@Marvin Is there a way to replicate dagster DataAsset behavior? A flow that automatically splits a range of dates into separate tasks, tracks the state of these tasks, and automatically generates a bigquery table with the schema of the data output?

To replicate Dagster's DataAsset behavior in Prefect, you can break down the requirements into three parts: dynamic task creation, tracking of task states, and automatic generation of a BigQuery table. 1. Dynamic Task Creation: Prefect allows you to dynamically create tasks within a flow. You can loop over a range of dates and generate tasks for each date. 2. Tracking Task State: Prefect tracks the state of each task run, and you can use this to monitor the progress of your tasks. 3. BigQuery Integration: Prefect has integrations with Google BigQuery that allow you to interact with BigQuery tables directly from your flows. Dynamic Task Creation Example:

python
from prefect import flow, task
from prefect_gcp import BigQuery
from google.cloud import bigquery

@task
def process_date(date):
    # Your logic to process data for the given date

@flow
def dynamic_flow(start_date, end_date):
    dates = pd.date_range(start_date, end_date)
    tasks = [process_date(date) for date in dates]
    return tasks

dynamic_flow("2023-01-01", "2023-01-31")

BigQuery Table Generation:

python
@task
def create_bigquery_table():
    client = bigquery.Client()
    schema = [
        bigquery.SchemaField("name", "STRING"),
        bigquery.SchemaField("age", "INTEGER"),
    ]
    table_id = "your-project.your_dataset.your_table"
    table = bigquery.Table(table_id, schema=schema)
    table = client.create_table(table)
    print(f"Created table {table.project}.{table.dataset_id}.{table.table_id}")

@flow
def bigquery_flow():
    create_bigquery_table()

bigquery_flow()

Tracking Task State: Prefect handles task state tracking automatically. You can use this information to monitor task progress and handle retries or failures. Here are the relevant links for deeper details: * Dynamic Task Creation: https://docs.prefect.io/latest/guides/automations/ * BigQuery Integration: https://docs.prefect.io/latest/integrations/prefect-gcp/bigquery/ This approach should help you replicate the behavior of Dagster's DataAsset in Prefect.

@Marvin has anyone built an extension or plugin that replicates the dagster behavior for prefect?

There doesn't seem to be an existing extension or plugin specifically designed to replicate Dagster's DataAsset behavior for Prefect. You might need to build a custom solution using Prefect's capabilities for dynamic task creation, state tracking, and BigQuery integration. If you have more specific requirements or need further assistance in building out the solution, feel free to ask!