Project deployment by name

Author: Daankrol

examples/README.md

@@ -138,7 +138,7 @@ This code sample shows how to get a deployment from the server.
 > geti = Geti(server_config=server_config)
 >
 > # Create deployment for the project, and prepare it for running inference
-> deployment = geti.deploy_project(PROJECT_NAME)
+> deployment = geti.deploy_project(project_name=PROJECT_NAME)
 >
 > # Save deployment on local
 > deployment.save(PATH_TO_DEPLOYMENT)

geti_sdk/geti.py

@@ -371,7 +371,7 @@ def download_project_data(
         # Download deployment
         if include_deployment:
             logging.info("Creating deployment for project...")
-            self.deploy_project(project, output_folder=target_folder)
+            self.deploy_project(project=project, output_folder=target_folder)
 
         logging.info(f"Project '{project.name}' was downloaded successfully.")
         return project
@@ -1132,7 +1132,8 @@ def upload_and_predict_video(
 
     def deploy_project(
         self,
-        project: Project,
+        project: Optional[Project] = None,
+        project_name: Optional[str] = None,
         output_folder: Optional[Union[str, os.PathLike]] = None,
         models: Optional[Sequence[BaseModel]] = None,
         enable_explainable_ai: bool = False,
@@ -1147,7 +1148,10 @@ def deploy_project(
         for each task in the project. However, it is possible to specify a particular
         model to use, by passing it in the list of `models` as input to this method.
 
-        :param project: Project object to deploy
+        :param project: Project object to deploy. Either `project` or `project_name`
+            must be specified.
+        :param project_name: Name of the project to deploy. Either `project` or
+            `project_name` must be specified.
         :param output_folder: Path to a folder on local disk to which the Deployment
             should be downloaded. If no path is specified, the deployment will not be
             saved.
@@ -1165,6 +1169,11 @@ def deploy_project(
             launch an OVMS container serving the models.
         :return: Deployment for the project
         """
+        if project is None and project_name is None:
+            raise ValueError("Either `project` or `project_name` must be specified.")
+        if project is None:
+            project = self.project_client.get_project_by_name(project_name=project_name)
+
         deployment_client = self._deployment_clients.get(project.id, None)
         if deployment_client is None:
             # Create deployment client and add to cache.

notebooks/012_post_inference_hooks.ipynb

@@ -70,7 +70,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "deployment = geti.deploy_project(PROJECT_NAME)"
+    "deployment = geti.deploy_project(project=project)"
    ]
   },
   {
@@ -101,8 +101,8 @@
    "source": [
     "import cv2\n",
     "\n",
-    "from geti_sdk.demos import EXAMPLE_IMAGE_PATH\n",
     "from geti_sdk import Visualizer\n",
+    "from geti_sdk.demos import EXAMPLE_IMAGE_PATH\n",
     "\n",
     "numpy_image = cv2.imread(EXAMPLE_IMAGE_PATH)\n",
     "numpy_rgb = cv2.cvtColor(numpy_image, cv2.COLOR_BGR2RGB)\n",

notebooks/014_asynchronous_inference.ipynb

@@ -75,7 +75,9 @@
    "source": [
     "DEPLOYMENT_FOLDER = \"deployments\"\n",
     "\n",
-    "deployment = geti.deploy_project(PROJECT_NAME, output_folder=DEPLOYMENT_FOLDER)"
+    "deployment = geti.deploy_project(\n",
+    "    project_name=PROJECT_NAME, output_folder=DEPLOYMENT_FOLDER\n",
+    ")"
    ]
   },
   {

tests/nightly/test_nightly_project.py

@@ -160,7 +160,7 @@ def test_deployment(
 
         deployment_folder = os.path.join(fxt_temp_directory, project.name)
         deployment = fxt_geti_no_vcr.deploy_project(
-            project,
+            project=project,
             output_folder=deployment_folder,
             enable_explainable_ai=True,
         )

tests/pre-merge/integration/test_geti.py

@@ -518,7 +518,7 @@ def test_deployment(
         for _ in range(n_attempts):
             try:
                 deployment = fxt_geti.deploy_project(
-                    project,
+                    project=project,
                     output_folder=deployment_folder,
                     enable_explainable_ai=True,
                 )
@@ -576,7 +576,7 @@ def test_post_inference_hooks(
         project = fxt_project_service.project
         deployment_folder = os.path.join(fxt_temp_directory, project.name)
 
-        deployment = fxt_geti.deploy_project(project)
+        deployment = fxt_geti.deploy_project(project=project)
         dataset_name = "Test hooks"
 
         # Add a GetiDataCollectionHook