hpcflow.app.Jobscript#

class hpcflow.app.Jobscript(task_insert_IDs, task_actions, task_elements, EARs, EAR_idx, resources, task_loop_idx, dependencies, submit_time=None, scheduler_job_ID=None, version_info=None)#

Bases: Jobscript

Methods

`compose_jobscript`	Prepare the jobscript file string.
`from_json_like`
`get_EAR_ID_array`
`get_EAR_run_idx_array`
`get_commands_file_name`
`get_task_element_idx_array`
`get_task_insert_IDs_array`
`get_task_loop_idx_array`
`make_artifact_dirs`
`submit`
`to_dict`
`to_json_like`
`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`
`write_need_EARs_file`	Write a text file with num_elements lines and num_actions delimited tokens per line, representing whether a given EAR must be executed.

Attributes

`EAR_idx`
`EARs`
`app`
`dependencies`
`element_run_dir_file_name`
`element_run_dir_file_path`
`index`
`is_array`
`jobscript_name`
`jobscript_path`
`need_EAR_file_name`
`need_EAR_file_path`
`num_actions`
`num_elements`
`os_name`
`resources`
`scheduler`
`scheduler_job_ID`
`scheduler_name`
`scheduler_version_info`
`shell`
`shell_name`
`submission`
`submit_time`
`task_actions`
`task_elements`
`task_insert_IDs`
`task_loop_idx`
`workflow`
`workflow_app_alias`

Parameters:

task_insert_IDs (List[int]) –
task_actions (List[Tuple]) –
task_elements (Dict[int, List[int]]) –
EARs (Dict[Tuple[int]:Tuple[int]]) –
EAR_idx (NDArray) –
resources (app.ElementResources) –
task_loop_idx (List[Dict]) –
dependencies (Dict[int:Dict]) –
submit_time (Optional[datetime]) –
scheduler_job_ID (Optional[str]) –
version_info (Optional[Tuple[str]]) –

property EAR_idx#

property EARs#

app = BaseApp(name='hpcFlow', version='0.2.0a48')#

compose_jobscript()#

Prepare the jobscript file string.

Return type:: str

property dependencies#

property element_run_dir_file_name#

property element_run_dir_file_path#

classmethod from_json_like(json_like, shared_data=None)#

get_EAR_ID_array()#

get_EAR_run_idx_array()#

get_commands_file_name(js_action_idx)#

get_task_element_idx_array()#

get_task_insert_IDs_array()#

get_task_loop_idx_array()#

property index#

property is_array#

property jobscript_name#

property jobscript_path#

make_artifact_dirs(task_artifacts_path)#

property need_EAR_file_name#

property need_EAR_file_path#

property num_actions#

property num_elements#

property os_name#

property resources#

property scheduler#

property scheduler_job_ID#

property scheduler_name: str | None#

property scheduler_version_info#

property shell#

property shell_name: str#

property submission#

submit(task_artifacts_path, scheduler_refs, print_stdout=False)#

Parameters:

task_artifacts_path (Path) –
scheduler_refs (Dict[int, str]) –
print_stdout (bool | None) –

Return type:

str

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 workflow#

property workflow_app_alias#

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()#

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