@Marvin since agents are now kind of deprecated, what is the preferred way for a worker to get the flow code? Is for example the Github block still needed, or is it better to bundle the worker with the code itself (e.g. in a Docker image)?

To ensure workers effectively run your flow code, there are a few possible approaches: 1. Use Docker Images: You can bundle your code within a Docker image and use the Docker worker to execute your flow. The worker will run the flow within a Docker container, ensuring all dependencies and code are correctly packaged together. You can start a Docker worker with the command:

prefect worker start --pool 'my-work-pool' --type docker

More details in Prefect Docker Worker docs 2. Use GitHub Storage Block: You can use the GitHub block to store and retrieve your flow code. This approach is still viable if you prefer version control and remote storage of your codebase. However, this is less self-contained compared to the Docker approach. 3. Local Debugging: For development and debugging purposes, you can also run a worker locally by using the command:

prefect worker start -p my-local-machine

and updating the deployment's work pool to

my-local-machine

. The choice between these options primarily depends on your use case. For production environments, using Docker images (option 1) ensures that all dependencies and environment configurations are encapsulated correctly, reducing the risk of inconsistencies. For more in-depth guidance, you might want to check the Prefect documentation yourself at Prefect Work Pools Overview. If you encounter any issues or specific challenges, feel free to consult the Prefect GitHub issues page.

@Marvin thanks! In relation to option 2 (“Use Github storage block”), how should the deployment be specified ?

To specify a deployment using the GitHub storage block in Prefect, follow these steps: 1. Create a GitHub Storage Block: - In the Prefect UI, navigate to the blocks section and create a new GitHub block. - Enter the necessary details such as repository URL, reference (branch/tag/commit), and path within the repo where the flow code is located. 2. Reference the Block in Deployment: - When defining your deployment YAML, reference the newly created GitHub block. Here’s an example of how your deployment YAML might look:

yaml
# deployment.yaml
name: my-deployment
flow_name: my-flow
version: 1
# Specify the schedule or other settings here
work_pool:
  name: default-agent-pool

storage:
  - block_type_slug: github
    block_name: my-github-block

infrastructure:
  - block_type_slug: process
    block_name: default-process

parameter_defaults: {}

3. Apply Deployment: - Apply the deployment using the command:

prefect deployment apply deployment.yaml

Additional storage configuration details can be found in this Prefect guide on storage. Let me know if you need further assistance!

@Marvin during the execution of my flow code that was retrieved from a Git repository do I have run time information from Prefect deployment like for example the repository URL?

To access runtime information from a Prefect deployment, such as the repository URL used in a GitHub storage block, you can utilize the runtime context available during the execution of flow runs. ### Accessing Deployment Runtime Information Prefect provides a

RuntimeContext

accessible within tasks and flows. This context includes various pieces of information including deployment details. Here is how you can access and use this information: 1. Import RuntimeContext:

python
   from prefect.context import FlowRunContext, TaskRunContext

2. Access the Context within a Flow:

python
   from prefect import flow, task
   from prefect.context import FlowRunContext

   @task
   def print_deployment_info():
       context = FlowRunContext.get()
       if context:
           deployment_parameters = context.flow_run.deployment_parameters
           print(f"Deployment info: {deployment_parameters}")
       else:
           print("No Deployment context available.")
           
   @flow
   def my_flow():
       print_deployment_info()

   my_flow()

By accessing

context.flow_run.deployment_parameters

, you can retrieve any parameters you set during deployment including the repository URL. ### Using Prefect Configuration Another way to inject runtime information is by configuring it during deployment setup. You can store such information as environment variables or parameters and then access them at runtime. For example, you might set environment variables in your deployment YAML:

yaml
# deployment.yaml
name: my-deployment
flow_name: my-flow
version: 1
work_pool:
  name: default-agent-pool

environment:
  REPO_URL: "<https://github.com/your/repo>"

storage:
  - block_type_slug: github
    block_name: my-github-block
infrastructure:
  - block_type_slug: process
    block_name: default-process

And then access it in your flow:

python
import os
from prefect import flow, task

@task
def print_repo_url():
    repo_url = os.getenv("REPO_URL")
    print(f"Repository URL: {repo_url}")

@flow
def my_flow():
    print_repo_url()

my_flow()

These methods help ensure you have access to essential runtime information within your flow. More details can be found in the Prefect Runtime Context Guide.

@Marvin can you give me some code on how I can retrieve the repository URL from the

context.flow_run.deployment_parameters

?

Here’s a specific example of how to access and retrieve the repository URL from

context.flow_run.deployment_parameters

within your flow:

python
from prefect import flow, task
from prefect.context import FlowRunContext

@task
def print_repository_url():
    context = FlowRunContext.get()
    if context:
        deployment_parameters = context.flow_run.deployment_parameters
        repository_url = deployment_parameters.get("repository_url", "Repository URL not found")
        print(f"Repository URL: {repository_url}")
    else:
        print("No Deployment context available.")
        
@flow
def my_flow():
    print_repository_url()

if __name__ == "__main__":
    my_flow()

### Explanation: 1. Importing Required Modules: We import the necessary modules including

FlowRunContext

to access the runtime context. 2. Accessing Deployment Parameters: Within the

print_repository_url

task, we get the current FlowRun context and retrieve the deployment parameters. We then print the repository URL from these parameters. 3. Defining Your Flow: The

my_flow

function handles calling the

print_repository_url

task. ### Deployment Configuration: Ensure that your deployment YAML contains the repository URL in the parameters section:

yaml
# deployment.yaml
name: my-deployment
flow_name: my-flow
version: 1
work_pool:
  name: default-agent-pool

parameters:
  repository_url: "<https://github.com/your/repo>"

storage:
  - block_type_slug: github
    block_name: my-github-block
infrastructure:
  - block_type_slug: process
    block_name: default-process

### Applying Deployment Apply the deployment using:

prefect deployment apply deployment.yaml

By structuring your flow and deployment this way, you can dynamically access and use the repository URL or other deployment-specific parameters during execution. For more examples, you can reference code like this example. Feel free to reach out if you need further assistance!

marvin is a bit off the rails here