Merge pull request #70 from isabelizimm/wrap-rsconnect

deploy to rsconnect

Author: isabelizimm

setup.cfg

@@ -33,6 +33,7 @@ install_requires =
     nest-asyncio
     requests
     pins
+    rsconnect-python
 
 [options.extras_require]
 dev =

vetiver/__init__.py

@@ -7,7 +7,7 @@
 import importlib
 from .ptype import *
 from .vetiver_model import VetiverModel
-from .server import VetiverAPI, vetiver_endpoint
+from .server import VetiverAPI, vetiver_endpoint, predict
 from .mock import get_mock_data, get_mock_model
 from .pin_read_write import vetiver_pin_write
 from .attach_pkgs import *
@@ -18,3 +18,4 @@
 from .handlers.base import VetiverHandler
 from .handlers.sklearn import SKLearnHandler
 from .handlers.torch import TorchHandler
+from .rsconnect import deploy_rsconnect

vetiver/rsconnect.py

@@ -0,0 +1,95 @@
+import tempfile
+import typing
+from rsconnect.actions import deploy_python_fastapi
+import shutil
+import os
+
+from .write_fastapi import write_app
+
+
+def deploy_rsconnect(
+    connect_server,
+    board,
+    pin_name: str,
+    version: str = None,
+    extra_files: typing.List[str] = None,
+    new: bool = False,
+    app_id: int = None,
+    title: str = None,
+    python: str = None,
+    conda_mode: bool = False,
+    force_generate: bool = False,
+    log_callback: typing.Callable = None,
+    image: str = None,
+):
+    """Deploy to RSConnect
+
+    Parameters
+    ----------
+        connect_server: 
+            RSConnect Server
+        board: 
+            Pins board
+        pin_name: str
+            Name of pin
+        version: str
+            Version of pin
+        extra_files: typing.List[str]
+            Any extra files to include in 
+        new:
+            Force as a new deploy
+        app_id:
+            ID of an existing application to deploy new files for.
+        title: str
+            Optional title for the deploy.
+        python: str
+            Optional name of a Python executable
+        conda_mode: bool
+            Use conda to build an environment.yml
+        force_generate: bool    
+            Force generating "requirements.txt" or "environment.yml"
+        log_callback: typing.Callable
+            Callback to use to write the log to
+        image: str
+            Docker image to be specified for off-host execution
+    """
+    if board.fs.protocol == "rsc":
+        raise NotImplementedError()
+
+    if not title:
+        title = pin_name + "_vetiver"
+
+    with tempfile.TemporaryDirectory() as temp:
+        if extra_files is not None:
+            new_files = []
+            for file in extra_files:
+                filename = os.path.basename(file)
+                shutil.copyfile(file, os.path.join(temp, filename))
+                new_files = new_files + [os.path.join(temp, filename)]
+            extra_files = new_files
+                
+        tmp_app = temp + "/app.py"
+
+        write_app(
+            board=board,
+            pin_name=pin_name,
+            version=version,
+            file=tmp_app,
+            overwrite=False,
+        )
+
+        deploy_python_fastapi(
+            connect_server=connect_server,
+            directory=temp,
+            extra_files=extra_files,
+            excludes=None,
+            entry_point="app:api",
+            new=new,
+            app_id=app_id,
+            title=title,
+            python=python,
+            conda_mode=conda_mode,
+            force_generate=force_generate,
+            log_callback=log_callback,
+            image=image,
+        )

vetiver/tests/test_rsconnect.py

@@ -1,20 +1,36 @@
 import pytest
 import json
-from pins.rsconnect.fs import RsConnectFs
+import sklearn
 from pins.boards import BoardRsConnect
 
+import vetiver
+from vetiver.rsconnect import deploy_rsconnect
+
+# Load data, model
+X_df, y = vetiver.mock.get_mock_data()
+model = vetiver.mock.get_mock_model().fit(X_df, y)
+
 RSC_SERVER_URL = "http://localhost:3939"
 RSC_KEYS_FNAME = "vetiver/tests/rsconnect_api_keys.json"
 
 pytestmark = pytest.mark.rsc_test  # noqa
 
+
+def server_from_key(name):
+    from rsconnect.api import RSConnectServer
+
+    with open(RSC_KEYS_FNAME) as f:
+        api_key = json.load(f)[name]
+        return RSConnectServer(RSC_SERVER_URL, api_key)
+
 def rsc_from_key(name):
     from pins.rsconnect.api import RsConnectApi
 
     with open(RSC_KEYS_FNAME) as f:
         api_key = json.load(f)[name]
         return RsConnectApi(RSC_SERVER_URL, api_key)
 
+
 def rsc_fs_from_key(name):
     from pins.rsconnect.fs import RsConnectFs
 
@@ -29,6 +45,7 @@ def rsc_delete_user_content(rsc):
     for entry in content:
         rsc.delete_content_item(entry["guid"])
 
+
 @pytest.fixture(scope="function")
 def rsc_short():
     # tears down content after each test
@@ -37,18 +54,34 @@ def rsc_short():
     # delete any content that might already exist
     rsc_delete_user_content(fs_susan.api)
 
-    yield BoardRsConnect("", fs_susan, allow_pickle_read=True) #fs_susan.ls to list content
+    yield BoardRsConnect(
+        "", fs_susan, allow_pickle_read=True
+    )  # fs_susan.ls to list content
 
     rsc_delete_user_content(fs_susan.api)
 
-from vetiver import VetiverModel, vetiver_pin_write, mock
-import sklearn
-# Load data, model
-X_df, y = mock.get_mock_data()
-model = mock.get_mock_model().fit(X_df, y)
 
 def test_board_pin_write(rsc_short):
-    v = VetiverModel(model=model, ptype_data=X_df,
-        model_name="susan/model", versioned=None)
-    vetiver_pin_write(board=rsc_short, model=v)
+    v = vetiver.VetiverModel(
+        model=model, ptype_data=X_df, model_name="susan/model", versioned=None
+    )
+    vetiver.vetiver_pin_write(board=rsc_short, model=v)
     assert isinstance(rsc_short.pin_read("susan/model"), sklearn.dummy.DummyRegressor)
+
+@pytest.mark.xfail
+def test_deploy(rsc_short):
+    # TODO: test in Dockerfile
+    v = vetiver.VetiverModel(
+        model=model, ptype_data=X_df, model_name="susan/model", versioned=None
+    )
+
+    vetiver.vetiver_pin_write(board=rsc_short, model=v)
+    
+    deploy_rsconnect(
+        connect_server=server_from_key("susan"), 
+        board=rsc_short, 
+        pin_name="susan/model"
+    )
+    response = vetiver.predict(RSC_SERVER_URL + "/predict/", json=X_df)
+    assert response.status_code == 200, response.text
+    assert response.json() == {"prediction": [44.47, 44.47]}, response.json()