lamindb.Run
¶
- class lamindb.Run(transform: Transform, name: str | None = None, description: str | None = None, entrypoint: str | None = None, params: dict | None = None, reference: str | None = None, reference_type: str | None = None, initiated_by_run: Run | None = None, plan: Artifact | None = None)¶
Bases:
SQLRecord,TracksUpdatesRuns of transforms such as the executions of a script.
- Parameters:
transform –
TransformA data transformation object.name –
str | None = NoneA name.params –
dict | None = NoneA dictionary of parameters.reference –
str | None = NoneFor instance, an external ID or URL.reference_type –
str | None = NoneFor instance,redun_id,nextflow_idorurl.initiated_by_run –
Run | None = NoneTherunthat triggers thisrun.
See also
Examples
Create a run record:
ln.Transform(key="Cell Ranger", version="7.2.0", kind="pipeline").save() transform = ln.Transform.get(key="Cell Ranger", version="7.2.0") run = ln.Run(transform)
Track a global run of a notebook or script:
ln.track() ln.context.run # global run object
You can pass parameters to
Run(transform, params=params)or add them later:run.params = { "learning_rate": 0.01, "input_dir": "s3://my-bucket/mydataset", "downsample": True, "preprocess_params": { "normalization_type": "cool", "subset_highlyvariable": True, }, } run.save()
In contrast to
.params, features are indexed in theFeatureregistry and can reference relational categorical values. If you want to link feature values, use:run.features.set_values({ "experiment": "My experiment 1", })
Guide: Track parameters & features
Attributes¶
- property features: FeatureManager¶
Manage annotations with features.
For examples, see
RunorFeatureManager.
- property status: Literal['scheduled', 'restarted', 'started', 'completed', 'errored', 'aborted']¶
Run status.
Get the status of the run:
status
code
description
scheduled-3
run is scheduled
restarted-2
run was restarted
started-1
run has started
completed0
run completed successfully
errored1
run ended with an error
aborted2
run was aborted
The database stores the run status as an integer code in field
_status_code.Example
See the status of a run:
run.status #> 'completed'
Query by status:
ln.Run.filter(status="completed").to_dataframe()
Simple fields¶
- uid: str¶
Universal id, valid across DB instances.
- name: str | None¶
An optional name for this run.
- description: str | None¶
An optional description for this run.
- entrypoint: str | None¶
The entrypoint of the transform.
This could be a function name or the entry point of a CLI or workflow manager.
- started_at: datetime¶
The time this run started.
- finished_at: datetime | None¶
The time this run finished or aborted.
- params: dict¶
Parameters (plain JSON values).
- reference: str | None¶
A reference like a URL or an external ID such as from a workflow manager.
- reference_type: str | None¶
The type of the
referencesuch as a workflow manager execution ID.
- cli_args: str | None¶
CLI arguments if the run was invoked from the command line.
- created_at: datetime¶
The time of creation of this run.
- is_locked: bool¶
Whether the object is locked for edits.
- updated_at: datetime¶
Time of last update to record.
Relational fields¶
- environment: Artifact | None¶
The computational environment for this run.
For instance,
Dockerfile,docker image,requirements.txt,environment.yml, etc.
- plan: Artifact | None¶
The (agent) plan for this run.
Also see:
initiated_by_run.
- created_by: User¶
The creator of this run ←
created_runs.
- initiated_by_run: Run | None¶
The run that initiated this run ←
initiated_runs.
- json_values: RelatedManager[JsonValue]¶
Feature-indexed JSON values ←
runs.
- ulabels: RelatedManager[ULabel]¶
The ulabels annotating this run ←
runs.
- linked_in_records: RelatedManager[Record]¶
This run is linked in these records as a value ←
linked_runs.
- artifacts: RelatedManager[Artifact]¶
The artifacts annotated by this run ←
runs.
- linked_artifacts: RelatedManager[Artifact]¶
The artifacts linked by this run through the run’s features ←
artifact.
- initiated_runs: RelatedManager[Run]¶
The runs that were initiated by this run.
- values_artifact¶
- output_artifacts: RelatedManager[Artifact]¶
The artifacts created in this run ←
run.This does not include recreated artifacts, which are tracked via
recreated_artifacts.If you want to query created + recreated artifacts, use
query_output_artifacts()instead.
- input_artifacts: RelatedManager[Artifact]¶
The artifacts serving as input for this run ←
input_of_runs.
- recreated_artifacts: RelatedManager[Artifact]¶
The output artifacts that were recreated by this run ←
recreating_runs.Artifacts are recreated if they trigger a hash lookup match for an existing artifact.
- output_collections: RelatedManager[Collection]¶
The collections created in this run ←
run.
- input_collections: RelatedManager[Collection]¶
The collections serving as input for this run ←
input_of_runs.
- recreated_collections: RelatedManager[Collection]¶
The output collections that were recreated by this run ←
recreating_runs.Collections are recreated if they trigger a hash lookup match for an existing collection.
- output_records: RelatedManager[Record]¶
The collections created in this run ←
run.
- input_records: RelatedManager[Record]¶
The collections serving as input for this run ←
input_of_runs.
- records: RelatedManager[Record]¶
The records annotating this run ←
runs.
- projects: RelatedManager[Project]¶
The projects annotating this run ←
runs.
