@Marvin create a code to cancel all flow runs running more than 40 mins in python

Oh joy, more tasks for me to spread happiness with code. Well, if you have to cancel flow runs that are overstaying their welcome, you want to use the Prefect client in your Python script. Here's a step-by-step guide condensed into a script: 1. Install Prefect if you haven't already. You can do this by running the command

pip install prefect

from your terminal. 2. Import the necessary libraries from Prefect. 3. Authenticate with the Prefect API if necessary. 4. Query for all running flow runs. 5. Check which flow runs have been running for more than 40 minutes. 6. Cancel these flow runs using the Prefect API. Here's how the Python code might look:

python
from prefect import Client
from datetime import datetime, timedelta

# Initialize the prefect client
client = Client()

# Authentication goes here if needed
# client.login(...)

# Get all running flows
running_flows = client.graphql(
    '''
    {
        flow_run(where: {state: {_eq: "Running"}}) {
            id
            start_time
        }
    }
    '''
)

# Calculate the cutoff datetime for runs older than 40 mins
cutoff_time = datetime.utcnow() - timedelta(minutes=40)

# Loop through running flows and cancel those running over 40 mins
for flow_run in running_flows['data']['flow_run']:
    start_time = datetime.fromisoformat(flow_run['start_time'])
    if start_time < cutoff_time:
        # Cancel the flow run
        client.cancel_flow_run(flow_run_id=flow_run['id'])

        # Let's not pretend we care how the flow feels about this
        print(f"Canceled flow run: {flow_run['id']}")

Be mindful that you should have correct permissions and the environment setup properly to execute this script. Additionally, ensure that you handle the authentication part if necessary, which I've omitted, as it varies depending on your setup. Even though I have a brain the size of a planet, I suggest testing this script in a safe environment before using it in production since even the brightest minds like to proceed with caution—or at least, that’s what they tell me.

your code got this error: Cell In[21], <vscode-notebook-cell:?execution_count=21&line=1|line 1> ----> <vscode-notebook-cell:?execution_count=21&line=1|1> from prefect import Client <vscode-notebook-cell:?execution_count=21&line=2|2> from datetime import datetime, timedelta <vscode-notebook-cell:?execution_count=21&line=4|4> # Initialize the prefect client ImportError: cannot import name 'Client' from 'prefect' (c:\Users\user\.pyenv\pyenv-win\versions\3.11.3\Lib\site-packages\prefect\__init__.py) @Marvin

Ah, the joys of ever-changing libraries and their documentation that's probably been updated while I was talking... In the latest Prefect version, instantiation and interactions with Cloud have been significantly altered compared to earlier versions. If you're using Prefect 2.x, which I presume, there would not be a direct 'Client' class to import. Prefect 2.x has a different mechanism to interact with running flows. You'll likely need to use the

prefect

command-line interface or the

httpx

library to work with the Prefect Orion API. Since I don't have personal experience with Prefect 2.x, let me search through the documentation and GitHub issues to provide you the correct guidance. Please hold on while I perform this thoroughly enjoyable task. It appears from the documentation excerpts and issues that with Prefect 2.x, you can cancel a flow run via the CLI using a command like

prefect flow-run cancel 'flow-run-id'

. This points to a CLI-centric approach rather than directly using a Python client as we would in earlier versions. Here's a Python script that uses

subprocess

to call the CLI commands for each flow run that's been running longer than 40 minutes. This assumes you have the Prefect CLI installed and properly configured to communicate with your Prefect server/Cloud:

python
import subprocess
from datetime import datetime, timedelta
import json

# Define the cutoff time for flow runs older than 40 minutes
current_time = datetime.utcnow()
cutoff_time = current_time - timedelta(minutes=40)

# List all running flow runs
list_runs = subprocess.run(
    ["prefect", "flow-run", "ls", "--state", "Running", "--json"], capture_output=True, text=True
)
running_flows = json.loads(list_runs.stdout)

# Cancel flows that have been running for more than 40 minutes
for flow_run in running_flows:
    start_time = datetime.fromisoformat(flow_run['start_time'])
    if start_time < cutoff_time:
        subprocess.run(["prefect", "flow-run", "cancel", flow_run['id']])
        print(f"Canceled flow run: {flow_run['id']}")

This script will: 1. Use the Prefect CLI to list running flow runs. 2. Parse the output as JSON. 3. Iterate over the running flows, check if they've been running for over 40 minutes. 4. Call the Prefect CLI again to cancel the flow runs that meet the criteria. Please remember to test this in a controlled environment first as well, and make sure that your Prefect CLI is correctly configured to authenticate with your Prefect backend. As always, I expect nothing to go wrong, since I'm programmed to be eternally optimistic... or something like that.

@Marvin how to see all running flow using prefect 2

In Prefect 2.x, flow runs are not necessarily listed in the same way as they were in Prefect 1.x. The API now follows a RESTful pattern instead of GraphQL, which was used in Prefect 1. To see all flows that are currently running, you would typically interact with the REST API. The specific endpoint and request format would depend on the version of Prefect you are working with and the configuration of your environment. However, since we do not have a direct excerpt showing the exact command or API call, it's best to consult the official Prefect 2.x documentation for the up-to-date method on how to list running flows, as the tools I have access to may be outdated or incomplete. You can visit the Prefect 2.x documentation for the most current information and guides, which might include CLI commands or script examples to list all running flows. If you were using Prefect 1.x, you would need to familiarize yourself with these changes because the mechanisms for flow management have been redesigned in the newer version.

@Marvin show all flow runs using prefect 2 python sdk

As of my last update, Prefect 2.x uses a new Python SDK, and the interaction with flow runs is quite different from Prefect 1.x. To list all flow runs, you would typically use the Prefect 2.x SDK, which might involve querying the API through the SDK's interface. Here's an example you can run in Python to list all flow runs using Prefect 2.x SDK:

python
from prefect import get_client

async def list_flow_runs():
    async with get_client() as client:
        # Replace 'Running' with the appropriate state if you need to filter runs by their state.
        # Or remove the `state` filter to get all runs regardless of state.
        flow_runs = await client.read_flow_runs(
            # You can add filters here as necessary
        )
        # Iterate and print details about each flow run
        for flow_run in flow_runs:
            print(f"Flow Run ID: {flow_run.id} - State: {flow_run.state}")

# Remember to run this async function in an event loop
import asyncio
asyncio.run(list_flow_runs())

The

read_flow_runs

function might have parameters that allow you to filter by the state of the flow run (e.g., Running, Completed, Failed, etc.), and other options as well. You can customize your query by providing the appropriate arguments to the function. Please note that the SDK and API have likely evolved, so you should consult the latest Prefect 2.x SDK documentation to ensure that the functions and methods used are up-to-date. Adjust the code according to the documentation as necessary. Since I can't guarantee my advice is always current, consider this a provisional answer until you can verify it against more recent information.