matflow.Workflow

class matflow.Workflow(workflow_ref, store_fmt=None, fs_kwargs=None, **kwargs)

Bases: Workflow

Methods

abort_run	Abort the currently running action-run of the specified task/element.
add_loop	Add a loop to a subset of workflow tasks.
add_submission
add_task
add_task_after	Add a new task after the specified task.
add_task_before	Add a new task before the specified task.
batch_update	A context manager that batches up structural changes to the workflow and commits them to disk all together when the context manager exits.
cancel	Cancel any running jobscripts.
check_loop_termination	Check if a loop should terminate, given the specified completed run, and if so, set downstream iteration runs to be skipped.
check_parameters_exist
copy	Copy the workflow to a new path and return the copied workflow path.
delete
elements
from_JSON_file	Generate from a JSON file.
from_JSON_string	Generate from a JSON string.
from_YAML_file	Generate from a YAML file.
from_YAML_string	Generate from a YAML string.
from_file	Generate from either a YAML or JSON file, depending on the file extension.
from_template	Generate from a WorkflowTemplate object.
from_template_data	Generate from the data associated with a WorkflowTemplate object.
get_EAR_IDs_of_tasks	Get EAR IDs belonging to multiple tasks
get_EAR_skipped	Check if an EAR is to be skipped.
get_EARs_from_IDs	Return element action run objects from a list of IDs.
get_EARs_of_tasks	Get EARs belonging to multiple tasks
get_all_EARs
get_all_element_iterations
get_all_elements
get_all_parameter_data	Retrieve all workflow parameter data.
get_all_parameter_sources	Retrieve all store parameters.
get_all_parameters	Retrieve all store parameters.
get_all_submission_run_IDs
get_element_IDs_from_EAR_IDs
get_element_iteration_IDs_from_EAR_IDs
get_element_iterations_from_IDs	Return element iteration objects from a list of IDs.
get_element_iterations_of_tasks	Get element iterations belonging to multiple tasks
get_elements_from_IDs	Return element objects from a list of IDs.
get_iteration_final_run_IDs	Retrieve the run IDs of those runs that correspond to the final action within a named loop iteration.
get_iteration_task_pathway
get_loop_map
get_parameter
get_parameter_data
get_parameter_set_statuses
get_parameter_source
get_parameter_sources
get_parameters
get_running_elements	Retrieve elements that are running according to the scheduler.
get_running_runs	Retrieve runs that are running according to the scheduler.
get_store_EARs
get_store_element_iterations
get_store_elements
get_store_tasks
get_task_IDs_from_element_IDs
get_task_elements
get_task_unique_names	Return the unique names of all workflow tasks.
is_parameter_set
process_shell_parameter_output	Process the shell stdout/stderr stream according to the associated Command object.
rechunk	Rechunk metadata/runs and parameters/base arrays.
rechunk_parameter_base
rechunk_runs
reload	Reload the workflow from disk.
resolve_jobscripts
save_parameter
set_EAR_end	Set the end time and exit code on an EAR.
set_EAR_skip	Record that an EAR is to be skipped due to an upstream failure or loop termination condition being met.
set_EAR_start	Set the start time on an EAR.
set_EAR_submission_index	Set the submission index of an EAR.
set_EARs_initialised	Set ElementIteration.EARs_initialised to True for the specified iteration.
set_parameter_value
show_all_EAR_statuses
submit	Submit the workflow for execution.
temporary_rename	Rename an existing same-path workflow (directory) so we can restore it if workflow creation fails.
unzip	param path: Path at which to create the new unzipped workflow. If this is an existing
wait	Wait for the completion of specified/all submitted jobscripts.
write_commands	Write run-time commands for a given EAR.
zip	param path: Path at which to create the new zipped workflow. If this is an existing

Attributes

app
artifacts_path
creation_info
execution_path
id_
input_files_path
loops
name	The workflow name may be different from the template name, as it includes the creation date-timestamp if generated.
num_EARs
num_added_tasks
num_element_iterations
num_elements
num_loops
num_submissions
num_tasks
store_format
submissions
submissions_path
task_artifacts_path
tasks
template
template_components
ts_fmt
ts_name_fmt
url	Get an fsspec URL for this workflow.

