hpcflow.sdk.persistence.base.StoreElementIter#

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

Bases: Generic[SerFormT, ContextT]

Represents an element iteration in a persistent store.

Parameters:

id (int) – The ID of this element iteration.
is_pending (bool) – Whether the element iteration has changes not yet persisted.
element_ID (int) – Which element is an iteration for.
EARs_initialised (bool) – Whether EARs have been initialised for this element iteration.
EAR_IDs (dict[int, list[int]] | None) – Maps task schema action indices to EARs by ID.
data_idx (DataIndex) – Overall data index for the element-iteration, which maps parameter names to parameter data indices.
schema_parameters (list[str]) – List of parameters defined by the associated task schema.
loop_idx (Mapping[str, int]) – What loops are being handled here and where they’re up to.
id_ (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.
`set_EARs_initialised`	Return a copy with EARs_initialised set to True.
`to_dict`	Prepare data for the user-facing ElementIteration object.
`update_loop_idx`	Return a copy, with the loop index updated.

Attributes

`id_`	The ID of this element iteration.
`is_pending`	Whether the element iteration has changes not yet persisted.
`element_ID`	Which element is an iteration for.
`EARs_initialised`	Whether EARs have been initialised for this element iteration.
`EAR_IDs`	Maps task schema action indices to EARs by ID.
`data_idx`	Overall data index for the element-iteration, which maps parameter names to parameter data indices.
`schema_parameters`	List of parameters defined by the associated task schema.
`loop_idx`	What loops are being handled here and where they're up to.

EAR_IDs: dict[int, list[int]] | None#: Maps task schema action indices to EARs by ID.

EARs_initialised: bool#: Whether EARs have been initialised for this element iteration.

append_EAR_IDs(pend_IDs)#

Return a copy, with additional EAR IDs.

Parameters:: pend_IDs (Mapping[int, Sequence[int]]) –
Return type:: Self

data_idx: DataIndex#: Overall data index for the element-iteration, which maps parameter names to parameter data indices.

abstract classmethod decode(iter_dat, context)#

Initialise a StoreElementIter from persistent store element iteration data

Parameters:

iter_dat (SerFormT) –
context (ContextT) –

Return type:

Self

element_ID: int#: Which element is an iteration for.

abstract encode(context)#

Prepare store element iteration data for the persistent store.

Parameters:: context (ContextT) –
Return type:: SerFormT

id_: int#: The ID of this element iteration.

is_pending: bool#: Whether the element iteration has changes not yet persisted.

loop_idx: Mapping[str, int]#: What loops are being handled here and where they’re up to.

schema_parameters: list[str]#: List of parameters defined by the associated task schema.

set_EARs_initialised()#

Return a copy with EARs_initialised set to True.

Return type:: Self

to_dict(EARs)#

Prepare data for the user-facing ElementIteration object.

Parameters:: EARs (dict[int, dict[str, Any]] | None) –
Return type:: dict[str, Any]

update_loop_idx(loop_idx)#

Return a copy, with the loop index updated.

Parameters:: loop_idx (Mapping[str, int]) –
Return type:: Self