<@ULVA73B9P> how to fix this Task run failed with ...
# marvin-ai
v
@Marvin how to fix this Task run failed with exception: Exception("dbt run failed: \x1b[0m091627 Running with dbt=1.8.3\n\x1b[0m091627 Encountered an error:\nParsing Error\n Env var required but not provided: 'ENV'\n") - Retries are exhausted Traceback (most recent call last): File "/usr/local/lib/python3.10/site-packages/prefect/task_engine.py", line 755, in run_context yield self File "/usr/local/lib/python3.10/site-packages/prefect/task_engine.py", line 1308, in run_task_sync engine.call_task_fn(txn) File "/usr/local/lib/python3.10/site-packages/prefect/task_engine.py", line 778, in call_task_fn result = call_with_parameters(self.task.fn, parameters) File "/usr/local/lib/python3.10/site-packages/prefect/utilities/callables.py", line 206, in call_with_parameters return fn(*args, **kwargs) File "/opt/prefect/dpro_mart/tasks/tasks.py", line 18, in run_dpro_mart_selects return run_dbt_command(selects, None, dbt_schema) File "/opt/prefect/common/dbt_utils.py", line 33, in run_dbt_command raise Exception(f"dbt run failed: {stdout}") Exception: dbt run failed: 091627 Running with dbt=1.8.3 091627 Encountered an error: Parsing Error Env var required but not provided: 'ENV' from helm chart basejobTemplate
m
thought for 35.7 seconds
Based on the error message and context, here's how to fix this issue: 1. The error is coming from dbt, not Prefect directly. dbt is expecting an environment variable called 'ENV' that's not being provided when the task runs. 2. There are several ways to fix this: a. Using Prefect Variables:
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python
   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:
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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:
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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:
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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:
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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.