< Marvin> Can you show me an example where you deploy multip Prefect Community #ask-marvin

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# ask-marvin

Jackson Nguyen

01/20/2025, 11:51 PM

@Marvin Can you show me an example where you deploy multiple flows at once programmatically?

✅ 1

Marvin

01/20/2025, 11:51 PM

To deploy multiple flows programmatically in Prefect 3.x, you can use the

deploy

function. This approach allows you to manage your flows efficiently by building a single Docker image for multiple deployments, which saves time and resources. Here's a simple example to illustrate this:

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python
from prefect import flow, deploy

@flow
def flow_one():
    print("Running Flow One")

@flow
def flow_two():
    print("Running Flow Two")

# Deploy both flows
deployments = deploy(
    flows=[flow_one, flow_two],
    # Additional deployment configurations can be added here
)

print("Deployments created:", deployments)

This script will deploy both

flow_one

and

flow_two

using a single deployment process. You can customize your deployment further by setting parameters and job variables as needed. For more details, you can refer to the Prefect documentation on deploying flows using the Python SDK: Deploy flows with Python.

Jackson Nguyen

01/20/2025, 11:52 PM

@Marvin Can you show me an example where I have code stored remotely in git repo named "git_repository"?

Marvin

01/20/2025, 11:52 PM

To deploy a flow with code stored remotely in a Git repository, you can use Prefect's support for remote code storage. Here's an example of how you might set this up:

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python
from prefect import flow, deploy
from prefect.deployments import GitRepository

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

# Specify the Git repository as the source
git_repo = GitRepository(
    url="<https://github.com/your_username/git_repository>",
    branch="main",  # or specify another branch or tag
    # If using a private repo, you may need to provide authentication
    # credentials via a Secret block or similar method
)

# Deploy the flow using the Git repository as the source
deployment = deploy(
    flow=my_flow,
    source=git_repo,
    # Additional deployment configurations can be added here
)

print("Deployment created:", deployment)

This script uses the

GitRepository

object to specify the remote Git repository where your flow code is stored. You can customize the branch or tag as needed. If the repository is private, you should manage authentication using Prefect's Secret blocks or similar methods. For more information, refer to the Prefect documentation on using remote code storage: Store flow code.

Jackson Nguyen

01/21/2025, 12:15 AM

@Marvin What is the difference between the prefect.deploy(), and the prefect.flow.deploy() methods?

Marvin

01/21/2025, 12:15 AM

The

prefect.deploy()

and

prefect.flow.deploy()

methods are not directly comparable because

prefect.flow.deploy()

does not exist as a method. Instead, the

prefect.deploy()

function is used for deploying flows in Prefect 3.x. The

prefect.deploy()

function is part of the top-level API and is used to create deployments for flows. A deployment in Prefect is a server-side representation of a flow, which stores metadata necessary for remote orchestration, such as schedules, parameters, and infrastructure configurations. For more detailed information on how to use the

prefect.deploy()

function, you can refer to the Prefect documentation here: Prefect Deployment Overview. If you have any specific questions about deploying flows or need further clarification, feel free to ask!

Jackson Nguyen

01/21/2025, 12:16 AM

@Marvin Let me correct myself. What is the difference between the prefect.deploy(), and the prefect.flow.Flow.deploy() methods? The second is the class method of the Flow class.

Marvin

01/21/2025, 12:16 AM

The

prefect.deploy()

function and the

prefect.flow.Flow.deploy()

method serve different purposes in Prefect. 1. prefect.deploy()
Function: - This is a top-level function in Prefect 3.x that is used to create deployments for flows. Deployments are server-side representations that include metadata necessary for remote orchestration, such as schedules and infrastructure configurations. This function is typically used when you want to deploy a flow using a YAML configuration file that describes the deployment details. - Documentation: Prefect Deployment Overview 2. prefect.flow.Flow.deploy()
Method: - This is a method of the

Flow

class, which allows you to deploy a flow programmatically using Python code rather than a YAML file. This method provides a more flexible and dynamic way to specify deployment details directly in your Python scripts, which can be advantageous if you need to customize deployments based on runtime conditions or other logic. - Documentation: Deploy via Python In summary, use

prefect.deploy()

when you prefer a declarative approach with YAML configurations, and

prefect.flow.Flow.deploy()

when you need an imperative, code-driven deployment process.

