Prepare transfer artifacts from a local instance to a cloud instance¶
!lamin settings set auto-connect false
import lamindb as ln
import bionty as bt
import wetlab as wl
import pandas as pd
ln.setup.init(storage="./test-transfer-to-cloud", modules="bionty,wetlab")
ln.setup.settings.auto_connect = False
→ initialized lamindb: testuser1/test-transfer-to-cloud
artifact = ln.Artifact.from_df(
pd.DataFrame({"a": [1, 2, 3]}), description="test-transfer-to-cloud"
).save()
features = bt.CellMarker.from_values(
["PD1", "CD21"], field=bt.CellMarker.name, organism="human"
)
ln.save(features)
artifact.features._add_schema(ln.FeatureSet(features), slot="var")
organism = bt.Organism.from_source(name="human").save()
artifact.labels.add(organism)
experiment = wl.Experiment(name="experiment-test-transfer-to-cloud").save()
artifact.experiments.add(experiment)
artifact.describe()
! no run & transform got linked, call `ln.track()` & re-run
Artifact .parquet · DataFrame · dataset ├── General │ ├── description: test-transfer-to-cloud │ ├── uid: 4Zvt5PZDNZxjoxM90000 hash: kBD-Hkm5bY3IAXR2FFiydA │ ├── size: 1.5 KB transform: none │ ├── space: all branch: main │ ├── created_by: testuser1 (Test User1) created_at: 2025-07-17 16:12:31 │ ├── n_observations: 3 │ └── storage path: │ /home/runner/work/lamindb/lamindb/docs/storage/test-transfer-to-cloud/.lamindb/4Zvt5PZDNZxjoxM90000.parquet ├── Dataset features │ └── var • 2 [bionty.CellMarker] │ PD1 num │ CD21 num └── Labels └── .experiments wetlab.Experiment experiment-test-transfer-to-cloud .organisms bionty.Organism human
assert artifact.features["var"].count() == 2
/tmp/ipykernel_3030/3568377865.py:1: FutureWarning: Use slots[slot].members instead of __getitem__, __getitem__ will be removed in the future.
assert artifact.features["var"].count() == 2