codeflare_sdk.ray.rayjobs package

Submodules

codeflare_sdk.ray.rayjobs.config module

Cluster spec building and file volume helpers for RayJobs.

Uses ClusterConfiguration from ray.cluster.config as the single config object.

codeflare_sdk.ray.rayjobs.config.add_file_volumes(config: ClusterConfiguration, secret_name: str, mount_path: str = '/home/ray/files') → None

Add file volume and mount to a ClusterConfiguration.

codeflare_sdk.ray.rayjobs.config.build_file_secret_spec(job_name: str, namespace: str, files: Dict[str, str]) → Dict[str, Any]

Build Secret specification for RayJob files.

codeflare_sdk.ray.rayjobs.config.build_file_volume_specs(secret_name: str, mount_path: str = '/home/ray/files') → Tuple[Dict[str, Any], Dict[str, Any]]

Build volume and mount specs for RayJob files.

codeflare_sdk.ray.rayjobs.config.build_ray_cluster_spec(config: ClusterConfiguration, cluster_name: str) → Dict[str, Any]

Build the inner RayCluster spec dict from a ClusterConfiguration for embedding in a RayJob.

Produces the same CRD structure as build_ray_cluster.py but returns only the spec portion (no apiVersion/kind/metadata) and sets restartPolicy: Never.

Args:

config: The cluster configuration. cluster_name: Name for the cluster (derived from the RayJob name).

Returns:

Dict containing the RayCluster spec for embedding in RayJob CR.

codeflare_sdk.ray.rayjobs.config.validate_secret_size(files: Dict[str, str]) → None

Validate that combined file size doesn’t exceed Kubernetes Secret 1MB limit.

codeflare_sdk.ray.rayjobs.pretty_print module

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.

codeflare_sdk.ray.rayjobs.pretty_print.print_job_status(job_info: RayJobInfo)

Pretty print the job status in a format similar to cluster status.

codeflare_sdk.ray.rayjobs.pretty_print.print_no_job_found(job_name: str, namespace: str)

Print a message when no job is found.

codeflare_sdk.ray.rayjobs.rayjob module

RayJob client for submitting and managing Ray jobs using the kuberay python client.

class codeflare_sdk.ray.rayjobs.rayjob.RayJob(job_name: str, entrypoint: str, cluster_name: str | None = None, cluster_config: ClusterConfiguration | None = None, namespace: str | None = None, runtime_env: RuntimeEnv | Dict[str, Any] | None = None, ttl_seconds_after_finished: int = 0, active_deadline_seconds: int | None = None, local_queue: str | None = None, priority_class: str | None = None, api_client: ApiClient | None = None)

Bases: object

A client for managing Ray jobs using the KubeRay operator.

This class provides a simplified interface for submitting and managing RayJob CRs (using the KubeRay RayJob python client).

delete() → bool

Delete the Ray job. Returns True if deleted successfully or if already deleted.

resubmit() → bool

Resubmit the Ray job.

status(print_to_console: bool = True) → Tuple[CodeflareRayJobStatus, bool]

Get the status of the Ray job.

Args:

print_to_console (bool): Whether to print formatted status to console (default: True)

Returns:

Tuple of (CodeflareRayJobStatus, ready: bool) where ready indicates job completion

stop() → bool

Suspend the Ray job.

submit() → str

codeflare_sdk.ray.rayjobs.runtime_env module

codeflare_sdk.ray.rayjobs.runtime_env.create_file_secret(job: RayJob, files: Dict[str, str], rayjob_result: Dict[str, Any])

Create Secret with owner reference for local files.

codeflare_sdk.ray.rayjobs.runtime_env.create_secret_from_spec(job: RayJob, secret_spec: Dict[str, Any], rayjob_result: Dict[str, Any] = None) → str

Create Secret from specification via Kubernetes API.

Args:

secret_spec: Secret specification dictionary rayjob_result: The result from RayJob creation containing UID

Returns:

str: Name of the created Secret

codeflare_sdk.ray.rayjobs.runtime_env.extract_all_local_files(job: RayJob) → Dict[str, str] | None

Prepare local files for Secret upload.

• If runtime_env has local working_dir: zip entire directory into single file

• If single entrypoint file (no working_dir): extract that file

• If remote working_dir URL: return None (pass through to Ray)

Returns:

Dict with either: - {“working_dir.zip”: <base64_encoded_zip>} for zipped directories - {“script.py”: <file_content>} for single files - None for remote working_dir or no files

codeflare_sdk.ray.rayjobs.runtime_env.parse_requirements_file(requirements_path: str) → List[str] | None

Parse a requirements.txt file and return list of dependencies.

Args:

requirements_path: Path to requirements.txt file

Returns:

List of pip dependencies

codeflare_sdk.ray.rayjobs.runtime_env.process_pip_dependencies(job: RayJob, pip_spec) → List[str] | None

Process pip dependencies from runtime_env.

Args:

pip_spec: Can be a list of packages, a string path to requirements.txt, or dict

Returns:

List of pip dependencies

codeflare_sdk.ray.rayjobs.runtime_env.process_runtime_env(job: RayJob, files: Dict[str, str] | None = None) → str | None

Process runtime_env field to handle env_vars, pip dependencies, and working_dir.

Returns:

Processed runtime environment as YAML string, or None if no processing needed

codeflare_sdk.ray.rayjobs.status module

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.

class codeflare_sdk.ray.rayjobs.status.CodeflareRayJobStatus(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

Defines the possible reportable states of a CodeFlare Ray job.

COMPLETE = 1

FAILED = 3

RUNNING = 2

SUSPENDED = 4

UNKNOWN = 5

class codeflare_sdk.ray.rayjobs.status.RayJobDeploymentStatus(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

Defines the possible deployment states of a Ray job (from the KubeRay RayJob API).

COMPLETE = 'Complete'

FAILED = 'Failed'

RUNNING = 'Running'

SUSPENDED = 'Suspended'

UNKNOWN = 'Unknown'

class codeflare_sdk.ray.rayjobs.status.RayJobInfo(name: str, job_id: str, status: RayJobDeploymentStatus, namespace: str, cluster_name: str, start_time: str | None = None, end_time: str | None = None, failed_attempts: int = 0, succeeded_attempts: int = 0)

Bases: object

For storing information about a Ray job.

cluster_name: str

end_time: str | None = None

failed_attempts: int = 0

job_id: str

name: str

namespace: str

start_time: str | None = None

status: RayJobDeploymentStatus

succeeded_attempts: int = 0

Module contents