Jackson Nguyen

01/21/2025, 12:32 AM

@Marvin when is a prefect.yaml preferred?

Marvin

01/21/2025, 12:33 AM

prefect.yaml

file is preferred in the following scenarios: 1. Declarative Configuration: If you prefer a declarative approach to managing your deployments, using a

prefect.yaml

file allows you to specify deployment settings, procedural steps, and execution environment instructions in a structured, readable format. 2. Standardization and Reusability: The

prefect.yaml

file can serve as a standardized configuration template that can be reused across different projects or teams. Prefect provides "recipes" that help you set up your

prefect.yaml

with common configurations, which can streamline deployment processes. 3. Version Control: YAML files can be easily version-controlled alongside your flow code in a repository, allowing for better tracking of changes and collaboration across team members. 4. CLI Integration: You can use the Prefect CLI to initialize and manage deployments using the

prefect.yaml

. This can be convenient for teams that prefer command-line operations. 5. Structure and Clarity: The

prefect.yaml

provides a clear structure for defining base settings, deployment steps, and execution instructions, which can be beneficial for larger projects with complex deployment needs. For more details, you can refer to the Prefect documentation on defining deployments with YAML: Prefect YAML Documentation.

Jackson Nguyen

01/21/2025, 12:41 AM

@Marvin What kind of permissions do I need on the access token for a GitLab project?

Marvin

01/21/2025, 12:41 AM

To integrate Prefect with a private GitLab repository, you will need to use a personal access token. The specific permissions required on this token depend on the actions you want to perform. Generally, you should ensure the token has the following permissions: 1. Read Repository: This permission is necessary to clone or pull the repository contents. It allows Prefect to access the code stored in your GitLab repository. 2. Write Repository (if needed): If your workflows require pushing changes back to the repository, you will need this permission. 3. API Access: If your integration involves interacting with GitLab's API for actions beyond simple repository access, ensure the token has API access. For security, it's recommended to use fine-grained permissions and limit the token's access to only what is necessary for your Prefect workflows. You can reference the token in a Prefect deployment using a credentials block in the

prefect.yaml

or directly in your Python code. For more details, you can refer to the Prefect GitLab integration documentation: Prefect GitLab Integration.

Jackson Nguyen

01/21/2025, 12:51 AM

@Marvin I have defined a prefect.yaml. How do I use it to deploy my flows?

Marvin

01/21/2025, 12:52 AM

To deploy your flows using a

prefect.yaml

file, follow these steps: 1. Ensure Authentication: Before deploying, authenticate with Prefect using the Prefect CLI. This ensures that your deployments are registered with your Prefect Cloud or server. 2. Navigate to Directory: Make sure you are in the directory containing your

prefect.yaml

file. This file should define the deployment configurations for your flows. 3. Run the Deploy Command: Use the Prefect CLI to deploy your flows by executing:

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bash
   prefect deploy

This command will read the

prefect.yaml

file and execute the deployment steps defined within it. 4. Deployment Process: - The

build

section of your

prefect.yaml

will load first, resolving any variable and block references, and running the specified steps. - The

push

section will load next, executing its steps. - The

pull

section is templated with any step outputs but is not run for security purposes. - Finally, the deployment specification is registered, completing the deployment. By using

prefect.yaml

, you can manage multiple deployments and configurations easily, allowing for a structured and repeatable deployment process. For more details, refer to the Prefect YAML Documentation.

Jackson Nguyen

01/21/2025, 12:54 AM

@Marvin When I run

prefect deploy

it prompts for me to respond. I want to run my deployment with no interaction on the command line. How can I do this?

