Hi, getting this error suddenly. Anyone aware of what this is? ImportError: cannot import name 'start_blocking_portal' from 'anyio' (/usr/local/lib/python3.8/dist-packages/anyio/__init__.py)

Is there an easy way to disable caching when running tests? Something like the

disable_run_logger

Hi there. I recently started getting some errors on VS Code using pylance. For example, the following line

from prefect import Flow, Parameter, task, unmapped

produces

"Flow" is not exported from module "prefect"
Import from "prefect.core" instead Pylance(reportPrivateImportUsage)

"Parameter" is not exported from module "prefect"
Import from "prefect.core" instead Pylance(reportPrivateImportUsage)

"task" is not exported from module "prefect"
Import from "prefect.utilities.tasks" instead Pylance(reportPrivateImportUsage)

is not exported from module "prefect"
Import from "prefect.utilities.edges" instead Pylance(reportPrivateImportUsage)

Also, I am getting pylance errors when passing Parameters to tasks that expect

str

arguments. I don't believe this was happening before. Do you know if something changed recently in pylance or in how we are supposed to import modules? I am using prefect 0.15.4 Thanks!

@Marvin I'm using minio as storage for my flow code in prefect 2.20.3 I have a bucket named flows in which I have my prefect flow and I'm trying to run the flow as follows: minio_credentials = MinIOCredentials( minio_root_user = minio_key_id, minio_root_password = minio_access_key ) s3_bucket_block = S3Bucket( bucket_name="flows", folder=folder_id, credentials=minio_credentials, # Use MinIO credentials directly endpoint_url=minio_url ) # Deploy the flow with the uploaded files training_flow = await flow.from_source( source=s3_bucket_block, entrypoint="train.py:train") However, I get botocore.exceptions.ClientError: An error occurred (InvalidAccessKeyId) when calling the ListObjects operation: The AWS Access Key Id you provided does not exist in our records. I'm 100% that the credential I'm passing are right

Hi guys ! I’m trying to setup a

Prefect Agent

and a

prefect server

on my local computer, everything residing inside of

containers

. My

Prefect Server

`container(s)`is based on the

docker-compose

file retrieved from

prefect server config > server-docker-compose.yaml

. When spinning up a container for an Agent and running

prefect agent local start --api <http://host.docker.internal:4200>

, it says that I must be authenticated to communicate with the containerized server living in my local machine. My first question is: Is

authentication

mandatory in this kind of situation , for local run ? When I authenticate by creating a new tenant using

prefect server create-tenant -n default

outside the Agent container, I’m able to spin up the

Agent Container

and run everything. The problem is that I wanted to run the

create-tenant

inside the container too, but it’s not possible as I’m getting connection refused between containers.

tl;dr How scalable is Prefect Server for scheduling concurrent runs of 10s of thousands of flows? I'm evaluating Prefect Server as a solution for managing a data pipeline. How I envisioned this working was using the Prefect framework as a computationally minimal "glue." Prefect would be the central pipe through which the state of the data flows (but not the data itself). It would hand off all computation to microservices via (a)sync requests and its only concern would be controlling how the state is pushed from service to service. Prefect seems to be a great tool for this job; I really like the API and how quickly a developer can get up and running. However, there are a couple of things that I don't yet have total clarity on. This documentation describes Server as a "highly scalable scheduler" but also says that it may start degrading at "~10-20 tasks running concurrently against a typical Server." Does the above degradation occur because the

typical Server

is deployed to a single node via docker-compose with a single agent, instead of being deployed via something like Helm, which horizontally scales scheduled flows across a cluster of agents? How quickly does the size of the PostgreSQL database generally grow, relative to the number of flows run? Is there any reason that regularly deleting old runs would be any more complicated than as suggested here? Are there any case studies with Prefect Server being used to run 10s of thousands of concurrent flows? I see that there used to be a Nomad Agent, are there any helpful resources for running Prefect on a nomad cluster? Thanks for any advice you are able to share. I have been diving into Prefect for only the past couple of days so greatly appreciate any referential pointers here.

Prefect 2.0. Is there a way to upload a file in the Cloud UI as a task argument? We have been using URLs for this but as we start to expand Prefect's use in our organization it is getting challenging to make sure the prefect agent has permissions to all the S3 buckets folks might upload a file to.

Hey Guys, I’m just getting started with prefect and I have a flow that uses custom modules. These modules are in the same directory as my flow script, and I do several

from my_module import my_function

within the flow script. Now here’s the thing; I have registered the flow and started my local agent. When I try to trigger the job to run from the prefect UI, I get the message:

Failed to load and execute flow run: FlowStorageError('An error occurred while unpickling the flow:\n ModuleNotFoundError("No module named \'extract_strings\'")\nThis may be due to a missing Python module in your current environment. Please ensure you have all required flow dependencies installed.')

The `extract_strings`function is defined in another module in the same director. Can anyone help?

Hi, I am trying to run a prefect flow using a trigger from a Webhook. I am trying to figure out a way to send the data I received in the body of the webhook to the flow as a parameter, but I can’t figure out a way to do it. I followed the example given here but instead of passing

{{ event }}

(which is basically just the name of the event, I tried passing in

{{ resource.event_data }}

. Please note that

resource.event_data

is a property I defined this property in my webhook template, it gets populated from the body of the webhook I received originally. So, what’s happening is that the flow gets executed but instead of receiving the actual

resource.event_data

it just received the raw string “{{ resource.event_data }}“. Is it even possible to pass on dynamic data from the original event to the deployment as a parameter?

@Marvin why am I getting TypeError: ‘NoneType’ object is not iterable when using the command

prefect deployment run