vineeth
07/03/2025, 9:22 AMMarvin
07/03/2025, 9:22 AMMarvin
07/03/2025, 9:23 AMpython
from prefect import flow, task
from prefect.variables import Variables
import os
@task
def run_dbt_command(selects, exclude, dbt_schema):
# Set the environment variable before running dbt
os.environ["ENV"] = Variables.get("ENV")
# Your existing dbt command code here
b. Using Flow-level Environment Variables:
python
@flow
def your_flow():
return run_dbt_command.with_options(
env={"ENV": "your_environment"}
).submit(selects, exclude, dbt_schema)
c. If using Deployments, you can set environment variables in your deployment configuration:
python
from prefect import flow
@flow
def your_flow():
...
if __name__ == "__main__":
your_flow.from_source(
source="<https://github.com/your/repo>",
env={"ENV": "production"}
).deploy(name="your-deployment")
3. If using Kubernetes/Helm:
Since your error mentions "from helm chart basejobTemplate", you should:
- Add the ENV variable to your Helm values.yaml:
yaml
env:
- name: ENV
value: "production" # or your desired environment
- Or modify your Helm chart's deployment/job template to include the environment variable.
4. For local development:
You can set the environment variable before running your Prefect flow:
bash
export ENV=development
prefect flow run your-flow
The best solution depends on your specific setup and requirements:
- For development/testing: Use local environment variables
- For production: Use Prefect Variables or deployment configuration
- For Kubernetes: Configure through Helm values or manifests
Remember that environment variables set at the infrastructure level (like in Kubernetes) take precedence over those set in your Prefect code.