Marvin

01/21/2025, 12:54 AM

To run

prefect deploy

without any interaction on the command line, you can automate the deployment process by ensuring that all necessary configurations and inputs are predefined in the

prefect.yaml

file. Here’s how you can achieve a non-interactive deployment: 1. Complete Configuration in
prefect.yaml
: Make sure your

prefect.yaml

file includes all necessary configurations, such as deployment settings, environment variables, and any other parameters that might otherwise prompt for input during deployment. 2. Use CLI Flags: If there are CLI flags that can be used to suppress prompts or provide default answers, ensure you use them when running the

prefect deploy

command. However, specific flags for non-interactive mode weren't found in the current documentation excerpts. 3. Automate with Scripts: Consider writing a shell script or using a CI/CD tool to automate the execution of the

prefect deploy

command. Ensure that your environment is properly authenticated and all dependencies are resolved beforehand. 4. Environment Variables: If your deployment requires dynamic values, consider using environment variables within your

prefect.yaml

to reference these values without manual input. By ensuring that the

prefect.yaml

file is fully configured and leveraging automation tools, you can achieve a seamless, non-interactive deployment process. If additional flags or options are available, they would typically be documented in the Prefect CLI documentation.

Jackson Nguyen

01/21/2025, 1:00 AM

@Marvin I set a

schedule: {}

parameter for each of my deployments. However, Prefect still wants to prompt me for a response. How can I prevent that?

Marvin

01/21/2025, 1:00 AM

The issue you're encountering with Prefect prompting for a response despite setting

schedule: {}

in your

prefect.yaml

may be due to how Prefect handles schedules. If you set an empty schedule, Prefect might still expect some form of schedule interaction. A recent update to Prefect allows for the use of multiple schedules in the

prefect.yaml

file. Setting the

schedules

list to an empty list (

schedules: []

) will result in all schedules being removed, which should prevent any schedule-related prompts during deployment. To prevent prompts, try the following in your `prefect.yaml`:

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yaml
schedules: []

This explicitly tells Prefect that there are no schedules to apply, which should bypass any interactive schedule configuration during deployment. If this doesn't resolve the issue, consider checking for updates or patches related to this behavior in the Prefect repository or documentation. You can also refer to the related GitHub pull request for more context: Add support for multiple schedules to `prefect deploy`.

Jackson Nguyen

01/21/2025, 1:03 AM

@Marvin It appears my problem with the schedule was because the variable should be called

schedules

, and not

schedule

. This information is not updated on the documentation.

Marvin

01/21/2025, 1:03 AM

It seems that there might be some inconsistency or lack of clarity in the Prefect documentation regarding the use of

schedule

versus

schedules

in the

prefect.yaml

file. This issue might be causing confusion for users who are trying to set up their deployments without interaction. If the documentation hasn't been updated to reflect the correct usage of

schedules

, it would be beneficial to report this discrepancy to the Prefect team. You can do this by creating an issue in the Prefect GitHub repository, explaining the problem and how it affects deployment configurations. Additionally, you can keep an eye on any existing issues or discussions related to scheduling in the Prefect repository to see if there are any updates or patches that address this documentation gap. For example, you might find related discussions or issues like this one about multiple schedules. If you need any further assistance or guidance on how to proceed, feel free to ask!

Jackson Nguyen

01/21/2025, 1:08 AM

@Marvin How can I use multiple prefect.yaml files in my project? For example, I want to define different deployments in different files.

Marvin

01/21/2025, 1:09 AM

To use multiple

prefect.yaml

files in your project for defining different deployments, you can follow these steps: 1. Separate YAML Files: Create separate

prefect.yaml

files for each deployment configuration you need. Each file should contain the specific deployment details for one or more flows. 2. Deploy Individually: Use the Prefect CLI to deploy each configuration individually. You can specify which

prefect.yaml

file to use by navigating to the directory containing the desired file or by specifying the file directly if your workflow supports it. 3. Unique Deployment Names: Ensure that each deployment declaration within your

prefect.yaml

files has a unique name. This allows you to manage and deploy them individually using the CLI. 4. CLI Commands: - To deploy a specific deployment from a

prefect.yaml

file, use the

--name

flag with the deployment name:

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bash
     prefect deploy --name <deployment-name>

- To deploy all deployments from a specific file, use the

--all

flag:

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bash
     prefect deploy --all

5. Pattern Matching: You can also deploy multiple deployments that match a specific pattern using the CLI. By organizing your deployments into separate

prefect.yaml

files and using the CLI to manage them, you can maintain clear separation and control over different deployment configurations within your project.

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