@Marvin I have a deployment that is dynamically generating more deployments. I use prefect_snowflake module and I have added it to the yaml -pull to load requirments.txt wich works fine. In the generated deployments I use prefect_snowflake again but it fails with error "ModuleNotFoundError: No module named 'prefect_snowflake'". Using prefect cloud with managed worker how can I install this dependencies for the dynamically generated deployments and flows?

The search results are not specifically addressing the question of installing dependencies for dynamically generated deployments within Prefect Cloud. However, there are typical strategies for ensuring your Prefect flows have the required dependencies when using managed workers: 1. Using a Custom Docker Image: Create a Docker image that contains all the necessary dependencies for your flows, including the

prefect-snowflake

module. You can specify this custom Docker image in your deployments so that all flows, including dynamically generated ones, use this image. This is often done by setting the

image

parameter in your deployment YAML file. 2. Injecting Dependencies at Runtime: Some users add a step in their flows to install dependencies at the beginning of the run. This would use something like the

ShellTask

to run

pip install prefect-snowflake

before proceeding with the flow's tasks. This approach can have an impact on the startup time of your flows. Unfortunately, since this didn't yield a direct result from documentation or open issues on GitHub, I would recommend exploring Prefect's Slack community or raising an issue directly on their GitHub repository for guidance tailored to your situation. Meanwhile, if you wish to attempt either of the aforementioned strategies, ensure that you have the correct permissions and that it complies with the best practices in your organization or in managed worker environments in Prefect Cloud. For setting up a custom Docker image here is a general guide from Prefect's documentation: Prefect Docker Please note that creating a custom Docker image or injecting dependencies at runtime may not be officially documented as solutions for this specific scenario with managed workers. If Prefect Cloud's managed worker setup has a different recommended approach, Prefect support would be the best source of up-to-date and accurate information.

@Marvin can i pass job variables to install pip packages to Deployment.build_from_flow

According to the Prefect upgrade guide, when translating from

Deployment.build_from_flow

to

flow.deploy

, you should replace

infra_overrides

with

job_variables

. This suggests that job variables can be used to customize the build environment for your deployment when using

flow.deploy

. You can pass job variables which could include arguments for installing pip packages as part of the deployment process. These job variables can be used to specify environment variables or other configuration settings required by your flow when executed. Please refer to the upgrade guide for more specific information on migrating from

Deployment.build_from_flow

to

flow.deploy

, including how to use

job_variables

with the new deployment method.

@Marvin can you give me an example how to use infra_overrides to install pip package prior to flow run

It appears there has been a misunderstanding retrieving the code example you're looking for. The example provided doesn't relate to using

infra_overrides

to install pip packages prior to a flow run. I don't have a direct example at hand where

infra_overrides

is used to install pip packages, as this might require a specific setup, which is configured on the infrastructure that is used to run your flows, and can vary based on the deployment method (Docker, Kubernetes, etc.). Typically, to install a pip package you would need to ensure that the required packages are included in your environment when the infrastructure is being set up, potentially by customizing the Dockerfile used to build your execution environment. You would provide the list of pip package requirements either directly in your Dockerfile using

RUN pip install some-package

or by copying a requirements.txt file into the image and running

pip install -r requirements.txt

. If you are using a custom Docker image with Prefect, the Dockerfile could look something like this:

dockerfile
FROM prefecthq/prefect:latest
COPY requirements.txt /requirements.txt
RUN pip install -r /requirements.txt

In the context of Prefect 2.0 (

orion

), the syntax and methodology have changed. You might want to create a custom Docker image based on your flow's needs and use it as the container for your work. The Prefect documentation or forums can provide more details on how to pass

job_variables

or customize the deployment environment in Prefect 2.0. Please consult the Prefect documentation or community forums for more specific examples based on your exact requirements.

@Marvin how can i add pip installation to work pool type Prefect:managed installation of pip package

The search results from the Prefect documentation do not provide a direct answer on how to install pip packages for Prefect-managed work pools. However, as Prefect-managed work pools are a fully managed environment, they might not support custom environment customizations such as installing additional pip packages directly. Instead, it generally offers a standardized execution environment for your flows. If you need to install additional pip packages for your flow, you could: 1. Build a custom Docker image that includes all of your dependencies, and then reference that Docker image within your deployment. Such a Dockerfile might look like the one I previously mentioned:

dockerfile
FROM prefecthq/prefect:latest
COPY requirements.txt /requirements.txt
RUN pip install -r /requirements.txt

2. Alternatively, if the Prefect-managed work pools allow specifying a

requirements.txt

file or providing pip install commands as part of the flow configuration, you would use that feature to ensure that your dependencies are installed when the flow executes. This level of customization isn't detailed in the search results, and as such, you might need to check the official Prefect documentation or inquire directly with the Prefect community or support team for beta features or any new functionality related to Prefect-managed work pools. For a detailed explanation or any available new features, please consult Prefect's official documentation or their community forum, as they will contain the most up-to-date and relevant information for your specific needs.

@Marvin if i schedule a deployment (cron) in the past will the deployment execute

According to the Prefect scheduling documentation, the Scheduler service creates new runs based on the deployment's schedule. However, it doesn't explicitly mention behavior related to schedules set in the past. That being said, typically in cron job schedulers or similar systems, if you set a schedule in the past, it will not execute those past occurrences automatically. The scheduler should start creating new runs according to the next upcoming time that matches the cron schedule. To be certain about the behavior of Prefect Cloud regarding past cron schedules, I would recommend consulting the Prefect community or support, as this behavior might depend on the version of Prefect being used or the specifics of the Prefect Cloud scheduler service that may not be detailed in the documentation.