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<@ULVA73B9P> I am deploying a flow using a kubern...
# ask-marvin
c
@Marvin I am deploying a flow using a kubernetes work pool. How do I avoid using '/opt/prefect/prefect/' as the working dir that it looks for the flow code in.
m
To assist you with setting a custom working directory for your Prefect flow deployed using a Kubernetes work pool, I first need to determine the version of Prefect you are using, as the solution might differ between versions 2.x and 3.x. Could you please specify your Prefect version?
c
@Marvin I'm using prefect 3.0.10
m
To change the default working directory when deploying a flow using a Kubernetes work pool in Prefect 3.0.10, you need to modify the job template. Prefect allows you to customize the base job template through advanced settings. Here's a general approach: 1. Access Advanced Settings: In your deployment configuration, navigate to the advanced settings where you can edit the JSON representation of the base job template. 2. Modify the Working Directory: Within the JSON template, identify the command or the entry point where the working directory is specified. Change the working directory path from '/opt/prefect/prefect/' to your desired path. 3. Save and Apply Changes: Ensure the changes are saved and re-deploy your flow so that the new configuration takes effect. For further details, you can refer to the Kubernetes deployment example in the Prefect 3.x documentation. If you need further assistance on how to specifically modify the job template, let me know!
c
@Marvin How do I visualize the following flow structure:
Copy code
from prefect import flow, task
from prefect_shell import ShellOperation

@task(name="bintrue")
def bintrue():
    return ShellOperation(commands=["/bin/true"])

@flow(name="flow_A")
def flow_A():
    bintrue()
        
@flow(name="flow_B")
def flow_B():
    flow_A()
    bintrue()

@flow(name="flow_C")
def flow_C():
    flow_B()
    bintrue()
m
To visualize the structure of your flow in Prefect 3.x, you can use the 
visualize()
method, which creates a schematic diagram of your flow and tasks. Follow these steps: 1. Install Graphviz: This is necessary since just installing the Python 
graphviz
package won't suffice. You need to have Graphviz installed on your system and accessible from your PATH. Download and install it from Graphviz's official site. 2. Use the 
visualize()
Method: Call this method on your flow without actually running it. Here's how you might call it:
Copy code
python
from prefect import flow, task
from prefect_shell import ShellOperation

@task(name="bintrue")
def bintrue():
    return ShellOperation(commands=["/bin/true"])

@flow(name="flow_A")
def flow_A():
    bintrue()
        
@flow(name="flow_B")
def flow_B():
    flow_A()
    bintrue()

@flow(name="flow_C")
def flow_C():
    flow_B()
    bintrue()

# Visualize the flow
flow_C.visualize()
3. Considerations: When using 
visualize()
, note that functions and code outside of flows or tasks will still be run, which might lead to unintended execution. Therefore, ensure your "setup" code is within tasks or flows to avoid this. If done correctly, this will open a window displaying a graphical diagram of your flow structure, allowing you to see how tasks and sub-flows relate to each other. For more details, you can check the Prefect 3.x documentation on visualizing flow structures. If you have any issues or questions while setting it up, feel free to ask!
c
@Marvin The above returns this error:
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prefect.utilities.visualization.FlowVisualizationError: Something went wrong building the flow's visualization. If you're interacting with the return value of a task directly inside of your flow, you must set a set a `viz_return_value`, for example `@task(viz_return_value=[1, 2, 3])`.
m
The error you're encountering, 
FlowVisualizationError
, is caused by attempting to directly interact with the return value of a task during flow visualization. In such cases, you must explicitly set a 
viz_return_value
for the task to aid in visualizing the flow's structure. Here’s how to modify your code to include the `viz_return_value`: 1. Set 
viz_return_value
for the Task: Modify your 
bintrue
task to include a 
viz_return_value
. This is helpful to Prefect for visualization purposes.
Copy code
python
from prefect import flow, task
from prefect_shell import ShellOperation

@task(name="bintrue", viz_return_value=None)  # You can set any dummy value or None
def bintrue():
    return ShellOperation(commands=["/bin/true"])

@flow(name="flow_A")
def flow_A():
    bintrue()
        
@flow(name="flow_B")
def flow_B():
    flow_A()
    bintrue()

@flow(name="flow_C")
def flow_C():
    flow_B()
    bintrue()

# Visualize the flow
flow_C.visualize()
2. Explanation: The 
viz_return_value
is used only for visualization purposes, allowing Prefect to bypass actually retrieving the task's output when generating the flow's graph. By implementing the above change, you should be able to successfully visualize your flow's structure. If you continue to experience issues, please let me know!
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