Hi — when is the

today

template filled in a result

location

or task

target

string? I keep getting a `KeyError`:

from prefect.engine.results import LocalResult

# Create a new local result pointing to current working directory.
result = LocalResult(dir=".", location="{today}.txt")
assert result.location == "{today}.txt"

# This raises `KeyError: 'today'`.
result.write(value_="hello!")

I’m following this doc: https://docs.prefect.io/core/concepts/results.html#choose-a-serializer (under “Templating

Result

locations”)

Hi, I am experiencing some weird behavior using prefect server. I can run a flow on prefect core, it executes completely but when I spin up the UI and run the exact same flow on a local agent (same machine and environment), I get an ModuleNotFoundError. I have modules I import as part of my flow

Is there a way to reference a task output in a result

location

or task

target

? I know the Prefect context gives you a bunch of variables – notably including

parameters

, which looks promising! – but what if we have some data (the strings

"foo"

or

"bar"

) computed by some task

compute_foo_or_bar

and we’d like to reference that output in a subsequent task’s output target?

Hey all, my docker agent stopped being able to auth (error 500) to my Gitlab storage. I don't think I changed anything to the Prefect Agent/Gitlab settings so I don't know what caused it. Any ideas?

hi guys i am not sure I am using correctly prefect … anyone know where I can buy a course to learn more easy and deeply about prefect and best practices ?

Hi everyone, I am running prefect server on my linux and I want someone else in my team to be able view the UI on their own machine. Typically to do this, I simply share <IP>:<port_number> and this works like a charm (I do this with airflow and streamlit while testing). We are on the same network. I tried the same for prefect (<IP>:8080) but it can't be reached. I am still learning about prefect and not sure why this behavior is different. Would appreciate any help Update: I tried to start a local agent from a different machine and I get

ConnectionRefusedError: [WinError 10061] No connection could be made because the target machine actively refused it

. I can't tell if this is related. I created a config.toml file

# base configuration directory 
home_dir = "C:/Users/XXX/.prefect"

backend = "server"

[server]
host = "<http://XXXXXX>"
port = "4200"
host_port = "4200"
endpoint = "${server.host}:${server.port}"

I am certain the server is running on the host ip address

Hi all! how to kick-off flow defend on another flow is success? Thanks

Hi, is there any prefect graphql api video tutorial or blog posts.. Thanks!!!

Hey folks simple smile We are using ECS Agent to execute flows. Is there a way to apply custom tags to the ECS task that is executed?

Hi all! Is anyone aware of a way of timing out a flow itself and not just the tasks? Ie Task has

timeout

which we can pass in, but Im currently experience some odd issues where tasks seem to be lost in dask somewhere (they are submitted to dask but never come back, never time out), and this means my flows never end. Ideally Ill try to dig into our env and dask and prefect and figure out what is causing silent untracked failure, but as an interim solution, does anyone know of a way I can say “Cancel the flows and all tasks if its been an hour since you started?”

Is anyone else having trouble logging into the UI? Status page is all green, but no one on my team can login

Yes

@jars @Brian Phillips and everyone else: We are aware of the issue and investigating it. We’ll update in the announcements channel once we know more.

All services are available again - we’ve updated the status page.

Thank you!

Hey everyone, what is the best way of finding out what labels a flow run was run with while executing inside the flow?

Hey everyone, I have a couple of flows that are running just fine and now I get this new error when trying to register a new flow -

raise InterruptedError(line.get("error"))
      InterruptedError: name invalid: Request contains an invalid argument.

