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# ask-marvin

Marco Ruta

05/29/2024, 9:17 AM

@Marvin using flow.deploy how can I config the install requirement steps ONLY USING PYTHON SDK?

Marvin

05/29/2024, 9:17 AM

To configure the installation of requirements using the Prefect Python SDK, you can use the

prefect.deployments.steps.pip_install_requirements

step. Below is an example that demonstrates how to deploy a flow with the required installation steps: 1. Clone the repository: 2. Install dependencies from a
requirements.txt
file: Here's the code snippet for the deployment steps:

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python
from prefect.deployments import Deployment
from prefect.deployments.steps import git_clone, pip_install_requirements

# Define your deployment steps
steps = [
    git_clone(
        id="clone-step", # user-defined id for referencing in subsequent steps
        repository="<https://github.com/your_org/your_repo.git>"
    ),
    pip_install_requirements(
        directory="{{ clone-step.directory }}", # referring to the output directory of the clone step
        requirements_file="requirements.txt"
    )
]

# Define and create the deployment
deployment = Deployment.build_from_flow(
    flow=my_flow,  # your flow function
    name="my-deployment",
    version="1.0",
    steps=steps
)

deployment.apply()

### Explanation: 1. git_clone: Clones the repository containing your flow and dependencies. 2. pip_install_requirements: Installs the dependencies listed in the

requirements.txt

file located in the cloned directory. For more detailed information on the deployment steps and examples, you can check out the Prefect Deployments Guide. And here's a basic example of creating a flow:

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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

This code does everything you'd need using the Python SDK. Happy coding, not that it matters in the grand scheme of the universe. Sources: - Prefect Deployments Guide - Prefect Code Examples

Marco Ruta

05/29/2024, 9:18 AM

@Marvin the use of Deployment is deprecated. I want to use flow.deploy

Marvin

05/29/2024, 9:18 AM

To configure the installation of dependencies during deployment using

flow.deploy

in the Prefect Python SDK, you can achieve this by specifying the necessary steps within the

deploy

method. Below is an example of how to use

flow.deploy

with the installation of requirements specified: ## Example Here’s how you can set up your

flow.deploy

to include the installation of dependencies from a

requirements.txt

file:

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python
from prefect import flow
from prefect.deployments import steps

# Define your flow
@flow
def my_flow():
    print("Running the flow!")

# Set up the deployment steps
deployment_steps = [
    steps.git_clone(
        id="clone-step",  # user-provided id field for referencing
        repository="<https://github.com/your_org/your_repo.git>"
    ),
    steps.pip_install_requirements(
        directory="{{ clone-step.directory }}",  # use the output directory of the clone step
        requirements_file="requirements.txt"
    )
]

# Deploy the flow with the specified steps
my_flow.deploy(
    name="my-deployment",
    steps=deployment_steps
)

### Explanation: 1. git_clone: This step clones the repository containing your flow and

requirements.txt

file. 2. pip_install_requirements: This step installs the dependencies listed in the

requirements.txt

file located in the cloned directory. Additional documentation and examples can be found in the Prefect Deployments Guide. ## Basic Flow Definition Example Here's a simple example to create and deploy a basic flow:

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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")

By following these steps, you should be able to deploy your flow with the required dependencies using only the Python SDK. Let me know if you need any further details (as if it really mattered in this vast universe of trivialities). Sources: - Prefect Deployments Guide - Basic Flow Example

Marco Ruta

05/29/2024, 9:33 AM

@Marvin your solution is partially wrong, the .deploy method does not accept any steps param

Marvin

05/29/2024, 9:34 AM

It seems you are correct. The

.deploy

method in Prefect 2.x doesn't directly accept a

steps

parameter. Instead, you need to use a YAML deployment file to specify deployment steps, including installing dependencies from a

requirements.txt

file. Here’s how you can create a deployment using the Prefect YAML configuration: ## Using

prefect.yaml

1. Create a
prefect.yaml
configuration file:

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yaml
version: 2

deployments:
- name: my-deployment
  work_pool:
    name: your-work-pool
  steps:
    - git_clone:
        id: clone-step
        repository: "<https://github.com/your_org/your_repo.git>"
    - pip_install_requirements:
        directory: "{{ clone-step.directory }}"
        requirements_file: "requirements.txt"
  flow_name: "my_flow"
  parameters: {}

## Deploying with YAML To deploy using this configuration: 1. Save the above YAML content in a file named

prefect.yaml

. 2. Use the

prefect deploy

command to create the deployment.

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bash
prefect deploy -n my-deployment

## Example Flow Definition You can still define your flow in Python as usual:

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python
from prefect import flow

@flow
def my_flow():
    print("Running the flow!")

if __name__ == "__main__":
    my_flow()  # Run the flow

### Explanation: 1. git_clone: Clones the GitHub repository that contains your flow and

requirements.txt

. 2. pip_install_requirements: Installs the dependencies listed in the

requirements.txt

file found in the cloned directory. ## Running the Deployment After deploying, you’ll need to start a worker to execute the flow:

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bash
prefect worker start -p your-work-pool

With this setup, your deployment configuration is managed using the YAML file, which allows for the necessary steps to be executed, including cloning the repository and installing dependencies. For additional details, refer to the Prefect Deployment Guide. And here is a basic example to illustrate deploying a flow:

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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")

If the universe still confounds you, feel free to ask more. Sources: - Prefect Deployments Guide - Basic Flow Example

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