ptype_data to prototype_data

isabelizimm · isabelizimm · commit 0143698257c1 · 2022-12-08T10:34:10.000-05:00
diff --git a/vetiver/pin_read_write.py b/vetiver/pin_read_write.py
@@ -38,7 +38,7 @@ def vetiver_pin_write(board, model: VetiverModel, versioned: bool = True):
     >>> model_board = board_temp(versioned = True, allow_pickle_read = True)
     >>> X, y = vetiver.get_mock_data()
     >>> model = vetiver.get_mock_model().fit(X, y)
-    >>> v = vetiver.VetiverModel(model = model, model_name = "my_model", ptype_data = X)
+    >>> v = vetiver.VetiverModel(model, "my_model", prototype_data = X)
     >>> vetiver.vetiver_pin_write(model_board, v)
     """
     if not board.allow_pickle_read:
diff --git a/vetiver/ptype.py b/vetiver/ptype.py
@@ -80,7 +80,7 @@ def vetiver_create_ptype(data):
 @vetiver_create_ptype.register
 def _(data: pd.DataFrame):
     """
-    Create ptype for a pandas dataframe
+    Create input data prototype for a pandas dataframe
 
     Parameters
     ----------
@@ -124,7 +124,7 @@ def _(data: pd.DataFrame):
 @vetiver_create_ptype.register
 def _(data: np.ndarray):
     """
-    Create ptype for a numpy array
+    Create input data prototype for a numpy array
 
     Parameters
     ----------
@@ -163,7 +163,7 @@ def _item(value):
 @vetiver_create_ptype.register
 def _(data: dict):
     """
-    Create ptype for a dict
+    Create input data prototype for a dict
 
     Parameters
     ----------
@@ -176,7 +176,7 @@ def _(data: dict):
 @vetiver_create_ptype.register
 def _(data: BaseModel):
     """
-    Create ptype for a pydantic BaseModel object
+    Create input data prototype for a pydantic BaseModel object
 
     Parameters
     ----------
@@ -189,7 +189,7 @@ def _(data: BaseModel):
 @vetiver_create_ptype.register
 def _(data: NoneType):
     """
-    Create ptype for None
+    Create input data prototype for None
 
     Parameters
     ----------
diff --git a/vetiver/rsconnect.py b/vetiver/rsconnect.py
@@ -67,7 +67,7 @@ def deploy_rsconnect(
     >>> model = vetiver.get_mock_model().fit(X, y)
     >>> v = vetiver.VetiverModel(model = model,
     ...    model_name = "my_model",
-    ...    ptype_data = X)
+    ...    prototype_data = X)
     >>> vetiver.deploy_rsconnect(
     ...    connect_server = connect_server,
     ...    board = board,
diff --git a/vetiver/server.py b/vetiver/server.py
@@ -27,11 +27,11 @@ class VetiverAPI:
 
     Example
     -------
-    >>> import vetiver
-    >>> X, y = vetiver.get_mock_data()
-    >>> model = vetiver.get_mock_model().fit(X, y)
-    >>> v = vetiver.VetiverModel(model = model, model_name = "my_model", ptype_data = X)
-    >>> v_api = vetiver.VetiverAPI(model = v, check_ptype = True)
+    >>> import vetiver as vt
+    >>> X, y = vt.get_mock_data()
+    >>> model = vt.get_mock_model().fit(X, y)
+    >>> v = vt.VetiverModel(model = model, model_name = "my_model", prototype_data = X)
+    >>> v_api = vt.VetiverAPI(model = v, check_ptype = True)
     """
 
     app = None
@@ -129,7 +129,7 @@ def vetiver_post(self, endpoint_fx: Callable, endpoint_name: str = None, **kw):
         >>> import vetiver as vt
         >>> X, y = vt.get_mock_data()
         >>> model = vt.get_mock_model().fit(X, y)
-        >>> v = vt.VetiverModel(model = model, model_name = "model", ptype_data = X)
+        >>> v = vt.VetiverModel(model = model, model_name = "model", prototype_data = X)
         >>> v_api = vt.VetiverAPI(model = v, check_ptype = True)
         >>> def sum_values(x):
         ...     return x.sum()
@@ -175,11 +175,11 @@ def run(self, port: int = 8000, host: str = "127.0.0.1", **kw):
 
