector": {"ray.io/cluster": self.cluster_name}, + }, + } + + # Add runtime environment if specified + if runtime_env: + rayjob_cr["spec"]["runtimeEnvYAML"] = str(runtime_env) + + return rayjob_cr 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..dccab7dd --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/test_rayjob.py @@ -0,0 +1,60 @@ +# Copyright 2024 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 unittest.mock import MagicMock +from codeflare_sdk.ray.rayjobs.rayjob import RayJob + + +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.assert_called_once() + call_args = mock_api_instance.submit.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']}" diff --git a/test.ipynb b/test.ipynb new file mode 100644 index 00000000..84861a6c --- /dev/null +++ b/test.ipynb @@ -0,0 +1,169 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8f8ed15a", + "metadata": {}, + "source": [ + "## Steps to reproduce the Job Agent bug\n", + "To get the below wheel file for codeflare-sdk set up you can run the following in your terminal \n", + "```bash\n", + "poetry lock\n", + "poetry install\n", + "poetry build\n", + "```\n", + "\n", + "Then you can run the below to install it. This is using a dev image of the kuberay python client found here -> https://test.pypi.org/project/odh-kuberay-client/#history. The referenced kuberay python client version is working as intended. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "10c8c12e", + "metadata": {}, + "outputs": [], + "source": [ + "%pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ dist/codeflare_sdk-0.0.0.dev0-py3-none-any.whl --force-reinstall" + ] + }, + { + "cell_type": "markdown", + "id": "3e021c61", + "metadata": {}, + "source": [ + "Below is the code I used to confirm that Kuberay Python Client is functional. It uses the cluster api to create a cluster, and submitting a job to this is successful. You don't need to run this" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5dc1a0fa", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "from odh_kuberay_client import kuberay_cluster_api\n", + "from odh_kuberay_client.utils import kuberay_cluster_builder\n", + "\n", + "cluster_name = \"working\"\n", + "namespace = \"default\"\n", + "\n", + "director = kuberay_cluster_builder.Director()\n", + "cluster_api = kuberay_cluster_api.RayClusterApi()\n", + "\n", + "# Build a small cluster\n", + "cluster_body = director.build_small_cluster(\n", + " name=cluster_name,\n", + " k8s_namespace=namespace,\n", + " labels={\"ray.io/cluster\": cluster_name},\n", + ")\n", + "\n", + "created_cluster = cluster_api.create_ray_cluster(\n", + " body=cluster_body, k8s_namespace=namespace\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "005c2ba2", + "metadata": {}, + "source": [ + "The below uses the default ray image. Creating this cluster and submitting a job will work. To recreate the bug, comment out the `image=\"ray-project/ray:2.47.1\"` line and submit the job again. Ensure the RayJob CR from the working job submission was deleted. \n", + "\n", + "You will need a Kind cluster with Kuberay installed for this to work FYI!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cb80c155", + "metadata": {}, + "outputs": [], + "source": [ + "from codeflare_sdk import Cluster, ClusterConfiguration\n", + "\n", + "cluster = Cluster(ClusterConfiguration(\n", + " name='test-cluster',\n", + " namespace='default',\n", + " head_cpu_requests='1',\n", + " head_cpu_limits='2',\n", + " head_memory_requests=4,\n", + " head_memory_limits=5,\n", + " head_extended_resource_requests={'nvidia.com/gpu':0},\n", + " worker_extended_resource_requests={'nvidia.com/gpu':0},\n", + " num_workers=1,\n", + " worker_cpu_requests='1',\n", + " worker_cpu_limits='2',\n", + " worker_memory_requests=3,\n", + " worker_memory_limits=4,\n", + " image=\"ray-project/ray:2.47.1\" # this image works, omit this line to use our default image which does not work\n", + "))\n", + "\n", + "cluster.apply()" + ] + }, + { + "cell_type": "markdown", + "id": "94841b95", + "metadata": {}, + "source": [ + "With the below, a pod gets created which submits the job. This will be marked as completed if its successful and you can view the job in the Dashboard as normal. If not, it will fail, and the CR will try to recreate new pods in a loop" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5e3c895", + "metadata": {}, + "outputs": [], + "source": [ + "from odh_kuberay_client.kuberay_job_api import RayjobApi\n", + "\n", + "rayjob_api = RayjobApi()\n", + "\n", + "job_body = {\n", + " \"apiVersion\": \"ray.io/v1\",\n", + " \"kind\": \"RayJob\",\n", + " \"metadata\": {\n", + " \"name\": \"test-job\",\n", + " \"namespace\": \"default\",\n", + " \"labels\": {\n", + " \"app.kubernetes.io/name\": \"test-job\",\n", + " \"app.kubernetes.io/managed-by\": \"kuberay\",\n", + " },\n", + " },\n", + " \"spec\": {\n", + " \"clusterSelector\": {\n", + " \"ray.io/cluster\": \"test-cluster\",\n", + " },\n", + " \"entrypoint\": 'python -c \"import time; time.sleep(20)\"',\n", + " \"submissionMode\": \"K8sJobMode\",\n", + " },\n", + "}\n", + "\n", + "rayjob_api.submit_job(job=job_body, k8s_namespace=\"default\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 77bc95a51379dd787b76ab99a4e71582461ebec4 Mon Sep 17 00:00:00 2001 From: Pat O'Connor Date: Fri, 25 Jul 2025 10:33:59 +0100 Subject: [PATCH 5/7] Removed managed cluster func and fixed tests Signed-off-by: Pat O'Connor --- src/codeflare_sdk/ray/cluster/cluster.py | 304 +----------------- src/codeflare_sdk/ray/cluster/test_cluster.py | 10 +- src/codeflare_sdk/ray/job/job.py | 173 ---------- src/codeflare_sdk/ray/rayjobs/test_rayjob.py | 32 +- test.ipynb | 169 ---------- .../appwrapper/unit-test-all-params.yaml | 2 + tests/test_cluster_yamls/kueue/aw_kueue.yaml | 2 + .../kueue/ray_cluster_kueue.yaml | 2 + .../ray/default-appwrapper.yaml | 2 + .../ray/default-ray-cluster.yaml | 2 + .../ray/unit-test-all-params.yaml | 2 + 11 files changed, 52 insertions(+), 648 deletions(-) delete mode 100644 src/codeflare_sdk/ray/job/job.py delete mode 100644 test.ipynb diff --git a/src/codeflare_sdk/ray/cluster/cluster.py b/src/codeflare_sdk/ray/cluster/cluster.py index 2e3d14dd..04b3b141 100644 --- a/src/codeflare_sdk/ray/cluster/cluster.py +++ b/src/codeflare_sdk/ray/cluster/cluster.py @@ -27,8 +27,6 @@ import uuid import warnings -from ..job.job import RayJobSpec - from ...common.kubernetes_cluster.auth import ( config_check, get_api_client, @@ -609,298 +607,6 @@ def _component_resources_down( yamls = yaml.safe_load_all(self.resource_yaml) _delete_resources(yamls, namespace, api_instance, cluster_name) - @staticmethod - def run_job_with_managed_cluster( - cluster_config: ClusterConfiguration, - job_config: RayJobSpec, - job_cr_name: Optional[str] = None, - submission_mode: str = "K8sJobMode", - shutdown_after_job_finishes: bool = True, - ttl_seconds_after_finished: