How to produce workflow artifacts

Create link artifacts

To create a link artifact, use the create_link_artifact() function. To create multiple versions of the same artifact and/or view them on the Artifacts page of the Prefect UI, provide a key argument to the create_link_artifact() function to track the artifact’s history over time. Without a key, the artifact is only visible in the Artifacts tab of the associated flow run or task run.

from prefect import flow, task
from prefect.artifacts import create_link_artifact


@task
def my_first_task():
    create_link_artifact(
        key="irregular-data",
        link="https://nyc3.digitaloceanspaces.com/my-bucket-name/highly_variable_data.csv",
        description="## Highly variable data",
    )


@task
def my_second_task():
    create_link_artifact(
        key="irregular-data",
        link="https://nyc3.digitaloceanspaces.com/my-bucket-name/low_pred_data.csv",
        description="# Low prediction accuracy",
    )


@flow
def my_flow():
    my_first_task()
    my_second_task()


if __name__ == "__main__":
    my_flow()

Specify multiple artifacts with the same key for artifact lineageYou can specify multiple artifacts with the same key to easily track something very specific, such as irregularities in your data pipeline.

After running flows that create artifacts, view the artifacts in the Artifacts page of the UI. Click into the “irregular-data” artifact to see its versions, along with custom descriptions and links to the relevant data.

Link artifact details with multiple versions

You can also view information about the artifact such as:

its associated flow run or task run id
previous and future versions of the artifact (multiple artifacts can have the same key to show lineage)
data (in this case a Markdown-rendered link)
an optional Markdown description
when the artifact was created or updated

To make the links more readable for you and your collaborators, you can pass a link_text argument:

from prefect import flow
from prefect.artifacts import create_link_artifact


@flow
def my_flow():
    create_link_artifact(
        key="my-important-link",
        link="https://www.prefect.io/",
        link_text="Prefect",
    )


if __name__ == "__main__":
    my_flow()

In the above example, the create_link_artifact method is used within a flow to create a link artifact with a key of my-important-link. The link parameter specifies the external resource to link to, and link_text specifies the text to display for the link. Add an optional description for context.

Create progress artifacts

Progress artifacts render dynamically on the flow run graph in the Prefect UI, indicating the progress of long-running tasks. To create a progress artifact, use the create_progress_artifact() function. To update a progress artifact, use the update_progress_artifact() function.

from time import sleep

from prefect import flow, task
from prefect.artifacts import (
    create_progress_artifact,
    update_progress_artifact,
)


def fetch_batch(i: int):
    # Simulate fetching a batch of data
    sleep(2)


@task
def fetch_in_batches():
    progress_artifact_id = create_progress_artifact(
        progress=0.0,
        description="Indicates the progress of fetching data in batches.",
    )
    for i in range(1, 11):
        fetch_batch(i)
        update_progress_artifact(artifact_id=progress_artifact_id, progress=i * 10)


@flow
def etl():
    fetch_in_batches()


if __name__ == "__main__":
    etl()

Progress artifacts are updated with the update_progress_artifact() function. Prefect updates a progress artifact in place, rather than versioning it.

Create Markdown artifacts

To create a Markdown artifact, you can use the create_markdown_artifact() function. To create multiple versions of the same artifact and/or view them on the Artifacts page of the Prefect UI, provide a key argument to the create_markdown_artifact() function to track an artifact’s history over time. Without a key, the artifact is only visible in the Artifacts tab of the associated flow run or task run.

Don’t indent MarkdownDon’t indent Markdown in multi-line strings. Otherwise it will be interpreted incorrectly.

from prefect import flow, task
from prefect.artifacts import create_markdown_artifact


@task
def markdown_task():
    na_revenue = 500000
    markdown_report = f"""# Sales Report

## Summary

In the past quarter, our company saw a significant increase in sales, with a total revenue of $1,000,000. 
This represents a 20% increase over the same period last year.

