juana
01/03/2024, 3:02 AMMarvin
01/03/2024, 3:03 AMNate
01/03/2024, 3:04 AMMarvin
01/03/2024, 3:04 AMNate
01/03/2024, 3:04 AMMarvin
01/03/2024, 3:05 AMpython
from prefect import flow, task
from prefect.artifacts import create_link, create_markdown
@task
def generate_data():
# Your logic to generate data
data = {"example": "data"}
return data
@task
def process_data(data):
# Your logic to process data
processed_data = f"Processed: {data}"
return processed_data
@flow
def my_flow():
data = generate_data()
processed_data = process_data(data)
# Create a Markdown artifact
create_markdown("# This is a Markdown artifact\nThis flow processed the following data:\n```\n" + str(processed_data) + "\n```")
# Suppose you have a link to a dashboard or external resource
dashboard_url = "<http://example.com/dashboard>"
# Create a link artifact
create_link(dashboard_url)
# Run the flow
my_flow()
In this code example:
- The generate_data
task simulates generating some data.
- The process_data
task simulates processing that data.
- In the my_flow
flow, after processing the data, we create a Markdown artifact using create_markdown
, which contains a description and the processed data.
- We also create a link artifact using create_link
, which could, for example, point to a dashboard related to the flow.
These artifacts will be stored and rendered in the Prefect UI, making it easy to monitor and share information with your team or stakeholders.