chore: import upstream snapshot with attribution

tests/pyfunc/utils.py

@@ -0,0 +1,39 @@
+import json
+import os
+from typing import TYPE_CHECKING
+
+from fastapi.testclient import TestClient
+
+import mlflow
+from mlflow.pyfunc import scoring_server
+
+if TYPE_CHECKING:
+    import httpx
+
+
+def score_model_in_process(model_uri: str, data: str, content_type: str) -> "httpx.Response":
+    """Score a model using in-process FastAPI TestClient (faster than subprocess)."""
+    import pandas as pd
+
+    env_snapshot = os.environ.copy()
+    try:
+        model = mlflow.pyfunc.load_model(model_uri)
+        app = scoring_server.init(model)
+        client = TestClient(app)
+
+        # Convert DataFrame to JSON format if needed (matching RestEndpoint.invoke behavior)
+        if isinstance(data, pd.DataFrame):
+            if content_type == scoring_server.CONTENT_TYPE_CSV:
+                data = data.to_csv(index=False)
+            elif content_type == scoring_server.CONTENT_TYPE_PARQUET:
+                data = data.to_parquet()
+            else:
+                assert content_type == scoring_server.CONTENT_TYPE_JSON
+                data = json.dumps({"dataframe_split": data.to_dict(orient="split")})
+        elif not isinstance(data, (str, dict)):
+            data = json.dumps({"instances": data})
+
+        return client.post("/invocations", content=data, headers={"Content-Type": content_type})
+    finally:
+        os.environ.clear()
+        os.environ.update(env_snapshot)