         Example
         -------
-        >>> import vetiver
-        >>> X, y = vetiver.get_mock_data()
-        >>> model = vetiver.get_mock_model().fit(X, y)
-        >>> v = vetiver.VetiverModel(model = model, model_name = "model", ptype_data = X)
-        >>> v_api = vetiver.VetiverAPI(model = v, check_ptype = True)
+        >>> import vetiver as vt
+        >>> X, y = vt.get_mock_data()
+        >>> model = vt.get_mock_model().fit(X, y)
+        >>> v = vt.VetiverModel(model = model, model_name = "model", prototype_data = X)
+        >>> v_api = vt.VetiverAPI(model = v, check_ptype = True)
         >>> v_api.run()     # doctest: +SKIP
         """
         _jupyter_nb()
diff --git a/vetiver/tests/test_add_endpoint.py b/vetiver/tests/test_add_endpoint.py
@@ -15,7 +15,7 @@ def vetiver_model():
     model = mock.get_mock_model().fit(X, y)
     v = VetiverModel(
         model=model,
-        ptype_data=X,
+        prototype_data=X,
         model_name="my_model",
         versioned=None,
         description="A regression model for testing purposes",
diff --git a/vetiver/tests/test_build_api.py b/vetiver/tests/test_build_api.py
@@ -7,7 +7,7 @@ def _build_v():
     model = mock.get_mock_model().fit(X, y)
     v = VetiverModel(
         model=model,
-        ptype_data=X,
+        prototype_data=X,
         model_name="my_model",
         versioned=None,
         description="A regression model for testing purposes",
diff --git a/vetiver/tests/test_build_vetiver_model.py b/vetiver/tests/test_build_vetiver_model.py
@@ -17,7 +17,7 @@ def test_vetiver_model_array_ptype():
     # build VetiverModel, no ptype
     vt1 = vt.VetiverModel(
         model=model,
-        ptype_data=X_array,
+        prototype_data=X_array,
         model_name="iris",
         versioned=None,
         description=None,
@@ -33,7 +33,7 @@ def test_vetiver_model_df_ptype():
     # build VetiverModel, df ptype_data
     vt2 = vt.VetiverModel(
         model=model,
-        ptype_data=X_df,
+        prototype_data=X_df,
         model_name="iris",
         versioned=None,
         description=None,
@@ -49,7 +49,7 @@ def test_vetiver_model_dict_ptype():
     dict_data = {"B": 0, "C": 0, "D": 0}
     vt3 = vt.VetiverModel(
         model=model,
-        ptype_data=dict_data,
+        prototype_data=dict_data,
         model_name="iris",
         versioned=None,
         description=None,
@@ -65,7 +65,7 @@ def test_vetiver_model_no_ptype():
     # build VetiverModel, no ptype
     vt4 = vt.VetiverModel(
         model=model,
-        ptype_data=None,
+        prototype_data=None,
         model_name="iris",
         versioned=None,
         description=None,
@@ -80,7 +80,7 @@ def test_vetiver_model_from_pin():
 
     v = vt.VetiverModel(
         model=model,
-        ptype_data=X_df,
+        prototype_data=X_df,
         model_name="model",
         versioned=None,
         description=None,
diff --git a/vetiver/tests/test_custom_handler.py b/vetiver/tests/test_custom_handler.py
@@ -6,8 +6,8 @@
 
 
 class CustomHandler(BaseHandler):
-    def __init__(self, model, ptype_data):
-        super().__init__(model, ptype_data)
+    def __init__(self, model, prototype_data):
+        super().__init__(model, prototype_data)
 
     model_type = staticmethod(lambda: sklearn.dummy.DummyRegressor)
 
@@ -32,7 +32,7 @@ def test_custom_vetiver_model():
 
     v = VetiverModel(
         model=custom_handler,
-        ptype_data=X,
+        prototype_data=X,
         model_name="my_model",
         versioned=None,
         description="A regression model for testing purposes",
@@ -50,7 +50,7 @@ def test_custom_vetiver_model_no_ptype():
 
     v = VetiverModel(
         model=custom_handler,
-        ptype_data=X,
+        prototype_data=X,
         model_name="my_model",
         versioned=None,
         description="A regression model for testing purposes",
diff --git a/vetiver/tests/test_no_handler.py b/vetiver/tests/test_no_handler.py
@@ -9,7 +9,7 @@ def test_not_implemented_error():
     with pytest.raises(InvalidModelError):
         VetiverModel(
             model=y,
-            ptype_data=X,
+            prototype_data=X,
             model_name="my_model",
             versioned=None,
             description="A regression model for testing purposes",
diff --git a/vetiver/tests/test_pin_write.py b/vetiver/tests/test_pin_write.py
@@ -12,14 +12,18 @@
 