In order to register my flow I use the following command -

prefect register --project "Project_name" --path path_to_flow_file.py --name "brands-recognition"

Project_name is the project I have at Prefect cloud path_to_flow_file is the path to the file which contains my flow brands-recognition is the flow name. This is my flow snippet (for debug purposes - just 2 tasks)-

schedule = IntervalSchedule(interval=timedelta(days=7))

with Flow("brands-recognition",
          storage=Docker(registry_url="us-central1-docker.pkg.dev/xxx/",
                         dockerfile="./Dockerfile"), schedule=schedule) as flow:  # , schedule=schedule
    mode = Parameter('FULL_UPDATE', default=None)
    task_a(mode)

flow.run_config = VertexRun(machine_type='e2-standard-8', labels=["ml"],
                            service_account='prefect-integration@xx')

# flow.run()

Now when running locally - the flow runs smoothly and generates a result. It seems like the problem is only at the pushing phase (when I register the flow). What am I missing? Thanks.

hi, is this behavior normal in the UI? I find it pretty frustrating that the

Run History

keeps re-materializing as I scroll

Hi every body !!! Let me share with you all an issue I have: First that is my code

This is the python that run the flow after …

Good morning, I have a question about the Prefect Cloud incident earlier today...

Hello, Is it possible to get a run history for all the flows using the GraphQL query rather than looking at each flow?

I have a question about prefect cloud billing. If I run a single map task on a list of 10K items. Do I get charged for 1 task or for 10K tasks?

Hi, is there a way to iteratively run a flow for batch processing over a large dataset? Here’s the flow I’m trying to achieve: 1. Start flow with 3 parameters: start timestamp (ts_start), batch size (n), end timestamp (ts_end) 2. Task extracts batch of n documents starting from ts_start 3. Cache nth document’s timestamp (ts_last) 4. Go back to (1) passing in ts_last as ts_start if ts_last < ts_end In other words, I want to iteratively process batches until we get a document with timestamp ts_end

Is there currently an issue with the prefect dockerhub image? I am getting an issue pulling it

Head <https://registry-1.docker.io/v2/prefecthq/prefect/manifests/0.15.5-python3.8>: received unexpected HTTP status: 503 Service Unavailable

I have a use case where I have some equipment in a lab and connected to a desktop. I wanted to use Prefect to schedule a shell task to run on the machine that backs up its data to blob storage and then other downstream tasks are fired off. I walked through and did examples from a decent chunk of the documentation yesterday. I'm a little bit unclear on best practices for agents. Are they supposed to be on all the time? So in the given example the desktop will sometimes be on, sometimes be off. Do I just need to set the machine to start the agent on bootup or can that behavior be controlled from within prefect? Additionally, for best practice, if I have several of these machines like this would it be better to put an agent on each machine, or to setup one 'staging' cloud vm, and then run the agent there and execute tasks that live on the remote machines, but via ssh commands from the cloud vm?

Hi folks. As part of working on https://github.com/PrefectHQ/prefect/issues/5171 I created draft PR https://github.com/PrefectHQ/prefect/pull/5258 Please take a look at the concept and if you agree I will add tests and proper formatting

Hello there! 🙂 I'd appreciate any help, as I'm truly stuck. I've locally developed a flow on Jupyter Notebook (Python). Agent - Vertex Storage - GCP run_config - VertexRun Executer - LocalExecutor In VertexRun I've defined an image, which I've locally created on my CMD (Based on a simple Docker file, based on prefect:latest + run pip installs that are relevant for the specific flow). I've pushed this image to my repository in docker hub. Following what I've read here, I understood that on my script I should login to my docker account before activating the agent, and so I've done. One of the packages I've set to install on my image is "Pandas". Yet, when trying to run the flow through the UI I get this error: "Failed to load and execute Flow's environment: FlowStorageError('An error occurred while unpickling the flow:\n ModuleNotFoundError("No module named \'pandas\'")\nThis may be due to one of the following version mismatches between the flow build and execution environments:\n - cloudpickle: (flow built with \'1.3.0\', currently running with \'2.0.0\')\n - prefect: (flow built with \'0.15.9\', currently running with \'0.15.10\')\n - python: (flow built with \'3.7.6\', currently running with \'3.7.12\')\nThis also may be due to a missing Python module in your current environment. Please ensure you have all required flow dependencies installed.')" What do I miss? Thanks in advance! 🍪

Hi all, for testing purposes is there any way to configure `.map`ped tasks to run sequentially instead of in parallel?

If a scheduled flow did not run and the errors I see say a lazarus process was attempted, what does that mean?