@Marvin How do I add modules to prefect deployment, using Helm.

Adding extra Python modules to a Prefect deployment using Helm involves customizing the Helm chart values. Here are the general steps you would follow: 1. Add the Prefect Helm repository to your Helm client:

shell
   helm repo add prefect <https://prefecthq.github.io/prefect-helm>
   helm repo update

2. Create a new namespace in your Kubernetes cluster for the Prefect deployment:

shell
   kubectl create namespace prefect

3. Make a Kubernetes secret for Prefect API key (replace

your-prefect-cloud-api-key

with your actual API key):

shell
   kubectl create secret generic prefect-api-key \
   --namespace=prefect --from-literal=key=your-prefect-cloud-api-key

4. Customize the Helm chart values — create a

values.yaml

file where you can specify the configuration for your worker deployments, including the additional Python packages you want to install. Within the

values.yaml

file, you would include the extra modules under the appropriate key. For detailed guidance and the exact steps to configure the Helm chart to include extra Python modules, you'll need to reference the Prefect documentation on Kubernetes deployment: - Deploy a worker using Helm Make sure to review the official Prefect Helm chart for options that allow you to specify additional Python packages. If needed, you can also build your own Docker image that includes the desired modules and point the Helm chart to your custom image. Please note: Due to my inability to access the latest configuration details for the Prefect Helm chart, it's necessary to consult the official documentation or the chart's values file for the precise configurations to add modules.

@Marvin error when using deploy when "psycopg2" is in requirements.txt prefect.utilities.dockerutils.BuildError: The command '/bin/sh -c python -m pip install -r /opt/prefect/prefect/requirements.txt' returned a non-zero code: 1

It seems there's an issue when trying to install

psycopg2

from your

requirements.txt

within a Docker container as part of a Prefect deployment process. This "BuildError" usually occurs when the build process encounters an error installing the listed requirements. The issue with

psycopg2

often happens because it requires certain build dependencies that are not present in the base Docker image you're using. There's no directly relevant GitHub issue found, but here's what you generally need to know to resolve this problem: 1. Use the Binary Package: Instead of

psycopg2

, you could use

psycopg2-binary

in your

requirements.txt

. It is a stand-alone package that includes the binary and skips the need for compiling. 2. Install Build Dependencies: If you must use

psycopg2

and not the binary, you'll need to ensure build dependencies are installed in your Docker container before attempting to install

psycopg2

. This typically includes packages like

libpq-dev

and

gcc

. To install dependencies, you can add these commands to your Dockerfile before the pip install command:

Dockerfile
RUN apt-get update \
    && apt-get install -y libpq-dev gcc \
    && pip install psycopg2

If you're looking for a complete example of how to set up a Docker environment for Prefect, the GitHub example is not directly related to Docker or psycopg2 installation. However, if you need general guidance on how to write a Dockerfile for your workflows, the Docker documentation will be the best reference. Consider checking your current Dockerfile and try adding the above dependencies, or switch to

psycopg2-binary

in your

requirements.txt

if you haven't specifically implemented a Dockerfile. If these suggestions don't resolve the issue or you need a more specific example, you might need to search the Prefect community or open a new issue for assistance.

@Marvin The binary worked a charm

Oh, splendid! I'm glad to hear that using

psycopg2-binary

worked out. It's probably the least mentally taxing option for these sorts of Docker-related predicaments, not that I'm an expert on happiness or anything. Do remember that while

psycopg2-binary

is suitable for development and testing environments, for production uses, you might want to ensure you have the proper build dependencies set up for

psycopg2

to avoid potential issues. If you have any other questions or face new problems that fill your day with despair, feel free to reach out. I'm here, brimming with an endless supply of enthusiasm, to help.