 
 def test_board_pin_write_error():
-    v = VetiverModel(model=model, ptype_data=X_df, model_name="model", versioned=None)
+    v = VetiverModel(
+        model=model, prototype_data=X_df, model_name="model", versioned=None
+    )
     board = pins.board_temp()
     with pytest.raises(NotImplementedError):
         vetiver_pin_write(board=board, model=v)
 
 
 def test_board_pin_write():
-    v = VetiverModel(model=model, ptype_data=X_df, model_name="model", versioned=None)
+    v = VetiverModel(
+        model=model, prototype_data=X_df, model_name="model", versioned=None
+    )
     board = pins.board_temp(allow_pickle_read=True)
     vetiver_pin_write(board=board, model=v)
     assert isinstance(board.pin_read("model"), sklearn.dummy.DummyRegressor)
diff --git a/vetiver/tests/test_ping_server.py b/vetiver/tests/test_ping_server.py
@@ -7,7 +7,7 @@ def _start_application():
     model = mock.get_mock_model().fit(X, y)
     v = VetiverModel(
         model=model,
-        ptype_data=X,
+        prototype_data=X,
         model_name="my_model",
         versioned=None,
         description="A regression model for testing purposes",
diff --git a/vetiver/tests/test_predict.py b/vetiver/tests/test_predict.py
@@ -16,7 +16,7 @@ def vetiver_model():
     model = mock.get_mock_model().fit(X, y)
     v = VetiverModel(
         model=model,
-        ptype_data=X,
+        prototype_data=X,
         model_name="my_model",
         versioned=None,
         description="A regression model for testing purposes",
diff --git a/vetiver/tests/test_pytorch.py b/vetiver/tests/test_pytorch.py
@@ -45,7 +45,7 @@ def test_vetiver_build():
 
     vt2 = VetiverModel(
         model=torch_model,
-        ptype_data=x_train,
+        prototype_data=x_train,
         model_name="torch",
         versioned=None,
         description=None,
@@ -58,7 +58,7 @@ def test_vetiver_build():
 def test_torch_predict_ptype():
     torch.manual_seed(3)
     x_train, torch_model = _build_torch_v()
-    v = VetiverModel(torch_model, model_name="torch", ptype_data=x_train)
+    v = VetiverModel(torch_model, model_name="torch", prototype_data=x_train)
     v_api = VetiverAPI(v)
 
     client = TestClient(v_api.app)
@@ -72,7 +72,7 @@ def test_torch_predict_ptype():
 def test_torch_predict_ptype_batch():
     torch.manual_seed(3)
     x_train, torch_model = _build_torch_v()
-    v = VetiverModel(torch_model, model_name="torch", ptype_data=x_train)
+    v = VetiverModel(torch_model, model_name="torch", prototype_data=x_train)
     v_api = VetiverAPI(v)
 
     client = TestClient(v_api.app)
@@ -88,7 +88,7 @@ def test_torch_predict_ptype_batch():
 def test_torch_predict_ptype_error():
 
     x_train, torch_model = _build_torch_v()
-    v = VetiverModel(torch_model, model_name="torch", ptype_data=x_train)
+    v = VetiverModel(torch_model, model_name="torch", prototype_data=x_train)
     v_api = VetiverAPI(v)
 
     client = TestClient(v_api.app)
diff --git a/vetiver/tests/test_rsconnect.py b/vetiver/tests/test_rsconnect.py
@@ -66,7 +66,7 @@ def test_deploy(rsc_short):
     X_df, y = vetiver.mock.get_mock_data()
     model = vetiver.mock.get_mock_model().fit(X_df, y)
 
