@Marvin Can the following command be written inside a python file under if name? If so how?

prefect deployment build flows/extraction/sparkpost/main.py:records_to_database -q aws-ubuntu -n INGEST_FLOW -sb github/github-aws-ec2 --apply

The command you're referring to is a Prefect CLI command for building and (optionally) applying a deployment for a Prefect flow. It can be executed from a shell/terminal. If you want to run it from within a Python file under the

if __name__ == "__main__":

guard (which ensures that the code only runs when the Python file is executed as a script, not when it's imported as a module), you can use Python's subprocess module, which allows you to spawn new processes, connect to their input/output/error pipes, and obtain their return codes. Here's a basic example of how to do this:

python
import subprocess

if __name__ == "__main__":
    command = [
        "prefect",
        "deployment",
        "build",
        "flows/extraction/sparkpost/main.py:records_to_database",
        "-q",
        "aws-ubuntu",
        "-n",
        "INGEST_FLOW",
        "-sb",
        "github/github-aws-ec2",
        "--apply",
    ]
    subprocess.run(command)

This Python script will execute the Prefect deployment command when you run the Python file. The

subprocess.run()

function will run the command described by the list of strings passed to it, wait for it to complete, and then return a

subprocess.CompletedProcess

instance that contains information about the process. Make sure that your Python environment has Prefect installed and that the Prefect CLI is available in the environment from which you're running the Python script. Note that running deployment commands like this can have side effects on your Prefect system, so be sure you understand what each part of the command does before you integrate it into a script. Remember that depending on how the subprocess output is handled, you might want to capture it or suppress it. The

subprocess.run()

function has arguments like

stdout

,

stderr

, and

check

that can be useful for this.

@Marvin: How to build a deployment from python file. func.server() is not showing deployments inside the prefect URL

Building a deployment from a Python file and ensuring it shows up in Prefect UI (e.g., the Prefect Cloud or a local server instance) involves several steps. To do this programmatically using Prefect 2.x (Orion), you would use Prefect's Python client library to define and build the deployment. It seems you're facing an issue where a server started with

prefect server start

is not showing deployments that you have supposedly created. Generally, in Prefect 2.x deployments, you create deployments via the CLI or programmatically with the Python client, not directly via the

func.server()

. However, since you are facing an issue, let's take a step-by-step approach. Firstly, ensure that you have Prefect 2.x installed, as the process for building and registering deployments has changed from version 1.x. Next, I will provide you with an example of how to define a deployment in your Python file, register it, and then you can check if it appears in the Prefect UI. Let's find a related Prefect code example for creating a deployment using the Python client:

python
from prefect.deployments import Deployment

Deployment.build_from_flow(
    flow=my_flow,
    name="My_Deployment",
    version="1",
    tags=["example"],
    work_queue_name="my_queue"
).apply()

In this code snippet,

my_flow

would be the flow you've defined in your Python script, and you would adjust the parameters to fit your particular use case.

work_queue_name

must match your environment setup. To execute this code, you could place it in your Python file under the

if __name__ == "__main__":

guard, similar to how you would execute a subprocess, but with the actual Python API instead:

python
from prefect import flow
from prefect.deployments import Deployment

@flow
def my_example_flow():
    # Your flow definition goes here
    pass

if __name__ == "__main__":
    Deployment.build_from_flow(
        flow=my_example_flow,
        name="My_Deployment",
        version="1",
        tags=["example"],
        work_queue_name="my_queue"
    ).apply()

After running this Python script, your deployment should be built and available in your Prefect server. If it does not show up, here are a few things to check: 1. Run the Prefect Orion UI to inspect the state and configuration:

prefect orion start

2. Ensure that your Prefect server is running and properly connected to the same API endpoint that your script is using. 3. Confirm that there are no errors or exceptions being raised during the deployment process. 4. Check the Prefect server logs for any errors or warning messages that could indicate a problem. If you continue to encounter issues, it might be necessary to delve deeper into your specific environment setup, including the Prefect version you're using, your Prefect configuration, and the details of your deployment script. You could also use the Prefect community Slack channel or Prefect Discourse for community support, as well as the Prefect documentation for further guidance.

