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<@ULVA73B9P> how can I deploy a flow using from_so...
# ask-marvin
k
@Marvin how can I deploy a flow using from_source() function?
m
To deploy a flow using the 
from_source()
function in Prefect 3.x, you need to load your flow from a remote storage location and make it deployable. Here are the steps: 1. Use `from_source`: This function is used to load your flow from a specified source. The source can be a remote location like a GitHub repository or a URL. For example:
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python
   flow = flow.from_source(source="<https://github.com/me/myrepo.git>")
2. Deploy the Flow: After loading the flow, you can deploy it using the 
deploy()
method. You might need to specify additional arguments like 
work_pool_name
if you're using infrastructure blocks:
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python
   flow.deploy(work_pool_name="my_work_pool")
3. Storage Blocks: If you are using a storage block to load your flow code, you can pass this block to the 
from_source
method as the 
source
argument. For more detailed information, you can check the Prefect documentation on deploying flows. If you need further assistance, feel free to ask.
k
@Marvin how can do this to load the flow from S3 block in prefect?
m
To load a flow from an S3 block in Prefect, you need to use the S3 storage block, which is part of the Prefect integration libraries. Here's how you can do it: 1. Install the Prefect AWS Integration Library: Make sure you have the 
prefect-aws
library installed, as it includes the S3 block functionality.
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bash
   pip install prefect-aws
2. Register the S3 Block: If the S3 block is not automatically registered, you can manually register it using the Prefect CLI.
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bash
   prefect block register -m prefect_aws
3. Use the S3 Block in Your Flow: - First, create an S3 block in your Prefect Cloud or Server UI, specifying the necessary credentials and bucket details. - Then, in your Python code, load the flow using the 
from_source()
method with the S3 block as the source. Here's a basic example:
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python
from prefect import flow
from prefect_aws import S3Bucket

# Load your S3 storage block
s3_block = S3Bucket.load("your-s3-block-name")

# Use the block to load your flow
my_flow = flow.from_source(source=s3_block)

# Deploy the flow
my_flow.deploy(work_pool_name="my_work_pool")
For more detailed information, you can refer to the Prefect documentation on blocks.
k
@Marvin I want an example for version 2.20
m
In Prefect 2.20, you can load a flow from an S3 storage block by configuring the S3 storage block and then using it in your flow. Here's how you can do it: 1. Configure the S3 Storage Block: - You need to create an S3 storage block in Prefect, either via the Prefect UI or CLI, specifying the necessary AWS credentials and bucket details. 2. Use the S3 Storage Block in Your Flow: - Load the S3 block within your flow and use it to download or run your flow code. Here's an example of how you might set up and use an S3 storage block in a flow:
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python
from prefect import flow
from prefect_aws import S3Bucket

@flow
def my_flow():
    # Load your S3 storage block
    s3_block = S3Bucket.load("my-s3-bucket-block")
    
    # Use the block to download your flow or data
    s3_block.download(from_path="path/to/your/flow.py", to_path="local/path/flow.py")
    
    # You can then execute your flow logic here
    # For example, you might import and run the downloaded flow

if __name__ == "__main__":
    my_flow()
In this example, 
"my-s3-bucket-block"
is the name of the S3 storage block you configured. Adjust the 
from_path
and 
to_path
to match your specific S3 bucket structure and local directory. For more details, you can check the Prefect 2.x documentation on storage.
k
@Marvin I want an example for version 2.20 how to deploy a flow using from_source function
m
Here's an example of how you can deploy a flow using the 
from_source
function in Prefect 2.20. This method allows you to specify the source of your flow code from a remote repository, such as GitHub:
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python
from prefect import deploy, flow

# Define a local flow for demonstration
@flow(log_prints=True)
def local_flow():
    print("I'm a flow!")

if __name__ == "__main__":
    # Deploy a local flow
    deploy(
        local_flow.to_deployment(name="example-deploy-local-flow"),
        
        # Deploy a flow from a remote source
        flow.from_source(
            source="<https://github.com/org/repo.git>",
            entrypoint="flows.py:my_flow"
        ).to_deployment(
            name="example-deploy-remote-flow",
        ),
        
