lamindb.Run

class lamindb.Run(transform: Transform, reference: str | None = None, reference_type: str | None = None)

Bases: Record

Runs.

A registry to store runs of transforms, such as an executation of a script.

Parameters:
  • transformTransform A Transform record.

  • referencestr | None = None For instance, an external ID or a download URL.

  • reference_typestr | None = None For instance, redun_id, nextflow_id or url.

See also

track()

Track global runs & transforms for a notebook or script.

Examples

Create a run record:

>>> ln.Transform(key="Cell Ranger", version="7.2.0", type="pipeline").save()
>>> transform = ln.Transform.get(key="Cell Ranger", version="7.2.0")
>>> run = ln.Run(transform)

Create a global run context for a custom transform:

>>> ln.track(transform=transform)
>>> ln.context.run  # globally available run

Track a global run context for a notebook or script:

>>> ln.track()  # Jupyter notebook metadata is automatically parsed
>>> ln.context.run

Attributes

params: ParamManager

Param manager.

Guide: Track run parameters

Example:

run.params.add_values({
    "learning_rate": 0.01,
    "input_dir": "s3://my-bucket/mydataset",
    "downsample": True,
    "preprocess_params": {
        "normalization_type": "cool",
        "subset_highlyvariable": True,
    },
})

Simple fields

uid: str

Universal id, valid across DB instances.

name: str | None

A name.

started_at: datetime

Start time of run.

finished_at: datetime | None

Finished time of run.

reference: str | None

A reference like a URL or external ID (such as from a workflow manager).

reference_type: str | None

Type of reference such as a workflow manager execution ID.

created_at: datetime

Time of first creation. Mismatches started_at if the run is re-run.

Relational fields

space: Space

The space in which the record lives.

transform: Transform

The transform Transform that is being run.

report: Artifact | None

Report of run, e.g.. n html file.

environment: Artifact | None

Computational environment for the run.

For instance, Dockerfile, docker image, requirements.txt, environment.yml, etc.

created_by: User

Creator of run.

initiated_by_run: Run | None

The run that triggered the current run.

This is not a preceding run. The preceding runs (“predecessors”) is the set of runs that produced the output artifacts that serve as the inputs for the present run.

ulabels: ULabel

ULabel annotations of this transform.

initiated_runs: Run

Runs that were initiated by this run.

output_artifacts: Artifact

The artifacts generated by this run.

Related accessor: via run

input_artifacts: Artifact

The artifacts serving as input for this run.

Related accessor: input_of_runs.

output_collections: Collection

The collections generated by this run.

input_collections: Collection

The collections serving as input for this run.

projects: Project

Linked projects.

Class methods

classmethod df(include=None, features=False, limit=100)

Convert to pd.DataFrame.

By default, shows all direct fields, except updated_at.

Use arguments include or feature to include other data.

Parameters:
  • include (str | list[str] | None, default: None) – Related fields to include as columns. Takes strings of form "ulabels__name", "cell_types__name", etc. or a list of such strings.

  • features (bool | list[str], default: False) – If True, map all features of the Feature registry onto the resulting DataFrame. Only available for Artifact.

  • limit (int, default: 100) – Maximum number of rows to display from a Pandas DataFrame. Defaults to 100 to reduce database load.

Return type:

DataFrame

Examples

Include the name of the creator in the DataFrame:

>>> ln.ULabel.df(include="created_by__name"])

Include display of features for Artifact:

>>> df = ln.Artifact.df(features=True)
>>> ln.view(df)  # visualize with type annotations

Only include select features:

>>> df = ln.Artifact.df(features=["cell_type_by_expert", "cell_type_by_model"])
classmethod filter(*queries, **expressions)

Query records.

Parameters:
  • queries – One or multiple Q objects.

  • expressions – Fields and values passed as Django query expressions.

Return type:

QuerySet

Returns:

A QuerySet.

See also

Examples

>>> ln.ULabel(name="my label").save()
>>> ln.ULabel.filter(name__startswith="my").df()
classmethod get(idlike=None, **expressions)

Get a single record.

Parameters:
  • idlike (int | str | None, default: None) – Either a uid stub, uid or an integer id.

  • expressions – Fields and values passed as Django query expressions.

Return type:

Record

Returns:

A record.

Raises:

lamindb.errors.DoesNotExist – In case no matching record is found.

See also

Examples

>>> ulabel = ln.ULabel.get("FvtpPJLJ")
>>> ulabel = ln.ULabel.get(name="my-label")
classmethod lookup(field=None, return_field=None)

Return an auto-complete object for a field.

Parameters:
  • field (str | DeferredAttribute | None, default: None) – The field to look up the values for. Defaults to first string field.

  • return_field (str | DeferredAttribute | None, default: None) – The field to return. If None, returns the whole record.

Return type:

NamedTuple

Returns:

A NamedTuple of lookup information of the field values with a dictionary converter.

See also

search()

Examples

>>> import bionty as bt
>>> bt.settings.organism = "human"
>>> bt.Gene.from_source(symbol="ADGB-DT").save()
>>> lookup = bt.Gene.lookup()
>>> lookup.adgb_dt
>>> lookup_dict = lookup.dict()
>>> lookup_dict['ADGB-DT']
>>> lookup_by_ensembl_id = bt.Gene.lookup(field="ensembl_gene_id")
>>> genes.ensg00000002745
>>> lookup_return_symbols = bt.Gene.lookup(field="ensembl_gene_id", return_field="symbol")
classmethod search(string, *, field=None, limit=20, case_sensitive=False)

Search.

Parameters:
  • string (str) – The input string to match against the field ontology values.

  • field (str | DeferredAttribute | None, default: None) – The field or fields to search. Search all string fields by default.

  • limit (int | None, default: 20) – Maximum amount of top results to return.

  • case_sensitive (bool, default: False) – Whether the match is case sensitive.

Return type:

QuerySet

Returns:

A sorted DataFrame of search results with a score in column score. If return_queryset is True. QuerySet.

See also

filter() lookup()

Examples

>>> ulabels = ln.ULabel.from_values(["ULabel1", "ULabel2", "ULabel3"], field="name")
>>> ln.save(ulabels)
>>> ln.ULabel.search("ULabel2")
classmethod using(instance)

Use a non-default LaminDB instance.

Parameters:

instance (str | None) – An instance identifier of form “account_handle/instance_name”.

Return type:

QuerySet

Examples

>>> ln.ULabel.using("account_handle/instance_name").search("ULabel7", field="name")
            uid    score
name
ULabel7  g7Hk9b2v  100.0
ULabel5  t4Jm6s0q   75.0
ULabel6  r2Xw8p1z   75.0

Methods

delete()

Delete.

Return type:

None

save(*args, **kwargs)

Save.

Always saves to the default database.

Return type:

Record