aws / aws/aws-step-functions-data-science-sdk-python
Execution inputs as container arguments for processing jobs
- Dominant language
- Python
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Description
I'm trying to use execution inputs as container arguements for my processing job:
```
execution_input = ExecutionInput(
schema={
"IngestaJobName": str,
"PreprocessingJobName": str,
"InferenceJobName": str,
"Fecha": str,
}
)
```
```
#Call step
ingesta_step = ProcessingStep(
inference_config["ingesta_step_name"],
processor=ingesta_processor,
job_name=execution_input['IngestaJobName'],
inputs=inputs_ingesta,
outputs=outputs_ingesta,
container_arguments=["--fecha", "$$.Execution.Input['Fecha']"],
container_entrypoint=["python3", "/opt/ml/processing/input/code/"+inference_config["ingesta_function"]],
)
```
I've also tried to replace container_arguments for `["--fecha", execution_input["Fecha"]] `
But in both cases it doesn't work.
### Use Case
When I lunch a new execution of my state machine, it would be useful to get some execution inputs as a container argument in order to define some parameters of intereset that will be define the behaviour of the step directly by the execution input without updating the state machine definition
---
This is a :rocket: Feature Request
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