lenskit.pipeline.PipelineConfig#

class lenskit.pipeline.PipelineConfig(*, meta, inputs=<factory>, components=<factory>, aliases=<factory>, default=None, literals=<factory>)#

Bases: BaseModel

Root type for serialized pipeline configuration. A pipeline config contains the full configuration, components, and wiring for the pipeline, but does not contain the learned parameters.

Stability:

Full (see Stability Levels).

Parameters:

meta (PipelineMeta)
inputs (list[PipelineInput])
components (OrderedDict[str, PipelineComponent])
aliases (dict[str, str])
default (str | None)
literals (dict[str, PipelineLiteral])

__init__(**data)#

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

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:: data (Any)
Return type:: None

Methods

`__init__`(**data)	Create a new model by parsing and validating input data from keyword arguments.
`construct`([_fields_set])
`copy`(*[, include, exclude, update, deep])	Returns a copy of the model.
`dict`(*[, include, exclude, by_alias, ...])
`from_orm`(obj)
`json`(*[, include, exclude, by_alias, ...])
`model_construct`([_fields_set])	Creates a new instance of the Model class with validated data.
`model_copy`(*[, update, deep])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
`model_dump`(*[, mode, include, exclude, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
`model_dump_json`(*[, indent, include, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
`model_json_schema`([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
`model_parametrized_name`(params)	Compute the class name for parametrizations of generic classes.
`model_post_init`(_BaseModel__context)	Override this method to perform additional initialization after __init__ and model_construct.
`model_rebuild`(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
`model_validate`(obj, *[, strict, ...])	Validate a pydantic model instance.
`model_validate_json`(json_data, *[, strict, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
`model_validate_strings`(obj, *[, strict, context])	Validate the given object with string data against the Pydantic model.
`parse_file`(path, *[, content_type, ...])
`parse_obj`(obj)
`parse_raw`(b, *[, content_type, encoding, ...])
`schema`([by_alias, ref_template])
`schema_json`(*[, by_alias, ref_template])
`update_forward_refs`(**localns)
`validate`(value)

Attributes

`model_computed_fields`
`model_config`	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
`model_extra`	Get extra fields set during validation.
`model_fields`
`model_fields_set`	Returns the set of fields that have been explicitly set on this model instance.
`meta`	Pipeline metadata.
`inputs`	Pipeline inputs.
`components`	Pipeline components, with their configurations and wiring.
`aliases`	Pipeline node aliases.
`default`	The default node for running this pipeline.
`literals`	Literals

meta: PipelineMeta#: Pipeline metadata.

inputs: list[PipelineInput]#: Pipeline inputs.

components: OrderedDict[str, PipelineComponent]#: Pipeline components, with their configurations and wiring.

aliases: dict[str, str]#: Pipeline node aliases.

default: str | None#: The default node for running this pipeline.

literals: dict[str, PipelineLiteral]#: Literals

model_config: ClassVar[ConfigDict] = {}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].