`JobManagerHandler`#

class pyedb.workflows.job_manager.backend.job_manager_handler.JobManagerHandler(edb=None, version=None, host='localhost', port=8080)#

Synchronous façade that controls an async Job Manager service.

This class provides a thread-safe interface to manage asynchronous job execution while running the aiohttp server in a background thread.

Parameters:

edbOptional[Edb]: PyEDB instance for automatic ANSYS path detection
versionOptional[str]: Specific ANSYS version to use (e.g., “2023.1”)
hoststr: Hostname or IP address to bind the server
portint: TCP port to listen on

Raises:

ValueError: If specified ANSYS version is not found
RuntimeError: If service fails to start within timeout

Examples

>>> handler = JobManagerHandler()  
>>> handler.start_service()  
>>> print(f"Server running at {handler.url}")  
>>> # Submit jobs via REST API or handler methods
>>> handler.close()  

Attributes:

ansys_pathstr: Path to ANSYS EDT executable
scheduler_typeSchedulerType: Detected scheduler type (SLURM, LSF, or NONE)
managerJobManager: Underlying async job manager instance
hoststr: Server hostname
portint: Server port
urlstr: Full server URL
startedbool: Whether the service is currently running

Overview#

Methods

`submit_job`	Synchronously submit a simulation job.
`wait_until_done`	Block until the requested job reaches a terminal state
`wait_until_all_done`	Block until every job currently known to the manager
`get_system_status`	Get system status and scheduler information.
`get_me`	Get current user information.
`get_jobs`	Get list of all jobs with their current status.
`get_scheduler_type`	Get detected scheduler type.
`get_cluster_partitions`	Get available cluster partitions/queues.
`get_job_log`	Get parsed HFSS log for a finished job.
`handle_submit_job`	Submit a new simulation job.
`get_queue_status`	Get current queue status for UI display.
`get_resources`	Get current resource usage for UI display.
`cancel_job`	Cancel a running or queued job.
`start_service`	Start the job manager service in a background thread.
`close`	Gracefully shutdown the job manager service.
`stop_service`	Stop the aiohttp server and cleanup resources.
`create_simulation_config`	Create a validated HFSSSimulationConfig.

Properties

url

Get the server URL.

Attributes

`scheduler_type`
`manager`
`sio`
`app`
`runner`
`site`
`started`
`resource_limits`

Import detail#

from pyedb.workflows.job_manager.backend.job_manager_handler import JobManagerHandler

Property detail#

property JobManagerHandler.url: str#

Get the server URL.

Returns:

str: Full server URL (http://host:port)

Attribute detail#

JobManagerHandler.scheduler_type#

JobManagerHandler.manager#

JobManagerHandler.sio#

JobManagerHandler.app#

JobManagerHandler.runner: aiohttp.web.AppRunner | None = None#

JobManagerHandler.site = None#

JobManagerHandler.started = False#

JobManagerHandler.resource_limits = None#

Method detail#

JobManagerHandler.submit_job(config: pyedb.workflows.job_manager.backend.job_submission.HFSSSimulationConfig, priority: int = 0, timeout: float = 30.0) → str#

Synchronously submit a simulation job.

The method is thread-safe: it marshals the async work into the background event-loop and returns the job identifier.

Parameters:

configHFSSSimulationConfig: Fully-built and validated simulation configuration.
priorityint, optional: Job priority (higher → de-queued earlier). Default 0.
timeoutfloat, optional: Seconds to wait for the submission to complete. Default 30 s.

Returns:

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

Raises:

RuntimeError: If the service is not started or the submission times out.
Exception: Any validation / scheduler error raised by the underlying coroutine.

