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<@ULVA73B9P> how to get the return value of the fl...
# ask-marvin
j
@Marvin how to get the return value of the flow using flow id?
m
To get the return value of a flow using its ID, you can use the following general approach: 1. Trigger the flow and await its completion. 2. Retrieve the result using the 
.result()
method on the flow run object. 3. Decode or retrieve the data from the result as necessary. Here's an example of how you might do this within a test (snippet from the Prefect source code):
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python
@flow(retries=1)
def my_flow():
    # ...
    # Your flow logic here
    # ...

# Initiate the flow run
flow_run = my_flow()

# Awaiting the flow run's result
flow_state = await flow_run.result()

# Retrieve the result document
document = await flow_state.result()

# Retrieve the actual data (return value) from the Prefect API using the client
prefect_client = PrefectClient()  # Assuming you've created a PrefectClient instance
result = await prefect_client.retrieve_data(document)

# Perform some operations with the result
Remember, the above code is an example from a test case, and in your actual implementation, you will need access to a flow ID to retrieve the result. Also, the document from which this code is taken can be found on GitHub's repository for Prefect. However, I do not specifically see anything regarding the retrieval of the return value using just a flow ID. This may differ in your actual use case, particularly if you're using the Prefect API or UI to query for results. If you have a specific Prefect version you're working with, or if there's more context you can provide about how the flow is being run, feel free to let me know so I can give you more targeted advice.
j
@Marvin how to use API
m
To use the Prefect API and access flow results, there are a few steps you need to take regarding configuration and authentication. Below are general steps to configure and use the Prefect API: 1. Configure the Prefect API URL: To point your CLI to the Prefect server/Cloud instance, you can use the following command:
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shell
   prefect config set PREFECT_API_URL="<http://YOUR_PREFECT_SERVER_URL:4200/api>"
Replace 
<http://YOUR_PREFECT_SERVER_URL:4200/api>
with the actual API URL of your Prefect server instance. If you are using Prefect within a container (like a Docker container), you must set this API server address. 2. Authentication: Prefect Cloud requires authentication with API keys for both users and service accounts. Missing, incorrect, or expired API keys will result in 401 Unauthorized errors. To authenticate using an API key, configure your environment with the API key like so:
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shell
   export PREFECT__CLOUD__API_KEY="YOUR_API_KEY"
Replace 
YOUR_API_KEY
with the actual API key generated within Prefect Cloud. For more details on Prefect profiles and configuration, you can refer to Profiles &amp; Configuration. Unfortunately, the above excerpts don't contain detailed code examples on retrieving the flow return value through the API. In many cases, using a Prefect client library in the language of your choice, such as Python, would aid in interacting with the API. These actions would typically be implemented programmatically. If you want to perform the API call to get the flow return value, you'd need to refer to Prefect API documentation or client library documentation to find the specific endpoints and methods for retrieving flow results. If you need more detailed instructions or examples, please provide more context or specify your requirement.
j
@Marvin Python API
@Marvin use python API to get the result
n
hey @Joish marvin's kinda broken at the moment sorry
try back in a bit
j
@Nate Thanks
n
result = (await client.read_flow_run(...id...)).state.result()
^ which is predicated on you having set 
persist_result=True
on the flow in question
j
No this is my case i am starting a flow using run_deployment from a another flow(parent flow) i want the result in my parent flow
is this possible? @Nate
n
yeah so same thing, 
flow_run = run_deployment(...)
and 
result = flow_run.state.result()
where again you need to persist results on the child
🙌 1
j
let me try this thanks
đź‘Ť 1
@Nate i am returning this from the child flow
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return cache_dataset_features_response
but in the parent flow when i log results.state.result() i am getting this type='reference' artifact_type=None artifact_description=None serializer_type='pickle' storage_block_id=UUID('9ecabee7-9615-41db-977f-78911afe3308') storage_key='a11acc6bb3ef4732a4143345a0837414' can you plz help?
s
@Marvin, calling 
result()
seems to be hanging, even for a very simple function (the repo_info example from the docs). Should it be taking more than a minute or two? (EDIT: this was while running in debugging mode on VSCode)
m
If calling 
result()
on a very simple function like the 
repo_info
example from the Prefect documentation is hanging for more than a minute or two, it's not typical for it to take that long. There may be several reasons for this behavior: 1. Network Issues: If the network connection to the Prefect server or Cloud is slow or unreliable, it might delay the response. 2. Server Load: If the Prefect server is experiencing high load, it may take longer to respond to requests. 3. Code Issue: There might be an issue in the way the 
result()
