• a

    Alexander van Eck

    2 months ago
    Question on dynamically creating flows; Say I have 3 tasks
    @task
    def task_1():
      print('1')
    
    @task
    def task_2():
      print('2')
    
    @task
    def task_3():
      print('3')
    And I wanted to give the user the ability to say in which order these should be executed, or who should consume which one. i.e. I want to user to describe a graph of these callables and then for the flow to execute them. How would I do this?
    a
    Kevin Kho
    3 replies
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  • Sandeep Dass

    Sandeep Dass

    2 months ago
    Question about prefect server graphql endpoint. Getting the below error. Any ideas as to why
    Sandeep Dass
    Kevin Kho
    +2
    13 replies
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  • s

    Sam Pibworth

    2 months ago
    Hello, got a problem with Prefect server UI not being able to connect to core. The toml file has the line
    apollo_url = "http:/<ip of azure vm>:4200/graphql"
    . Any help would be much apperciated!
    s
    Kevin Kho
    6 replies
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  • Abin Antony

    Abin Antony

    2 months ago
    Hello, I am setting up PREFECT on my Openshift environment refering PREFECT Helm (https://github.com/PrefectHQ/server/tree/master/helm/prefect-server#installing-released-versions). BY default, I can see prefect backend is set as CLOUD. My question is , Any options available to set up it with defaulted as "SERVER"
    Abin Antony
    1 replies
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  • j

    Jacob Longhurst

    2 months ago
    Can anyone help me work out a bug? I’m building the docker image with prefecthq/prefect:1.1.0-python3.8. I’m also registering the flow with prefect 1.1.0 and doing so using the cli. The error is
    Failed to load and execute flow run: FlowStorageError('An error occurred while unpickling the flow:\n  AttributeError("Can\'t get attribute \'_make_function\' on <module \'cloudpickle.cloudpickle\' from \'/usr/local/lib/python3.8/site-packages/cloudpickle/cloudpickle.py\'>")\nThis may be due to one of the following version mismatches between the flow build and execution environments:\n  - cloudpickle: (flow built with \'2.1.0\', currently running with \'2.0.0\')')
    j
    Kevin Kho
    6 replies
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  • k

    Kelvin

    2 months ago
    Hi! Just a question about DeploymentSpec, been searching through the docs and slack and still a bit confused. I'm on orion beta 2.0b6 about to move up to latest: • What will happen to my existing old deployments, will I need to redeploy them? Thanks!
    k
    1 replies
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  • Lana Dann

    Lana Dann

    2 months ago
    does anyone know the best way to look up how a flow was kicked off? (manually, via schedule, via run flow task) i assume we’d be able to find this info using the graphql api
    Lana Dann
    Mason Menges
    2 replies
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  • Karanveer Mohan

    Karanveer Mohan

    1 month ago
    Hi all, Just updated to 2.0b14 and ran into a couple of issues: 1/ Running
    prefect cloud login -k KEY -w WORKSPACE
    now asks for
    "Creating a profile for this Prefect Cloud login. Please specify a profile name:"
    This breaks my deployment flow since I need it to be programmatic. I also tried running
    prefect profile create
    before but that doesn't seem to help. I also can't give the name of an existing profile. Could someone help explain what I'm doing wrong? I tried searching in the docs but maybe I'm missing something 2/ I was able to just hit enter locally and got the following message "Logged in to Prefect Cloud using profile ''." However, if I try to do
    prefect cloud login
    or
    prefect profile inspect
    after this, it throws the following error. I had to fix this by manually deleting
    profiles.toml
    . Code in thread
    Karanveer Mohan
    Anna Geller
    +2
    8 replies
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  • j

    Jacob Longhurst

    1 month ago
    I’m hoping someone can help me with getting Dask Distributed working inside a k8s cluster. We have our flows configured to use a KubernetesRun. The run config and the executor are using the same image with a base image of
    prefecthq/prefect:1.1.0-python3.8
    . If we use the
    DaskExecutor
    with a custom class and kwargs, we get an error message saying we need to install kubectl. If we choose to use a
    LocalDaskExecutor
    it works just fine. It seems it’s failing some where around attempting to talk between the dask scheduler and workers. We’ve created the roles and role bindings dask requires in order to function properly and we’re not sure if we need to pass in a dask scheduler spec and / or service spec to the dask KubeCluster object? Hoping someone has been able to solve running a temporary, on demand distributed dask cluster in K8S with the KubernetesRun prefect run config
    j
    1 replies
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  • Anna Geller

    Anna Geller

    1 month ago
    archived the channel