@Marvin how do i build a deployment if i don’t want to use github as the method of flow code storage?

To build a deployment in Prefect 2.x without using GitHub for flow code storage, you can still use other Git-based storage options such as GitLab or Bitbucket. When you run

prefect deploy

from within a Git repository, Prefect will prompt you to create a new deployment, select your flow code entrypoint, and name your deployment. Then, it will detect if you're in a Git repository and ask if you want to store your flow code in a Git repository. You'll need to confirm the URL of your Git repository, the branch name, and whether the repository is private. If the repository is private, you will need to enter a token for access. You can reference repositories directly through interactive prompts with

prefect deploy

or specify them in a

prefect.yaml

file. For cases requiring authentication, you can use Secret or Credential blocks that can be referenced to provide the required access tokens or credentials securely. For your specific requirement, if you don't want to use GitHub or any other Git-based repository hosting provider, the documentation doesn't provide a direct excerpt answering that. However, you can use other methods like storing your flow's code in an artifact repository that Prefect can access, such as S3 or GCS, or you could use a local filesystem if the deployment is running in an environment where the local filesystem is accessible to Prefect's runtime. To set up these alternatives, you would need to ensure that your Prefect deployment environment has the correct access permissions and configurations to pull the flow code from your chosen storage solution. More detailed steps would depend on the specific storage method you choose and how you configure your Prefect environment to access that storage.

@Marvin I don’t want to use any git based storage?

If you don't want to use any Git-based storage options for your Prefect 2.x flows, you can consider using other storage options such as: 1. Local Filesystem: If your flow runs where the code resides, such as on your personal machine or a dedicated server, you can simply use the local filesystem to store your flow code. 2. Object Storage: You can host your flow code on an object storage service like Amazon S3, Google Cloud Storage, or Azure Blob Storage. Prefect can pull the flow code from these services if configured correctly. 3. Artifact Repository: Services like Artifactory or Nexus can be used to store flow code as artifacts, and Prefect can be set up to fetch the code from there. 4. Custom Solution: You can implement a custom storage solution, but you would need to ensure that your Prefect workers have the necessary logic and access to fetch flow code at runtime. When configuring a deployment that does not rely on Git-based storage, you must ensure that wherever your flow code is stored, it is accessible by your Prefect agents/workers at runtime. This might involve setting up appropriate credentials and access policies. To create a deployment with storage other than Git, you would usually define your storage configuration in the Prefect deployment spec using a

StorageBlock

, and possibly using a

RunConfig

to specify execution environment details. Then, your flow code will be uploaded or referenced in the defined storage during deployment. Prefect documentation or community forums could possibly provide more detailed steps and examples for setting up these alternatives. If you need further assistance with a specific storage method, please let me know, and I can provide additional guidance or check for recent issues or updates in the Prefect GitHub repository.

@Marvin Could I use a container to store my flow code?

Yes, you can use a container to store your flow code in Prefect 2.x. Packaging your flow code in a Docker container is a common way to ensure that your code and its runtime environment are consistent across different stages of development, testing, and production. Here's how you can use a container to store and run your flow code: 1. Containerize Your Flow: Write a Dockerfile that defines the environment for your flow. It should install all the necessary dependencies and include your flow code within the image. You can copy your flow code directly into the image or install it as part of your application. 2. Build and Push the Image: Build the Docker image and push it to a container registry such as Docker Hub, Google Container Registry, AWS Elastic Container Registry (ECR), or any other you prefer. 3. Configure Prefect to Use the Image: In your Prefect deployment, you'll specify the Docker image as the execution environment for your flow. You can do this by using a

DockerContainerBlock

in Prefect to define the container settings, including the image URL. 4. Deploy Your Flow: Deploy your Prefect flow using the Prefect CLI or UI. The deployment specification will reference the

DockerContainerBlock

that you configured. 5. Run Your Flow: When your Prefect agent (which must have access to Docker) picks up a flow run, it will pull the specified Docker image from the registry and run your flow in a containerized environment. Here's a simple example of how you might structure your Dockerfile:

Dockerfile
# Use an official Python runtime as a parent image
FROM python:3.8

# Set the working directory in the container
WORKDIR /usr/src/app

# Copy the current directory contents into the container at /usr/src/app
COPY . .

# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Run flow.py when the container launches
CMD ["python", "./flow.py"]

And an example of defining a

DockerContainerBlock

in Prefect:

python
from prefect.deployments import DeploymentSpec
from prefect.filesystems import DockerContainerBlock

docker_block = DockerContainerBlock.load("docker-block-name")

DeploymentSpec(
    flow=your_flow,
    name="example-deployment",
    execution=RunConfig(executor=DaskExecutor(), infrastructure=docker_block)
)

Please adjust the

Dockerfile

,

DockerContainerBlock

, and

DeploymentSpec

according to your actual flow, dependencies, and Prefect version since these examples are generic. This method ensures that your flow is executed in the same environment it was developed and tested in, reducing the chances of encountering unexpected runtime issues due to environment discrepancies.