Client side changes to support tasktype being a property of projects now

CHANGELOG.md

@@ -11,6 +11,8 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 
 * Models and datasets must be added to projects. Added a `Project` helper class.
 * 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`.
 
 ## [0.2.0a1]
 

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

@@ -233,20 +233,21 @@
  "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",
  " name=\"Banking Churn Project\",\n",
- " description=\"Project for predicting Banking Churn\"\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",
  "dataset = project.add_dataframe(\n",
  " df=x_val,\n",
  " class_names=class_names,\n",
@@ -270,7 +271,6 @@
  " function=predict_proba, \n",
  " model=sklearn_model,\n",
  " model_type=ModelType.sklearn,\n",
- " task_type=TaskType.TabularClassification,\n",
  " class_names=class_names,\n",
  " name='Churn Classifier',\n",
  " description='this is my churn classification model',\n",
@@ -292,6 +292,14 @@
  "metadata": {},
  "outputs": [],
  "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b4ecb0cf",
+ "metadata": {},
+ "outputs": [],
+ "source": []
  }
  ],
  "metadata": {

examples/tabular-classification/fetal-health/fetal-health-sklearn.ipynb

@@ -182,7 +182,8 @@
  "# Comment this out and uncomment the next section to load the project\n",
  "project = client.create_project(\n",
  " name=\"Sklearn Fetal Health Project\",\n",
- " description=\"Project for predicting fetal health\"\n",
+ " description=\"Project for predicting fetal health\",\n",
+ " task_type=TaskType.TabularClassification\n",
  ")\n",
  "\n",
  "# Use this for loading the project on subsequent runs\n",
@@ -214,7 +215,6 @@
  " function=predict_proba, \n",
  " model=clf,\n",
  " model_type=ModelType.sklearn,\n",
- " task_type=TaskType.TabularClassification,\n",
  " class_names=class_names,\n",
  " name='Fetal Classifier - N3',\n",
  " description='this is my second tabular classification model',\n",

examples/tabular-classification/fraud-detection/fraud-classifier-sklearn.ipynb

@@ -253,7 +253,8 @@
  "# Comment this out and uncomment the next section to load the project\n",
  "project = client.create_project(\n",
  " name=\"Sklearn Fraud Classifier\",\n",
- " description=\"Project for Classifying Fraud\"\n",
+ " description=\"Project for Classifying Fraud\",\n",
+ " task_type=TaskType.TabularClassification\n",
  ")\n",
  "\n",
  "# Use this for loading the project on subsequent runs\n",
@@ -287,7 +288,6 @@
  " function=predict_proba, \n",
  " model=sklearn_model,\n",
  " model_type=ModelType.sklearn,\n",
- " task_type=TaskType.TabularClassification,\n",
  " class_names=class_names,\n",
  " name='Fraud detection',\n",
  " description='this is my fraud classification model',\n",

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

@@ -157,7 +157,8 @@
  "# Comment this out and uncomment the next section to load the project\n",
  "project = client.create_project(\n",
  " name=\"Sklearn Iris Tabular\",\n",
- " description=\"Project for Iris Tabular data\"\n",
+ " description=\"Project for Iris Tabular data\",\n",
+ " task_type=TaskType.TabularClassification,\n",
  ")\n",
  "\n",
  "# Use this for loading the project on subsequent runs\n",
@@ -189,7 +190,6 @@
  " function=predict_proba, \n",
  " model=classifiers['L1 logistic'],\n",
  " model_type=ModelType.sklearn,\n",
- " task_type=TaskType.TabularClassification,\n",
  " class_names=class_names,\n",
  " name='Iris - L1 Logistic',\n",
  " description='this is my first tabular classification model',\n",

examples/text-classification/fasttext/fasttext.ipynb

@@ -179,7 +179,8 @@
  "# Comment this out and uncomment the next section to load the project\n",
  "project = client.create_project(\n",
  " name=\"Fasttext Demo\",\n",
- " description=\"Fasttext Demo Project\"\n",
+ " description=\"Fasttext Demo Project\",\n",
+ " task_type=TaskType.TextClassification,\n",
  ")\n",
  "\n",
  "# Use this for loading the project on subsequent runs\n",
@@ -193,7 +194,6 @@
  " function=get_predictions, \n",
  " model=model,\n",
  " model_type=ModelType.fasttext,\n",
- " task_type=TaskType.TextClassification,\n",
  " class_names=class_names,\n",
  " name='Cooking Fast Text',\n",
  " description='this is my fasttext model',\n",

examples/text-classification/sklearn/banking/demo-banking.ipynb

@@ -197,7 +197,8 @@
  "# Comment this out and uncomment the next section to load the project\n",
  "project = client.create_project(\n",
  " name=\"Sklearn Banking Project\",\n",
- " description=\"Project to Demo Sklearn with Unbox\"\n",
+ " description=\"Project to Demo Sklearn with Unbox\",\n",
+ " task_type=TaskType.TextClassification,\n",
  ")\n",
  "\n",
  "# Use this for loading the project on subsequent runs\n",
@@ -211,7 +212,6 @@
  " function=predict_function, \n",
  " model=model,\n",
  " model_type=ModelType.sklearn,\n",
- " task_type=TaskType.TextClassification,\n",
  " class_names=label_list,\n",
  " name='Banking Model',\n",
  " description='this is my sklearn banking model'\n",

