`JobManager`#

class pyedb.workflows.job_manager.backend.service.JobManager(resource_limits: ResourceLimits = None, scheduler_type: pyedb.workflows.job_manager.backend.job_submission.SchedulerType = SchedulerType.NONE)#

Async job manager combining resource monitoring and job scheduling.

This class provides the core functionality for:

Resource monitoring via ResourceMonitor
Job scheduling via JobPoolManager
REST/Socket.IO API via aiohttp web server
Background task for continuous job processing

Parameters:

resource_limitsResourceLimits, optional: Host constraints. Creates default instance if None.
scheduler_typeSchedulerType, optional: Type of job scheduler to use. Default is SchedulerType.NONE.

Attributes:

jobsDict[str, JobInfo]: Dictionary of all managed jobs
resource_limitsResourceLimits: Current resource constraints
job_poolJobPoolManager: Priority-aware job queue manager
resource_monitorResourceMonitor: Host resource usage monitor
ansys_pathstr or None: Path to ANSYS EDT executable
siosocketio.AsyncServer: Socket.IO server for real-time updates
appweb.Application: aiohttp web application

Overview#

Methods

`setup_routes`	Internal method that wires aiohttp routes to class methods.
`handle_get_system_status`	Get system and scheduler status.
`handle_get_partitions`	Get scheduler partitions/queues.
`handle_start_monitoring`	Manually start resource monitoring.
`handle_index`	Serve the main web interface.
`handle_submit_job`	Submit a new job for execution.
`handle_cancel_job`	Cancel a running or queued job.
`handle_get_jobs`	Get list of all jobs.
`handle_get_resources`	Get current resource usage.
`handle_get_queue`	Get queue statistics.
`handle_set_priority`	Change job priority and re-queue.
`handle_edit_concurrent_limits`	Edit concurrent job limits.
`wait_until_all_done`	Coroutine that blocks until every job reaches a terminal state.
`submit_job`	Async entry point for job submission.
`cancel_job`	Cancel a queued or running job.
`edit_concurrent_limits`	Edit concurrent job limits in the pool.

Attributes

`jobs`
`resource_limits`
`job_pool`
`resource_monitor`
`ansys_path`
`scheduler_type`
`sio`
`app`

Import detail#

from pyedb.workflows.job_manager.backend.service import JobManager

Attribute detail#

JobManager.jobs: Dict[str, JobInfo]#

JobManager.resource_limits = None#

JobManager.job_pool#

JobManager.resource_monitor#

JobManager.ansys_path = None#

JobManager.scheduler_type#

JobManager.sio#

JobManager.app#

Method detail#

JobManager.setup_routes()#

Internal method that wires aiohttp routes to class methods.

Called once from __init__. Sets up all REST API endpoints.

async JobManager.handle_get_system_status(request)#

Get system and scheduler status.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON response with system status information

async JobManager.handle_get_partitions(request)#

Get scheduler partitions/queues.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON response with partition information or error

async JobManager.handle_start_monitoring(request)#

Manually start resource monitoring.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON response indicating success or failure

async JobManager.handle_index(request)#

Serve the main web interface.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.FileResponse: Static HTML file

async JobManager.handle_submit_job(request)#

Submit a new job for execution.

Parameters:

requestaiohttp.web.Request: HTTP POST request with JSON payload

Returns:

aiohttp.web.Response: JSON response with job ID or error

Notes

Expected JSON payload:

{
    "config": {
        "jobid": "job_123",
        "project_path": "/path/to/project.aedt",
        ... other HFSS config fields
    },
    "priority": 0
}

async JobManager.handle_cancel_job(request)#

Cancel a running or queued job.

Parameters:

requestaiohttp.web.Request: HTTP request with job_id in URL path

Returns:

aiohttp.web.Response: JSON response indicating success or failure

async JobManager.handle_get_jobs(request)#

Get list of all jobs.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON array of job objects with status information

async JobManager.handle_get_resources(request)#

Get current resource usage.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON with current host resource usage

async JobManager.handle_get_queue(request)#

Get queue statistics.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON with queue statistics for dashboard display

async JobManager.handle_set_priority(request)#

Change job priority and re-queue.

Parameters:

requestaiohttp.web.Request: HTTP POST request with JSON payload

Returns:

aiohttp.web.Response: JSON response indicating success or failure

async JobManager.handle_edit_concurrent_limits(request)#

Edit concurrent job limits.

Parameters:

requestaiohttp.web.Request: HTTP PUT request with JSON payload

Returns:

aiohttp.web.Response: JSON response indicating success or failure

async JobManager.wait_until_all_done() → None#

Coroutine that blocks until every job reaches a terminal state.

Safe to call from REST handlers or CLI scripts. Polls job status until all jobs are completed, failed, or cancelled.

async JobManager.submit_job(config: pyedb.workflows.job_manager.backend.job_submission.HFSSSimulationConfig, priority: int = 0) → str#

Async entry point for job submission.

Parameters:

configHFSSSimulationConfig: Validated simulation configuration.
priorityint, optional: Job priority. Default is 0.

Returns:

str: Unique job identifier (same as config.jobid).

Notes

This method: 1. Creates a JobInfo object with QUEUED status 2. Adds the job to the appropriate queue 3. Notifies web clients via Socket.IO 4. Starts the processing loop if not already running

async JobManager.cancel_job(job_id: str) → bool#

Cancel a queued or running job.

Parameters:

job_idstr: Identifier returned by submit_job().

Returns:

bool: True → cancellation succeeded, False → job not found or already terminal.

Notes

For queued jobs: immediately removes from queue and marks as cancelled. For running jobs: attempts to terminate the process and cleanup.

async JobManager.edit_concurrent_limits(update_data: Dict[str, Any]) → Dict[str, Any] | None#

Edit concurrent job limits in the pool.

Parameters:

update_datadict: Fields to update in resource limits. Valid fields: - max_concurrent_jobs: Positive integer - max_cpu_percent: Float between 0 and 100 - min_memory_gb: Non-negative float - min_disk_gb: Non-negative float

Returns:

dict or None: Updated limits data or None if update failed

Raises:

ValueError: If any field validation fails

JobManager#

Overview#

Import detail#

Attribute detail#

Method detail#

`JobManager`#