@Marvin I am using the .deploy() method, and set the "env" field on my job_variables argument. To access the job variables inside my flow, is it sufficient to use os.environ.get()?

When you set the "env" field in the

job_variables

argument of the

.deploy()

method, these variables are indeed accessible within your flow using

os.environ.get()

. This is because Prefect sets the specified job variables as environment variables for the flow run. Here's a concise overview: - Job variables specified in the deployment (using the

job_variables

argument) are set as environment variables during the flow execution. - You can access them in your flow using standard Python methods like

os.environ.get('YOUR_VARIABLE_NAME')

. For more detailed information, you can refer to the Prefect documentation on customizing deployments. Additionally, be aware of some changes in Prefect 3.x, such as the replacement of agents with workers and the use of work pools. More details about these changes can be found in the Prefect 3.x gotchas. If you need to explore further, the top-level API of Prefect includes methods like

deploy

,

flow

, and

task

, which might be useful for your tasks.

@Marvin I tried to deploy my flow by adding the job_variables. I sent a value in my env as a bool value False, but I am getting an error for not following the deployment schema. What types of values are allowed?

In Prefect deployments, job variables—when specified in the

env

field—are expected to be strings. This means that if you try to pass a boolean value like

False

, it will not adhere to the deployment schema, which is why you're encountering an error. To resolve this, you should convert boolean values to strings. For example, you can use

"False"

instead of

False

. This conversion ensures compatibility with the deployment schema. For more information, you can refer to the Prefect documentation on customizing deployments.