## Sales by Region

| Region        | Revenue |
|:--------------|-------:|
| North America | ${na_revenue:,} |
| Europe        | $250,000 |
| Asia          | $150,000 |
| South America | $75,000 |
| Africa        | $25,000 |

## Top Products

1. Product A - $300,000 in revenue
2. Product B - $200,000 in revenue
3. Product C - $150,000 in revenue

## Conclusion

Overall, these results are very encouraging and demonstrate the success of our sales team in increasing revenue 
across all regions. However, we still have room for improvement and should focus on further increasing sales in 
the coming quarter.
"""
    create_markdown_artifact(
        key="gtm-report",
        markdown=markdown_report,
        description="Quarterly Sales Report",
    )


@flow()
def my_flow():
    markdown_task()
    

if __name__ == "__main__":
    my_flow()

After running the above flow, you should see your “gtm-report” artifact in the Artifacts page of the UI.

You can view the associated flow run id or task run id, previous versions of the artifact, the rendered Markdown data, and the optional Markdown description.

Create table artifacts

Create a table artifact by calling create_table_artifact(). To create multiple versions of the same artifact and/or view them on the Artifacts page of the Prefect UI, provide a key argument to the create_table_artifact() function to track an artifact’s history over time. Without a key, the artifact is only visible in the artifacts tab of the associated flow run or task run.

The create_table_artifact() function accepts a table argument. Pass this as a list of lists, a list of dictionaries, or a dictionary of lists.

from prefect.artifacts import create_table_artifact


def my_fn():
    highest_churn_possibility = [
       {'customer_id':'12345', 'name': 'John Smith', 'churn_probability': 0.85 }, 
       {'customer_id':'56789', 'name': 'Jane Jones', 'churn_probability': 0.65 } 
    ]

    create_table_artifact(
        key="personalized-reachout",
        table=highest_churn_possibility,
        description= "# Marvin, please reach out to these customers today!"
    )


if __name__ == "__main__":
    my_fn()

Create image artifacts

Image artifacts render publicly available images in the Prefect UI. To create an image artifact, use the create_image_artifact() function.

from prefect import flow, task
from prefect.artifacts import (
    create_image_artifact,
)


@task
def create_image():
    # Do something to create an image and upload to a url
    image_url = "https://media3.giphy.com/media/v1.Y2lkPTc5MGI3NjExZmQydzBjOHQ2M3BhdWJ4M3V1MGtoZGxuNmloeGh6b2dvaHhpaHg0eSZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/3KC2jD2QcBOSc/giphy.gif"
    create_image_artifact(image_url=image_url, description="A gif.", key="gif")
    return image_url


@flow
def my_flow():
    return create_image()


if __name__ == "__main__":
    image_url = my_flow()
    print(f"Image URL: {image_url}")

To create an artifact that links to a private image, use the create_link_artifact() function instead.

Reading artifacts

In the Prefect UI, you can view all of the latest versions of your artifacts and click into a specific artifact to see its lineage over time. Additionally, you can inspect all versions of an artifact with a given key from the CLI by running:

prefect artifact inspect <my_key>

or view all artifacts by running:

prefect artifact ls

You can also use the Prefect REST API to programmatically filter your results.

Fetching artifacts

In Python code, you can retrieve an existing artifact with the Artifact.get class method:

from prefect.artifacts import Artifact

my_retrieved_artifact = Artifact.get("my_artifact_key")

Delete artifacts

Delete an artifact in the CLI by providing a key or id:

prefect artifact delete <my_key>

prefect artifact delete --id <my_id>

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How to produce workflow artifacts

Create link artifacts

Create progress artifacts

Create Markdown artifacts

Create table artifacts

Create image artifacts

Reading artifacts

Fetching artifacts

Delete artifacts

​Create link artifacts

​Create progress artifacts

​Create Markdown artifacts

​Create table artifacts

​Create image artifacts

​Reading artifacts

​Fetching artifacts

​Delete artifacts

Create link artifacts

Create progress artifacts

Create Markdown artifacts

Create table artifacts

Create image artifacts

Reading artifacts

Fetching artifacts

Delete artifacts