Optional[int] = None, - suspend_rayjob_creation: bool = False, - wait_for_completion: bool = True, - job_timeout_seconds: Optional[int] = 3600, - job_polling_interval_seconds: int = 10, - ): - """ - Manages the lifecycle of a Ray cluster and a job by creating a RayJob custom resource. - KubeRay operator will then create/delete the RayCluster based on the RayJob definition. - - This method will: - 1. Generate a RayCluster specification from the provided 'cluster_config'. - 2. Construct a RayJob custom resource definition using 'job_config' and embedding the RayCluster spec. - 3. Create the RayJob resource in Kubernetes. - 4. Optionally, wait for the RayJob to complete or timeout, monitoring its status. - 5. The RayCluster lifecycle (creation and deletion) is managed by KubeRay - based on the RayJob's 'shutdownAfterJobFinishes' field. - - Args: - cluster_config: Configuration for the Ray cluster to be created by RayJob. - job_config: RayJobSpec object containing job-specific details like entrypoint, runtime_env, etc. - job_cr_name: Name for the RayJob Custom Resource. If None, a unique name is generated. - submission_mode: How the job is submitted ("K8sJobMode" or "RayClientMode"). - shutdown_after_job_finishes: If True, RayCluster is deleted after job finishes. - ttl_seconds_after_finished: TTL for RayJob after it's finished. - suspend_rayjob_creation: If True, creates the RayJob in a suspended state. - wait_for_completion: If True, waits for the job to finish. - job_timeout_seconds: Timeout for waiting for job completion. - job_polling_interval_seconds: Interval for polling job status. - - Returns: - A dictionary containing details like RayJob CR name, reported job submission ID, - final job status, dashboard URL, and the RayCluster name. - - Raises: - TimeoutError: If the job doesn't complete within the specified timeout. - ApiException: For Kubernetes API errors. - ValueError: For configuration issues. - """ - config_check() - k8s_co_api = k8s_client.CustomObjectsApi(get_api_client()) - namespace = cluster_config.namespace - - if not job_config.entrypoint: - raise ValueError("job_config.entrypoint must be specified.") - - # Warn if Pydantic V1/V2 specific fields in RayJobSpec are set, as they are not used for RayJob CR. - if ( - job_config.entrypoint_num_cpus is not None - or job_config.entrypoint_num_gpus is not None - or job_config.entrypoint_memory is not None - ): - warnings.warn( - "RayJobSpec fields 'entrypoint_num_cpus', 'entrypoint_num_gpus', 'entrypoint_memory' " - "are not directly used when creating a RayJob CR. They are primarily for the Ray Job Submission Client. " - "Resource requests for the job driver pod should be configured in the RayCluster head node spec via ClusterConfiguration.", - UserWarning, - ) - - # Generate rayClusterSpec from ClusterConfiguration - temp_config_for_spec = copy.deepcopy(cluster_config) - temp_config_for_spec.appwrapper = False - - with warnings.catch_warnings(): - warnings.simplefilter("ignore", UserWarning) - dummy_cluster_for_spec = Cluster(temp_config_for_spec) - - ray_cluster_cr_dict = dummy_cluster_for_spec.resource_yaml - if ( - not isinstance(ray_cluster_cr_dict, dict) - or "spec" not in ray_cluster_cr_dict - ): - raise ValueError( - "Failed to generate RayCluster CR dictionary from ClusterConfiguration. " - f"Got: {type(ray_cluster_cr_dict)}" - ) - ray_cluster_spec = ray_cluster_cr_dict["spec"] - - # Prepare RayJob CR - actual_job_cr_name = job_cr_name or f"rayjob-{uuid.uuid4().hex[:10]}" - - runtime_env_yaml_str = "" - if job_config.runtime_env: - try: - runtime_env_yaml_str = yaml.dump(job_config.runtime_env) - except yaml.YAMLError as e: - raise ValueError( - f"Invalid job_config.runtime_env, failed to dump to YAML: {e}" - ) - - ray_job_cr_spec = { - "entrypoint": job_config.entrypoint, - "shutdownAfterJobFinishes": shutdown_after_job_finishes, - "rayClusterSpec": ray_cluster_spec, - "submissionMode": submission_mode, - } - - if runtime_env_yaml_str: - ray_job_cr_spec["runtimeEnvYAML"] = runtime_env_yaml_str - if job_config.submission_id: - ray_job_cr_spec["jobId"] = job_config.submission_id - if job_config.metadata: - ray_job_cr_spec["metadata"] = job_config.metadata - if ttl_seconds_after_finished is not None: - ray_job_cr_spec["ttlSecondsAfterFinished"] = ttl_seconds_after_finished - if suspend_rayjob_creation: - ray_job_cr_spec["suspend"] = True - if job_config.entrypoint_resources: - ray_job_cr_spec["entrypointResources"] = job_config.entrypoint_resources - - ray_job_cr = { - "apiVersion": "ray.io/v1", - "kind": "RayJob", - "metadata": { - "name": actual_job_cr_name, - "namespace": namespace, - }, - "spec": ray_job_cr_spec, - } - - returned_job_submission_id = None - final_job_status = "UNKNOWN" - dashboard_url = None - ray_cluster_name_actual = None - - try: - print( - f"Submitting RayJob '{actual_job_cr_name}' to namespace '{namespace}'..." - ) - k8s_co_api.create_namespaced_custom_object( - group="ray.io", - version="v1", - namespace=namespace, - plural="rayjobs", - body=ray_job_cr, - ) - print(f"RayJob '{actual_job_cr_name}' created successfully.") - - if wait_for_completion: - print(f"Waiting for RayJob '{actual_job_cr_name}' to complete...") - start_time = time.time() - while True: - try: - ray_job_status_cr = ( - k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", - version="v1", - namespace=namespace, - plural="rayjobs", - name=actual_job_cr_name, - ) - ) - except ApiException as e: - if e.status == 404: - print( - f"RayJob '{actual_job_cr_name}' status not found yet, retrying..." - ) - time.sleep(job_polling_interval_seconds) - continue - raise - - status_field = ray_job_status_cr.get("status", {}) - job_deployment_status = status_field.get( - "jobDeploymentStatus", "UNKNOWN" - ) - current_job_status = status_field.get("jobStatus", "PENDING") - - dashboard_url = status_field.get("dashboardURL", dashboard_url) - ray_cluster_name_actual = status_field.get( - "rayClusterName", ray_cluster_name_actual - ) - returned_job_submission_id = status_field.get( - "jobId", job_config.submission_id - ) - - final_job_status = current_job_status - print( - f"RayJob '{actual_job_cr_name}' status: JobDeployment='{job_deployment_status}', Job='{current_job_status}'" - ) - - if current_job_status in ["SUCCEEDED", "FAILED", "STOPPED"]: - break - - if ( - job_timeout_seconds - and (time.time() - start_time) > job_timeout_seconds - ): - try: - ray_job_status_cr_final = ( - k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", - version="v1", - namespace=namespace, - plural="rayjobs", - name=actual_job_cr_name, - ) - ) - status_field_final = ray_job_status_cr_final.get( - "status", {} - ) - final_job_status = status_field_final.get( - "jobStatus", final_job_status - ) - returned_job_submission_id = status_field_final.get( - "jobId", returned_job_submission_id - ) - dashboard_url = status_field_final.get( - "dashboardURL", dashboard_url - ) - ray_cluster_name_actual = status_field_final.get( - "rayClusterName", ray_cluster_name_actual - ) - except Exception: - pass - raise TimeoutError( - f"RayJob '{actual_job_cr_name}' timed out after {job_timeout_seconds} seconds. Last status: {final_job_status}" - ) - - time.sleep(job_polling_interval_seconds) - - print( - f"RayJob '{actual_job_cr_name}' finished with status: {final_job_status}" - ) - else: - try: - ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", - version="v1", - namespace=namespace, - plural="rayjobs", - name=actual_job_cr_name, - ) - status_field = ray_job_status_cr.get("status", {}) - final_job_status = status_field.get("jobStatus", "SUBMITTED") - returned_job_submission_id = status_field.get( - "jobId", job_config.submission_id - ) - dashboard_url = status_field.get("dashboardURL", dashboard_url) - ray_cluster_name_actual = status_field.get( - "rayClusterName", ray_cluster_name_actual - ) - except ApiException as e: - if e.status == 404: - final_job_status = "SUBMITTED_NOT_FOUND" - else: - print( - f"Warning: Could not fetch initial status for RayJob '{actual_job_cr_name}': {e}" - ) - final_job_status = "UNKNOWN_API_ERROR" - - return { - "job_cr_name": actual_job_cr_name, - "job_submission_id": returned_job_submission_id, - "job_status": final_job_status, - "dashboard_url": dashboard_url, - "ray_cluster_name": ray_cluster_name_actual, - } - - except ApiException as e: - print( - f"Kubernetes API error during RayJob '{actual_job_cr_name}' management: {e.reason} (status: {e.status})" - ) - final_status_on_error = "ERROR_BEFORE_SUBMISSION" - if actual_job_cr_name: - try: - ray_job_status_cr = k8s_co_api.get_namespaced_custom_object_status( - group="ray.io", - version="v1", - namespace=namespace, - plural="rayjobs", - name=actual_job_cr_name, - ) - status_field = ray_job_status_cr.get("status", {}) - final_status_on_error = status_field.get( - "jobStatus", "UNKNOWN_AFTER_K8S_ERROR" - ) - except Exception: - final_status_on_error = "UNKNOWN_FINAL_STATUS_FETCH_FAILED" - raise - except Exception as e: - print( - f"An unexpected error occurred during managed RayJob execution for '{actual_job_cr_name}': {e}" - ) - raise - def list_all_clusters(namespace: str, print_to_console: bool = True): """ @@ -1057,13 +763,7 @@ def get_cluster( head_extended_resource_requests=head_extended_resources, worker_extended_resource_requests=worker_extended_resources, ) - # 1. Prepare RayClusterSpec from ClusterConfiguration - # Create a temporary config with appwrapper=False to ensure build_ray_cluster returns RayCluster YAML - temp_cluster_config_dict = cluster_config.dict( - exclude_none=True - ) # Assuming Pydantic V1 or similar .dict() method - temp_cluster_config_dict["appwrapper"] = False - temp_cluster_config_for_spec = ClusterConfiguration(**temp_cluster_config_dict) + # Ignore the warning here for the lack of a ClusterConfiguration with warnings.catch_warnings(): warnings.filterwarnings( @@ -1071,7 +771,7 @@ def get_cluster( message="Please provide a ClusterConfiguration to initialise the Cluster object", ) cluster = Cluster(None) - cluster.config = temp_cluster_config_for_spec + cluster.config = cluster_config # Remove auto-generated fields like creationTimestamp, uid and etc. remove_autogenerated_fields(resource) 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/job/job.py b/src/codeflare_sdk/ray/job/job.py deleted file mode 100644 index 8a6962c8..00000000 --- a/src/codeflare_sdk/ray/job/job.py +++ /dev/null @@ -1,173 +0,0 @@ -from dataclasses import dataclass, field -from typing import Dict, Any, Optional, Union, List -from enum import Enum - - -class RayJobStatus(str, Enum): - """Status of a RayJob""" - - PENDING = "PENDING" - RUNNING = "RUNNING" - STOPPED = "STOPPED" - SUCCEEDED = "SUCCEEDED" - FAILED = "FAILED" - - -@dataclass -class RayJobSpec: - """Specification for a RayJob Custom Resource""" - - # Required fields - entrypoint: str - """The command to execute for this job (e.g., "python script.py")""" - - # Optional fields - submission_id: Optional[str] = None - """Unique ID for the job submission. If not provided, one will be generated.""" - - runtime_env: Optional[Dict[str, Any]] = None - """Runtime environment configuration for the job, including: - - working_dir: Directory containing files that your job will run in - - pip: List of pip packages to install - - conda: Conda environment specification - - env_vars: Environment variables to set - - py_modules: Python modules to include - """ - - metadata: Optional[Dict[str, str]] = None - """Arbitrary metadata to store with the job""" - - entrypoint_num_cpus: Optional[Union[int, float]] = None - """Number of CPU cores to reserve for the entrypoint command""" - - entrypoint_num_gpus: Optional[Union[int, float]] = None - """Number of GPUs to reserve for the entrypoint command""" - - entrypoint_memory: Optional[int] = None - """Amount of memory to reserve for the entrypoint command""" - - entrypoint_resources: Optional[Dict[str, float]] = None - """Custom resources to reserve for the entrypoint command""" - - cluster_name: Optional[str] = None - """Name of the RayCluster to run this job on""" - - cluster_namespace: Optional[str] = None - """Namespace of the RayCluster to run this job on""" - - # Status fields (managed by the controller) - status: RayJobStatus = field(default=RayJobStatus.PENDING) - """Current status of the job""" - - message: Optional[str] = None - """Detailed status message""" - - start_time: Optional[str] = None - """Time when the job started""" - - end_time: Optional[str] = None - """Time when the job ended""" - - driver_info: Optional[Dict[str, str]] = None - """Information about the job driver, including: - - id: Driver ID - - node_ip_address: IP address of the node running the driver - - pid: Process ID of the driver - """ - - -@dataclass -class RayJob: - """RayJob Custom Resource Definition""" - - metadata: Dict[str, Any] - """Kubernetes metadata for the job""" - - spec: RayJobSpec - """Job specification""" - - api_version: str = "ray.io/v1" - kind: str = "RayJob" - - status: Optional[Dict[str, Any]] = None - """Status of the job (managed by the controller)""" - - def to_dict(self) -> Dict[str, Any]: - """Convert the RayJob to a dictionary suitable for Kubernetes API""" - return { - "apiVersion": self.api_version, - "kind": self.kind, - "metadata": self.metadata, - "spec": { - "entrypoint": self.spec.entrypoint, - "submission_id": self.spec.submission_id, - "runtime_env": self.spec.runtime_env, - "metadata": self.spec.metadata, - "entrypoint_num_cpus": self.spec.entrypoint_num_cpus, - "entrypoint_num_gpus": self.spec.entrypoint_num_gpus, - "entrypoint_memory": self.spec.entrypoint_memory, - "entrypoint_resources": self.spec.entrypoint_resources, - "cluster_name": self.spec.cluster_name, - "cluster_namespace": self.spec.cluster_namespace, - }, - "status": { - "status": self.spec.status, - "message": self.spec.message, - "start_time": self.spec.start_time, - "end_time": self.spec.end_time, - "driver_info": self.spec.driver_info, - } - if