Update model description -> commit_message

Author: whoseoyster

CHANGELOG.md

@@ -13,6 +13,8 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 * Deprecates `categorical_features_map` in favor of `categorical_feature_names` for model and dataset uploads.
 * Added a convenience method `create_or_load_project` which loads in a project in if it is already created.
 * Moved `TaskType` attribute from the `Model` level to the `Project` level. Creating a `Project` now requires specifying the `TaskType`.
+* Removed `name` from `add_dataset`.
+* Changed `description` to `commit_message` from `add_dataset`, `add_dataframe` and `add_model`.
 
 ## [0.2.0a1]
 

examples/tabular-classification/churn-classifier/churn-classifier-sklearn.ipynb

@@ -233,31 +233,32 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
     "from unboxapi.tasks import TaskType\n",
     "\n",
-    "# Comment this out and uncomment the next section to load the project\n",
-    "project = client.create_project(\n",
+    "project = client.create_or_load_project(\n",
     "    name=\"Banking Churn Project\",\n",
     "    description=\"Project for Predicting Banking Churn\",\n",
     "    task_type=TaskType.TabularClassification,\n",
-    ")\n",
-    "'''\n",
-    "# Use this for loading the project on subsequent runs\n",
-    "project = client.load_project(\n",
-    "    name=\"Banking Churn Project\"\n",
-    ")\n",
-    "'''\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d19865ca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "dataset = project.add_dataframe(\n",
     "    df=x_val,\n",
     "    class_names=class_names,\n",
     "    label_column_name='churn',\n",
-    "    name=\"Churn Validation\",\n",
-    "    description='this is my churn dataset',\n",
+    "    commit_message='first version',\n",
     "    task_type=TaskType.TabularClassification,\n",
     "    feature_names=feature_names,\n",
     "    categorical_feature_names=[\"Gender\", \"Geography\"],\n",
-    ")"
+    ")\n",
+    "dataset.to_dict()"
    ]
   },
   {
@@ -273,7 +274,7 @@
     "    model_type=ModelType.sklearn,\n",
     "    class_names=class_names,\n",
     "    name='Churn Classifier',\n",
-    "    description='this is my churn classification model',\n",
+    "    commit_message='first version',\n",
     "    feature_names=feature_names,\n",
     "    train_sample_df=x_train[:3000],\n",
     "    train_sample_label_column_name='churn',\n",
@@ -284,22 +285,6 @@
     ")\n",
     "model.to_dict()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "74cae32f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b4ecb0cf",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -318,7 +303,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,

unboxapi/__init__.py

@@ -99,7 +99,7 @@ def add_model(
         setup_script: Optional[str] = None,
         custom_model_code: Optional[str] = None,
         dependent_dir: Optional[str] = None,
-        description: str = None,
+        commit_message: str = None,
         project_id: str = None,
         **kwargs,
     ) -> Model:
@@ -152,7 +152,7 @@ def add_model(
         dependent_dir : str, default None
             Path to a dir of file dependencies needed to load the model. Required if your ``model_type``
             is :obj:`ModelType.custom`.
-        description : str, default None
+        commit_message : str, default None
             Commit message for this version.
         **kwargs
             Any additional keyword args you would like to pass to your ``predict_proba`` function.
@@ -447,7 +447,7 @@ def add_model(
                     endpoint = f"projects/{project_id}/ml-models"
                     payload = dict(
                         name=name,
-                        description=description,
+                        commitMessage=commit_message,
                         classNames=class_names,
                         architectureType=model_type.name,
                         kwargs=list(kwargs.keys()),