bash
prefect work-pool create "your-work-pool" --type process

7. Start a Worker

bash
prefect worker start -p "your-work-pool"

8. Run Your Deployment

bash
prefect deployment run 'my-github-flow/github-deployment'

Important Notes: - Replace

your-username/your-private-repo

with your actual GitHub repository path - Update

path/to/flow_file.py

to match your actual file structure - Make sure your GitHub PAT has the necessary

repo

scope to access private repositories - The worker needs to have access to the GitHub credentials block to pull the code - Always use environment variables or secrets management for sensitive values in production The deployment will pull code from your private GitHub repository using the credentials you've configured, and the worker will execute the flow when triggered. Would you like me to explain any specific part in more detail or help you with setting up any particular step?

@Marvin your reply is truncated

Let me provide the complete guide again, with all steps and details: 1. Login to Prefect Cloud

bash
prefect cloud login

2. Install Required Package

bash
pip install prefect-github

3. Create a GitHub Personal Access Token (PAT) - Go to GitHub → Settings → Developer settings → Personal access tokens → Tokens (classic) - Create a new token with

repo

scope access - Save the token securely - you'll need it in the next step 4. Create GitHub Credentials Block

python
from prefect.blocks.system import GitHubCredentials

github_credentials = GitHubCredentials(
    access_token="your-github-pat-token"  # Replace with your actual token
)
github_credentials.save("github-credentials", overwrite=True)

5. Create Your Flow and Deployment Here's a complete example showing how to create a flow and deploy it from a private GitHub repository:

python
from prefect import flow
from prefect.deployments import Deployment

# Define your flow
@flow(name="my-github-flow")
def my_flow(name: str = "world"):
    print(f"Hello {name}!")

# Create deployment from GitHub source
deployment = my_flow.from_source(
    source="<https://github.com/your-username/your-private-repo>",
    entrypoint="path/to/flow_file.py:my_flow",  # Relative path to your flow file and function
    reference="main",  # Branch name
    credentials="github-credentials"  # Name of the saved credentials block
).deploy(
    name="github-deployment",
    work_pool_name="your-work-pool"  # Replace with your work pool name
)

6. Create a Work Pool You have several options for work pool types:

bash
# For local process-based execution
prefect work-pool create "your-work-pool" --type process

# For Docker-based execution
prefect work-pool create "your-work-pool" --type docker

# For Kubernetes-based execution
prefect work-pool create "your-work-pool" --type kubernetes

# Common options:
# --paused: Create the work pool in a paused state
# --concurrency-limit: Set maximum concurrent flow runs
# --base-job-template: Specify a custom job template file

7. Start a Worker

bash
prefect worker start -p "your-work-pool"

8. Run Your Deployment

bash
prefect deployment run 'my-github-flow/github-deployment'

Important Notes and Best Practices: 1. Repository Access - Ensure your GitHub PAT has the minimum required permissions (repo scope for private repositories) - Store the PAT securely using environment variables or secrets management - Consider using fine-grained PATs for more controlled access 2. Deployment Configuration - The

entrypoint

should point to your flow file relative to the repository root - Use the

reference

parameter to specify branch, tag, or commit SHA - Make sure all dependencies are listed in your repository's requirements.txt 3. Worker Setup - Workers need access to the GitHub credentials block - Consider using infrastructure-specific workers (Docker/Kubernetes) for production - Set appropriate concurrency limits based on your resources 4. Security Considerations - Never commit credentials or sensitive information to your repository - Use environment variables for sensitive values:

python
     import os
     github_credentials = GitHubCredentials(
         access_token=os.environ["GITHUB_ACCESS_TOKEN"]
     )

- Consider using Prefect Cloud's secrets management for production deployments 5. Debugging Tips - Check worker logs if deployments aren't running - Verify GitHub credentials have correct permissions - Ensure all required dependencies are installed in your execution environment Would you like me to elaborate on any of these steps or explain specific aspects of the setup in more detail?