self.status is None - else self.status, - } - - def apply(self, force=False): - """ - Applies the RayJob using server-side apply. - If 'force' is set to True, conflicts will be forced. - - Args: - force (bool): If True, force conflicts during server-side apply. - """ - from kubernetes import client - from kubernetes.dynamic import DynamicClient - from ...common.kubernetes_cluster.auth import get_api_client, config_check - from ...common import _kube_api_error_handling - - CF_SDK_FIELD_MANAGER = "codeflare-sdk" - - try: - # Check Kubernetes configuration - config_check() - - # Get the dynamic client - crds = DynamicClient(get_api_client()).resources - - # Get the RayJob API instance - api_version = "ray.io/v1" - api_instance = crds.get(api_version=api_version, kind="RayJob") - - # Get namespace from metadata - namespace = self.metadata.get("namespace", "default") - name = self.metadata.get("name") - - # Convert job to dictionary - body = self.to_dict() - - # Apply the job using server-side apply - api_instance.server_side_apply( - field_manager=CF_SDK_FIELD_MANAGER, - group="ray.io", - version="v1", - namespace=namespace, - plural="rayjobs", - body=body, - force_conflicts=force, - ) - - print(f"RayJob: '{name}' has successfully been applied") - - except AttributeError as e: - raise RuntimeError(f"Failed to initialize DynamicClient: {e}") - except Exception as e: - return _kube_api_error_handling(e) diff --git a/src/codeflare_sdk/ray/rayjobs/test_rayjob.py b/src/codeflare_sdk/ray/rayjobs/test_rayjob.py index dccab7dd..1136e6e5 100644 --- a/src/codeflare_sdk/ray/rayjobs/test_rayjob.py +++ b/src/codeflare_sdk/ray/rayjobs/test_rayjob.py @@ -12,6 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. +import pytest from unittest.mock import MagicMock from codeflare_sdk.ray.rayjobs.rayjob import RayJob @@ -45,8 +46,8 @@ def test_rayjob_submit_success(mocker): assert job_id == "test-rayjob" # Verify the API was called with correct parameters - mock_api_instance.submit.assert_called_once() - call_args = mock_api_instance.submit.call_args + 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" @@ -58,3 +59,30 @@ def test_rayjob_submit_success(mocker): 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() diff --git a/test.ipynb b/test.ipynb deleted file mode 100644 index 84861a6c..00000000 --- a/test.ipynb +++ /dev/null @@ -1,169 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "8f8ed15a", - "metadata": {}, - "source": [ - "## Steps to reproduce the Job Agent bug\n", - "To get the below wheel file for codeflare-sdk set up you can run the following in your terminal \n", - "```bash\n", - "poetry lock\n", - "poetry install\n", - "poetry build\n", - "```\n", - "\n", - "Then you can run the below to install it. This is using a dev image of the kuberay python client found here -> https://test.pypi.org/project/odh-kuberay-client/#history. The referenced kuberay python client version is working as intended. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "10c8c12e", - "metadata": {}, - "outputs": [], - "source": [ - "%pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ dist/codeflare_sdk-0.0.0.dev0-py3-none-any.whl --force-reinstall" - ] - }, - { - "cell_type": "markdown", - "id": "3e021c61", - "metadata": {}, - "source": [ - "Below is the code I used to confirm that Kuberay Python Client is functional. It uses the cluster api to create a cluster, and submitting a job to this is successful. You don't need to run this" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5dc1a0fa", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "from odh_kuberay_client import kuberay_cluster_api\n", - "from odh_kuberay_client.utils import kuberay_cluster_builder\n", - "\n", - "cluster_name = \"working\"\n", - "namespace = \"default\"\n", - "\n", - "director = kuberay_cluster_builder.Director()\n", - "cluster_api = kuberay_cluster_api.RayClusterApi()\n", - "\n", - "# Build a small cluster\n", - "cluster_body = director.build_small_cluster(\n", - " name=cluster_name,\n", - " k8s_namespace=namespace,\n", - " labels={\"ray.io/cluster\": cluster_name},\n", - ")\n", - "\n", - "created_cluster = cluster_api.create_ray_cluster(\n", - " body=cluster_body, k8s_namespace=namespace\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "005c2ba2", - "metadata": {}, - "source": [ - "The below uses the default ray image. Creating this cluster and submitting a job will work. To recreate the bug, comment out the `image=\"ray-project/ray:2.47.1\"` line and submit the job again. Ensure the RayJob CR from the working job submission was deleted. \n", - "\n", - "You will need a Kind cluster with Kuberay installed for this to work FYI!" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cb80c155", - "metadata": {}, - "outputs": [], - "source": [ - "from codeflare_sdk import Cluster, ClusterConfiguration\n", - "\n", - "cluster = Cluster(ClusterConfiguration(\n", - " name='test-cluster',\n", - " namespace='default',\n", - " head_cpu_requests='1',\n", - " head_cpu_limits='2',\n", - " head_memory_requests=4,\n", - " head_memory_limits=5,\n", - " head_extended_resource_requests={'nvidia.com/gpu':0},\n", - " worker_extended_resource_requests={'nvidia.com/gpu':0},\n", - " num_workers=1,\n", - " worker_cpu_requests='1',\n", - " worker_cpu_limits='2',\n", - " worker_memory_requests=3,\n", - " worker_memory_limits=4,\n", - " image=\"ray-project/ray:2.47.1\" # this image works, omit this line to use our default image which does not work\n", - "))\n", - "\n", - "cluster.apply()" - ] - }, - { - "cell_type": "markdown", - "id": "94841b95", - "metadata": {}, - "source": [ - "With the below, a pod gets created which submits the job. This will be marked as completed if its successful and you can view the job in the Dashboard as normal. If not, it will fail, and the CR will try to recreate new pods in a loop" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c5e3c895", - "metadata": {}, - "outputs": [], - "source": [ - "from odh_kuberay_client.kuberay_job_api import RayjobApi\n", - "\n", - "rayjob_api = RayjobApi()\n", - "\n", - "job_body = {\n", - " \"apiVersion\": \"ray.io/v1\",\n", - " \"kind\": \"RayJob\",\n", - " \"metadata\": {\n", - " \"name\": \"test-job\",\n", - " \"namespace\": \"default\",\n", - " \"labels\": {\n", - " \"app.kubernetes.io/name\": \"test-job\",\n", - " \"app.kubernetes.io/managed-by\": \"kuberay\",\n", - " },\n", - " },\n", - " \"spec\": {\n", - " \"clusterSelector\": {\n", - " \"ray.io/cluster\": \"test-cluster\",\n", - " },\n", - " \"entrypoint\": 'python -c \"import time; time.sleep(20)\"',\n", - " \"submissionMode\": \"K8sJobMode\",\n", - " },\n", - "}\n", - "\n", - "rayjob_api.submit_job(job=job_body, k8s_namespace=\"default\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "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": "3.11.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} 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 From 797942911b98f28c7a28bc17b1fe6aba1661a5a6 Mon Sep 17 00:00:00 2001 From: Pat O'Connor Date: Mon, 28 Jul 2025 14:40:43 +0100 Subject: [PATCH 6/7] task(RHOAIENG-26590): Report RayJob status via SDK Signed-off-by: Pat O'Connor --- src/codeflare_sdk/ray/__init__.py | 3 + src/codeflare_sdk/ray/rayjobs/__init__.py | 1 + src/codeflare_sdk/ray/rayjobs/pretty_print.py | 104 ++++++++ src/codeflare_sdk/ray/rayjobs/rayjob.py | 76 +++++- src/codeflare_sdk/ray/rayjobs/status.py | 62 +++++ .../ray/rayjobs/test_pretty_print.py | 246 ++++++++++++++++++ src/codeflare_sdk/ray/rayjobs/test_status.py | 219 ++++++++++++++++ 7 files changed, 708 insertions(+), 3 deletions(-) create mode 100644 src/codeflare_sdk/ray/rayjobs/pretty_print.py create mode 100644 src/codeflare_sdk/ray/rayjobs/status.py create mode 100644 src/codeflare_sdk/ray/rayjobs/test_pretty_print.py create mode 100644 src/codeflare_sdk/ray/rayjobs/test_status.py diff --git a/src/codeflare_sdk/ray/__init__.py b/src/codeflare_sdk/ray/__init__.py index 7c8e84da..b2278a05 100644 --- a/src/codeflare_sdk/ray/__init__.py +++ b/src/codeflare_sdk/ray/__init__.py @@ -6,6 +6,9 @@ from .rayjobs import ( RayJob, + RayJobDeploymentStatus, + CodeflareRayJobStatus, + RayJobInfo, ) from .cluster import ( diff --git a/src/codeflare_sdk/ray/rayjobs/__init__.py b/src/codeflare_sdk/ray/rayjobs/__init__.py index d9cbae34..47b573af 100644 --- a/src/codeflare_sdk/ray/rayjobs/__init__.py +++ b/src/codeflare_sdk/ray/rayjobs/__init__.py @@ -1 +1,2 @@ from .rayjob import RayJob +from .status import RayJobDeploymentStatus, CodeflareRayJobStatus, RayJobInfo 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..a9f559db --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/pretty_print.py @@ -0,0 +1,104 @@ +# 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(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("Have you run rayjob.submit() yet?") + 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) \ No newline at end of file diff --git a/src/codeflare_sdk/ray/rayjobs/rayjob.py b/src/codeflare_sdk/ray/rayjobs/rayjob.py index e7a9a588..f018ee4f 100644 --- a/src/codeflare_sdk/ray/rayjobs/rayjob.py +++ b/src/codeflare_sdk/ray/rayjobs/rayjob.py @@ -3,9 +3,16 @@ """ import logging -from typing import Dict, Any, Optional +from typing import Dict, Any, Optional, Tuple from odh_kuberay_client.kuberay_job_api import RayjobApi +from .status import ( + RayJobDeploymentStatus, + CodeflareRayJobStatus, + RayJobInfo, +) +from . import pretty_print + # Set up logging logger = logging.getLogger(__name__) @@ -15,7 +22,7 @@ class RayJob: A client for managing Ray jobs using the KubeRay operator. This class provides a simplified interface for submitting and managing - Ray jobs in a Kubernetes cluster with the KubeRay operator installed. + Ray jobs via the Codeflare SDK (using the KubeRay RayJob python client). """ def __init__( @@ -40,7 +47,7 @@ def __init__( self.cluster_name = cluster_name self.entrypoint = entrypoint self.runtime_env = runtime_env - + # Initialize the KubeRay job API client self._api = RayjobApi() @@ -109,3 +116,66 @@ def _build_rayjob_cr( rayjob_cr["spec"]["runtimeEnvYAML"] = str(runtime_env) 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: 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), + dashboard_url=status_data.get('dashboardURL') + ) + + # 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..345c3717 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/status.py @@ -0,0 +1,62 @@ +# 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 + dashboard_url: Optional[str] = None \ No newline at end of file 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..14beef30 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/test_pretty_print.py @@ -0,0 +1,246 @@ +# 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("[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("[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("[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("Have you run rayjob.submit() yet?"), # 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) \ No newline at end of file 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..a42a8c04 --- /dev/null +++ b/src/codeflare_sdk/ray/rayjobs/test_status.py @@ -0,0 +1,219 @@ +# 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, + 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', + '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, + 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', + '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, + 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', + '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, + 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', + '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, + dashboard_url="test-cluster-head-svc.test-ns.svc.cluster.local:8265" + ) + + # 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 + assert job_info.dashboard_url == "test-cluster-head-svc.test-ns.svc.cluster.local:8265" \ No newline at end of file From b8b973998641fdec9450456200f993fe0f5b91f7 Mon Sep 17 00:00:00 2001 From: Pat O'Connor Date: Tue, 29 Jul 2025 12:33:39 +0100 Subject: [PATCH 7/7] feat(RHOAIENG-26487): Cluster lifecycling via RayJob Signed-off-by: Pat O'Connor --- src/codeflare_sdk/ray/rayjobs/pretty_print.py | 41 ++-- src/codeflare_sdk/ray/rayjobs/rayjob.py | 230 +++++++++++++----- src/codeflare_sdk/ray/rayjobs/status.py | 6 +- .../ray/rayjobs/test_pretty_print.py | 115 +++++---- src/codeflare_sdk/ray/rayjobs/test_rayjob.py | 225 ++++++++++++++++- src/codeflare_sdk/ray/rayjobs/test_status.py | 124 +++++----- 6 files changed, 551 insertions(+), 190 deletions(-) diff --git a/src/codeflare_sdk/ray/rayjobs/pretty_print.py b/src/codeflare_sdk/ray/rayjobs/pretty_print.py index a9f559db..c9a239cc 100644 --- a/src/codeflare_sdk/ray/rayjobs/pretty_print.py +++ b/src/codeflare_sdk/ray/rayjobs/pretty_print.py @@ -30,22 +30,23 @@ 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) @@ -54,36 +55,46 @@ 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 = _create_info_table( + "[white on red][bold]Name", job_name, "[bold red]No RayJob found" + ) table.add_row() table.add_row("Have you run rayjob.submit() yet?") 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.