strand-sdk

Python client for Lattice spatial proteomics from H&E. Upload H&E whole-slide images, predict spatially resolved protein-marker maps, and download the virtual mIF channels as AnnData or OME-Zarr/OME-TIFF.

📚 Full documentation: https://docs.strandai.com/sdks/python

Agent-readable API reference: https://app.strandai.com/docs/api.md · LLM index: https://app.strandai.com/llms.txt

Requires Python 3.12+.

Install

pip install strand-sdk
# or with bioinformatics extras (AnnData / zarr):
pip install "strand-sdk[anndata]"

The package also installs the strand command. It supports the same sample and run lifecycle without renaming the SDK-native verbs:

sample_id=$(strand upload biopsy.svs --mpp 0.26 | jq -r .id)
while :; do
  status=$(strand samples get "$sample_id" | jq -r .status)
  case "$status" in ready) break ;; *failed) exit 1 ;; esac
  sleep 2
done
strand predict "$sample_id" -m CD8,PanCK --dry-run
job_id=$(strand predict "$sample_id" -m CD8,PanCK | jq -r .job_id)
strand wait "$job_id" --timeout 1800
strand export "$job_id" --format ome-tiff --out result.ome.tiff --timeout 1800

Use strand cancel "$job_id" for an eligible in-flight run and strand results "$job_id" --out ./results/ for the OME-Zarr tree.

Quickstart

One blocking call runs the full pipeline: upload, submit, wait, and download.

from strand import Client, SampleFieldFilter

client = Client()  # reads STRAND_API_KEY; mint one at https://app.strandai.com/settings/api-keys
result = client.predict(
    "biopsy.ome.tiff",
    markers=["PanCK", "CD8", "CD45"],
    output_dir="./outputs/",
)
print(f"Used {result.credits_used} credits; wrote {len(result.marker_outputs)} markers")

Scoped sample reads and updates use one namespace:

definitions = client.samples.fields()
tags_id = next(field.id for field in definitions if field.key == "tags")
page = client.samples.list(
    scope="mine",
    field=SampleFieldFilter(tags_id, "eq", "trial-042"),
)
sample_id = page.items[0].id
sample = client.samples.get(sample_id)
client.samples.patch(
    sample_id,
    name="Baseline",
    fields={"tags": ["trial-042"]},
    mpp=0.26,
)

estimate = client.predict.submit(sample_id, ["CD8", "PanCK"], dry_run=True)
job = client.predict.submit(sample_id, ["CD8", "PanCK"])

Uploads, model selection, async jobs, public OME-Zarr reads, OME-TIFF export, and error handling are covered in the hosted docs.

Issues & support

File bug reports and feature requests at Strand-AI/strand-sdk-python/issues, or email support@strandai.com. This repository is a generated, read-only mirror of Strand's monorepo. Pull requests opened here are overwritten by the next sync.

License

Apache 2.0