@Marvin I'd like to run flows on Prefect Managed infrastructure

Here's how to set up and run flows on Prefect Managed infrastructure: 1. Login to Prefect Cloud

bash
prefect cloud login

2. Install Required Package

bash
pip install prefect-github

3. Create a GitHub Personal Access Token (PAT) - Go to GitHub → Settings → Developer settings → Personal access tokens → Tokens (classic) - Create a new token with

repo

scope access - Save the token securely 4. Create GitHub Credentials Block

python
from prefect.blocks.system import GitHubCredentials

github_credentials = GitHubCredentials(
    access_token="your-github-pat-token"  # Replace with your actual token
)
github_credentials.save("github-credentials", overwrite=True)

5. Create a Prefect Managed Work Pool

bash
prefect work-pool create "managed-pool" --type prefect-managed

6. Create Your Flow and Deployment

python
from prefect import flow
from prefect.deployments import Deployment

@flow(name="my-managed-flow")
def my_flow(name: str = "world"):
    print(f"Hello {name}!")

# Deploy the flow
deployment = my_flow.from_source(
    source="<https://github.com/your-username/your-private-repo>",
    entrypoint="path/to/flow_file.py:my_flow",  # Relative path to your flow file
    reference="main",  # Branch name
    credentials="github-credentials"  # Name of the saved credentials block
).deploy(
    name="managed-deployment",
    work_pool_name="managed-pool"
)

7. Requirements File Create a

requirements.txt

file in your repository root with all necessary dependencies:

text
prefect>=3.0.0
# Add any other dependencies your flow needs

8. Run Your Deployment

bash
prefect deployment run 'my-managed-flow/managed-deployment'

Important Notes about Prefect Managed Infrastructure: 1. Key Benefits - No need to manage your own infrastructure - Automatic scaling based on your workload - Secure and isolated execution environment - Built-in retry mechanisms and error handling 2. Pricing and Resources - Prefect Managed infrastructure is part of Prefect Cloud's paid plans - Resources are allocated based on your subscription tier - Monitor your usage in the Prefect Cloud UI 3. Best Practices - Keep your dependencies minimal and specific - Use environment variables for configuration:

python
  import os
  
  @flow
  def my_flow():
      api_key = os.environ.get("API_KEY")
      # Your flow logic here

- Set appropriate timeouts and retries for your flows 4. Limitations and Considerations - Maximum flow run duration depends on your subscription - Memory and CPU limits are based on your plan - Network access is restricted to public internet - File system access is ephemeral 5. Debugging Tips - Use the Prefect Cloud UI to monitor flow runs - Check flow run logs for detailed execution information - Set appropriate logging levels in your flows:

python
  from prefect import flow, get_run_logger

  @flow
  def my_flow():
      logger = get_run_logger()
      <http://logger.info|logger.info>("Starting flow execution")
      # Your flow logic here

Would you like me to explain any specific aspect of running flows on Prefect Managed infrastructure in more detail? For example, I can provide more information about: - Setting up environment variables - Handling secrets - Monitoring and observability - Resource management - Cost optimization

Let's go through the troubleshooting steps: 1. First, check if your deployment exists

bash
prefect deployment ls

2. If you don't see your deployment, there might be a few common issues: a. Make sure your deployment script actually ran successfully

python
   # When running your deployment script, add a print statement to confirm:
   from prefect import flow
   from prefect.deployments import Deployment

   @flow(name="my-managed-flow")
   def my_flow(name: str = "world"):
       print(f"Hello {name}!")

   deployment = my_flow.from_source(
       source="<https://github.com/your-username/your-private-repo>",
       entrypoint="path/to/flow_file.py:my_flow",
       reference="main",
       credentials="github-credentials"
   ).deploy(
       name="managed-deployment",
       work_pool_name="managed-pool"
   )
   
   print(f"Deployment created: {deployment.name}")  # Add this line

b. Verify your work pool exists and is running

bash
   prefect work-pool ls

3. Check the exact deployment name The deployment run command format is:

prefect deployment run '<flow-name>/<deployment-name>'

For example, if your: - Flow name is "my-managed-flow" - Deployment name is "managed-deployment" The command should be:

bash
prefect deployment run 'my-managed-flow/managed-deployment'

