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<@ULVA73B9P> write me a python script that checks ...
# ask-marvin
a
@Marvin write me a python script that checks the last deployment, fetches that deployment and runs the last deployment, then takes the logs from the flow run
m
To help you create a Python script that checks the last deployment, fetches it, runs it, and retrieves the logs from the flow run, here are the key steps and relevant Prefect 3.x concepts: 1. Fetch the Last Deployment: - Utilize the Prefect API to list and fetch the last deployment. You may use the 
prefect.deploy
module to interact with deployments. 2. Run the Deployment: - Deployments can be triggered manually. Use the 
prefect.flow
module to trigger a flow run from a deployment. 3. Retrieve Logs from the Flow Run: - Prefect provides logging capabilities that can be accessed via the API or UI. Use 
get_run_logger
from 
prefect.logging
for custom logs and inspect logs through the Prefect API. Here's a basic script outline using these concepts:
Copy code
python
from prefect import get_client, flow
from prefect.logging import get_run_logger

async def run_last_deployment():
    async with get_client() as client:
        # Fetch the last deployment
        deployments = await client.read_deployments()
        last_deployment = deployments[-1]  # Assuming the last one is the most recent

        # Trigger a flow run from the last deployment
        flow_run = await client.create_flow_run_from_deployment(last_deployment.id)

        # Wait for the flow run to complete
        state = await flow_run.wait()

        # Get logs from the flow run
        logs = await client.read_logs(flow_run.id)
        for log in logs:
            print(log)

if __name__ == "__main__":
    import asyncio
    asyncio.run(run_last_deployment())
### Key Notes: - Logging: Prefect automatically logs flow and task activities. Use 
get_run_logger
for custom logging. - API Usage: This script uses asynchronous calls to interact with Prefect's API. ### References: - Deployments in Prefect - Logging in Prefect Ensure your Prefect environment is correctly set up and you're authenticated to access the Prefect API. Adjust the script as necessary for your specific use case.
a
@Marvin give me the python code
m
Here's a Python script tailored to check the last deployment, fetch it, run it, and retrieve the logs from the flow run using Prefect 3.x:
Copy code
python
import asyncio
from prefect import get_client

async def run_last_deployment():
    async with get_client() as client:
        # Fetch all deployments
        deployments = await client.read_deployments()
        if not deployments:
            print("No deployments found.")
            return

        # Get the last deployment
        last_deployment = deployments[-1]  # Assuming the last one is the most recent

        # Trigger a flow run from the last deployment
        flow_run = await client.create_flow_run_from_deployment(last_deployment.id)
        print(f"Triggered flow run: {flow_run.id}")

        # Wait for the flow run to complete
        state = await client.wait_for_flow_run(flow_run.id)
        print(f"Flow run completed with state: {state}")

        # Get logs from the flow run
        logs = await client.read_logs(flow_run.id)
        for log in logs:
            print(log.message)

if __name__ == "__main__":
    asyncio.run(run_last_deployment())
### Key Points: - Async Operations: The script uses asynchronous operations to interact with the Prefect API. - Deployment Handling: It fetches all deployments and assumes the last one is the most recent. - Logging: Retrieves and prints logs from the flow run. Make sure your environment is set up with Prefect 3.x and you have the necessary permissions to access the deployments and flow runs. Adjust the script as needed for your specific use case.
a
@Marvin i don't want to trigger a new flow run, i want the logs of the flow run whose ID I will give you
m
To retrieve logs for a specific flow run using its ID in Prefect 3.x, you can use the following script:
Copy code
python
import asyncio
from prefect import get_client

async def get_logs_for_flow_run(flow_run_id):
    async with get_client() as client:
        # Retrieve logs for the specified flow run ID
        logs = await client.read_logs(flow_run_id)
        for log in logs:
            print(log.message)

if __name__ == "__main__":
    flow_run_id = "your-flow-run-id-here"  # Replace with your actual flow run ID
    asyncio.run(get_logs_for_flow_run(flow_run_id))
### Key Points: - Flow Run ID: Replace 
"your-flow-run-id-here"
with the actual ID of the flow run whose logs you want to fetch. - Async Operations: The script uses asynchronous operations to interact with the Prefect API to retrieve logs. This script will print out the logs for the specified flow run ID. Ensure you have the correct permissions and environment setup to access the Prefect API.
a
@Marvin i get this error: File "C:\Software\MiniConda\envs\workflow\Lib\site-packages\prefect\client\orchestration.py", line 2637, in read_logs "logs": log_filter.model_dump(mode="json") if log_filter else None, ^^^^^^^^^^^^^^^^^^^^^ AttributeError: 'str' object has no attribute 'model_dump'
m
The error you're encountering suggests that the 
read_logs
function is expecting a 
log_filter
object with a 
model_dump
method, rather than a simple string. It seems there might be a misunderstanding in how the 
read_logs
function is being used or a potential issue in Prefect's implementation. Here's a revised script to help you retrieve logs without triggering the error. It assumes no 
log_filter
is needed unless specified:
Copy code
python
import asyncio
from prefect import get_client

async def get_logs_for_flow_run(flow_run_id):
    async with get_client() as client:
        # Retrieve logs for the specified flow run ID
        logs = await client.read_logs(flow_run_id, log_filter=None)
        for log in logs:
            print(log.message)