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"), + RayJobDeploymentStatus.SUSPENDED: ( + "Suspended :pause_button:", + "[white on yellow][bold]Name", + ), } - - return status_mapping.get(status, ("Unknown :question:", "[white on red][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 """ @@ -99,6 +110,8 @@ 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 = Table( + box=None, title="[bold] :package: CodeFlare RayJob Status :package:" + ) main_table.add_row(Panel.fit(table)) - console.print(main_table) \ No newline at end of file + console.print(main_table) diff --git a/src/codeflare_sdk/ray/rayjobs/rayjob.py b/src/codeflare_sdk/ray/rayjobs/rayjob.py index f018ee4f..b0aa8af7 100644 --- a/src/codeflare_sdk/ray/rayjobs/rayjob.py +++ b/src/codeflare_sdk/ray/rayjobs/rayjob.py @@ -6,14 +6,18 @@ from typing import Dict, Any, Optional, Tuple from odh_kuberay_client.kuberay_job_api import RayjobApi +from ..cluster.cluster import Cluster +from ..cluster.config import ClusterConfiguration +from ..cluster.build_ray_cluster import build_ray_cluster + from .status import ( RayJobDeploymentStatus, - CodeflareRayJobStatus, + CodeflareRayJobStatus, RayJobInfo, ) from . import pretty_print -# Set up logging + logger = logging.getLogger(__name__) @@ -22,80 +26,117 @@ class RayJob: A client for managing Ray jobs using the KubeRay operator. This class provides a simplified interface for submitting and managing - Ray jobs via the Codeflare SDK (using the KubeRay RayJob python client). + Ray jobs via the CodeFlare SDK. It can work with existing clusters or + create new clusters automatically using the native RayJob CRD capabilities. """ def __init__( self, job_name: str, - cluster_name: str, + cluster_name: Optional[str] = None, + cluster_config: Optional[ClusterConfiguration] = None, namespace: str = "default", - entrypoint: str = "None", + entrypoint: Optional[str] = None, runtime_env: Optional[Dict[str, Any]] = None, + shutdown_after_job_finishes: bool = True, + ttl_seconds_after_finished: int = 0, + active_deadline_seconds: Optional[int] = None, ): """ Initialize a RayJob instance. Args: - name: The name for the Ray job - namespace: The Kubernetes namespace to submit the job to (default: "default") - cluster_name: The name of the Ray cluster to submit the job to - **kwargs: Additional configuration options + job_name: The name for the Ray job + 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 (default: "default") + entrypoint: The Python script or command to run (required for submission) + runtime_env: Ray runtime environment configuration (optional) + shutdown_after_job_finishes: Whether to automatically cleanup the cluster after job completion (default: True) + 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) """ + # Validate input parameters + if cluster_name is None and cluster_config is None: + raise ValueError("Either cluster_name or cluster_config must be provided") + + if cluster_name is not None and cluster_config is not None: + raise ValueError("Cannot specify both cluster_name and cluster_config") + self.name = job_name self.namespace = namespace - self.cluster_name = cluster_name self.entrypoint = entrypoint self.runtime_env = runtime_env - + self.shutdown_after_job_finishes = shutdown_after_job_finishes + self.ttl_seconds_after_finished = ttl_seconds_after_finished + self.active_deadline_seconds = active_deadline_seconds + + # Cluster configuration + self._cluster_name = cluster_name + self._cluster_config = cluster_config + + # Determine cluster name for the job + if cluster_config is not None: + # Ensure cluster config has the same namespace as the job + if cluster_config.namespace is None: + cluster_config.namespace = namespace + elif cluster_config.namespace != namespace: + logger.warning( + f"Cluster config namespace ({cluster_config.namespace}) differs from job namespace ({namespace})" + ) + + self.cluster_name = cluster_config.name or f"{job_name}-cluster" + # Update the cluster config name if it wasn't set + if not cluster_config.name: + cluster_config.name = self.cluster_name + else: + self.cluster_name = cluster_name + # Initialize the KubeRay job API client self._api = RayjobApi() logger.info(f"Initialized RayJob: {self.name} in namespace: {self.namespace}") - def submit( - self, - ) -> str: + def submit(self) -> str: """ Submit the Ray job to the Kubernetes cluster. - Args: - entrypoint: The Python script or command to run - runtime_env: Ray runtime environment configuration (optional) + The RayJob CRD will automatically: + - Create a new cluster if cluster_config was provided + - Use existing cluster if cluster_name was provided + - Clean up resources based on shutdown_after_job_finishes setting Returns: The job ID/name if submission was successful Raises: - RuntimeError: If the job has already been submitted or submission fails + ValueError: If entrypoint is not provided + RuntimeError: If job submission fails """ + # 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( - entrypoint=self.entrypoint, - runtime_env=self.runtime_env, - ) + rayjob_cr = self._build_rayjob_cr() - # Submit the job - logger.info( - f"Submitting RayJob {self.name} to RayCluster {self.cluster_name} in namespace {self.namespace}" - ) + # 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, - entrypoint: str, - runtime_env: Optional[Dict[str, Any]] = None, - ) -> Dict[str, Any]: + def _build_rayjob_cr(self) -> Dict[str, Any]: """ - Build the RayJob custom resource specification. - - This creates a minimal RayJob CR that can be extended later. + Build the RayJob custom resource specification using native RayJob capabilities. """ # Basic RayJob custom resource structure rayjob_cr = { @@ -106,68 +147,131 @@ def _build_rayjob_cr( "namespace": self.namespace, }, "spec": { - "entrypoint": entrypoint, - "clusterSelector": {"ray.io/cluster": self.cluster_name}, + "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 runtime_env: - rayjob_cr["spec"]["runtimeEnvYAML"] = str(runtime_env) + 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: + # Use rayClusterSpec to create a new cluster - leverage existing build logic + ray_cluster_spec = self._build_ray_cluster_spec() + 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]: + + def _build_ray_cluster_spec(self) -> Dict[str, Any]: + """ + Build the RayCluster spec from ClusterConfiguration using existing build_ray_cluster logic. + + Returns: + Dict containing the RayCluster spec for embedding in RayJob + """ + if not self._cluster_config: + raise RuntimeError("No cluster configuration provided") + + # Create a shallow copy of the cluster config to avoid modifying the original + import copy + + temp_config = copy.copy(self._cluster_config) + + # Ensure we get a RayCluster (not AppWrapper) and don't write to file + temp_config.appwrapper = False + temp_config.write_to_file = False + + # Create a minimal Cluster object for the build process + from ..cluster.cluster import Cluster + + temp_cluster = Cluster.