Run Analytics Workflow¶
This chapter shows how to create and run workflow with a data source and analytics/processing algorithm.
Authenticate¶
First connect with UP42 as explained in the authentication chapter.
import up42
up42.authenticate(
project_id="your-project-ID",
project_api_key="your-project-API-key"
)
Create a workflow¶
This simple workflow consists of Sentinel-2 L2A data
and Sharpening Filter.
See up42.get_blocks
or the UP42 marketplace for all other data and
analytics tasks.
project = up42.initialize_project()
workflow = project.create_workflow(name="Workflow-example")
workflow.add_workflow_tasks(["Sentinel-2 L2A Visual (GeoTIFF)",
"Sharpening Filter"])
Configure the workflow¶
Provide workflow input parameters to configure the workflow, e.g. the area of interest, time period etc. with the help of the construct_parameters function.
aoi = up42.read_vector_file("data/aoi_berlin.geojson")
aoi = up42.get_example_aoi()
input_parameters = workflow.construct_parameters(geometry=aoi,
geometry_operation="bbox",
start_date="2020-01-01",
end_date="2022-12-31",
limit=1)
input_parameters["esa-s2-l2a-gtiff-visual:1"].update({"max_cloud_cover":5})
Estimate costs & Test¶
Before running the workflow, estimate the costs. You can also run a free test job to confirm the correct job configuration and data availability.
workflow.estimate_job(input_parameters)
workflow.test_job(input_parameters, track_status=True)
Run the workflow¶
job = workflow.run_job(input_parameters, track_status=True)
job.download_results()
job.plot_results()
⏭️ Continue with the Advanced section or see the examples & code reference.