Parameters:

• workflow_ref (Union[str, Path, int]) –

• store_fmt (Optional[str]) –

• fs_kwargs (Optional[Dict]) –

abort_run(submission_idx=-1, task_idx=None, task_insert_ID=None, element_idx=None)

Abort the currently running action-run of the specified task/element.

Parameters:

• task_idx (int | None) – The parent task of the run to abort.

• element_idx (int) – For multi-element tasks, the parent element of the run to abort.

• submission_idx (int) – Defaults to the most-recent submission.

• task_insert_ID (int | None) –

add_loop(loop)

Add a loop to a subset of workflow tasks.

Parameters:

loop (Loop) –

Return type:

None

add_submission(tasks=None, JS_parallelism=None)

Parameters:

• tasks (List[int] | None) –

• JS_parallelism (bool | None) –

Return type:

Submission

add_task(task, new_index=None)

Parameters:

• task (Task) –

• new_index (int | None) –

Return type:

None

add_task_after(new_task, task_ref=None)

Add a new task after the specified task.

Parameters:

• task_ref (Task) – If not given, the new task will be added at the end of the workflow.

• new_task (Task) –

Return type:

None

add_task_before(new_task, task_ref=None)

Add a new task before the specified task.

Parameters:

• task_ref (Task) – If not given, the new task will be added at the beginning of the workflow.

• new_task (Task) –

Return type:

None

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

property artifacts_path

batch_update(is_workflow_creation=False)

A context manager that batches up structural changes to the workflow and commits them to disk all together when the context manager exits.

Parameters:

is_workflow_creation (bool) –

Return type:

Iterator[None]

cancel(hard=False)

Cancel any running jobscripts.

check_loop_termination(loop_name, run_ID)

Check if a loop should terminate, given the specified completed run, and if so, set downstream iteration runs to be skipped.

Parameters:

• loop_name (str) –

• run_ID (int) –

Return type:

bool

check_parameters_exist(id_lst)

Parameters:

id_lst (int | List[int]) –

Return type:

bool | List[bool]

copy(path=None)

Copy the workflow to a new path and return the copied workflow path.

Return type:

str

property creation_info

delete()

elements()

Return type:

Iterator[Element]

property execution_path

classmethod from_JSON_file(JSON_path, path=None, name=None, overwrite=False, store='zarr', ts_fmt=None, ts_name_fmt=None, store_kwargs=None, variables=None, status=None)

Generate from a JSON file.

Parameters:

• JSON_path (PathLike) – The path to a workflow template in the JSON file format.

• path (str | None) – The directory in which the workflow will be generated. The current directory if not specified.

• name (str | None) – The name of the workflow. If specified, the workflow directory will be path joined with name. If not specified the WorkflowTemplate name will be used, in combination with a date-timestamp.

• overwrite (bool | None) – If True and the workflow directory (path + name) already exists, the existing directory will be overwritten.

• store (str | None) – The persistent store to use for this workflow.

• ts_fmt (str | None) – The datetime format to use for storing datetimes. Datetimes are always stored in UTC (because Numpy does not store time zone info), so this should not include a time zone name.

• ts_name_fmt (str | None) – The datetime format to use when generating the workflow name, where it includes a timestamp.

• store_kwargs (Dict | None) – Keyword arguments to pass to the store’s write_empty_workflow method.

• variables (Dict[str, str] | None) – String variables to substitute in the file given by JSON_path.

• status (Any | None) –

Return type:

Workflow

classmethod from_JSON_string(JSON_str, path=None, name=None, overwrite=False, store='zarr', ts_fmt=None, ts_name_fmt=None, store_kwargs=None, variables=None, status=None)

Generate from a JSON string.

Parameters:

• JSON_str (PathLike) – The JSON string containing a workflow template parametrisation.

• path (str | None) – The directory in which the workflow will be generated. The current directory if not specified.

• name (str | None) – The name of the workflow. If specified, the workflow directory will be path joined with name. If not specified the WorkflowTemplate name will be used, in combination with a date-timestamp.

• overwrite (bool | None) – If True and the workflow directory (path + name) already exists, the existing directory will be overwritten.

• store (str | None) – The persistent store to use for this workflow.

• ts_fmt (str | None) – The datetime format to use for storing datetimes. Datetimes are always stored in UTC (because Numpy does not store time zone info), so this should not include a time zone name.

