Python: `lamindb`¶

A data framework for biology.

Lineage¶

Track inputs, outputs & environment of a notebook or script run.

`track`([transform, project, space, branch, ...])	Track a run of your notebook or script.
`finish`([ignore_non_consecutive])	Finish the run and write a run report.

Decorate a function with @tracked() to track inputs, outputs & environment of function executions.

Track function runs.

Files, folders & arrays and their storage locations.

`Artifact`()	Datasets & models stored as files, folders, or arrays.
`Storage`()	Storage locations of artifacts such as local directories or S3 buckets.

Data transformations and their executions.

`Transform`()	Data transformations such as scripts, notebooks, functions, or pipelines.
`Run`()	Runs of transforms such as the execution of a script.

Create labels and manage flexible records, e.g., for samples or donors.

Metadata records for labeling and organizing entities in sheets.

Define features & schemas to validate artifacts & records.

`Feature`()	Variables, such as dataframe columns or run parameters.
`Schema`()	Schemas of a dataset such as the set of columns of a `DataFrame`.

`User`()	Users.
`Collection`()	Versioned collections of artifacts.
`Project`()	Projects to label artifacts, transforms, and runs.
`Space`()	Workspaces with managed access for specific users or teams.
`Branch`()	Branches for change management with archive and trash states.
`Reference`()	References such as internal studies, papers, documents, or URLs.

Connecting, viewing database content, accessing settings & run context.

`connect`([instance])	Connect to an instance.
`view`(*[, limit, modules, registries, df])	View metadata.
`save`(records[, ignore_conflicts, batch_size])	Bulk save records.
`UPath`(*args[, protocol])	Paths: low-level key-value access to files.
`settings`	Global live settings (`Settings`).
`context`	Global run context (`Context`).

`curators`	Curators.
`integrations`	Integrations.

Backwards compatibility.

Universal labels.