@Marvin when in Python I am scheduling a job using flow.from_source(source="...", entrypoint="generate_report_flow_test").deploy(...) The source must exist in the python repository right? And it must match the same path as the file contained in the docker image with the flow in it? Because what I am doing now is only copying the file for generating the flow into a docker image to be used when the flow is deployed, and so in a container if the workdir is /software then the source on the docker image will be /software/flow_module.py, instead from the python repo from where I schedule the flow is software/my_module/prefect/handler/flow_module.py

When using

flow.from_source

and deploying with

.deploy(...)

, the source specified must indeed be accessible in the environment where the flow will run. This typically means the source file should be present in the Docker image if you're deploying using a Docker image. Here's a summary of the relevant points: 1. Source Path: The path you specify in

flow.from_source(source="...")

should match the location of the file in the Docker image. For example, if your working directory in the Docker container is

/software

, and the flow file is located at

/software/flow_module.py

, then the source should reflect that path. 2. Deployment with Docker: If you're using a Docker image, ensure that the flow file is copied into the image at build time. Prefect can generate a Dockerfile that copies the current directory into the image. If you have a custom directory structure, you need to ensure that the Dockerfile reflects this structure. 3. Remote Sources: If using remote sources (e.g., a GitHub repository), the flow doesn't need to be available locally before running your script. However, if you're baking the flow into a Docker image, it needs to be present in the image. For more detailed guidance on using

flow.from_source

and deploying with Docker, you can refer to the Prefect documentation and the SDK reference. If you have further questions or need more specific assistance with your setup, feel free to ask.

@Marvin ok but then if my path is structured on my python service from which I run the flow as software/my_module/prefect/handler/flow_module.py, then on the docker image, on which I put the same flow_module with dependencies in order to not rely on a remote storage I need to copy all the file of the service so that ast runtime the job will find the same path on the docker image as the service. right?

Yes, that's correct. If your Python service has a structured path like

software/my_module/prefect/handler/flow_module.py

, and you want the flow to find the same path in the Docker image, you should ensure that the entire directory structure is copied into the Docker image. Here's what you need to do: 1. Dockerfile Configuration: In your Dockerfile, you should copy the entire directory structure from your local environment into the Docker image. For example:

dockerfile
    FROM python:3.9-slim

    WORKDIR /app

    # Copy the entire directory structure
    COPY ./software /app/software

    # Install any dependencies
    RUN pip install -r /app/software/my_module/prefect/handler/requirements.txt

2. Ensure Path Consistency: By copying the

software

directory into the Docker image at

/app/software

, you maintain the same path structure. This way, when your flow runs within the Docker container, it will find the

flow_module.py

at the expected path

/app/software/my_module/prefect/handler/flow_module.py

. 3. Flow Deployment: When deploying the flow, ensure that the entry point (

entrypoint="generate_report_flow_test"

) is correctly set to match the function or method within

flow_module.py

. By following these steps, your flow should be able to locate and execute the module as expected within the Docker environment. If you need more details on Dockerfile configurations or Prefect deployments, feel free to ask.