chore(retail): migrate code from googleapis/python-retail

.github/CODEOWNERS

@@ -71,6 +71,7 @@
 /profiler/**/*                         @GoogleCloudPlatform/python-samples-reviewers
 /pubsub/**/*                           @anguillanneuf @hongalex @GoogleCloudPlatform/python-samples-reviewers
 /pubsublite/**/*                       @anguillanneuf @hongalex @GoogleCloudPlatform/python-samples-reviewers
+/retail/**/*                           @GoogleCloudPlatform/dee-data-ai @GoogleCloudPlatform/python-samples-reviewers
 /run/**/*                              @GoogleCloudPlatform/aap-dpes  @GoogleCloudPlatform/python-samples-reviewers
 /run/django/**/*                       @glasnt @GoogleCloudPlatform/aap-dpes  @GoogleCloudPlatform/python-samples-reviewers
 /secretmanager/**/*                    @GoogleCloudPlatform/aap-dpes @GoogleCloudPlatform/python-samples-reviewers

.github/blunderbuss.yml

@@ -91,8 +91,9 @@ assign_issues_by:
 - labels:
   - 'api: language'
   - 'api: texttospeech'
+  - 'api: retail'
   to:
-    - GoogleCloudPlatform/dee-data-ai
+  - GoogleCloudPlatform/dee-data-ai
 - labels:
   - 'api: ml'
   to:
@@ -186,7 +187,10 @@ assign_prs_by:
   - 'api: cloudtasks'
   to:
   - GoogleCloudPlatform/infra-db-dpes
-
+- labels:
+  - 'api: retail'
+  to: 
+  - GoogleCloudPlatform/dee-data-ai
 assign_issues:
   - GoogleCloudPlatform/python-samples-owners
 

retail/interactive-tutorials/README.md

@@ -0,0 +1,188 @@
+#Retail Search Interactive Tutorials
+
+##Run tutorials in Cloud Shell
+
+To advance with the interactive tutorials, use Retail Search step-by-step manuals on the right side of the Cloud Shell IDE: 
+![Interactive tutorials](images/tutorial1.png)
+
+The interactive tutorial should open by default. If it didn’t, click on the Tutorial symbol in the menu bar to open the step-by-step manual:
+![Toggle tutorial](images/tutorials2.png)
+
+For more details about the Cloud Shell environment, refer to the [Cloud Shell documentation](https://cloud.google.com/shell/docs).
+
+## Interactive tutorial flow
+
+Interactive guides are intended to help you understand the features provided by Google Cloud Retail Search and test the Retail API in action.
+
+To proceed with the tutorial, choose a language you’ll be deploying your project in:
+![Select a programming language](images/tutorials3.png)
+
+
+To begin with the tutorial workflow, click the Start button:
+![Begin with the tutorial](images/tutorials4.png)
+
+Then, you can use Next and Previous buttons to navigate the tutorial pages.
+
+## Get started with the Google Cloud Retail API
+
+The Retail API provides you with the following possibilities to: 
+  - Create and maintaining the catalog data. 
+  - Fine-tune the search configuration.
+  - Import and maintain the user events data.
+
+You can find the information about the Retail services in the [documentation](https://cloud.google.com/retail/docs)
+
+<!--TODO(tkarasova) update the link to the tutorials when will be published-->
+If you would like to have a closer look at the Retail API features and try them yourself,
+the best option is to use the [Interactive Tutorials](https://cloud.google.com/retail/docs/overview). The tutorials will be launched in the CloudShell environment, and you will be able to request the Retail services and check the response with minimum time and effort.
+
+The code samples in the directory **python-retail/samples/interactive-tutorials** are explicitly created for use with the Retail Interactive Tutorials.
+
+If, for some reason, you have decided to proceed with these code samples without the tutorial, please go through the following steps and set up the required preconditions.
+
+### Select your project and enable the Retail API
+
+Google Cloud organizes resources into projects. This lets you
+collect all related resources for a single application in one place.
+
+If you don't have a Google Cloud project yet or you're not the owner of an existing one, you can
+[create a new project](https://console.cloud.google.com/projectcreate).
+
+After the project is created, set your PROJECT_ID to a ```project``` variable:
+
+1. Run the following command in the Terminal:
+
+    ```bash
+    gcloud config set project <YOUR_PROJECT_ID>
+    ```
+
+1. Ensure that the Retail API is enabled for your project in the [API & Services page](https://console.cloud.google.com/apis/api/retail.googleapis.com/).
+
+## Prepare your work environment
+
+To prepare the work environment you should perform the following steps:
+- Create a service account.
+- Create service account key and set it to authorize your calls to the Retail API.
+- Install Google Cloud Retail library.
+
+### Create service account
+
+To access the Retail API, you must create a service account. Check that you are an owner of your Google Cloud project on the [IAM page](https://console.cloud.google.com/iam-admin/iam).
+
+1. To create a service account, perform the following command:
+
+    ```bash
+    gcloud iam service-accounts create <YOUR_SERVICE_ACCOUNT_ID>
+    ```
+
+1. Assign the needed roles to your service account:
+
+    ```bash
+    for role in {retail.admin,storage.admin}
+    do gcloud projects add-iam-policy-binding <YOUR_PROJECT_ID> --member="serviceAccount:<YOUR_SERVICE_ACCOUNT_ID>@<YOUR_PROJECT_ID>.iam.gserviceaccount.com" --role="roles/${role}"
+    done
+    ```
+
+1. Use the following command to print out the service account email:
+
+    ```bash
+    gcloud iam service-accounts list|grep <YOUR_SERVICE_ACCOUNT_ID>
+    ```
+
+    Copy the service account email.
+
+
+1.  Upload your service account key JSON file and use it to activate the service
+    account:
+
+    ```bash
+    gcloud iam service-accounts keys create ~/key.json --iam-account <YOUR_SERVICE_ACCOUNT_EMAIL>
+    ```
+
+    ```bash
+    gcloud auth activate-service-account --key-file ~/key.json
+    ```
+
+1.  Set the key as the GOOGLE_APPLICATION_CREDENTIALS environment variable to
+    use it for sending requests to the Retail API.
+
+    ```bash
+    export GOOGLE_APPLICATION_CREDENTIALS=~/key.json
+    ```
+
+### Install Google Cloud Retail libraries
+
+To run Python code samples for the Retail API tutorial, you need to set up your virtual environment.
+
+1. Run the following commands in a Terminal to create an isolated Python environment:
+
+    ```bash
+    virtualenv -p python3 myenv
+    source myenv/bin/activate
+    ```
+
+1. Next, install Google packages:
+
+    ```bash
+    pip install google
+    pip install google-cloud-retail
+    pip install google-cloud-storage
+    pip install google-cloud-bigquery
+
+    ```
+
+## Import catalog data
+
+There is a python-retail/samples/interactive-tutorials/resources/products.json file with valid products prepared in the `resources` directory.
+
+The other file, python-retail/samples/interactive-tutorials/resources/products_some_invalid.json, contains both valid and invalid products. You will use it to check the error handling.
+
+### Upload catalog data to Cloud Storage
+
+In your own project you need to create a Cloud Storage bucket and put the JSON file there.
+The bucket name must be unique. For convenience, you can name it `<YOUR_PROJECT_ID>_<TIMESTAMP>`.
+
+1. The code samples for each of the Retail services are stored in different directories.
+
+    Go to the code samples directory, your starting point to run more commands.
+
+    ```bash
+    cd python-retail/samples/interactive-tutorials
+    ```
+
+1. To create the bucket and upload the JSON file, open python-retail/samples/interactive-tutorials/product/setup_product/products_create_gcs_bucket.py file
+
+1. Go to the **product** directory and run the following command in the Terminal:
+
+    ```bash
+    python product/setup_product/products_create_gcs_bucket.py
+    ```
+
+    Now you can see the bucket is created in the [Cloud Storage](https://console.cloud.google.com/storage/browser), and the files are uploaded.
+
+1. The name of the created Cloud Storage bucket is printed in the Terminal.
+
+    ```
+    The gcs bucket <YOUR_PROJECT_ID>_<TIMESTAMP> was created
+    ```
+
+    Copy the name and set it as the environment variable `BUCKET_NAME`:
+
+    ```bash
+    export BUCKET_NAME=<YOUR_BUCKET_NAME>
+    ```
+
+### Import products to the Retail Catalog
+
+To import the prepared products to a catalog, open python-retail/samples/interactive-tutorials/product/import_products_gcs.py file and run the following command in the Terminal:
+
+```bash
+python product/import_products_gcs.py
+```
+
+## Run your code sample
+
+Run the sample in a terminal with the following command:
+```bash
+python search/search_with_boost_spec.py
+```