__new__(Cluster) # Create without calling __init__ + temp_cluster.config = temp_config + + """ + For now, RayJob with a new/auto-created cluster will not work with Kueue. + This is due to the Kueue label not being propagated to the RayCluster. + """ + + # Use the existing build_ray_cluster function to generate the RayCluster + ray_cluster_dict = build_ray_cluster(temp_cluster) + + # Extract just the RayCluster spec - RayJob CRD doesn't support metadata in rayClusterSpec + # Note: CodeFlare Operator should still create dashboard routes for the RayCluster + ray_cluster_spec = ray_cluster_dict["spec"] + + logger.info( + f"Built RayCluster spec using existing build logic for cluster: {self.cluster_name}" + ) + return ray_cluster_spec + + def status( + self, print_to_console: bool = True + ) -> Tuple[CodeflareRayJobStatus, bool]: """ Get the status of the Ray job. - + Args: print_to_console: 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) - + 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') - + 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', ''), + 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), - dashboard_url=status_data.get('dashboardURL') + 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]: + + 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) """ @@ -177,5 +281,7 @@ def _map_to_codeflare_status(self, deployment_status: RayJobDeploymentStatus) -> RayJobDeploymentStatus.FAILED: (CodeflareRayJobStatus.FAILED, False), RayJobDeploymentStatus.SUSPENDED: (CodeflareRayJobStatus.SUSPENDED, False), } - - return status_mapping.get(deployment_status, (CodeflareRayJobStatus.UNKNOWN, 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 index 345c3717..027ed09c 100644 --- a/src/codeflare_sdk/ray/rayjobs/status.py +++ b/src/codeflare_sdk/ray/rayjobs/status.py @@ -27,8 +27,9 @@ class RayJobDeploymentStatus(Enum): """ Defines the possible deployment states of a Ray job (from the KubeRay RayJob API). """ + COMPLETE = "Complete" - RUNNING = "Running" + RUNNING = "Running" FAILED = "Failed" SUSPENDED = "Suspended" UNKNOWN = "Unknown" @@ -38,6 +39,7 @@ class CodeflareRayJobStatus(Enum): """ Defines the possible reportable states of a CodeFlare Ray job. """ + COMPLETE = 1 RUNNING = 2 FAILED = 3 @@ -50,6 +52,7 @@ class RayJobInfo: """ For storing information about a Ray job. """ + name: str job_id: str status: RayJobDeploymentStatus @@ -59,4 +62,3 @@ class RayJobInfo: end_time: Optional[str] = None failed_attempts: int = 0 succeeded_attempts: int = 0 - dashboard_url: Optional[str] = None \ No newline at end of file diff --git a/src/codeflare_sdk/ray/rayjobs/test_pretty_print.py b/src/codeflare_sdk/ray/rayjobs/test_pretty_print.py index 14beef30..f4334bf2 100644 --- a/src/codeflare_sdk/ray/rayjobs/test_pretty_print.py +++ b/src/codeflare_sdk/ray/rayjobs/test_pretty_print.py @@ -29,22 +29,22 @@ def test_get_status_display(): 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:" @@ -60,15 +60,17 @@ def test_print_job_status_running_format(mocker): 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) - + + 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", @@ -78,38 +80,43 @@ def test_print_job_status_running_format(mocker): cluster_name="test-cluster", start_time="2025-07-28T11:37:07Z", failed_attempts=0, - succeeded_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 + 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( + "[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) @@ -123,15 +130,17 @@ def test_print_job_status_complete_format(mocker): 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) - + + 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", @@ -141,21 +150,24 @@ def test_print_job_status_complete_format(mocker): cluster_name="prod-cluster", start_time="2025-07-28T11:37:07Z", failed_attempts=0, - succeeded_attempts=1 + 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( + "[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) @@ -170,15 +182,17 @@ def test_print_job_status_failed_with_attempts_format(mocker): 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) - + + 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", @@ -188,12 +202,12 @@ def test_print_job_status_failed_with_attempts_format(mocker): cluster_name="test-cluster", start_time="2025-07-28T11:37:07Z", failed_attempts=3, # Has failures - succeeded_attempts=0 + 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 @@ -203,6 +217,7 @@ def test_print_job_status_failed_with_attempts_format(mocker): 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 ] @@ -218,22 +233,26 @@ def test_print_no_job_found_format(mocker): 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) - + + 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( + "[bold underline]missing-job", "[bold red]No RayJob found" + ), # Error message in red call(), # Empty separator call(), # Another empty row call("Have you run rayjob.submit() yet?"), # Helpful hint @@ -241,6 +260,6 @@ def test_print_no_job_found_format(mocker): 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) \ No newline at end of file + 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 index 1136e6e5..6665c2e4 100644 --- a/src/codeflare_sdk/ray/rayjobs/test_rayjob.py +++ b/src/codeflare_sdk/ray/rayjobs/test_rayjob.py @@ -13,8 +13,9 @@ # limitations under the License. import pytest -from unittest.mock import MagicMock +from unittest.mock import MagicMock, patch from codeflare_sdk.ray.rayjobs.rayjob import RayJob +from codeflare_sdk.ray.cluster.config import ClusterConfiguration def test_rayjob_submit_success(mocker): @@ -86,3 +87,225 @@ def test_rayjob_submit_failure(mocker): # 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(): + """Test that providing both cluster_name and cluster_config raises error.""" + cluster_config = ClusterConfiguration(name="test-cluster", namespace="test") + + with pytest.raises( + ValueError, match="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(): + """Test that providing neither cluster_name nor cluster_config raises error.""" + with pytest.raises( + ValueError, match="Either cluster_name or cluster_config must be provided" + ): + RayJob(job_name="test-job", entrypoint="python script.py") + + +def test_rayjob_init_with_cluster_config(): + """Test RayJob initialization with cluster configuration for auto-creation.""" + cluster_config = ClusterConfiguration( + name="auto-cluster", namespace="test-namespace", num_workers=2 + ) + + rayjob = RayJob( + job_name="test-job", + cluster_config=cluster_config, + entrypoint="python script.py", + ) + + assert rayjob.name == "test-job" + assert rayjob.cluster_name == "auto-cluster" + assert rayjob._cluster_config == cluster_config + assert rayjob._cluster_name is None + + +def test_rayjob_cluster_name_generation(): + """Test that cluster names are generated when config has empty name.""" + cluster_config = ClusterConfiguration( + name="", # Empty name should trigger generation + namespace="test-namespace", + num_workers=1, + ) + + rayjob = RayJob( + job_name="my-job", cluster_config=cluster_config, entrypoint="python script.py" + ) + + assert rayjob.cluster_name == "my-job-cluster" + assert cluster_config.name == "my-job-cluster" # Should be updated + + +@patch("codeflare_sdk.ray.rayjobs.rayjob.build_ray_cluster") +def test_build_ray_cluster_spec(mock_build_ray_cluster, mocker): + """Test _build_ray_cluster_spec method.""" + mocker.patch("kubernetes.config.load_kube_config") + + mock_ray_cluster = { + "apiVersion": "ray.io/v1", + "kind": "RayCluster", + "metadata": {"name": "test-cluster", "namespace": "test"}, + "spec": { + "rayVersion": "2.9.0", + "headGroupSpec": {"replicas": 1}, + "workerGroupSpecs": [{"replicas": 2}], + }, + } + mock_build_ray_cluster.return_value = mock_ray_cluster + + cluster_config = ClusterConfiguration( + name="test-cluster", namespace="test", num_workers=2 + ) + + rayjob = RayJob( + job_name="test-job", + cluster_config=cluster_config, + entrypoint="python script.py", + ) + + spec = rayjob._build_ray_cluster_spec() + + # Should return only the spec part, not metadata + assert spec == mock_ray_cluster["spec"] + assert "metadata" not in spec + + # Verify build_ray_cluster was called with correct parameters + mock_build_ray_cluster.assert_called_once() + call_args = mock_build_ray_cluster.call_args[0][0] + assert call_args.config.appwrapper is False + assert call_args.config.write_to_file is False + + +def test_build_rayjob_cr_with_existing_cluster(mocker): + """Test _build_rayjob_cr method with existing cluster.""" + mocker.patch("kubernetes.config.load_kube_config") + + rayjob = RayJob( + job_name="test-job", + cluster_name="existing-cluster", + namespace="test-namespace", + entrypoint="python main.py", + shutdown_after_job_finishes=False, + 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" + 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 + + +@patch("codeflare_sdk.ray.rayjobs.rayjob.build_ray_cluster") +def test_build_rayjob_cr_with_auto_cluster(mock_build_ray_cluster, mocker): + """Test _build_rayjob_cr method with auto-created cluster.""" + mocker.patch("kubernetes.config.load_kube_config") + + mock_ray_cluster = { + "apiVersion": "ray.io/v1", + "kind": "RayCluster", + "metadata": {"name": "auto-cluster", "namespace": "test"}, + "spec": { + "rayVersion": "2.9.0", + "headGroupSpec": {"replicas": 1}, + "workerGroupSpecs": [{"replicas": 2}], + }, + } + mock_build_ray_cluster.return_value = mock_ray_cluster + + cluster_config = ClusterConfiguration( + name="auto-cluster", namespace="test-namespace", num_workers=2 + ) + + rayjob = RayJob( + job_name="test-job", cluster_config=cluster_config, entrypoint="python main.py" + ) + + 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 + ) + + with pytest.raises( + ValueError, match="entrypoint must be provided to submit a RayJob" + ): + rayjob.submit() + + +@patch("codeflare_sdk.ray.rayjobs.rayjob.build_ray_cluster") +def test_submit_with_auto_cluster(mock_build_ray_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": "2.9.0", + "headGroupSpec": {"replicas": 1}, + "workerGroupSpecs": [{"replicas": 1}], + }, + } + mock_build_ray_cluster.return_value = mock_ray_cluster + + # 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 + + cluster_config = ClusterConfiguration( + name="auto-cluster", namespace="test", num_workers=1 + ) + + rayjob = RayJob( + job_name="test-job", + cluster_config=cluster_config, + entrypoint="python script.py", + ) + + 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"] diff --git a/src/codeflare_sdk/ray/rayjobs/test_status.py b/src/codeflare_sdk/ray/rayjobs/test_status.py index a42a8c04..88cc2d58 100644 --- a/src/codeflare_sdk/ray/rayjobs/test_status.py +++ b/src/codeflare_sdk/ray/rayjobs/test_status.py @@ -27,74 +27,74 @@ def test_rayjob_status(mocker): # 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", + cluster_name="test-cluster", namespace="test-ns", - entrypoint="python test.py" + 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, - 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', - 'rayClusterName': 'test-cluster' + "jobId": "test-job-abc123", + "jobDeploymentStatus": "Running", + "startTime": "2025-07-28T11:37:07Z", + "failed": 0, + "succeeded": 0, + "dashboardURL": "test-cluster-head-svc.test-ns.svc.cluster.local:8265", + "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, - 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', - 'rayClusterName': 'test-cluster' + "jobId": "test-job-abc123", + "jobDeploymentStatus": "Complete", + "startTime": "2025-07-28T11:37:07Z", + "endTime": "2025-07-28T11:42:30Z", + "failed": 0, + "succeeded": 1, + "dashboardURL": "test-cluster-head-svc.test-ns.svc.cluster.local:8265", + "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, - 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', - 'rayClusterName': 'test-cluster' + "jobId": "test-job-abc123", + "jobDeploymentStatus": "Failed", + "startTime": "2025-07-28T11:37:07Z", + "endTime": "2025-07-28T11:42:30Z", + "failed": 1, + "succeeded": 0, + "dashboardURL": "test-cluster-head-svc.test-ns.svc.cluster.local:8265", + "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, - 'dashboardURL': 'test-cluster-head-svc.test-ns.svc.cluster.local:8265', - 'rayClusterName': 'test-cluster' + "jobId": "test-job-abc123", + "jobDeploymentStatus": "Suspended", + "startTime": "2025-07-28T11:37:07Z", + "failed": 0, + "succeeded": 0, + "dashboardURL": "test-cluster-head-svc.test-ns.svc.cluster.local:8265", + "rayClusterName": "test-cluster", } status, ready = rayjob.status(print_to_console=False) assert status == CodeflareRayJobStatus.SUSPENDED @@ -107,23 +107,23 @@ def test_rayjob_status_unknown_deployment_status(mocker): """ 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" + 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, + "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 @@ -135,20 +135,20 @@ def test_rayjob_status_missing_fields(mocker): """ 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" + 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', + "jobDeploymentStatus": "Running", } - + status, ready = rayjob.status(print_to_console=False) assert status == CodeflareRayJobStatus.RUNNING assert ready == False @@ -160,31 +160,31 @@ def test_map_to_codeflare_status(mocker): """ # 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" + 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 @@ -196,16 +196,15 @@ def test_rayjob_info_dataclass(): """ job_info = RayJobInfo( name="test-job", - job_id="test-job-abc123", + 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, - dashboard_url="test-cluster-head-svc.test-ns.svc.cluster.local:8265" ) - + # Test all fields are accessible assert job_info.name == "test-job" assert job_info.job_id == "test-job-abc123" @@ -216,4 +215,3 @@ def test_rayjob_info_dataclass(): assert job_info.end_time is None # Default value assert job_info.failed_attempts == 0 assert job_info.succeeded_attempts == 0 - assert job_info.dashboard_url == "test-cluster-head-svc.test-ns.svc.cluster.local:8265" \ No newline at end of file