• ts_name_fmt (str | None) – The datetime format to use when generating the workflow name, where it includes a timestamp.

• store_kwargs (Dict | None) – Keyword arguments to pass to the store’s write_empty_workflow method.

• variables (Dict[str, str] | None) – String variables to substitute in the string JSON_str.

• status (Any | None) –

Return type:

Workflow

classmethod from_YAML_file(YAML_path, path=None, name=None, overwrite=False, store='zarr', ts_fmt=None, ts_name_fmt=None, store_kwargs=None, variables=None)

Generate from a YAML file.

Parameters:

• YAML_path (PathLike) – The path to a workflow template in the YAML file format.

• path (str | None) – The directory in which the workflow will be generated. The current directory if not specified.

• name (str | None) – The name of the workflow. If specified, the workflow directory will be path joined with name. If not specified the WorkflowTemplate name will be used, in combination with a date-timestamp.

• overwrite (bool | None) – If True and the workflow directory (path + name) already exists, the existing directory will be overwritten.

• store (str | None) – The persistent store to use for this workflow.

• ts_fmt (str | None) – The datetime format to use for storing datetimes. Datetimes are always stored in UTC (because Numpy does not store time zone info), so this should not include a time zone name.

• ts_name_fmt (str | None) – The datetime format to use when generating the workflow name, where it includes a timestamp.

• store_kwargs (Dict | None) – Keyword arguments to pass to the store’s write_empty_workflow method.

• variables (Dict[str, str] | None) – String variables to substitute in the file given by YAML_path.

Return type:

Workflow

classmethod from_YAML_string(YAML_str, path=None, name=None, overwrite=False, store='zarr', ts_fmt=None, ts_name_fmt=None, store_kwargs=None, variables=None)

Generate from a YAML string.

Parameters:

• YAML_str (PathLike) – The YAML string containing a workflow template parametrisation.

• path (str | None) – The directory in which the workflow will be generated. The current directory if not specified.

• name (str | None) – The name of the workflow. If specified, the workflow directory will be path joined with name. If not specified the WorkflowTemplate name will be used, in combination with a date-timestamp.

• overwrite (bool | None) – If True and the workflow directory (path + name) already exists, the existing directory will be overwritten.

• store (str | None) – The persistent store to use for this workflow.

• ts_fmt (str | None) – The datetime format to use for storing datetimes. Datetimes are always stored in UTC (because Numpy does not store time zone info), so this should not include a time zone name.

• ts_name_fmt (str | None) – The datetime format to use when generating the workflow name, where it includes a timestamp.

• store_kwargs (Dict | None) – Keyword arguments to pass to the store’s write_empty_workflow method.

• variables (Dict[str, str] | None) – String variables to substitute in the string YAML_str.

Return type:

Workflow

classmethod from_file(template_path, template_format=None, path=None, name=None, overwrite=False, store='zarr', ts_fmt=None, ts_name_fmt=None, store_kwargs=None, variables=None, status=None)

Generate from either a YAML or JSON file, depending on the file extension.

Parameters:

• template_path (PathLike) – The path to a template file in YAML or JSON format, and with a “.yml”, “.yaml”, or “.json” extension.

• template_format (str | None) – If specified, one of “json” or “yaml”. This forces parsing from a particular format regardless of the file extension.

• path (str | None) – The directory in which the workflow will be generated. The current directory if not specified.

• name (str | None) – The name of the workflow. If specified, the workflow directory will be path joined with name. If not specified the WorkflowTemplate name will be used, in combination with a date-timestamp.

• overwrite (bool | None) – If True and the workflow directory (path + name) already exists, the existing directory will be overwritten.

• store (str | None) – The persistent store to use for this workflow.

• ts_fmt (str | None) – The datetime format to use for storing datetimes. Datetimes are always stored in UTC (because Numpy does not store time zone info), so this should not include a time zone name.

• ts_name_fmt (str | None) – The datetime format to use when generating the workflow name, where it includes a timestamp.

• store_kwargs (Dict | None) – Keyword arguments to pass to the store’s write_empty_workflow method.

• variables (Dict[str, str] | None) – String variables to substitute in the file given by template_path.

