CustomWorkflowComponent

class openff.qcsubmit.workflow_components.CustomWorkflowComponent(*, type='CustomWorkflowComponent')[source]

This is an abstract base class which should be used to create all workflow components, following the design of this class should allow users to easily create new work flow components with out needing to change any of the dataset factory code.

Parameters:

type (Literal['CustomWorkflowComponent']) –

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

Parameters:

data (Any) –

Return type:

None

Methods

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

apply(molecules, toolkit_registry[, ...])

This is the main feature of the workflow component which should accept a molecule, perform the component action and then return any resulting molecules.

construct([_fields_set])

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.

copy(*[, include, exclude, update, deep])

Duplicate a model, optionally choose which fields to include, exclude and change.

description()

Returns a friendly description of the workflow component.

dict(*[, include, exclude, by_alias, ...])

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

fail_reason()

Returns a friendly description of why a molecule would fail to pass the component.

from_orm(obj)

info()

Returns a dictionary of the friendly descriptions of the class.

is_available()

This method should identify if the component can be used by checking if the requirements are available.

json(*[, include, exclude, by_alias, ...])

Generate a JSON representation of the model, include and exclude arguments as per dict().

parse_file(path, *[, content_type, ...])

parse_obj(obj)

parse_raw(b, *[, content_type, encoding, ...])

properties()

Returns the runtime properties of the component such as parallel safe.

provenance(toolkit_registry)

This function should detail the programs with version information and procedures called during activation of the workflow component.

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

update_forward_refs(**localns)

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate(value)

Attributes

type

abstract classmethod description()[source]

Returns a friendly description of the workflow component.

Return type:

str

abstract classmethod fail_reason()[source]

Returns a friendly description of why a molecule would fail to pass the component.

Return type:

str

abstract classmethod properties()[source]

Returns the runtime properties of the component such as parallel safe.

Return type:

ComponentProperties

classmethod info()[source]

Returns a dictionary of the friendly descriptions of the class.

Return type:

Dict[str, str]

abstract classmethod is_available()[source]

This method should identify if the component can be used by checking if the requirements are available.

Returns:

True if the component can be used else False.

Return type:

bool

apply(molecules, toolkit_registry, processors=None, verbose=True)[source]

This is the main feature of the workflow component which should accept a molecule, perform the component action and then return any resulting molecules.

Parameters:

  • molecules (List[Molecule]) – The list of molecules to be processed by this component.

  • toolkit_registry (ToolkitRegistry) – The openff.toolkit.utils.ToolkitRegistry which declares the available backend toolkits to be used.

  • processors (int | None) – The number of processor the component can use to run the job in parallel across molecules, None will default to all cores.

  • verbose (bool) – If true a progress bar should be shown on screen.

Returns:

A component result class which handles collecting together molecules that pass and fail the component

Return type:

ComponentResult

abstract provenance(toolkit_registry)[source]

This function should detail the programs with version information and procedures called during activation of the workflow component.

Returns:

A dictionary containing the information about the component and the functions called.

Parameters:

toolkit_registry (ToolkitRegistry) –

Return type:

Dict