examples/text-classification/sklearn/stacked-models/fastttext-stacked.ipynb

@@ -225,7 +225,8 @@
  "# Comment this out and uncomment the next section to load the project\n",
  "project = client.create_project(\n",
  " name=\"Fasttext Stacked Model\",\n",
- " description=\"Project to Demo Fasttext Stacked\"\n",
+ " description=\"Project to Demo Fasttext Stacked\",\n",
+ " task_type=TaskType.TextClassification,\n",
  ")\n",
  "\n",
  "# Use this for loading the project on subsequent runs\n",
@@ -257,7 +258,6 @@
  " dependent_dir=folder_name,\n",
  " custom_model_code=custom_model_code,\n",
  " model_type=ModelType.custom,\n",
- " task_type=TaskType.TextClassification,\n",
  " class_names=all_class_names,\n",
  " requirements_txt_file=\"./requirements.txt\",\n",
  " name='Stacked model',\n",

examples/text-classification/transformers/transformers.ipynb

@@ -126,7 +126,8 @@
  "# Comment this out and uncomment the next section to load the project\n",
  "project = client.create_project(\n",
  " name=\"Transformer Demo Project\",\n",
- " description=\"Project to Demo Transformers with Unbox\"\n",
+ " description=\"Project to Demo Transformers with Unbox\",\n",
+ " task_type=TaskType.TextClassification,\n",
  ")\n",
  "\n",
  "# Use this for loading the project on subsequent runs\n",
@@ -140,7 +141,6 @@
  " function=predict_proba, \n",
  " model=model,\n",
  " model_type=ModelType.transformers,\n",
- " task_type=TaskType.TextClassification,\n",
  " class_names=['negative', 'positive'],\n",
  " name='transformers.sentiment_analyzer',\n",
  " description='this is my transformers sentiment model',\n",

unboxapi/__init__.py

@@ -1,23 +1,23 @@
 import csv
 import os
-import pandas as pd
 import shutil
 import tarfile
 import tempfile
 import uuid
-
 from enum import Enum
+from typing import Dict, List, Optional
 
-from .api import Api
+import pandas as pd
 from bentoml.saved_bundle.bundler import _write_bento_content_to_dir
 from bentoml.utils.tempdir import TempDirectory
-from .exceptions import UnboxException, UnboxInvalidRequest
-from .models import Model, ModelType, create_template_model
+
+from .api import Api
 from .datasets import Dataset
-from .tasks import TaskType
-from typing import Dict, List, Optional
+from .exceptions import UnboxDuplicateTask, UnboxException, UnboxInvalidRequest
+from .models import Model, ModelType, create_template_model
 from .projects import Project
-from .version import __version__
+from .tasks import TaskType
+from .version import __version__ # noqa: F401
 
 
 class DeploymentType(Enum):
@@ -62,9 +62,13 @@ def __init__(self, api_key: str):
  else:
  self.upload = self.api.transfer_blob
 
- def create_project(self, name: str, description: str):
+ def create_project(self, name: str, description: str, task_type: TaskType):
  endpoint = "projects"
- payload = dict(name=name, description=description)
+ payload = dict(
+ name=name,
+ description=description,
+ taskType=task_type.value,
+ )
  project_data = self.api.post_request(endpoint, body=payload)
  return Project(project_data, self.upload, self.subscription_plan, self)
 
@@ -73,6 +77,12 @@ def load_project(self, name: str):
  project_data = self.api.get_request(endpoint)
  return Project(project_data, self.upload, self.subscription_plan, self)
 
+ def create_or_load_project(self, name: str, description: str, task_type: TaskType):
+ try:
+ return self.create_project(name, description, task_type)
+ except UnboxDuplicateTask:
+ return self.load_project(name)
+
  def add_model(
  self,
  name: str,
@@ -440,7 +450,6 @@ def add_model(
  project_id=project_id,
  description=description,
  classNames=class_names,
- taskType=task_type.value,
  architectureType=model_type.name,
  kwargs=list(kwargs.keys()),
  featureNames=feature_names,

unboxapi/api.py

@@ -12,7 +12,7 @@
 
 # UNBOX_ENDPOINT = "https://api-dev.unbox.ai/api"
 # UNBOX_ENDPOINT = "https://api.unbox.ai/api"
-UNBOX_ENDPOINT = "http://localhost:8080/v1"
+UNBOX_ENDPOINT = "http://localhost:8080/api"
 UNBOX_STORAGE_PATH = os.path.expanduser("~/unbox/unbox-onpremise/userStorage")
 
 

unboxapi/projects.py

@@ -1,5 +1,7 @@
-from .models import Model
+from unboxapi import tasks
+
 from .datasets import Dataset
+from .models import Model
 
 
 class Project:
@@ -40,8 +42,9 @@ def add_model(
  *args,
  **kwargs,
  ) -> Model:
- kwargs["project_id"] = self.id
- return self.client.add_model(*args, **kwargs)
+ return self.client.add_model(
+ *args, project_id=self.id, task_type=tasks.TaskType(self.taskType), **kwargs
+ )
 
  def add_dataset(
  self,