        # Specify the work pool name
        work_pool_name="my-work-pool",
    )
In this example: - The 
from_source
function is used to pull the flow code from a specified remote location at runtime. - You specify the 
source
as a URL to the GitHub repository and the 
entrypoint
as the path to the flow within the repository. - The 
deploy
function is used to deploy both a local and a remote flow to the specified 
work_pool_name
. For more details, you can refer to the Prefect deployment guide.
k
@Marvin I load the source from an S3 block
m
To deploy a flow using the 
from_source
function with an S3 block in Prefect 2.20, you can specify the S3 bucket path as the source. Here's an example:
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python
from prefect import flow

if __name__ == "__main__":
    flow.from_source(
        source="<s3://my-bucket/my-folder>",
        entrypoint="flows.py:my_flow"
    ).deploy(
        name="deployment-from-aws-flow",
        work_pool_name="my_pool"
    )
In this example: - The 
source
parameter is set to the S3 bucket path where your flow code is stored. - The 
entrypoint
specifies the path to the flow within the S3 bucket. - The 
deploy
function is used to create a deployment with the specified 
name
and 
work_pool_name
. Ensure your AWS credentials are correctly configured in your environment, as they will be auto-discovered during deployment creation. For more details on configuring S3 blocks, refer to the Prefect blocks documentation.
k
@Marvin how I can I push my flow code to S3 bucket?
m
To push your flow code to an S3 bucket in Prefect 2.20, you can use the 
s3_upload
function to upload your files. Here's a basic example of how you might achieve this:
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python
from prefect_aws.s3 import S3Bucket
from prefect.filesystems import LocalFileSystem
import os

# Configure your local file system
local_storage = LocalFileSystem(basepath="path/to/your/flow/code")

# Configure your S3 bucket
s3_bucket = S3Bucket(
    bucket_name="your-s3-bucket-name",
    credentials=AWSCredentials.load("your-aws-credentials")
)

# Upload files to S3
for file_name in os.listdir(local_storage.basepath):
    file_path = os.path.join(local_storage.basepath, file_name)
    with open(file_path, "rb") as data:
        s3_bucket.upload_from_path(file_path=file_path, key=file_name)
In this example: - You configure a 
LocalFileSystem
to specify the path where your flow code is stored locally. - An 
S3Bucket
block is configured with your bucket name and AWS credentials. - The code iterates over files in the local directory and uploads them to the specified S3 bucket using the 
upload_from_path
method. For more detailed information, refer to the Prefect AWS S3 integration documentation.
k
@Marvin I had a deploy in this way : deployment = Deployment.build_from_flow( flow=test, name="On Demand", version=version, work_queue_name="default", storage=S3.load("flow-code"), path=f"test/{version}", infrastructure=infrastructure infrastructure=infrastructure, ) and I want to convert it using from_source function
m
To convert your existing deployment using 
Deployment.build_from_flow
to use the 
from_source
function with S3 storage, you can follow this example:
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python
from prefect import flow
from prefect.infrastructure import KubernetesJob  # Replace with your actual infrastructure
from prefect_aws.s3 import S3Bucket

# Assuming 'test' is your flow and 'infrastructure' is your configured infrastructure
@flow
def test():
    # Your flow logic here
    pass

if __name__ == "__main__":
    # Use from_source to specify the S3 source
    test.from_source(
        source="<s3://your-bucket/test/{version}>",
        entrypoint="flows.py:test"  # Adjust the entrypoint as necessary
    ).deploy(
        name="On Demand",
        version="your-version",
        work_pool_name="default",
        infrastructure=infrastructure
    )
In this conversion: - Replace 
source="<s3://your-bucket/test/{version}>"
with the actual S3 path where your flow code is stored. - The 
entrypoint
should point to the specific flow within your code in the S3 bucket. - Ensure that your infrastructure setup is correctly configured as per your original deployment. This approach uses the 
from_source
method to specify the location of your flow code in S3, allowing Prefect to load it dynamically at runtime.
k
@Marvin how to upload flow code to S3?
m
To upload your flow code to an S3 bucket, you can use the 
boto3
library in Python, which is the AWS SDK for interacting with S3. Here's a simple example of how you might do this:
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python
import boto3
import os

# Configure your AWS credentials and S3 bucket
s3_client = boto3.client('s3', aws_access_key_id='YOUR_ACCESS_KEY', aws_secret_access_key='YOUR_SECRET_KEY')
bucket_name = 'your-s3-bucket-name'
local_directory = 'path/to/your/flow/code'

# Upload files to S3
for root, dirs, files in os.walk(local_directory):
    for file_name in files:
        local_path = os.path.join(root, file_name)
        s3_path = os.path.relpath(local_path, local_directory)
        
        s3_client.upload_file(local_path, bucket_name, s3_path)
        print(f"Uploaded {local_path} to {bucket_name}/{s3_path}")
### Explanation: - AWS Credentials: Ensure your AWS credentials are set up. You can either pass them directly as shown or configure them in your environment. - Local Directory: Specify the path where your flow code is located. - Upload Process: The script walks through the local directory, uploading each file to the specified S3 bucket, maintaining the directory structure. This approach allows you to automate the process of uploading your flow code to S3, making it ready for deployment using Prefect's 
from_source
function.
k
@Marvin how can define source for a S3Bucket?
m
To define a source for an S3 bucket in Prefect, you would typically use the 
S3Bucket
block from the 
prefect_aws
module. However, the specific details on how to implement this aren't available in the current documentation snippets. You can explore the Prefect Integrations Documentation for more information on how to use blocks like 
S3Bucket
. Also, it might be helpful to check the Prefect Blocks Documentation for additional guidance on defining and using blocks in Prefect. If you need further assistance with the code, feel free to ask!
k
@Marvin how can define source for flow deploy using from_source function from a S3Bucket?
m
To define a source for flow deployment using the 
from_source
function with an 
S3Bucket
, you will typically follow these steps: 1. Create an S3Bucket Block: First, you need to create an 
S3Bucket
block in Prefect. This block will handle the connection to your S3 bucket and is part of the 
prefect-aws
integration. 2. Use the 
from_source
Function: The 
from_source
function is used to specify the source of your flow code. This can be an S3 bucket, among other options like Google Cloud Storage or Azure Blob Storage. 3. Specify the S3 Path: When using an S3 bucket as a source, you will specify the path to your flow's code using the 
s3://
scheme. Here's a conceptual example of how you might set this up:
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python
from prefect.deployments import deploy
from prefect_aws import S3Bucket

# Assuming you have defined an S3Bucket block named 'my-s3-bucket'
s3_bucket = S3Bucket.load("my-s3-bucket")

# Deploying a flow from source in the S3 bucket
deployment = deploy.from_source(
    source="<s3://my-bucket/path/to/flow.py>",
    entrypoint="flow:my_flow_function"
)
In this code: - Replace 
"my-s3-bucket"
with the name of your S3 bucket block. - 
"<s3://my-bucket/path/to/flow.py>"
is the path to your flow script in the S3 bucket. - 
"flow:my_flow_function"
specifies the entry point to your flow function within the script. For more detailed guidance, you can refer to the Prefect Deployments Documentation. If you have any specific questions or need further clarification, feel free to ask!
k
@Marvin in this way I do not use the block for the deployment
m
To use an 
S3Bucket
block for deployment in Prefect, you need to create and configure the block to reference your S3 bucket. This allows Prefect to use the block as a storage location for your flow's code. Here's a general outline on how to achieve this: 1. Install and Register Prefect AWS: - Ensure you have the 
prefect-aws
library installed. - Register the blocks in 
prefect-aws
with the following command:
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bash
     prefect block register -m prefect_aws
2. Create an S3Bucket Block: - You can create an 
S3Bucket
block either through the Prefect UI or programmatically. This block will manage the connection to your S3 bucket. 3. Use the Block in Deployment: - When deploying your flow, reference the 
S3Bucket
block as the storage location. This ensures that Prefect uses the bucket to store and retrieve your flow code. Here's a conceptual example in code:
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python
from prefect.deployments import deploy
from prefect_aws import S3Bucket

# Load your S3Bucket block
s3_block = S3Bucket.load("my-s3-bucket")

# Use the S3Bucket block in your deployment
deployment = deploy.from_source(
    source=s3_block,
    entrypoint="flow:my_flow_function"
)
In this example: - 
"my-s3-bucket"
is the name of your registered 
S3Bucket
block. - The 
source
parameter in 
deploy.from_source
is set to the 
s3_block
, which handles the connection to your S3 bucket. For more detailed instructions, refer to the Prefect Deployment Documentation. If you have more questions or need further assistance, feel free to ask!
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