lamindb.Transform#
- 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:
BaseORMData 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.
Attributes
-
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]#
-
id: