lamindb.core.Context¶
- class lamindb.core.Context¶
Bases:
object
Run context.
Enables convenient data lineage tracking by managing a transform & run upon
track()
&finish()
.Examples
Is typically used via the global
context
object vialn.track()
andln.finish()
:>>> import lamindb as ln >>> ln.track() >>> # do things >>> ln.finish()
Attributes¶
- property name: str | None¶
name argument for `context.transform
.
- property uid: str | None¶
uid
argument forcontext.transform
.
- property version: str | None¶
version
argument forcontext.transform
.
Methods¶
- finish(ignore_non_consecutive=None)¶
Finish a tracked run.
writes a timestamp:
run.finished_at
saves the source code:
transform.source_code
When called in the last cell of a notebook:
prompts for user input if not consecutively executed
requires to save the notebook in your editor right before
saves a run report:
run.report
- Parameters:
ignore_non_consecutive (
bool
|None
, default:None
) – Whether to ignore if a notebook was non-consecutively executed.- Return type:
None
Examples
>>> import lamindb as ln >>> ln.track() >>> # do things while tracking data lineage >>> ln.finish()
See also
lamin save script.py
orlamin save notebook.ipynb
→ docs
- track(uid=None, *, params=None, new_run=None, path=None, transform=None)¶
Initiate a run with tracked data lineage.
sets
transform
&run
by creating or loadingTransform
&Run
recordssaves compute environment as a
requirements.txt
file:run.environment
If
sync_git_repo
is set, checks whether a script-like transform exists in a git repository and links it.- Parameters:
uid (
str
|None
, default:None
) – Auid
to create or load a transform.params (
dict
|None
, default:None
) – A dictionary of parameters to track for the run.new_run (
bool
|None
, default:None
) – IfFalse
, loads latest run of transform (default notebook), ifTrue
, creates new run (default pipeline).path (
str
|None
, default:None
) – Filepath of notebook or script. Only needed if it can’t be automatically detected.transform (
Transform
|None
, default:None
) – Useful to track an abstract pipeline.
- Return type:
None
Examples
To track the run of a notebook or script, call:
>>> import lamindb as ln >>> ln.track()