retail/interactive-tutorials/TEST_RESOURCES_SETUP_CLEANUP.md

@@ -0,0 +1,50 @@
+# How to set up/ tear down the test resources
+
+## Required environment variables
+
+To successfully import the catalog data for tests, the following environment variables should be set:
+ - BUCKET_NAME
+ - EVENTS_BUCKET_NAME
+These values are stored in the Secret Manager and will be submitted as 
+   docker environment variables before the test run.
+
+The Secret Manager name is set in .kokoro/presubmit/common.cfg file, SECRET_MANAGER_KEYS variable.
+
+## Import catalog data
+
+There are JSON files with valid products and user events prepared in `resources` directory:
+`samples/resources/products.json` and `samples/resources/user_events.json` respectively.
+
+Run the `create_test_resources.py` to perform the following actions:
+   - create the GCS bucket <BUCKET_NAME>, 
+      - upload the product data from `resources/products.json` file to products bucket,
+   - import products to the default branch of the Retail catalog,
+   - create the GCS bucket <EVENTS_BUCKET_NAME>, 
+      - upload the product data from `resources/user_events.json` file to events bucket,
+   - create a BigQuery dataset and table `products`,
+      - insert products from resources/products.json to the created products table,
+   - create a BigQuery dataset and table `events`,
+      - insert user events from resources/user_events.json to the created events table
+
+
+```
+$ python create_test_resources.py
+```
+
+In the result 316 products should be created in the test project catalog.
+
+
+## Remove catalog data
+
+Run the `remove_test_resources.py` to perform the following actions:
+   - remove all objects from the GCS bucket <BUCKET_NAME>, 
+   - remove the <BUCKET_NAME> bucket,
+   - delete all products from the Retail catalog.
+   - remove all objects from the GCS bucket <EVENTS_BUCKET_NAME>, 
+   - remove the <EVENTS_BUCKET_NAME> bucket,
+   - remove dataset `products` along with tables
+   - remove dataset `user_events` along with tables 
+
+```
+$ python remove_test_resources.py
+```

retail/interactive-tutorials/events/conftest.py

@@ -0,0 +1,30 @@
+# Copyright 2022 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import pytest
+import test_utils.prefixer
+
+prefixer = test_utils.prefixer.Prefixer(
+    "python-retail", "samples/interactive-tutorials/product"
+)
+
+
+@pytest.fixture(scope="session")
+def table_id_prefix() -> str:
+    return prefixer.create_prefix()
+
+
+@pytest.fixture(scope="session")
+def bucket_name_prefix() -> str:
+    return prefixer.create_prefix()