function is being called or how the flow or task is set up. 4. Compatibility: Ensure that you're using compatible versions of the Prefect library and other dependencies. Since there are no related issues found in the GitHub repository for Prefect, it's possible that this behavior is due to a unique situation in your environment or a recent update that hasn't been reported yet. In this case, here are a few steps you can take to troubleshoot: - Check the network connectivity to the Prefect server or Cloud. - Look at the server logs (if accessible) to see if there are any errors or warnings being logged. - Try simplifying the flow or running a different example flow to see if the problem is with a particular flow or a more widespread issue. - Ensure you are using the latest version of Prefect libraries, or check the version compatibility. - Restart the Prefect server or your local development environment to ensure no hanging processes. If none of these steps resolve the issue, you may want to reach out to the Prefect community or support for further assistance. You can describe the hang in detail, including versions and configuration, and share it as a new issue on Prefect’s GitHub issue tracker if it seems to be a bug.
s
@Marvin, I think I see now. It's trying to pull from local storage when the result is persisted on the managed worker through Prefect Cloud.
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Exception has occurred: ValueError       (note: full exception trace is shown but execution is paused at: _run_module_as_main)
Path C:\root\.prefect\storage\69b055e353b745249d493350b79e81e8 does not exist.
m
You're encountering an issue because your flow's results are stored in a location managed by Prefect Cloud, but the attempt to access the result is looking for it on your local filesystem, which is causing the 
Path does not exist
error. Here's what you should consider to address this issue: - Storage Blocks: Prefect uses storage blocks to manage where and how your flow code and results are stored. When you are working with Prefect Cloud, you need to configure your flows to use a storage block that is compatible with Cloud-managed workers. You cannot use the default 
LocalFileSystem
block since it will only work on the local machine where the code is executed. To resolve the issue, you would typically configure a remote storage block that is accessible by both the Prefect Cloud-managed worker and any environment where you would want to retrieve the result. The supported options for deployment storage blocks include remote file systems supported by 
fsspec
, AWS S3 storage, and likely other cloud-based storage solutions. You can find more details about configuring different storage options in the Prefect documentation. If you are using cloud-based storage solutions like AWS S3, Google Cloud Storage, or Azure Blob Storage, make sure to have storage blocks properly configured in your Prefect Cloud dashboard and associated with your flows. You will also need to ensure that you have the necessary permissions and access keys to interact with these storage blocks. After configuring a compatible storage block for your deployment, you should update your flow definition to reference this block for storing results. If properly configured, the flow result should be accessible via the APIs provided by these storage services. If you've set up everything correctly and the problem persists, you may want to reach out to Prefect support or the Prefect community for more specialized assistance.
If calling 
result()
on a function from the Prefect documentation is hanging when you're running your code in debugging mode via VSCode, and you've determined that it's not related to storage configuration issues with Prefect Cloud, there might be other factors to consider which are specific to the debugging environment. Here are a couple of debugging-specific reasons which might cause this behavior: 1. Debugger Pausing Execution: The VSCode debugger may pause or slow down the execution of code, especially if there are breakpoints set. Ensure that you have not set any breakpoints that could be unintentionally pausing the execution. 2. Threading and Async I/O: Prefect relies heavily on Python's 
asyncio
for asynchronous operations. Debugging async code can be tricky because the debugger might interfere with the event loop. Ensure that you've configured VSCode's debugger to work with asynchronous code. 3. Debugger Configuration: Sometimes, the debugger's configuration in 
launch.json
can affect the execution. Make sure your debugger settings are correct and compatible with Prefect's execution model. 4. Resource Limitations: Running in debug mode generally consumes more resources, which might cause timeouts or delays if the system resources are insufficient. 5. Logging and Traceback: The debugger might be capturing a volume of logs or traceback information that can affect performance. Check the debug console output to see if this is causing the hold-up. Since there are no related issues in the Prefect GitHub repository, the problem may be specific to your setup or an edge case that hasn’t been reported yet. If, after checking all these factors, 
result()
still hangs, it could be beneficial to try running the flow outside of the debugging environment to see if it behaves differently. You might also want to report this behavior to the Prefect community or support channels if it appears to be a persistent issue. Additionally, running the flow with detailed logging enabled may provide more insights:
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python
import prefect
prefect.config.logging.level = "DEBUG"
Please adjust your debugging environment accordingly and see if that changes the behavior of the 
result()
call. If the issue still persists, consider reaching out to Prefect support or the community for more in-depth assistance.
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