hpcflow.sdk.persistence.base.StoreElementIter#

class hpcflow.sdk.persistence.base.StoreElementIter(id_, is_pending, element_ID, EAR_IDs, data_idx, schema_parameters, loop_idx=<factory>)#

Bases: object

Parameters:

  • data_idx (Dict[str, int]) – Overall data index for the element-iteration, which maps parameter names to parameter data indices.

  • EAR_IDs (Dict[int, List[int]]) – Maps task schema action indices to EARs by ID.

  • schema_parameters (List[str]) – List of parameters defined by the associated task schema.

  • id_ (int) –

  • is_pending (bool) –

  • element_ID (int) –

  • loop_idx (Dict[str, int]) –

Methods

append_EAR_IDs

Return a copy, with additional EAR IDs.

decode

Initialise a StoreElementIter from persistent store element iteration data

encode

Prepare store element iteration data for the persistent store.

to_dict

Prepare data for the user-facing ElementIteration object.

update_loop_idx

Return a copy, with the loop index updated.

Attributes

id_

is_pending

element_ID

EAR_IDs

data_idx

schema_parameters

loop_idx

EAR_IDs: Dict[int, List[int]]#
append_EAR_IDs(pend_IDs)#

Return a copy, with additional EAR IDs.

Parameters:
Return type:

AnySElementIter

data_idx: Dict[str, int]#
classmethod decode(iter_dat)#

Initialise a StoreElementIter from persistent store element iteration data

Parameters:

iter_dat (Dict) –

Return type:

StoreElementIter

element_ID: int#
encode()#

Prepare store element iteration data for the persistent store.

Return type:

Dict

id_: int#
is_pending: bool#
loop_idx: Dict[str, int]#
schema_parameters: List[str]#
to_dict(EARs)#

Prepare data for the user-facing ElementIteration object.

update_loop_idx(loop_idx)#

Return a copy, with the loop index updated.

Parameters:

  • self (AnySElementIter) –

  • loop_idx (Dict[str, int]) –

Return type:

AnySElementIter