The Python here is doing exactly what it should - extracting nested data and flattening it into proper relational tables. Most of the 'Python' is actually just the return statement defining table schemas. The schema can be defined separately and reused across API calls. With such reuse the Python part would be really compact. This is the right balance between declarative config and the flexibility needed for real-world API responses. I can confirm it from my experience developing many integrations with Sequor - this approach handles real-world complexity much better than pure declarative tools.
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But there’s a gigantic multi line string in your yaml. Full of Python.
The Python here is doing exactly what it should - extracting nested data and flattening it into proper relational tables. Most of the 'Python' is actually just the return statement defining table schemas. The schema can be defined separately and reused across API calls. With such reuse the Python part would be really compact. This is the right balance between declarative config and the flexibility needed for real-world API responses. I can confirm it from my experience developing many integrations with Sequor - this approach handles real-world complexity much better than pure declarative tools.
Scroll down and you’ll see the example with raw SQL.