@Marvin I'm trying to implement UV in my flows. How do I add a custom entrypoint to a prefect.yaml file? It should be something like "uv run main.py"

To help you with adding a custom entrypoint to a

prefect.yaml

file for Prefect's Universal Virtualization (UV) feature, I need to first determine your Prefect version. Could you please specify whether you are using Prefect 2.x or 3.x? If you're unsure, I can look up relevant documentation for both versions.

@Marvin I'm using Prefect 3.x. Also, I'm referring to UV by Astral

hey @Nils! nice question

To add a custom entrypoint in a

prefect.yaml

file using Prefect 3.x and Astral for Universal Virtualization (UV), you should define the entrypoint within the

prefect.yaml

configuration. Though the search didn't yield precise results, here's a general approach based on common practices for such configurations: 1. Initialize your Project: First, ensure your project is initialized with Prefect. You can run:

sh
   prefect init

This will create a

prefect.yaml

file if it does not already exist. 2. Configure the

prefect.yaml

File: In the

prefect.yaml

file, you need to specify the deployment configuration. While the documentation doesn't provide an explicit example of a custom entrypoint like "uv run main.py," you generally include the script or command you'd like to run within your deployment instructions. Here is a possible snippet you might consider within your `prefect.yaml`:

yaml
   deployments:
     - name: my-deployment
       entrypoint: path/to/main:flow_function_name
       command: uv run main.py

Replace

path/to/main:flow_function_name

with the actual path and function name of your flow. 3. Use the Prefect CLI: Once this file is set up, use the Prefect CLI to deploy and manage your flows. It would translate your configurations into runtime operations. Unfortunately, detailed and specific examples of using "uv run" directly in

prefect.yaml

are not readily available, but the configurations typically allow you to run custom scripts and commands aligned with packaging, execution, and deployment processes. For more detailed guidance, refer to the Prefect Documentation on YAML Deployment. If Astral has particular nuances for implementing UV, the Astral or Prefect community forums may also offer insights.

though, when overriding command, you have to be careful that you dont forget to invoke the prefect engine like

python -m prefect.engine

Thanks 😄 You're rapid! I'm using a Docker work pool as my flows are baked into images so I don't think the custom UV worker will work?

hmm, what are you intending to get from

uv run

when submitting a docker container? i would think that it could help when building the image but docker is sort of already doing the "ephemeral environment" thing that

uv run

gives you right?

I've fixed it by putting the following in the Dockerfile. This ensures that the dependencies are installed in the images directly instead of a venv

ENV UV_PROJECT_ENVIRONMENT=/usr/local/
RUN uv sync --frozen --no-cache