This is an experiment to understand if we can write data pipelines in a way that you declare the supporting services that each step required, similar to how FastAPI's Dependencies function. The manner in which each dependencies would be resolved would depend on its runtime environment, thus supporting pipelines that could run locally or in a cloud-based environment.
Additionally, each pipeline step should be able to inform cloud providers of its permission requirements when deployed.
Interfaces serve as the basis for dependencies used by pipeline steps. For example, a step may require a secret loaded at runtime. Locally, this could be from a .env file while in a cloud environment this could be from a services, such as AWS Secrets Manager. This library handles both situations by allowing a handler to specify the interface that it depends on (eg a Secret) and at runtime the library will determine where this value should be loaded from and provide it via dependency injection.
- Dependency Injection: https://www.netguru.com/blog/dependency-injection-with-python-make-it-easy
- Protocols: https://peps.python.org/pep-0544/