I have a task with retries parameter set to 2 that I am intentionally failing so that I can put the flow in a 'AwaitingRetry' state. I set up the email automation hook so that it triggers on Retrying state, but it looks like these events are not being triggered

Great work everyone! 🎉 See you tomorrow at 9am ET for more Prefect goodness! 🚀

@Jeff Hale I guess you will posting the video here, when it's done processing? Is that right? You mentioned something in our short zoom chat but I already forgot!

Recording from Day 1 here: https://us06web.zoom.us/rec/share/u4FmcbK9QpduJPfRlgMV6XIC27P1KPpNP6TWT9YnLzkgsdWexwvdsciFipo1vSU.-DIH4WYOWHw0_tc8 Passcode: gZ!Rh8=H

Just as a reminder, here are the slides and here is the example code.

Are agents going away - to be replaced by workers/work pools?

prefect project init

creates some files and directories, one of those is the directory

.prefect

- should we keep that one in VCS or not? I assume the other 3 should be version-controlled

in the deployment.yaml files there is an working_dir parameter, for what is it used?

Can you post the lab goals for 104? (similarly to https://prefect-community.slack.com/archives/C059R6NNYUR/p1685545915837549)

104 Lab Instructions: Use your flow from 103 Lab • If you have flow function parameters, create default arguments in your flow function • Make a project • Start a worker • Run a deployment from the UI • Check it out in the UI

my prefect local ui is trying to access api.prefect.could. how do i tell it to just do local?

1. I removed the default values for my entrypoint function:

@flow
def get_weather_data(lat, lon):
    weather_data = fetch_weather(lat, lon)
    soil_data = fetch_soil_data(lat, lon)
    to_write = transform_weather_data(weather_data, soil_data)
    save_weather(to_write)


if __name__ == '__main__':
    get_weather_data()

2. I created a deployment and left

parameters

as an empty dict:

deployments:
  - name: My weather deployment
    version: 0.1
    tags: [ ]
    description: null
    schedule: { }
    flow_name: null
    entrypoint: "weather.py:get_weather_data"
    parameters: {}
    work_pool:
      name: null
      work_queue_name: null
      job_variables: { }

3. I deployed it:

prefect deploy "./weather.py:get_weather_data" -p my_pool

4. Now if I open the deployment in the UI and choose "Quick Run", I am shown a form with

lat

and

lon

fields, which are empty, but they're also marked as (Optional) when they clearly aren't. The Run button is also enabled, it allows me to click it even if I leave the form fields empty, and if I do that, the flow fails. Did I do something wrong?

Thank you @Songlu Li @Luke here are the files for 104

Suggestion for future pacc's: Maybe show people who already use Prefect 2 how to create and switch Profiles before 101 Lab. Even though I used a new project and a new venv with the newly installed prefect, it still used my default Profile and sent all flow runs to my cloud UI. I don't know if this would be too confusing for new people. And then maybe on 102 Lab show how to configure the new local server UI to that profile.

@Stratos happy to dive into the issue you were seeing in the next lab, or after the course.

@Tim Lin Mind posting the errors you’re getting?

A couple times when trying to deploy I got an error

'NoneType' object has no attribute 'split'

without any other useful info. does anyone have advice?

Lab 105 Instructions • Create a deployment with an entrypoint flow with several parameters • Edit the deployment from the UI to override the parameters • Add two types of schedules - add each a different way (CLI, UI) • Pause the schedules • Create two kinds of artifacts in your flow code code • See your artifacts in the UI

@Tim Lin https://docs.prefect.io/2.10.11/concepts/projects/#reusing-configuration-across-deployments

I keep getting a FileNotFoundError for the script with my flow in it. Any thoughts on cause?

Error is Flow could not be retrieved from deployment

@Will Raphaelson <- Will

Here's the abstract base class for the `EventsClient`: https://github.com/PrefectHQ/prefect/blob/main/src/prefect/events/clients.py#L12 and the Cloud-specific implementation: https://github.com/PrefectHQ/prefect/blob/main/src/prefect/events/clients.py#L82 a test double: https://github.com/PrefectHQ/prefect/blob/main/src/prefect/events/clients.py#L49 The key method to implement is

emit

One question that’s not related to automations. Is is possible to use prefect to orquestrate flows that gets data in real time (streaming)?

@Chris Guidry <- Chris

Survey: https://forms.gle/AG6Pg6tmhNWzGP94A

My microphone died at the end. I was going to ask you why did prefect cloud UI changed back to having deployments in the menu, few weeks ago you had them shown in the flow page connected to flow, now they are separate again