• status (Any | None) –

Return type:

Workflow

classmethod from_template(template, path=None, name=None, overwrite=False, store='zarr', ts_fmt=None, ts_name_fmt=None, store_kwargs=None, status=None)

Generate from a WorkflowTemplate object.

Parameters:

• template (WorkflowTemplate) – The WorkflowTemplate object to make persistent.

• path (PathLike | None) – The directory in which the workflow will be generated. The current directory if not specified.

• name (str | None) – The name of the workflow. If specified, the workflow directory will be path joined with name. If not specified the WorkflowTemplate name will be used, in combination with a date-timestamp.

• overwrite (bool | None) – If True and the workflow directory (path + name) already exists, the existing directory will be overwritten.

• store (str | None) – The persistent store to use for this workflow.

• ts_fmt (str | None) – The datetime format to use for storing datetimes. Datetimes are always stored in UTC (because Numpy does not store time zone info), so this should not include a time zone name.

• ts_name_fmt (str | None) – The datetime format to use when generating the workflow name, where it includes a timestamp.

• store_kwargs (Dict | None) – Keyword arguments to pass to the store’s write_empty_workflow method.

• status (Any | None) –

Return type:

Workflow

classmethod from_template_data(template_name, tasks=None, loops=None, resources=None, path=None, workflow_name=None, overwrite=False, store='zarr', ts_fmt=None, ts_name_fmt=None, store_kwargs=None)

Generate from the data associated with a WorkflowTemplate object.

Parameters:

• template_name (str) – Name of the new workflow template, from which the new workflow will be generated.

• tasks (List[Task] | None) – List of Task objects to add to the new workflow.

• loops (List[Loop] | None) – List of Loop objects to add to the new workflow.

• resources (Dict[str, Dict] | None) – Mapping of action scopes to resource requirements, to be applied to all element sets in the workflow. resources specified in an element set take precedence of those defined here for the whole workflow.

• path (PathLike | None) – The directory in which the workflow will be generated. The current directory if not specified.

• workflow_name (str | None) – The name of the workflow. If specified, the workflow directory will be path joined with name. If not specified template_name will be used, in combination with a date-timestamp.

• overwrite (bool | None) – If True and the workflow directory (path + name) already exists, the existing directory will be overwritten.

• store (str | None) – The persistent store to use for this workflow.

• ts_fmt (str | None) – The datetime format to use for storing datetimes. Datetimes are always stored in UTC (because Numpy does not store time zone info), so this should not include a time zone name.

• ts_name_fmt (str | None) – The datetime format to use when generating the workflow name, where it includes a timestamp.

• store_kwargs (Dict | None) – Keyword arguments to pass to the store’s write_empty_workflow method.

Return type:

Workflow

get_EAR_IDs_of_tasks(id_lst)

Get EAR IDs belonging to multiple tasks

Parameters:

id_lst (int) –

Return type:

List[int]

get_EAR_skipped(EAR_ID)

Check if an EAR is to be skipped.

Parameters:

EAR_ID (int) –

Return type:

None

get_EARs_from_IDs(id_lst)

Return element action run objects from a list of IDs.

Parameters:

id_lst (Iterable[int]) –

Return type:

List[ElementActionRun]

get_EARs_of_tasks(id_lst)

Get EARs belonging to multiple tasks

Parameters:

id_lst (Iterable[int]) –

Return type:

List[ElementActionRun]

get_all_EARs()

Return type:

List[ElementActionRun]

get_all_element_iterations()

Return type:

List[ElementIteration]

get_all_elements()

Return type:

List[Element]

get_all_parameter_data(**kwargs)

Retrieve all workflow parameter data.

Parameters:

kwargs (Dict) –

Return type:

Dict[int, Any]

get_all_parameter_sources(**kwargs)

Retrieve all store parameters.

Parameters:

kwargs (Dict) –

Return type:

List[Dict]

get_all_parameters(**kwargs)

Retrieve all store parameters.

Parameters:

kwargs (Dict) –

Return type:

List[AnySParameter]

get_all_submission_run_IDs()

Return type:

List[int]

get_element_IDs_from_EAR_IDs(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[int]

get_element_iteration_IDs_from_EAR_IDs(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[int]

get_element_iterations_from_IDs(id_lst)

Return element iteration objects from a list of IDs.