if __name__ == "__main__":
    flow_run_id = "your-flow-run-id-here"  # Replace with your actual flow run ID
    asyncio.run(get_logs_for_flow_run(flow_run_id))
### Key Points: - 
log_filter=None
: This explicitly sets the 
log_filter
to 
None
, which should bypass any filtering logic that might expect a specific object structure. - Flow Run ID: Replace 
"your-flow-run-id-here"
with the actual ID of the flow run whose logs you want to fetch. If the issue persists, it might be worth checking Prefect's documentation or support channels for any updates or patches related to the 
read_logs
function.
a
@Marvin error: logs = await client.read_logs(flow_run_id, log_filter=None) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: PrefectClient.read_logs() got multiple values for argument 'log_filter'
m
It seems there was an error in retrieving the exact signature for the 
read_logs
method. However, based on the module exploration, here's a revised approach for retrieving logs using Prefect 3.x:
Copy code
python
import asyncio
from prefect.client.orchestration import PrefectClient
from prefect.schemas.filters import LogFilter, LogFilterFlowRunId

async def get_logs_for_flow_run(flow_run_id):
    async with PrefectClient() as client:
        # Create a log filter for the specific flow run ID
        log_filter = LogFilter(flow_run_id=LogFilterFlowRunId(any_=[flow_run_id]))

        # Retrieve logs for the specified flow run ID
        logs = await client.read_logs(log_filter=log_filter)
        for log in logs:
            print(log.message)

if __name__ == "__main__":
    flow_run_id = "your-flow-run-id-here"  # Replace with your actual flow run ID
    asyncio.run(get_logs_for_flow_run(flow_run_id))
### Key Points: - Log Filter: The 
LogFilter
object is used to specify which logs to retrieve, filtering by the flow run ID. - Flow Run ID: Replace 
"your-flow-run-id-here"
with the actual ID of the flow run whose logs you want to fetch. This script should help you fetch logs for a specific flow run. Ensure you have the correct Prefect version and environment setup. If you encounter any further issues, checking the Prefect documentation or community forums may provide additional insights.
a
@Marvin what to give as api in PrefectClient()
m
To initialize a 
PrefectClient
and connect to the Prefect API, you need to specify the API URL. This can be done using the 
PREFECT_API_URL
environment variable or by directly passing the URL to the 
PrefectClient
constructor. Here's how you can set it up: 1. Environment Variable: Set the 
PREFECT_API_URL
environment variable to point to your Prefect API endpoint. This is typically used for Prefect Cloud or a self-hosted Prefect server.
Copy code
bash
   export PREFECT_API_URL="<https://your-prefect-api-url>"
2. Direct Parameter: Pass the 
api
parameter directly when initializing the 
PrefectClient
. Here's an example of how to use the 
PrefectClient
with a direct API URL:
Copy code
python
import asyncio
from prefect.client.orchestration import PrefectClient
from prefect.schemas.filters import LogFilter, LogFilterFlowRunId

async def get_logs_for_flow_run(flow_run_id):
    async with PrefectClient(api="<https://your-prefect-api-url>") as client:
        # Create a log filter for the specific flow run ID
        log_filter = LogFilter(flow_run_id=LogFilterFlowRunId(any_=[flow_run_id]))

        # Retrieve logs for the specified flow run ID
        logs = await client.read_logs(log_filter=log_filter)
        for log in logs:
            print(log.message)

if __name__ == "__main__":
    flow_run_id = "your-flow-run-id-here"  # Replace with your actual flow run ID
    asyncio.run(get_logs_for_flow_run(flow_run_id))
### Key Points: - API URL: Replace 
"<https://your-prefect-api-url>"
with the actual URL of your Prefect Cloud or self-hosted Prefect server. - Environment Configuration: Ensure that your environment is configured to connect to the correct Prefect API endpoint.
a
@Marvin raise JSONDecodeError("Expecting value", s, err.value) from None json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0
m
The 
JSONDecodeError
you're encountering suggests that the response from the API is not valid JSON, possibly due to an incorrect API URL, network issue, or server-side problem. Here are a few steps to troubleshoot and resolve this issue: 1. Verify the API URL: - Double-check the API URL you're using in the 
PrefectClient
. Ensure it's the correct endpoint for your Prefect Cloud or self-hosted server. 2. Check Network Connectivity: - Ensure that your machine has network access to the Prefect API server. You can try accessing the API URL in a web browser or using a tool like 
curl
to see if it responds. 3. Inspect Response Content: - You might want to add some debugging to inspect what the response content is. Modify the script to print out the response content before attempting to parse it as JSON. 4. API Key and Authentication: - Ensure that any required authentication (e.g., API key) is correctly set up. For Prefect Cloud, you might need to set the 
PREFECT_API_KEY
environment variable. Here's a small modification to help debug the response:
Copy code
python
import asyncio
from prefect.client.orchestration import PrefectClient
from prefect.schemas.filters import LogFilter, LogFilterFlowRunId

async def get_logs_for_flow_run(flow_run_id):
    async with PrefectClient(api="<https://your-prefect-api-url>") as client:
        try:
            # Create a log filter for the specific flow run ID
            log_filter = LogFilter(flow_run_id=LogFilterFlowRunId(any_=[flow_run_id]))

            # Retrieve logs for the specified flow run ID
            logs = await client.read_logs(log_filter=log_filter)
            for log in logs:
                print(log.message)
        except Exception as e:
            print(f"Error occurred: {e}")

if __name__ == "__main__":
    flow_run_id = "your-flow-run-id-here"  # Replace with your actual flow run ID
    asyncio.run(get_logs_for_flow_run(flow_run_id))
### Additional Steps: - Debugging: Add additional print statements or logging to capture the exact response from the server. - Prefect Support: If the issue persists, consider reaching out to Prefect support or community forums for more specific guidance related to your setup.
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