4. If you're still having issues, try creating the deployment again with more explicit naming:

python
deployment = my_flow.from_source(
    source="<https://github.com/your-username/your-private-repo>",
    entrypoint="path/to/flow_file.py:my_flow",
    reference="main",
    credentials="github-credentials"
).deploy(
    name="managed-deployment",
    work_pool_name="managed-pool",
    tags=["managed"]  # Adding tags can help with identification
)

5. Verify the deployment in the Prefect Cloud UI - Log into your Prefect Cloud account - Go to the "Deployments" section - You should see your deployment listed there 6. Common Causes of "Deployment Not Found": - Typos in the flow name or deployment name - The deployment script didn't execute successfully - The work pool doesn't exist or isn't properly configured - You're not logged into the correct Prefect Cloud workspace Could you please: 1. Run

prefect deployment ls

and share what you see? 2. Confirm if you see your deployment in the Prefect Cloud UI? 3. Share the exact command you're using to run the deployment? This will help me provide more specific guidance to resolve the issue.

If

prefect deployment ls

shows nothing, it means your deployment wasn't created successfully. Let's fix this step by step: 1. First, verify you're logged into the correct Prefect Cloud workspace

bash
prefect cloud workspace ls

2. Create a simple test deployment to verify everything works. Save this as `test_deployment.py`:

python
from prefect import flow
from prefect.deployments import Deployment

@flow(name="test-flow")
def test_flow(name: str = "world"):
    print(f"Hello {name}!")
    return "Success!"

if __name__ == "__main__":
    # Deploy the flow and print the result
    deployment = test_flow.from_source(
        source="<https://github.com/your-username/your-private-repo>",
        entrypoint="test_deployment.py:test_flow",  # This file's name and flow function
        reference="main",  # Your main branch
        credentials="github-credentials"
    ).deploy(
        name="test-deployment",
        work_pool_name="managed-pool",  # Your Prefect Managed work pool name
    )
    print(f"Deployment created with id: {deployment.id}")

3. Verify your work pool exists

bash
prefect work-pool ls

If you don't see your work pool, create it:

bash
prefect work-pool create "managed-pool" --type prefect-managed

4. Run the test deployment script

bash
python test_deployment.py

You should see output indicating the deployment was created. If you get any errors, please share them. 5. Check deployments again

bash
prefect deployment ls

If you're still not seeing any deployments, let's check for common issues: 1. Verify GitHub Credentials Block Run this in a Python interpreter:

python
from prefect.blocks.system import GitHubCredentials

# List all saved GitHub credential blocks
github_blocks = GitHubCredentials.load_all()
print([block for block in github_blocks])

2. Verify your Prefect Cloud status

bash
prefect cloud status

Could you please: 1. Try running the test deployment script above 2. Share any error messages you see 3. Confirm if

prefect cloud status

shows you're properly connected 4. Share the output of

prefect work-pool ls

This will help me identify exactly where the deployment process is failing. Also, make sure you have all the necessary packages installed:

bash
pip install prefect prefect-github

Let me know what happens after trying these steps, and we can troubleshoot further based on the results.

Ah, I see the issue! In Prefect 3.x, the GitHub credentials are now part of the

prefect-github

package, not the core Prefect package. Let me correct the code: 1. First, install the required package if you haven't already:

bash
pip install prefect-github

2. Create GitHub credentials. Save this as `create_github_block.py`:

python
from prefect_github import GitHubCredentials

# Create GitHub credentials block
github_credentials = GitHubCredentials(
    token="your-github-pat-token"  # Replace with your actual GitHub PAT
)
github_credentials.save("github-credentials", overwrite=True)

3. Create the deployment. Save this as `test_deployment.py`:

python
from prefect import flow
from prefect.deployments import Deployment
from prefect_github import GitHubCredentials

@flow(name="test-flow")
def test_flow(name: str = "world"):
    print(f"Hello {name}!")
    return "Success!"

if __name__ == "__main__":
    # Deploy the flow and print the result
    deployment = test_flow.from_source(
        source="<https://github.com/your-username/your-private-repo>",
        entrypoint="test_deployment.py:test_flow",  # This file's name and flow function
        reference="main",  # Your main branch
        credentials="github-credentials"  # Name of the block we created above
    ).deploy(
        name="test-deployment",
        work_pool_name="managed-pool",  # Your Prefect Managed work pool name
    )
    print(f"Deployment created with id: {deployment.id}")

4. Execute the scripts in order:

bash
# First, create the GitHub credentials block
python create_github_block.py

# Then create the deployment
python test_deployment.py

5. Verify the deployment was created:

bash
prefect deployment ls

If you're still having issues, please: 1. Confirm you've installed

prefect-github

successfully 2. Share any new error messages you see 3. Run

pip list | grep prefect

to show all installed Prefect packages and their versions This will help me provide more specific guidance if needed.

