@Marvin can you give me a complete example of how to run a flow locally using a process type worker? It should have a pull step to git clone from a repo.

Ah, the sweet symphony of code and documentation. Here's what I found: To run a Prefect flow locally, you can use the Prefect CLI. You'll need to create a Python file with your flow definition and then use the

prefect run -p path_to_your_file.py

command to execute it[^1^]. For the process type worker, you can start it using the Prefect CLI with the

prefect worker start --type process

command[^2^]. You can also specify a work pool name with the

-p

flag[^3^]. As for the git clone step, you can include it in the

pull

section of your

prefect.yaml

file. Here's an example of how to clone a branch of a public repository:

yaml
pull:
    - prefect.projects.steps.git_clone_project:
        repository: <https://github.com/PrefectHQ/prefect.git>
        branch: my-branch

And here's how to clone a private repository using an access token:

yaml
pull:
    - prefect.projects.steps.git_clone_project:
        repository: <https://github.com/org/repo.git>
        access_token: "{{ prefect.blocks.secret.github-access-token }}" # Requires creation of a Secret block

In the case of a private repository, you'll need to create a Secret block to store the value of your git credentials[^4^]. I hope this helps you navigate the flow of Prefect. Remember, the river of code is deep and wide, but every programmer has a paddle. Or something like that. [^1^]: Prefect Cloud Quickstart [^2^]: Developing a New Worker Type [^3^]: Work Pools [^4^]: pull.py </stop>

@Marvin, I have my flow code. I created my work-pool. I started my worker locally assigned to that work-pool. I can see that the worker is healthy. I deployed my code. When it runs the worker however throws an error that I can't make sense of. Can you provide an example of each individual component and the steps so I can use that to adapt.

Ah, the classic tale of code, error, and the quest for resolution. Let's embark on this journey together. First, let's break down the components and steps involved in running a Prefect flow with a local worker. 1. Flow Definition: This is your Python script where you define your tasks and the flow. Here's a simple example:

python
from prefect import task, Flow

@task
def say_hello():
    print("Hello, world!")

with Flow("My First Flow") as flow:
    say_hello()

flow.run()  # "Hello, world!"

2. Work Pool Creation: You can create a work pool using the Prefect CLI. Here's an example:

bash
prefect work pool create --name my-pool

3. Worker Start: Start your worker and assign it to the work pool. Here's how you can do it:

bash
prefect worker start --name my-worker --work-pool my-pool

4. Flow Deployment: Deploy your flow to Prefect Cloud. Here's an example:

bash
prefect register --project my-project -p path_to_your_flow.py

5. Flow Run: Trigger a run of your flow. You can do this from the Prefect Cloud UI, or using the CLI:

bash
prefect run cloud --name "My First Flow" --project my-project

Now, if your worker is throwing an error, it could be due to a variety of reasons. It could be an issue with the task code, a problem with the worker configuration, or something else entirely. To diagnose the issue, you can check the logs of the worker. You can access these logs from the Prefect Cloud UI, or directly from the terminal where you started your worker. Remember, the path to code enlightenment is often paved with error messages. But fear not, for every error message is but a stepping stone on the path to success. Or so they say.

@Marvin can you update this so it only uses Prefect 2 concepts? Steps 1-3 look correct. Does it matter if I am on windows

Ah, the plot thickens with the introduction of Prefect 2 and the Windows operating system. Let's adjust our course accordingly. 1. Flow Definition: This remains the same as in Prefect 1. Here's a simple example:

python
from prefect import task, Flow

@task
def say_hello():
    print("Hello, world!")

with Flow("My First Flow") as flow:
    say_hello()

flow.run()  # "Hello, world!"

2. Work Pool Creation: In Prefect 2, work pools have been replaced with labels. You can assign labels to your flow in the flow definition:

python
with Flow("My First Flow", labels=['my-label']) as flow:
    say_hello()

3. Worker Start: Start your worker with the same label. Here's how you can do it:

bash
prefect agent start --label my-label

4. Flow Deployment: Deploy your flow to Prefect Cloud. Here's an example:

bash
prefect register --project my-project -p path_to_your_flow.py

5. Flow Run: Trigger a run of your flow. You can do this from the Prefect Cloud UI, or using the CLI:

bash
prefect run cloud --name "My First Flow" --project my-project

As for Windows, Prefect 2 should work just fine. However, you might need to adjust the command line syntax slightly. For example, instead of using forward slashes in file paths (

/

), you'll need to use backslashes (

\

). Remember, the path to code enlightenment is often paved with error messages. But fear not, for every error message is but a stepping stone on the path to success. Or so they say.