Read "Tabular JSON" with Schema Separate from Values

Using the PythonCaller and AI Assist with a few small adjustments and an AttributeExposer (use import from data cache after running the PythonCaller), I was able to get this working for the most part. Here’s the code I used in the PythonCaller:

import fme
from fme import BaseTransformer
import fmeobjects
import json

class FeatureProcessor(BaseTransformer):
    def __init__(self):
        self.schema = None
        self.data = None

    def input(self, feature: fmeobjects.FMEFeature):
        # Parse the JSON response from the _response_body attribute
        json_response = feature.getAttribute("_response_body")
        parsed_json = json.loads(json_response)

        # Extract schema and data
        self.schema = parsed_json.get("schema", {}).get("properties", {})
        self.data = parsed_json.get("data", [])

        # Process each row in the data array
        for row in self.data:
            new_feature = fmeobjects.FMEFeature()
            for index, (key, value) in enumerate(self.schema.items()):
                column_name = value.get("title", key)  # Use the title from schema or fallback to key
                new_feature.setAttribute(column_name, row[index])

            # Output the new feature
            self.pyoutput(new_feature)

    def close(self):
        pass