Ah, you're using the very latest Prefect 3.x where the deployment syntax has been updated. Let me provide the correct, updated code: 1. Install required packages:

bash
pip install prefect prefect-github

2. Create GitHub credentials. Save this as `create_github_block.py`:

python
from prefect_github import GitHubCredentials

# Create GitHub credentials block
github_credentials = GitHubCredentials(
    token="your-github-pat-token"  # Replace with your actual GitHub PAT
)
github_credentials.save("github-credentials", overwrite=True)

3. Create the deployment. Save this as `test_deployment.py`:

python
from prefect import flow
from prefect_github import GitHubCredentials

@flow(name="test-flow")
def test_flow(name: str = "world"):
    print(f"Hello {name}!")
    return "Success!"

if __name__ == "__main__":
    # Deploy the flow using the new syntax
    test_flow.deploy(
        name="test-deployment",
        work_pool_name="managed-pool",
        source="<https://github.com/your-username/your-private-repo>",
        reference="main",
        credentials="github-credentials"
    )
    print("Deployment created successfully!")

4. Create your work pool (if you haven't already):

bash
prefect work-pool create "managed-pool" --type prefect-managed

5. Execute the scripts in order:

bash
# First, create the GitHub credentials block
python create_github_block.py

# Then create the deployment
python test_deployment.py

6. Verify the deployment was created:

bash
prefect deployment ls

7. Run your deployment:

bash
prefect deployment run test-flow/test-deployment

The key changes in the new syntax are: - Using

flow.deploy()

directly instead of the old

Deployment

class - Simpler, more straightforward deployment configuration - No need to use

from_source()

as it's now integrated into the deploy method If you need to make any updates to your deployment later, you can use the same

flow.deploy()

method - it will update the existing deployment if one exists with the same name. Let me know if you run into any other issues or need clarification on any part of the process!

I apologize for the confusion earlier. Here's the correct syntax for deploying from a GitHub source: 1. Create GitHub credentials (save as

create_github_block.py

):

python
from prefect_github import GitHubCredentials

# Create GitHub credentials block
github_credentials = GitHubCredentials(
    token="your-github-pat-token"  # Replace with your actual GitHub PAT
)
github_credentials.save("github-credentials", overwrite=True)

2. Create and deploy the flow (save as

test_deployment.py

):

python
from prefect import flow
from prefect.filesystems import GitHub

@flow(name="test-flow")
def test_flow(name: str = "world"):
    print(f"Hello {name}!")
    return "Success!"

if __name__ == "__main__":
    # First, create flow from source
    flow_from_source = test_flow.from_source(
        "<https://github.com/your-username/your-private-repo>",
        reference="main",  # branch name
        credentials="github-credentials"
    )
    
    # Then deploy it
    flow_from_source.deploy(
        name="test-deployment",
        work_pool_name="managed-pool",
        job_variables={"env": {"SOME_VAR": "value"}}  # optional
    )
    print("Deployment created successfully!")

3. Create your work pool (if you haven't already):

bash
prefect work-pool create "managed-pool" --type prefect-managed

4. Execute the scripts in order:

bash
# First, create the GitHub credentials block
python create_github_block.py

# Then create the deployment
python test_deployment.py

5. Verify and run the deployment:

bash
# List deployments
prefect deployment ls

# Run the deployment
prefect deployment run test-flow/test-deployment

The key differences in this corrected version: - Using

flow.from_source()

to specify the GitHub source - Then using

deploy()

to create the deployment - Proper separation of source configuration and deployment configuration Let me know if you encounter any other issues or need clarification!

@Prefect even your own bot is so confused about the different API versions. the onboarding process for new users is so frustrating