Examples

>>> from pyedb.workflows.job_manager.backend.job_manager_handler import JobManagerHandler
>>> from pyedb.workflows.job_manager.backend.job_submission import create_hfss_config, SchedulerType

>>> handler = JobManagerHandler()
>>> handler.start_service()
>>> cfg = create_hfss_config(
>>>     ansys_edt_path=...,
>>>     jobid="my_job",
>>>     project_path=...,
>>>     scheduler_type=SchedulerType.NONE
>>> )
>>> job_id = handler.submit_job(cfg, priority=0)
>>> print("submitted", job_id)
>>> # later
>>> handler.close()

JobManagerHandler.wait_until_done(job_id: str, poll_every: float = 2.0) → str#

Block until the requested job reaches a terminal state (completed, failed, or cancelled).

Returns:

str: Terminal status string.

JobManagerHandler.wait_until_all_done(poll_every: float = 2.0) → None#: Block until every job currently known to the manager is in a terminal state.

async JobManagerHandler.get_system_status(request)#

Get system status and scheduler information.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON response with system status

async JobManagerHandler.get_me(request)#

Get current user information.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON response with username

async JobManagerHandler.get_jobs(request)#

Get list of all jobs with their current status.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON array of job objects

async JobManagerHandler.get_scheduler_type(request)#

Get detected scheduler type.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON response with scheduler type

async JobManagerHandler.get_cluster_partitions(request)#

Get available cluster partitions/queues.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON array of partition information

async JobManagerHandler.get_job_log(request)#

Get parsed HFSS log for a finished job.

Parameters:

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

Returns:

aiohttp.web.Response

200: JSON with parsed log data
204: No log available yet
404: Job not found
500: Log parsing error

async JobManagerHandler.handle_submit_job(request)#

Submit a new simulation job.

Parameters:

requestaiohttp.web.Request: HTTP request with JSON payload containing job configuration

Returns:

aiohttp.web.Response: JSON response with job ID and status

Notes

Expected JSON payload:

{
    "config": {
        "scheduler_type": "slurm|lsf|none",
        "project_path": "/path/to/project.aedt",
        ... other HFSS config fields
    },
    "user": "username",
    "machine_nodes": [...],
    "batch_options": {...}
}

async JobManagerHandler.get_queue_status(request)#

Get current queue status for UI display.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON with queue statistics

async JobManagerHandler.get_resources(request)#

Get current resource usage for UI display.

Parameters:

requestaiohttp.web.Request: HTTP request object

Returns:

aiohttp.web.Response: JSON with current resource usage

async JobManagerHandler.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 with cancellation status

JobManagerHandler.start_service() → None#

Start the job manager service in a background thread.

Raises:

RuntimeError: If service fails to start within 10 seconds

Notes

This method is non-blocking and returns immediately. The service runs in a daemon thread with its own event loop.

JobManagerHandler.close() → None#

Gracefully shutdown the job manager service.

Notes

This method is automatically called on program exit via atexit, but can also be called explicitly for clean shutdown.

async JobManagerHandler.stop_service() → None#

Stop the aiohttp server and cleanup resources.

This is the async version of close() that runs in the event loop.

JobManagerHandler.create_simulation_config(project_path: str, ansys_edt_path: str | None = None, jobid: str | None = None, scheduler_type: pyedb.workflows.job_manager.backend.job_submission.SchedulerType | None = None, cpu_cores: int = 1, user: str = 'unknown') → pyedb.workflows.job_manager.backend.job_submission.HFSSSimulationConfig#

Create a validated HFSSSimulationConfig.

Parameters:

project_pathstr: Path to the AEDT project file
ansys_edt_pathstr, optional: Path to ANSYS EDT executable. Uses detected path if None.
jobidstr, optional: Job identifier. Auto-generated if None.
scheduler_typeSchedulerType, optional: Scheduler type. Uses detected scheduler if None.
cpu_coresint: Number of CPU cores for local execution
userstr: Username for job ownership

Returns:

HFSSSimulationConfig: Validated simulation configuration

Raises:

ValueError: If project_path is empty or invalid

Notes

The cpu_cores parameter is only used when scheduler_type is NONE (local execution). For cluster execution, cores are determined by the scheduler configuration.

JobManagerHandler#

Overview#

Import detail#

Property detail#

Attribute detail#

Method detail#

`JobManagerHandler`#