Parameters:

id_lst (Iterable[int]) –

Return type:

List[ElementIteration]

get_element_iterations_of_tasks(id_lst)

Get element iterations belonging to multiple tasks

Parameters:

id_lst (Iterable[int]) –

Return type:

List[ElementIteration]

get_elements_from_IDs(id_lst)

Return element objects from a list of IDs.

Parameters:

id_lst (Iterable[int]) –

Return type:

List[Element]

get_iteration_final_run_IDs(loop_map=None, id_lst=None)

Retrieve the run IDs of those runs that correspond to the final action within a named loop iteration.

These runs represent the final action of a given element-iteration; this is used to identify which commands file to append a loop-termination check to.

Parameters:

• loop_map (Dict | None) –

• id_lst (List[int] | None) –

Return type:

Dict[str, List[int]]

get_iteration_task_pathway(ret_iter_IDs=False, ret_data_idx=False)

get_loop_map(id_lst=None)

Parameters:

id_lst (List[int] | None) –

get_parameter(index, **kwargs)

Parameters:

• index (int) –

• kwargs (Dict) –

Return type:

AnySParameter

get_parameter_data(index, **kwargs)

Parameters:

• index (int) –

• kwargs (Dict) –

Return type:

Any

get_parameter_set_statuses(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[bool]

get_parameter_source(index)

Parameters:

index (int) –

Return type:

Dict

get_parameter_sources(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[Dict]

get_parameters(id_lst, **kwargs)

Parameters:

• id_lst (Iterable[int]) –

• kwargs (Dict) –

Return type:

List[AnySParameter]

get_running_elements(submission_idx=-1, task_idx=None, task_insert_ID=None)

Retrieve elements that are running according to the scheduler.

Parameters:

• submission_idx (int) –

• task_idx (int | None) –

• task_insert_ID (int | None) –

Return type:

List[Element]

get_running_runs(submission_idx=-1, task_idx=None, task_insert_ID=None, element_idx=None)

Retrieve runs that are running according to the scheduler.

Parameters:

• submission_idx (int) –

• task_idx (int | None) –

• task_insert_ID (int | None) –

• element_idx (int) –

Return type:

List[ElementActionRun]

get_store_EARs(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[AnySEAR]

get_store_element_iterations(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[AnySElementIter]

get_store_elements(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[AnySElement]

get_store_tasks(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[AnySTask]

get_task_IDs_from_element_IDs(id_lst)

Parameters:

id_lst (Iterable[int]) –

Return type:

List[int]

get_task_elements(task, idx_lst=None)

Parameters:

• task (Task) –

• idx_lst (List[int] | None) –

Return type:

List[Element]

get_task_unique_names(map_to_insert_ID=False)

Return the unique names of all workflow tasks.

Parameters:

map_to_insert_ID (bool, optional) – If True, return a dict whose values are task insert IDs, otherwise return a list.

Return type:

List[str] | Dict[str, int]

property id_

property input_files_path

is_parameter_set(index)

Parameters:

index (int) –

Return type:

bool

property loops: WorkflowLoopList

property name

The workflow name may be different from the template name, as it includes the creation date-timestamp if generated.

property num_EARs

property num_added_tasks: int

property num_element_iterations

property num_elements

property num_loops: int

property num_submissions

property num_tasks

process_shell_parameter_output(name, value, EAR_ID, cmd_idx, stderr=False)

Process the shell stdout/stderr stream according to the associated Command object.

Parameters:

• name (str) –

• value (str) –

• EAR_ID (int) –

• cmd_idx (int) –

• stderr (bool) –

Return type:

Any

rechunk(chunk_size=None, backup=True, status=True)

Rechunk metadata/runs and parameters/base arrays.

Parameters:

• chunk_size (int | None) –

• backup (bool | None) –

• status (bool | None) –

rechunk_parameter_base(chunk_size=None, backup=True, status=True)

Parameters:

• chunk_size (int | None) –

• backup (bool | None) –

• status (bool | None) –

rechunk_runs(chunk_size=None, backup=True, status=True)

Parameters:

• chunk_size (int | None) –

• backup (bool | None) –

• status (bool | None) –

reload()

Reload the workflow from disk.

resolve_jobscripts(tasks=None)

Parameters:

tasks (List[int] | None) –

Return type:

List[Jobscript]

save_parameter(name, value, EAR_ID)

Parameters:

• name (str) –

• value (Any) –

• EAR_ID (int) –

set_EAR_end(js_idx, js_act_idx, EAR_ID, exit_code)

Set the end time and exit code on an EAR.

