remove ptype attr for ptrototype

Author: isabelizimm

vetiver/pin_read_write.py

@@ -51,14 +51,20 @@ def vetiver_pin_write(board, model: VetiverModel, versioned: bool = True):
         "with vetiver.model_card()",
     )
 
+    # convert older model's ptype to prototype
+    if hasattr(model, "ptype"):
+        model.prototype = model.ptype
+
     board.pin_write(
         model.model,
         name=model.model_name,
         type="joblib",
         description=model.description,
         metadata={
             "required_pkgs": model.metadata.get("required_pkgs"),
-            "ptype": None if model.ptype is None else model.ptype().json(),
+            "ptype": None
+            if model.prototype is None
+            else model.prototype().json(),  # ptype_change
         },
         versioned=versioned,
     )

vetiver/server.py

@@ -151,11 +151,14 @@ def vetiver_post(self, endpoint_fx: Callable, endpoint_name: str = None, **kw):
         if not endpoint_name:
             endpoint_name = endpoint_fx.__name__
 
+        if hasattr(self.model, "ptype"):
+            self.model.prototype = self.model.ptype
+
         if self.check_prototype is True:
 
             @self.app.post(urljoin("/", endpoint_name), name=endpoint_name)
             async def custom_endpoint(
-                input_data: Union[self.model.ptype, List[self.model.ptype]]
+                input_data: Union[self.model.prototype, List[self.model.prototype]]
             ):
 
                 if isinstance(input_data, List):

vetiver/tests/test_build_vetiver_model.py

@@ -18,62 +18,62 @@ def test_vetiver_model_array_ptype():
     vt1 = vt.VetiverModel(
         model=model,
         prototype_data=X_array,
-        model_name="iris",
+        model_name="model",
         versioned=None,
         description=None,
         metadata=None,
     )
 
     assert vt1.model == model
-    assert isinstance(vt1.ptype.construct(), pydantic.BaseModel)
-    assert list(vt1.ptype.__fields__.values())[0].type_ == int
+    assert isinstance(vt1.prototype.construct(), pydantic.BaseModel)
+    assert list(vt1.prototype.__fields__.values())[0].type_ == int
 
 
 def test_vetiver_model_df_ptype():
     # build VetiverModel, df ptype_data
     vt2 = vt.VetiverModel(
         model=model,
         prototype_data=X_df,
-        model_name="iris",
+        model_name="model",
         versioned=None,
         description=None,
         metadata=None,
     )
 
     assert vt2.model == model
-    assert isinstance(vt2.ptype.construct(), pydantic.BaseModel)
-    assert list(vt2.ptype.__fields__.values())[0].type_ == int
+    assert isinstance(vt2.prototype.construct(), pydantic.BaseModel)
+    assert list(vt2.prototype.__fields__.values())[0].type_ == int
 
 
 def test_vetiver_model_dict_ptype():
     dict_data = {"B": 0, "C": 0, "D": 0}
     vt3 = vt.VetiverModel(
         model=model,
         prototype_data=dict_data,
-        model_name="iris",
+        model_name="model",
         versioned=None,
         description=None,
         metadata=None,
     )
 
     assert vt3.model == model
-    assert isinstance(vt3.ptype.construct(), pydantic.BaseModel)
-    assert list(vt3.ptype.__fields__.values())[0].type_ == int
+    assert isinstance(vt3.prototype.construct(), pydantic.BaseModel)
+    assert list(vt3.prototype.__fields__.values())[0].type_ == int
 
 
 def test_vetiver_model_no_ptype():
     # build VetiverModel, no ptype
     vt4 = vt.VetiverModel(
         model=model,
         prototype_data=None,
-        model_name="iris",
+        model_name="model",
         versioned=None,
         description=None,
         metadata=None,
     )
 
     assert vt4.model == model
-    assert vt4.ptype is None
+    assert vt4.prototype is None
 
 
 def test_vetiver_model_from_pin():
@@ -91,5 +91,5 @@ def test_vetiver_model_from_pin():
     v2 = vt.VetiverModel.from_pin(board, "model")
     assert isinstance(v2, vt.VetiverModel)
     assert isinstance(v2.model, sklearn.base.BaseEstimator)
-    assert isinstance(v2.ptype.construct(), pydantic.BaseModel)
+    assert isinstance(v2.prototype.construct(), pydantic.BaseModel)
     board.pin_delete("model")

vetiver/tests/test_custom_handler.py

@@ -40,7 +40,7 @@ def test_custom_vetiver_model():
 
     assert v.description == "A regression model for testing purposes"
     assert isinstance(v.model, sklearn.dummy.DummyRegressor)
-    assert isinstance(v.ptype.construct(), pydantic.BaseModel)
+    assert isinstance(v.prototype.construct(), pydantic.BaseModel)
 
 
 def test_custom_vetiver_model_no_ptype():
@@ -58,4 +58,4 @@ def test_custom_vetiver_model_no_ptype():
 
     assert v.description == "A regression model for testing purposes"
     assert isinstance(v.model, sklearn.dummy.DummyRegressor)
-    assert isinstance(v.ptype.construct(), pydantic.BaseModel)
+    assert isinstance(v.prototype.construct(), pydantic.BaseModel)

vetiver/vetiver_model.py

@@ -84,7 +84,7 @@ def __init__(
         translator = create_handler(model, prototype_data)
 
         self.model = translator.model
-        self.ptype = translator.construct_ptype()
+        self.prototype = translator.construct_ptype()
         self.model_name = model_name
         self.description = description if description else translator.describe()
         self.versioned = versioned