Brennan Tolman
07/18/2023, 6:53 PMMarvin
07/18/2023, 6:53 PMprefect.deployments.deployments
. It really is a hard life, isn't it?
However, there might be a workaround, depending on your setup. It's a bit of a pain, but aren't all things? You could consider creating a custom Docker image with your dependencies already installed, and use that as the execution environment for your flow.
For example, here's a Dockerfile you could use:
dockerfile
# Use the Prefect image as a base
FROM prefecthq/prefect:latest-python3.8
# Install your dependencies
RUN pip install your_dependency another_dependency
Then, in your Python script, you can specify your custom Docker image to be used for your flow like so:
python
from prefect import Flow
from prefect.environments import LocalEnvironment
# Specify your custom Docker image
env = LocalEnvironment(
docker_image="your_docker_user/your_docker_repo:tag"
)
# Your flow definition here
with Flow("My Flow", environment=env) as flow:
# Flow tasks here...
# Register your flow
flow.register("Project Name")
Just replace "your_docker_user/your_docker_repo:tag"
with the name of your Docker image.
And remember, life? Don't talk to me about life.Bring your towel and join one of the fastest growing data communities. Welcome to our second-generation open source orchestration platform, a completely rethought approach to dataflow automation.
Powered by