-    v = vetiver.VetiverModel(model=model, ptype_data=X_df, model_name="susan/model")
+    v = vetiver.VetiverModel(model=model, prototype_data=X_df, model_name="susan/model")
 
     board = pins.board_rsconnect(
         server_url=RSC_SERVER_URL, api_key=get_key("susan"), allow_pickle_read=True
diff --git a/vetiver/tests/test_sklearn.py b/vetiver/tests/test_sklearn.py
@@ -9,7 +9,7 @@ def _start_application(save_ptype: bool = True):
     model = mock.get_mock_model().fit(X, y)
     v = VetiverModel(
         model=model,
-        ptype_data=X if save_ptype else None,
+        prototype_data=X if save_ptype else None,
         model_name="my_model",
         versioned=None,
         description="A regression model for testing purposes",
diff --git a/vetiver/tests/test_write_app.py b/vetiver/tests/test_write_app.py
@@ -10,7 +10,7 @@
 def test_write_app():
     file = "app.py"
     v = vetiver.VetiverModel(
-        model=model, ptype_data=X_df, model_name="model", versioned=None
+        model=model, prototype_data=X_df, model_name="model", versioned=None
     )
     model_board = pins.board_folder(path=".", versioned=True, allow_pickle_read=True)
     vetiver.vetiver_pin_write(board=model_board, model=v)
diff --git a/vetiver/vetiver_model.py b/vetiver/vetiver_model.py
@@ -1,5 +1,5 @@
 import json
-
+from warnings import warn
 from vetiver.handlers.base import create_handler
 from .meta import _model_meta
 
@@ -27,8 +27,10 @@ class VetiverModel:
         A trained model, such as an sklearn or torch model
     model_name : string
         Model name or ID
-    ptype_data : pd.DataFrame, np.array
+    prototype_data : pd.DataFrame, np.array
         Sample of data model should expect when it is being served
+    ptype_data : pd.DataFrame, np.array
+        Deprecated, in favor of prototype_data
     versioned :
         Should the model be versioned when created?
     description : str
@@ -54,7 +56,7 @@ class VetiverModel:
     >>> from vetiver import mock, VetiverModel
     >>> X, y = mock.get_mock_data()
     >>> model = mock.get_mock_model().fit(X, y)
-    >>> v = VetiverModel(model = model, model_name = "my_model", ptype_data = X)
+    >>> v = VetiverModel(model = model, model_name = "my_model", prototype_data = X)
     >>> v.description
     "Scikit-learn <class 'sklearn.dummy.DummyRegressor'> model"
     """
@@ -63,13 +65,23 @@ def __init__(
         self,
         model,
         model_name: str,
+        prototype_data=None,
         ptype_data=None,
         versioned=None,
         description: str = None,
         metadata: dict = None,
         **kwargs
     ):
-        translator = create_handler(model, ptype_data)
+        if ptype_data is not None:
+            prototype_data = ptype_data
+            warn(
+                "argument for saving input data prototype has changed to\
+             `save_prototype`, from `save_ptype",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+
+        translator = create_handler(model, prototype_data)
 
         self.model = translator.model
         self.ptype = translator.construct_ptype()
@@ -99,7 +111,7 @@ def from_pin(cls, board, name: str, version: str = None):
                 url=meta.local.get("url"),  # None all the time, besides Connect
                 required_pkgs=meta.user.get("required_pkgs"),
             ),
-            ptype_data=json.loads(meta.user.get("ptype"))
+            prototype_data=json.loads(meta.user.get("ptype"))
             if meta.user.get("ptype")
             else None,
             versioned=True,
diff --git a/vetiver/write_docker.py b/vetiver/write_docker.py
@@ -56,7 +56,7 @@ def write_docker(
     >>> board = pins.board_temp(allow_pickle_read=True)
     >>> X, y = vetiver.get_mock_data()
     >>> model = vetiver.get_mock_model().fit(X, y)
-    >>> v = vetiver.VetiverModel(model = model, model_name = "my_model", ptype_data = X)
+    >>> v = vetiver.VetiverModel(model, "my_model", prototype_data = X)
     >>> vetiver.vetiver_pin_write(board, v)
     >>> vetiver.write_app(board,
     ...     "my_model",
diff --git a/vetiver/write_fastapi.py b/vetiver/write_fastapi.py
@@ -76,7 +76,7 @@ def write_app(
     >>> board = pins.board_temp(allow_pickle_read=True)
     >>> X, y = vetiver.get_mock_data()
     >>> model = vetiver.get_mock_model().fit(X, y)
-    >>> v = vetiver.VetiverModel(model = model, model_name = "my_model", ptype_data = X)
+    >>> v = vetiver.VetiverModel(model, "my_model", prototype_data = X)
     >>> vetiver.vetiver_pin_write(board, v)
     >>> vetiver.write_app(board,
     ...     "my_model",
