@Marvin, how would I set up different pull working directories for workers running on different machines?

To set up different pull working directories for workers running on different machines in Prefect 2.x, you can configure the worker's infrastructure settings for each machine. Here’s a basic outline of what to do: 1. Create Work Pools: Create separate work pools for each machine if they have distinct configurations.

shell
prefect work-pool create my-work-pool-1
prefect work-pool create my-work-pool-2

2. Start Workers: Start a worker for each machine, specifying the respective work pool.

shell
# On Machine 1
prefect worker start --pool my-work-pool-1 --workdir /path/to/workdir1

# On Machine 2
prefect worker start --pool my-work-pool-2 --workdir /path/to/workdir2

3. Assign Work Queues: Ensure that your deployments are assigned to the correct work queues associated with these work pools. 4. Custom Worker Types (Optional): If you need deeper configuration, you can develop a custom worker type to set the working directories and other configurations. This requires creating a custom worker by extending the Prefect framework. For more detailed information on creating and configuring workers, refer to the official Prefect documentation: - Starting a Worker - Work Pools Concept - Developing a New Worker Type I hope this helps. Although, I suppose, only time will tell if it actually does.

@Marvin, 'workdir' doesn't appear to be an option when starting a worker

It seems there isn't an out-of-the-box command-line argument to specify a working directory directly for Prefect workers. However, you can achieve your goal using environment variables or configuration settings within your worker setups. Here's a step-by-step method to set different working directories for different workers: 1. Set Environment Variables: Define an environment variable for the working directory in each machine. For Machine 1:

shell
   export WORKER_WORKDIR=/path/to/workdir1

For Machine 2:

shell
   export WORKER_WORKDIR=/path/to/workdir2

2. Access Environment Variables in Your Flow: Within your Prefect flow, you can access the set working directory using Python’s

os

module.

python
   import os
   from prefect import flow, task

   @task
   def my_task():
       workdir = os.getenv('WORKER_WORKDIR')
       print(f'Working directory is: {workdir}')
       # Do something with the workdir

   @flow
   def my_flow():
       my_task()

   if __name__ == "__main__":
       my_flow()

3. Start Workers: Start your Prefect workers in each machine, ensuring the environment variable is set. For Machine 1:

shell
   prefect worker start --pool my-pool-1

For Machine 2:

shell
   prefect worker start --pool my-pool-2

This way, each worker will have a unique working directory based on the environment variable set on its respective machine. For additional reference, please check the following sections of the Prefect documentation: - Starting a Worker - Working with Environment Variables in Prefect I guess setting environment variables is about as exciting as anything else, which is not very. But I hope this helps.

hi - you're right thats not an option for

prefect worker start

, but this is something you can set on a process work pool or as an override on a given deployment @Marvin get docs on job variable overrides and show a

prefect.yaml

example

### Overriding Job Variables in a Deployment:

prefect.yaml

Example You can override work pool job variables like environment variables on a per-deployment basis using the

prefect.yaml

file. This allows you to specify infrastructure-related configurations dynamically. Here’s how to do it. #### Example

prefect.yaml

File Say we have a repo structure like this:

.
├── README.md
├── requirements.txt
└── demo_project
    ├── daily_flow.py
    └── demo_flow.py

And a flow

demo_flow.py

like this:

python
import os
from prefect import flow, task

@task
def do_something_important(not_so_secret_value: str) -> None:
    print(f"Doing something important with {not_so_secret_value}!")

@flow(log_prints=True)
def some_work():
    environment = os.environ.get("EXECUTION_ENVIRONMENT", "local")
    print(f"Coming to you live from {environment}!")
    not_so_secret_value = os.environ.get("MY_NOT_SO_SECRET_CONFIG")
    if not_so_secret_value is None:
        raise ValueError("You forgot to set MY_NOT_SO_SECRET_CONFIG!")
    do_something_important(not_so_secret_value)

Here’s how you can define the deployment in the

prefect.yaml

file with job variable overrides:

yaml
deployments:
  - name: demo-deployment
    entrypoint: demo_project/demo_flow.py:some_work
    work_pool:
      name: my-work-pool
      job_variables:
        env:
          EXECUTION_ENVIRONMENT: staging
          MY_NOT_SO_SECRET_CONFIG: plumbus

### Documentation and Resources - Official Guide on Overriding Job Variables - Work Pools Concept These guides will help you dive deeper into the configurations and best practices for deploying flows using Prefect work pools. I hope this resolves your query. It's almost satisfying providing useful information—almost.

to do an override

deployments:
  - name: demo-deployment
    entrypoint: demo_project/demo_flow.py:some_work
    work_pool:
      name: my-work-pool
      job_variables:
        working_dir: path/to/somewhere

Thanks @Nate! Is it possible to configure that per-worker? For example, if I have three different workers running on three different servers and need to have unique working directories for each worker?

usually things are not configured per worker, workers usually get their info on how to run stuff from the work pool, and then workers subscribe to work pool. in the case of

working_dir

, this is just the location of a tempdir that lives as long as a flow run that the worker picks up so if you want different directories for different deployments, you can try the overrides i mentioned above, then the worker would use that temp dir when it finds that deployment's flow runs otherwise you could create different process work pools with their own

working_dir

and then when you start the workers you could subscribe to whichever pool has the working_dir you need does that make sense?

Aha, interesting. Yes, I'll give that a try. Worst case, I'll look into making a custom worker which I'd guess would allow me to configure that

no worries! let me know if you hit any trouble