If the exit code is non-zero, also set all downstream dependent EARs to be skipped. Also save any generated input/output files.

Parameters:

• js_idx (int) –

• js_act_idx (int) –

• EAR_ID (int) –

• exit_code (int) –

Return type:

None

set_EAR_skip(EAR_ID)

Record that an EAR is to be skipped due to an upstream failure or loop termination condition being met.

Parameters:

EAR_ID (int) –

Return type:

None

set_EAR_start(EAR_ID)

Set the start time on an EAR.

Parameters:

EAR_ID (int) –

Return type:

None

set_EAR_submission_index(EAR_ID, sub_idx)

Set the submission index of an EAR.

Parameters:

• EAR_ID (int) –

• sub_idx (int) –

Return type:

None

set_EARs_initialised(iter_ID)

Set ElementIteration.EARs_initialised to True for the specified iteration.

Parameters:

iter_ID (int) –

set_parameter_value(param_id, value, commit=False)

Parameters:

• param_id (int) –

• value (Any) –

• commit (bool) –

Return type:

None

show_all_EAR_statuses()

property store_format

property submissions: List[Submission]

property submissions_path

submit(ignore_errors=False, JS_parallelism=None, print_stdout=False, wait=False, add_to_known=True, return_idx=False, tasks=None, cancel=False, status=True)

Submit the workflow for execution.

Parameters:

• ignore_errors (bool | None) – If True, ignore jobscript submission errors. If False (the default) jobscript submission will halt when a jobscript fails to submit.

• JS_parallelism (bool | None) – If True, allow multiple jobscripts to execute simultaneously. Raises if set to True but the store type does not support the jobscript_parallelism feature. If not set, jobscript parallelism will be used if the store type supports it.

• print_stdout (bool | None) – If True, print any jobscript submission standard output, otherwise hide it.

• wait (bool | None) – If True, this command will block until the workflow execution is complete.

• add_to_known (bool | None) – If True, add the submitted submissions to the known-submissions file, which is used by the show command to monitor current and recent submissions.

• return_idx (bool | None) – If True, return a dict representing the jobscript indices submitted for each submission.

• tasks (List[int] | None) – List of task indices to include in the new submission if no submissions already exist. By default all tasks are included if a new submission is created.

• cancel (bool | None) – Immediately cancel the submission. Useful for testing and benchmarking.

• status (bool | None) – If True, display a live status to track submission progress.

Return type:

Dict[int, int]

property task_artifacts_path

property tasks: WorkflowTaskList

property template: WorkflowTemplate

property template_components: Dict

classmethod temporary_rename(path, fs)

Rename an existing same-path workflow (directory) so we can restore it if workflow creation fails.

Renaming will occur until the successfully completed. This means multiple new paths may be created, where only the final path should be considered the successfully renamed workflow. Other paths will be deleted.

Parameters:

path (str) –

Return type:

List[str]

property ts_fmt

property ts_name_fmt

unzip(path='.', log=None)

Parameters:

path – Path at which to create the new unzipped workflow. If this is an existing directory, the new workflow directory will be created within this directory. Otherwise, this path will represent the new workflow directory path.

Return type:

str

property url

Get an fsspec URL for this workflow.

wait(sub_js=None)

Wait for the completion of specified/all submitted jobscripts.

Parameters:

sub_js (Dict | None) –

write_commands(submission_idx, jobscript_idx, JS_action_idx, EAR_ID)

Write run-time commands for a given EAR.

Parameters:

• submission_idx (int) –

• jobscript_idx (int) –

• JS_action_idx (int) –

• EAR_ID (int) –

Return type:

None

zip(path='.', log=None, overwrite=False, include_execute=False, include_rechunk_backups=False)

Parameters:

path – Path at which to create the new zipped workflow. If this is an existing directory, the zip file will be created within this directory. Otherwise, this path is assumed to be the full file path to the new zip file.

Return type:

str