class lamindb.Transform(*, id: Optional[str] = None, version: Optional[str] = None, name: str, type: TransformType = TransformType.pipeline, title: Optional[str] = None, reference: Optional[str] = None, created_by_id: str = None, created_at: datetime, updated_at: Optional[datetime] = None)#

Bases: BaseORM

Data transformations.

Jupyter notebooks, pipelines, and apps.

A pipeline is typically versioned software that can perform a data transformation/processing workflow. This can be anything from typical workflow tools (Nextflow, Snakemake, Prefect, Apache Airflow, etc.) to simple (versioned) scripts.

Data can also be ingested & transformed through an app.


id: Optional[str]#
version: Optional[str]#

Version identifier, defaults to “1”.

Use this to label different versions of the same transform.

Consider using semantic versioning with Python versioning.

name: str#

A name for the transform, a pipeline name, or a file name of a notebook or script.

type: TransformType#

Transform type. Defaults to notebook if run from IPython, otherwise to pipeline.

title: Optional[str]#

An additional title, like a notebook title.

reference: Optional[str]#

Reference for the transform, e.g., a URL.

created_by_id: str#
created_at: datetime#
updated_at: Optional[datetime]#
created_by: User#