matflow.Jobscript#

class matflow.Jobscript(task_insert_IDs, task_actions, task_elements, EAR_ID, resources, task_loop_idx, dependencies, submit_time=None, submit_hostname=None, submit_machine=None, submit_cmdline=None, scheduler_job_ID=None, process_ID=None, version_info=None, os_name=None, shell_name=None, scheduler_name=None, running=None)#

Bases: Jobscript

Methods

`cancel`
`compose_jobscript`	Prepare the jobscript file string.
`from_json_like`
`get_active_states`	If this jobscript is active on this machine, return the state information from the scheduler.
`get_commands_file_name`
`get_task_loop_idx_array`
`make_artifact_dirs`
`submit`
`to_dict`
`to_json_like`
`write_EAR_ID_file`	Write a text file with num_elements lines and num_actions delimited tokens per line, representing whether a given EAR must be executed.
`write_element_run_dir_file`	Write a text file with num_elements lines and num_actions delimited tokens per line, representing the working directory for each EAR.
`write_jobscript`

Attributes

`EAR_ID`
`EAR_ID_file_name`
`EAR_ID_file_path`
`all_EAR_IDs`
`all_EARs`
`app`
`dependencies`
`direct_stderr_file_name`	For direct execution stderr.
`direct_stderr_path`
`direct_stdout_file_name`	For direct execution stdout.
`direct_stdout_path`
`direct_win_pid_file_name`
`direct_win_pid_file_path`
`element_run_dir_file_name`
`element_run_dir_file_path`
`end_time`	Get the last end time from all EARs.
`index`
`is_array`
`is_submitted`	Return True if this jobscript has been submitted.
`jobscript_name`
`jobscript_path`
`num_actions`
`num_elements`
`os_name`
`process_ID`
`resources`
`scheduler`	Retrieve the scheduler object for submission.
`scheduler_job_ID`
`scheduler_js_ref`
`scheduler_name`
`scheduler_ref`
`shell`	Retrieve the shell object for submission.
`shell_name`
`start_time`	Get the first start time from all EARs.
`submission`
`submit_cmdline`
`submit_hostname`
`submit_machine`
`submit_time`
`task_actions`
`task_elements`
`task_insert_IDs`
`task_loop_idx`
`version_info`
`workflow`
`workflow_app_alias`

Parameters:

task_insert_IDs (List[int]) –
task_actions (List[Tuple]) –
task_elements (Dict[int, List[int]]) –
EAR_ID (NDArray) –
resources (app.ElementResources) –
task_loop_idx (List[Dict]) –
dependencies (Dict[int:Dict]) –
submit_time (Optional[datetime]) –
submit_hostname (Optional[str]) –
submit_machine (Optional[str]) –
submit_cmdline (Optional[str]) –
scheduler_job_ID (Optional[str]) –
process_ID (Optional[int]) –
version_info (Optional[Tuple[str]]) –
os_name (Optional[str]) –
shell_name (Optional[str]) –
scheduler_name (Optional[str]) –
running (Optional[bool]) –

property EAR_ID#

property EAR_ID_file_name#

property EAR_ID_file_path#

property all_EAR_IDs: List[int]#

property all_EARs: List#

app = App(name='MatFlow', version='0.3.0a129')#

cancel()#

compose_jobscript(deps=None, os_name=None, shell_name=None, os_args=None, shell_args=None, scheduler_name=None, scheduler_args=None)#

Prepare the jobscript file string.

Parameters:

deps (Dict | None) –
os_name (str) –
shell_name (str) –
os_args (Dict | None) –
shell_args (Dict | None) –
scheduler_name (str | None) –
scheduler_args (Dict | None) –

Return type:

str

property dependencies#

property direct_stderr_file_name#: For direct execution stderr.

property direct_stderr_path#

property direct_stdout_file_name#: For direct execution stdout.

property direct_stdout_path#

property direct_win_pid_file_name#

property direct_win_pid_file_path#

property element_run_dir_file_name#

property element_run_dir_file_path#

property end_time#: Get the last end time from all EARs.

classmethod from_json_like(json_like, shared_data=None)#

get_active_states(as_json=False)#

If this jobscript is active on this machine, return the state information from the scheduler.

Parameters:: as_json (bool) –
Return type:: Dict[int, JobscriptElementState]

get_commands_file_name(js_action_idx, shell=None)#

get_task_loop_idx_array()#

property index#

property is_array#

property is_submitted#: Return True if this jobscript has been submitted.

property jobscript_name#

property jobscript_path#

make_artifact_dirs()#

property num_actions#

property num_elements#

property os_name: str | None#

property process_ID#

property resources#

property scheduler#: Retrieve the scheduler object for submission.

property scheduler_job_ID#

property scheduler_js_ref#

property scheduler_name: str | None#

property scheduler_ref#

property shell#: Retrieve the shell object for submission.

property shell_name: str | None#

property start_time#: Get the first start time from all EARs.

property submission#

submit(scheduler_refs, print_stdout=False)#

Parameters:

scheduler_refs (Dict[int, (str, bool)]) –
print_stdout (Optional[bool]) –

Return type:

str

property submit_cmdline#

property submit_hostname#

property submit_machine#

property submit_time#

property task_actions#

property task_elements#

property task_insert_IDs#

property task_loop_idx#

to_dict()#

to_json_like(dct=None, shared_data=None, exclude=None, path=None)#

property version_info#

property workflow#

property workflow_app_alias#

write_EAR_ID_file()#: Write a text file with num_elements lines and num_actions delimited tokens per line, representing whether a given EAR must be executed.

write_element_run_dir_file(run_dirs)#

Write a text file with num_elements lines and num_actions delimited tokens per line, representing the working directory for each EAR.

We assume a given task element’s actions all run in the same directory, but in general a jobscript “element” may cross task boundaries, so we need to provide the directory for each jobscript-element/jobscript-action combination.

Parameters:: run_dirs (List[List[Path]]) –

write_jobscript(os_name=None, shell_name=None, deps=None, os_args=None, shell_args=None, scheduler_name=None, scheduler_args=None)#

Parameters:

os_name (str) –
shell_name (str) –
deps (Dict | None) –
os_args (Dict | None) –
shell_args (Dict | None) –
scheduler_name (str | None) –
scheduler_args (Dict | None) –