run_pipeline.py

import os

from codeocean import CodeOcean
from codeocean.computation import RunParams
from codeocean.data_asset import (
    DataAssetParams,
    DataAssetsRunParam,
    PipelineProcessParams,
    Source,
    ComputationSource,
    Target,
    AWSS3Target,
)


# Create the client using your domain and API token.

client = CodeOcean(domain=os.environ["CODEOCEAN_URL"], token=os.environ["API_TOKEN"])

# Run a pipeline with ordered parameters.

run_params = RunParams(
    pipeline_id=os.environ["PIPELINE_ID"],
    data_assets=[
        DataAssetsRunParam(
            id="eeefcc52-b445-4e3c-80c5-0e65526cd712",
            mount="Reference",
        ),
    ],
    processes=[
        PipelineProcessParams(
            name="capsule_art_simulation_illumina_1",
            parameters=["75", "1", "HS25", "SingleEnded"],
        ),
        PipelineProcessParams(
            name="capsule_copy_of_fast_qc_2",
        ),
    ],
)

computation = client.computations.run_capsule(run_params)

# Wait for pipeline to finish.

computation = client.computations.wait_until_completed(computation)

# Create an external (S3) data asset from computation results.

data_asset_params = DataAssetParams(
    name="My External Result",
    description="Computation result",
    mount="my-result",
    tags=["my", "external", "result"],
    source=Source(
        computation=ComputationSource(
            id=computation.id,
        ),
    ),
    target=Target(
        aws=AWSS3Target(
            bucket=os.environ["EXTERNAL_S3_BUCKET"],
            prefix=os.environ.get("EXTERNAL_S3_BUCKET_PREFIX"),
        ),
    ),
)

data_asset = client.data_assets.create_data_asset(data_asset_params)

data_asset = client.data_assets.wait_until_ready(data_asset)