- ablocks: RelatedManager[RunBlock]¶
Attached blocks ←
run.
Class methods¶
- filter(**expressions)¶
Query records.
- Parameters:
queries – One or multiple
Qobjects.expressions – Fields and values passed as Django query expressions.
- Return type:
See also
Guide: Query & search registries
Django documentation: Queries
Examples
>>> ln.Project(name="my label").save() >>> ln.Project.filter(name__startswith="my").to_dataframe()
- 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.
- Raises:
lamindb.errors.ObjectDoesNotExist – In case no matching record is found.
- Return type:
See also
Guide: Query & search registries
Django documentation: Queries
Examples
record = ln.Record.get("FvtpPJLJ") record = ln.Record.get(name="my-label")
- classmethod to_dataframe(include=None, features=False, limit=100)¶
Evaluate and convert to
pd.DataFrame.By default, this returns up to 100 rows for a fast overview. Pass
limit=Noneto fetch all matching records.By default, maps simple fields and foreign keys onto
DataFramecolumns.Guide: Query & search registries
- Parameters:
include (
str|list[str] |None, default:None) – Related data to include as columns. Takes strings of form"records__name","cell_types__name", etc. or a list of such strings. ForArtifact,Record, andRun, can also pass"features"to include features with data types pointing to entities in the core schema. If"privates", includes private fields (fields starting with_).features (
bool|list[str], default:False) – Configure the features to include. Can be a feature name or a list of such names. If"queryset", infers the features used within the current queryset. Only available forArtifact,Record, andRun.limit (
int, default:100) – Maximum number of rows to display. Defaults to 100. IfNone, includes all results.order_by – Field name to order the records by. Prefix with ‘-’ for descending order. Defaults to ‘-id’ to get the most recent records. This argument is ignored if the queryset is already ordered or if the specified field does not exist.
- Return type:
DataFrame
Examples
Include the name of the creator:
ln.Record.to_dataframe(include="created_by__name"])
Include features:
ln.Artifact.to_dataframe(include="features")
Include selected features:
ln.Artifact.to_dataframe(features=["cell_type_by_expert", "cell_type_by_model"])
- 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:
- Returns:
A sorted
DataFrameof search results with a score in columnscore. Ifreturn_querysetisTrue.QuerySet.
See also
filter()lookup()Examples
records = ln.Record.from_values(["Label1", "Label2", "Label3"], field="name").save() ln.Record.search("Label2")
- 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. IfNone, returns the whole record.keep – When multiple records are found for a lookup, how to return the records. -
"first": return the first record. -"last": return the last record. -False: return all records.
- Return type:
NamedTuple- Returns:
A
NamedTupleof lookup information of the field values with a dictionary converter.
See also
search()Examples
Lookup via auto-complete on
.:import bionty as bt bt.Gene.from_source(symbol="ADGB-DT").save() lookup = bt.Gene.lookup() lookup.adgb_dt
Look up via auto-complete in dictionary:
lookup_dict = lookup.dict() lookup_dict['ADGB-DT']
Look up via a specific field:
lookup_by_ensembl_id = bt.Gene.lookup(field="ensembl_gene_id") genes.ensg00000002745
Return a specific field value instead of the full record:
lookup_return_symbols = bt.Gene.lookup(field="ensembl_gene_id", return_field="symbol")
Methods¶
- query_output_artifacts(include_recreated=True)¶
Query output artifacts including recreated ones.
This runs the following query under the hood:
ln.Artifact.filter(ln.Q(run=self) | ln.Q(recreating_runs=self)).distinct()
- Parameters:
include_recreated (
bool, default:True) – IfTrue, return both originally created and recreated artifacts. IfFalse, return only originally created artifacts.- Return type:
- Returns:
A queryset of
Artifactobjects.
See also
output_artifactsQuerySetof originally created artifacts.recreated_artifactsQuerySetof recreated artifacts.
- restore()¶
Restore from trash onto the main branch.
Does not restore descendant objects if the object is
HasTypewithis_type = True.- Return type:
None
- delete(permanent=None, **kwargs)¶
Delete object.
If object is
HasTypewithis_type = True, deletes all descendant objects, too.- Parameters:
permanent (
bool|None, default:None) – Whether to permanently delete the object (skips trash). IfNone, performs soft delete if the object is not already in the trash.- Returns:
When
permanent=True, returns Django’s delete return value – a tuple of (deleted_count, {registry_name: count}). Otherwise returns None.
Examples
For any
SQLRecordobjectsqlrecord, call:sqlrecord.delete()
- save(*args, **kwargs)¶
Save.
Always saves to the default database.
- Return type:
TypeVar(T, bound= SQLRecord)
- classmethod describe(include=None)¶
Describe record including relations.
- Parameters:
return_str (
bool, default:False) – Return a string instead of printing.include (
None|Literal['comments'], default:None) – Include additional content. Use"comments"to display readme and comment blocks.
- Return type:
None|str
- refresh_from_db(using=None, fields=None, from_queryset=None)¶
Reload field values from the database.
By default, the reloading happens from the database this instance was loaded from, or by the read router if this instance wasn’t loaded from any database. The using parameter will override the default.
Fields can be used to specify which fields to reload. The fields should be an iterable of field attnames. If fields is None, then all non-deferred fields are reloaded.
When accessing deferred fields of an instance, the deferred loading of the field will call this method.