add response_to_frame function

Author: isabelizimm

vetiver/helpers.py

@@ -33,19 +33,8 @@ def _dict(pred_data):
     return api_data_to_frame([pred_data])
 
 
-# possible other names
-# prototype_to_frame
-# prototype_to_data
-# prototype_to_dataframe
-# prototype_to_datatype
-# prototype_to_type
-# api_data_to_
-# json_to_
-# server_data_to_
-# transport_data_to_
-# request
-# query
-# transit
-# interchange/exchange
-# transfer
-# through
+def response_to_frame(response: dict) -> pd.DataFrame:
+
+    response_df = pd.DataFrame.from_dict(response.json())
+
+    return response_df

vetiver/server.py

@@ -16,7 +16,7 @@
 from .utils import _jupyter_nb
 from .vetiver_model import VetiverModel
 from .meta import VetiverMeta
-from .helpers import api_data_to_frame
+from .helpers import api_data_to_frame, response_to_frame
 
 
 class VetiverAPI:
@@ -178,7 +178,11 @@ def vetiver_post(self, endpoint_fx: Callable, endpoint_name: str = None, **kw):
             async def custom_endpoint(input_data: List[self.model.prototype]):
                 _to_frame = api_data_to_frame(input_data)
                 predictions = endpoint_fx(_to_frame, **kw)
-                return {endpoint_name: predictions}
+
+                if isinstance(predictions, List):
+                    return {endpoint_name: predictions}
+                else:
+                    return predictions
 
         else:
 
@@ -187,7 +191,10 @@ async def custom_endpoint(input_data: Request):
                 served_data = await input_data.json()
                 predictions = endpoint_fx(served_data, **kw)
 
-                return {endpoint_name: predictions}
+                if isinstance(predictions, List):
+                    return {endpoint_name: predictions}
+                else:
+                    return predictions
 
     def run(self, port: int = 8000, host: str = "127.0.0.1", **kw):
         """
@@ -262,7 +269,9 @@ def predict(endpoint, data: Union[dict, pd.DataFrame, pd.Series], **kw) -> pd.Da
     # TO DO: dispatch
 
     if isinstance(data, pd.DataFrame):
-        response = requester.post(endpoint, data=data.to_json(orient="records"), **kw)
+        response = requester.post(
+            endpoint, content=data.to_json(orient="records"), **kw
+        )
     elif isinstance(data, pd.Series):
         response = requester.post(endpoint, json=[data.to_dict()], **kw)
     elif isinstance(data, dict):
@@ -279,9 +288,9 @@ def predict(endpoint, data: Union[dict, pd.DataFrame, pd.Series], **kw) -> pd.Da
             f"Could not obtain data from endpoint with error: {e}"
         )
 
-    response_df = pd.DataFrame.from_dict(response.json())
+    response_frame = response_to_frame(response)
 
-    return response_df
+    return response_frame
 
 
 def vetiver_endpoint(url: str = "http://127.0.0.1:8000/predict") -> str: