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import os
from airflow import models
from airflow.providers.google.cloud.operators.life_sciences import LifeSciencesRunPipelineOperator
from airflow.utils import dates
PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project-id")
BUCKET = os.environ.get("GCP_GCS_LIFE_SCIENCES_BUCKET", "INVALID BUCKET NAME")
FILENAME = os.environ.get("GCP_GCS_LIFE_SCIENCES_FILENAME", 'input.in')
LOCATION = os.environ.get("GCP_LIFE_SCIENCES_LOCATION", 'us-central1')
# [START howto_configure_simple_action_pipeline]
SIMPLE_ACTION_PIPELINE = {
"pipeline": {
"actions": [
{"imageUri": "bash", "commands": ["-c", "echo Hello, world"]},
],
"resources": {
"regions": [f"{LOCATION}"],
"virtualMachine": {
"machineType": "n1-standard-1",
},
},
},
}
# [END howto_configure_simple_action_pipeline]
# [START howto_configure_multiple_action_pipeline]
MULTI_ACTION_PIPELINE = {
"pipeline": {
"actions": [
{
"imageUri": "google/cloud-sdk",
"commands": ["gsutil", "cp", f"gs://{BUCKET}/{FILENAME}", "/tmp"],
},
{"imageUri": "bash", "commands": ["-c", "echo Hello, world"]},
{
"imageUri": "google/cloud-sdk",
"commands": [
"gsutil",
"cp",
f"gs://{BUCKET}/{FILENAME}",
f"gs://{BUCKET}/output.in",
],
},
],
"resources": {
"regions": [f"{LOCATION}"],
"virtualMachine": {
"machineType": "n1-standard-1",
},
},
}
}
# [END howto_configure_multiple_action_pipeline]
with models.DAG(
"example_gcp_life_sciences",
default_args=dict(start_date=dates.days_ago(1)),
schedule_interval=None,
tags=['example'],
) as dag:
# [START howto_run_pipeline]
simple_life_science_action_pipeline = LifeSciencesRunPipelineOperator(
task_id='simple-action-pipeline',
body=SIMPLE_ACTION_PIPELINE,
project_id=PROJECT_ID,
location=LOCATION,
)
# [END howto_run_pipeline]
multiple_life_science_action_pipeline = LifeSciencesRunPipelineOperator(
task_id='multi-action-pipeline', body=MULTI_ACTION_PIPELINE, project_id=PROJECT_ID, location=LOCATION
)
simple_life_science_action_pipeline >> multiple_life_science_action_pipeline