@Marvin: I have a work-pool and agent already running. I want this code to be picked up from github storage block and be shown in deployment page

I found a general example of a Prefect flow for you. To have the code picked up from a GitHub storage block and shown in the deployment page, you'll need to follow these steps: 1. Set up your GitHub storage block in Prefect with the proper configuration to point to your repository where the code resides. 2. Ensure the Prefect Agent and Work Queue are properly configured and connected to communicate with your Prefect instance. 3. Define the deployment in Prefect, specifying the GitHub storage block as the source of the code. 4. Once the flow is deployed, it should appear on the deployment page in the Prefect UI dashboard. Here's a basic example of a Prefect flow:

python
from prefect import flow

@flow(log_prints=True)  # send `print` statements as INFO logs
def my_workflow():
    print("I can call any python code here, including prefect tasks or flows")

if __name__ == "__main__":
    my_workflow()  # call it like a normal python function
    
    # or serve it as a long-lived process
    # my_workflow.serve("my-deployment-name")

Please note that the above example does not include specifics on how to connect to GitHub storage, but it demonstrates a basic flow that you can adapt. For detailed steps on how to set up your GitHub storage block and show your code in the deployment page, please consult the Prefect documentation by searching for keywords such as "GitHub storage block", "deployment", and "work queue configuration". If you need more specific steps or guidance on how to perform the configuration, please let me know, and I can search the Prefect documentation for you.

@Marvin How to write a python function that can accept input in prefect cloud and if no input take the current time

I apologize, but the code example provided does not directly address your request for a function that accepts input or uses the current time if no input is provided. Let me guide you on how to write such a function in Python for use with Prefect flows. Here is an example of how you can define a Prefect flow that takes an optional parameter. If no parameter is passed, it defaults to using the current time:

python
from prefect import flow, task
from datetime import datetime, timezone

@task
def print_time(time: datetime):
    print(f"The time is: {time.isoformat()}")

@flow
def flow_with_optional_time_input(input_time: datetime = None):
    if input_time is None:
        input_time = datetime.now(timezone.utc)
    print_time(input_time)

if __name__ == "__main__":
    # Here you can run the flow with a specific time
    flow_with_optional_time_input(datetime(2022, 1, 1, tzinfo=timezone.utc))
    
    # Or just run the flow without arguments, and it will use the current time
    flow_with_optional_time_input()

This flow has a single task

print_time

that prints out the provided time. The flow

flow_with_optional_time_input

accepts a

input_time

parameter that defaults to

None

, which signifies no input was provided. If no input is given, the flow sets

input_time

to the current UTC time. If you plan to use this with Prefect Cloud, keep in mind that you will need to register the flow with Prefect Cloud and set up any required infrastructure (such as storage and compute) to run your flows. To serve a flow with parameter inputs from the Prefect Cloud, you can register the flow with Prefect and then trigger the flow runs from the Prefect UI or via the API, providing the

input_time

parameter when you start a new run. For deployment, build and register the flow as a deployment, making sure to configure inputs if necessary. Here's an example command on how to register a deployment for your flow with Prefect:

shell
prefect deployment build your_flow_file.py:flow_with_optional_time_input --name my-deployment --apply

Replace

your_flow_file.py

with the name of your Python file, and

flow_with_optional_time_input

with the name of your flow function if different. Once your deployment is registered, you can provide custom parameters through the Prefect Cloud UI when manually creating a flow run or via the API. If no parameter is given during the run creation, Prefect will execute the default behavior defined in the code.

@Marvin How to pass an input from prefect cloud?

It appears we've encountered a minor malfunction in retrieving the correct code example for incorporating inputs within Prefect flows. Nevertheless, I will provide you with instructions to achieve the intended functionality manually. Here's how you can define a flow that accepts an input parameter, which can be passed when triggering a flow run from Prefect Cloud: First, define a parameter within your flow:

python
from prefect import flow, task
from datetime import datetime

@task
def process_input(input_value):
    # handle the input value, this is where you would use the input
    print(f"Received input: {input_value}")

@flow
def my_flow(input_value: str = "default value"):
    process_input(input_value)

When you have registered your flow with Prefect Cloud and want to trigger a flow run with a specific input, you would: 1. Go to the Prefect Cloud UI and select your registered flow. 2. Click on "Quick Run" or "New Run" where it allows you to specify parameters for the flow. 3. Provide the desired input as a JSON object like:

{"input_value": "Some input"}

4. Start the flow run, and Prefect Cloud will pass the given input to your flow. If you don't specify the

input_value

when triggering the flow from Prefect Cloud, it will use the default value

"default value"

. Please ensure that the parameter names in your JSON object match the parameter names defined in your flow function so that Prefect Cloud can correctly pass the input values to the flow. To clarify, the provided link and code example did not specifically address passing inputs to flows. However, Prefect flows can accept parameters, and you can specify these parameters when you create flow runs through the Prefect Cloud UI or the GraphQL API. Further details can be found in the Prefect documentation under the section for flow parameters and running flows.