@Marvin What is the equivalent of these terminal commands:

prefect flow-run ls --state Cancelling

and

prefect flow-run delete

To achieve the equivalent of the terminal commands

prefect flow-run ls --state Cancelling

and

prefect flow-run delete

in Python using Prefect 3.x, you can use the

PrefectClient

class from the

prefect.client.orchestration

module. Here's a concise guide: 1. List Flow Runs by State ("Cancelling"): You can use the

FlowRunFilter

class from

prefect.client.schemas.filters

to filter flow runs by state. Specifically, use

FlowRunFilterStateName

to filter for the "Cancelling" state. 2. Delete Flow Runs: The Prefect 3.x documentation does not provide a direct method to delete flow runs via the client. Typically, deletion is managed through the Prefect UI or REST API, so ensure you check the latest API capabilities or UI options. Here's an example to list flow runs by state using Python:

python
from prefect.client.orchestration import PrefectClient
from prefect.client.schemas.filters import FlowRunFilter, FlowRunFilterStateName

async def list_cancelling_flow_runs():
    async with PrefectClient() as client:
        filter = FlowRunFilter(state_name=FlowRunFilterStateName(any_=["Cancelling"]))
        flow_runs = await client.read_flow_runs(flow_run_filter=filter)
        return flow_runs

# Use asyncio to run the async function
# import asyncio
# asyncio.run(list_cancelling_flow_runs())

For detailed management of flow runs, refer to the Prefect documentation: Prefect 3.x Documentation.

@Marvin basically I want to list and delete all flow-runs within my workspace that are in the state of the cancelling through a python script

To list and delete all flow runs in the "Cancelling" state within your workspace using a Python script with Prefect 3.x, you can utilize the

PrefectClient

class. Here's a step-by-step guide: 1. List Flow Runs in "Cancelling" State: Use the

FlowRunFilter

with

FlowRunFilterStateName

to filter flow runs by the "Cancelling" state. 2. Delete Flow Runs: Currently, Prefect does not provide a direct method to delete flow runs via the Python client. However, you can interact with the REST API for such operations if necessary. Here's a script to list the flow runs:

python
from prefect.client.orchestration import PrefectClient
from prefect.client.schemas.filters import FlowRunFilter, FlowRunFilterStateName

async def list_and_delete_cancelling_flow_runs():
    async with PrefectClient() as client:
        # List flow runs in "Cancelling" state
        filter = FlowRunFilter(state_name=FlowRunFilterStateName(any_=["Cancelling"]))
        flow_runs = await client.read_flow_runs(flow_run_filter=filter)
        
        # Display the flow runs
        for flow_run in flow_runs:
            print(f"Flow Run ID: {flow_run.id}, State: {flow_run.state_name}")
            
        # Note: Direct deletion via the client is not supported; use API or UI for deletion

# To execute the async function, use asyncio
# import asyncio
# asyncio.run(list_and_delete_cancelling_flow_runs())

For deletion, you might need to use the Prefect REST API directly or manage deletions through the Prefect UI. Always ensure you're operating within the latest API capabilities. For more details, refer to the Prefect 3.x Documentation.

@Marvin

PrefectHTTPStatusError                    Traceback (most recent call last)
Cell In[1], line 11
      8 async with PrefectClient(api=api_url,api_key=api_key) as client:
      9     # List flow runs in "Cancelling" state
     10     filter = FlowRunFilter(state_name=FlowRunFilterStateName(any_=["Cancelling"]))
---> 11     flow_runs = await client.read_flow_runs(flow_run_filter=filter)
     13     # Display the flow runs
     14     for flow_run in flow_runs:

File /opt/homebrew/lib/python3.11/site-packages/prefect/client/orchestration/_flow_runs/client.py:733, in FlowRunAsyncClient.read_flow_runs(self, flow_filter, flow_run_filter, task_run_filter, deployment_filter, work_pool_filter, work_queue_filter, sort, limit, offset)
    690 """
    691 Query the Prefect API for flow runs. Only flow runs matching all criteria will
    692 be returned.
   (...)
    707         of the flow runs
    708 """
    709 body: dict[str, Any] = {
    710     "flows": flow_filter.model_dump(mode="json") if flow_filter else None,
    711     "flow_runs": (
   (...)
    730     "offset": offset,
    731 }
--> 733 response = await self.request("POST", "/flow_runs/filter", json=body)
    734 from prefect.client.schemas.objects import FlowRun
...
    162 except HTTPStatusError as exc:
--> 163     raise PrefectHTTPStatusError.from_httpx_error(exc) from exc.__cause__

PrefectHTTPStatusError: Server error '500 Internal Server Error' for url '<http://ephemeral-prefect/api/csrf-token?client=6c03ee1d-db07-4afe-ac85-95117b452ec7>'

Your message was too long by 117 tokens...

@Marvin

PrefectHTTPStatusError: Server error '500 Internal Server Error' for url '<http://ephemeral-prefect/api/csrf-token?client=6c03ee1d-db07-4afe-ac85-95117b452ec7>'

The

PrefectHTTPStatusError: Server error '500 Internal Server Error'

you are encountering could be related to a few known issues. Here are some insights and potential steps to resolve it: 1. Retry Configuration Issue: There is a known issue where setting retries to zero with an exponential backoff can cause a 500 internal server error. Ensure that your retry configurations are not set to zero in combination with exponential backoff. 2. Random Server Errors: Another reported issue involves random 500 errors due to server-side timeouts. Increasing the

PREFECT_API_DATABASE_CONNECTION_TIMEOUT

and

PREFECT_API_DATABASE_TIMEOUT

environment variables has been suggested as a workaround. This could help if your Prefect server is experiencing high load or slow database responses. 3. General Troubleshooting: - Ensure your Prefect server and agents are up-to-date with the latest version. - Check server logs for more detailed error messages that might indicate the root cause. - Verify network connectivity and that your Prefect server is properly configured. For more detailed information, you can review these related GitHub issues: - Exponential backoff with retries=0 causes a 500 error - Random 500 Internal Server Error in UI If the issue persists, consider reaching out to the Prefect community or support for more tailored assistance.