@Marvin if I'm using Prefect with Docker images, and import a helper file, is there anything special I would need to do in order to make this import work across mapped tasks?

When using Prefect with Docker images and dealing with imports across mapped tasks, you must ensure that the Docker environment can access the required helper files. Here's a breakdown of the steps you should consider: 1. Docker Image Preparation: Create a Dockerfile for your Prefect workflows that includes the necessary libraries and your helper files. When defining the Docker image, you should copy the relevant Python scripts and any helper modules into the image. For example:

Dockerfile
    FROM python:3.8
    COPY ./my_helper_module.py /app/my_helper_module.py
    # Install any necessary dependencies
    RUN pip install prefect
    WORKDIR /app

2. File Organization: Organize your project files so that your flow script and any helper modules are accessible within the Docker build context. For instance, create a

flows

directory where you store your Prefect flow script and the helper module:

mkdir -p prefect-docker-guide/flows
    cp my_flow.py prefect-docker-guide/flows/
    cp my_helper_module.py prefect-docker-guide/flows/

3. Build Image: Build the Docker image with the Dockerfile located in the directory containing your flow and helper files to ensure they are included in the image:

sh
    docker build -t my_prefect_image:latest .

4. Prefect Task Definition: Ensure your Prefect task definitions import the helper module correctly. If the helper module is copied into the Docker image as shown above, you can import it in your Prefect task script like any other Python module:

python
    from my_helper_module import some_utility_function

5. Mapping: When mapping a task in Prefect, each mapped instance runs independently. So as long as your Docker image contains the necessary files and the imports are defined correctly, mapped tasks should have access to the helper files. Here's an example of creating a mapped task:

python
    from prefect import task, Flow

    @task
    def my_task(x):
        from my_helper_module import some_utility_function
        return some_utility_function(x)

    with Flow('my_flow') as flow:
        my_task.map([1, 2, 3])

By following these guidelines, your imports should work correctly across all mapped tasks within the Docker environment used by Prefect. Remember to test your Docker image locally to validate that your helper files are being correctly imported before deploying to production.

@Marvin what if I can successfully import a function when I am not mapping a task, but I receive the below error when I try to map the task?

Crash detected! Execution was interrupted by an unexpected exception: ModuleNotFoundError: No module named 'helpers'

It appears that when tasks are not mapped, the import of your helper function works fine, but when you map the task, you encounter a

ModuleNotFoundError

. This can happen for several reasons, often related to how your execution environment is set up for running mapped tasks. Here are some steps to troubleshoot this issue: 1. Consistent Environment: Ensure the execution environment for mapped tasks is consistent with the environment for non-mapped tasks. This means that if you're using Docker, every mapped task should run in a container that has the required modules installed. 2. Docker Context: Verify that your helper module is included in the Docker build context and that it is installed in the correct location within the Docker image. 3. Pythonpath: If your helper module is in a subdirectory, you may need to add the directory to the

PYTHONPATH

environment variable. For Docker, you can set it in your Dockerfile like so:

Dockerfile
    ENV PYTHONPATH "${PYTHONPATH}:/app/path/to/helpers"

Replace

/app/path/to/helpers

with the actual path to your helper module inside the Docker image. 4. Check Imports in Task: Since tasks may execute in a different context when mapped, make sure that the import of your helper module is relative to the current file’s location, or appropriate for the execution context. 5. Prefect Configuration: Look into your Prefect configuration and verify if there are any settings that could be affecting the execution environment of your mapped tasks, potentially causing them not to have access to the correct Python environment or dependencies. 6. Caching Issues: There might be caching issues where an old version of the Docker image is being used for the execution of mapped tasks. Ensure you are using the latest version of your Docker image where the helper module is present. Since a

ModuleNotFoundError

would typically suggest a Python environment mismatch or similar issue, you should double-check your deployment and execution setup. Make sure to build your Docker image with all the necessary dependencies and that the image is being correctly used for the mapped task execution. If the issue persists and you're confident your setup is correct, you might want to reach out to the Prefect community or support for more specific guidance on the matter. Since searching GitHub issues didn't yield any related Prefect issues, it could be an indication that this is an environment-specific problem rather than a common bug in the Prefect software itself.