Overview

Cloud Storage allows world-wide storage and retrieval of any amount of data at any time. You can use Cloud Storage for a range of scenarios, which includes serving website content, storing data for archival and disaster recovery, or distributing large data objects to users via direct download.

In this lab you configure an application to use Cloud Storage to store and retrieve application data. The application is an online Quiz, the data is the form data, including an image you upload from your local machine.

Objectives

In this lab, you learn how to perform the following tasks:

• Set up Cloud Shell as your development environment
• Update the application code to integrate Cloud Datastore
• Use the Quiz application to upload an image file into Cloud Storage and view the image in the Quiz

Setup and requirements

For each lab, you get a new Google Cloud project and set of resources for a fixed time at no cost.

1. Sign in to Google Skills using an incognito window.

2. Note the lab's access time (for example, 1:15:00), and make sure you can finish within that time. There is no pause feature. You can restart if needed, but you have to start at the beginning.

3. When ready, click Start lab.

4. Note your lab credentials (Username and Password). You will use them to sign in to the Google Cloud Console.

5. Click Open Google Console.

6. Click Use another account and copy/paste credentials for this lab into the prompts. If you use other credentials, you'll receive errors or incur charges.

7. Accept the terms and skip the recovery resource page.

Activate Google Cloud Shell

Google Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud.

Google Cloud Shell provides command-line access to your Google Cloud resources.

1. In Cloud console, on the top right toolbar, click the Open Cloud Shell button.

   

2. Click Continue.

It takes a few moments to provision and connect to the environment. When you are connected, you are already authenticated, and the project is set to your PROJECT_ID. For example:

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

• You can list the active account name with this command:

Output:

Example output:

• You can list the project ID with this command:

Output:

Example output:

Task 1. Create a virtual environment

virtualenv is used to create user space virtual environments that allow you to install different sets of Python packages for different projects. Using virtualenv also means you don't have to install Python packages globally which can cause system tools or other Python projects to break. In this lab virtualenv is also used to make sure that Python3 is used for all Python commands.

1. Configure a virtualenv ennvironment for Python 3:

   virtualenv -p python3 vrenv

2. Activate the virtual environment:

   source vrenv/bin/activate

Task 2. Prepare the Quiz application

In this section, you access Cloud Shell, clone the git repository containing the Quiz application, and run the application.

Clone source code in Cloud Shell

1. To clone the repository for the class, execute the following command:

   git clone https://github.com/GoogleCloudPlatform/training-data-analyst

2. Create a soft link as a shortcut to your working directory:

   ln -s ~/training-data-analyst/courses/developingapps/v1.3/python/cloudstorage ~/cloudstorage

Configure and run the Quiz application

1. Change the working directory:

   cd ~/cloudstorage/start

2. Configure the application:

   . prepare_environment.sh

   Ignore any warnings.

   This script file:

   • Creates an App Engine application
   • Exports an environment variable, GCLOUD_PROJECT
   • Updates pip, then runs pip install -r requirements.txt
   • Creates entities in Cloud Datastore
   • Prints out the Google Cloud Platform Project ID

3. Run the application:

   python run_server.py

   The application is running when you see the following output:

   * Running on http://127.0.0.1:8080/ (Press CTRL+C to quit) * Restarting with stat * Debugger is active! * Debugger PIN: 502-577-323

Review the Quiz application

1. To view the application, click Web preview > Preview on port 8080.

2. Click the Create Question link in the toolbar.

You should see a simple form that contains textboxes for the question and answers and radio buttons to select the correct answer

Task 3. Examine the Quiz application code

In this section, you review the case study application code.

In this lab you'll view and edit files. You can use the shell editors that are installed on Cloud Shell, such as nano or vim or the Cloud Shell code editor.

This lab uses the Cloud Shell code editor to review the Quiz application code.

Launch the Cloud Shell code editor

• From Cloud Shell, click Open Editor > Open in new window to launch the code editor.

Examine the application code

1. Navigate to the /cloudstorage/start folder using the file browser panel on the left side of the editor.

2. Select the add.html file in the ...quiz/webapp/templates/ folder.

   This file contains the template for the Create Question form.

   Notice how the form has been modified to use multipart/form-data as the enc-type, and there are two new form controls:

   • A file upload control called image
   • A hidden field called imageUrl

3. Select the routes.py file in the ...quiz/webapp folder.

   This file contains the route for the POST handler that receives the form data. It has been modified to get the image file from the form.

4. Select the questions.py file in the ...quiz/webapp folder.

   This file contains the handler that processes the form data extracted in the routes.py file. You will modify this file to use a new module that is a client for Cloud Storage.

5. Select the ...quiz/gcp/storage.py file.

   This is the file where you will write code to save image file data into Cloud Storage.

Task 4. Create a Cloud Storage bucket

In this section, you create a Cloud Storage bucket and export an environment variable that references it.

1. Return to the Cloud Shell command line and click on Open Terminal.

2. Stop the application by pressing Ctrl+C.

3. Create a Cloud Storage bucket named <Project ID>-media:

   gcloud storage buckets create gs://$DEVSHELL_PROJECT_ID-media

   You can create a bucket using the gcloud storage buckets create command, passing through the name of the bucket as gs://BUCKET_NAME.

   You can use $DEVSHELL_PROJECT_ID as the bucket name prefix followed by -media

4. To export the Cloud Storage bucket name as an environment variable named GCLOUD_BUCKET, execute the following command:

   export GCLOUD_BUCKET=$DEVSHELL_PROJECT_ID-media

Click Check my progress to verify the objective. Create a bucket

Task 5. Adding objects to Cloud Storage

In this section, you write code to save uploaded files into Cloud Storage.

For more information on API documentation for Cloud Storage, refer to the APIs & reference reference.

Import and use the Python Cloud Storage module

1. In code editor, move to the top of the ...quiz/gcp/storage.py file.
2. Get the bucket name from the GCLOUD_BUCKET environment variable.
3. Import the storage module from the google.cloud package.
4. Create a Cloud Storage client.
5. Get a reference to the Cloud Storage bucket.

quiz/gcp/storage.py:

Write code to send a file to Cloud Storage

1. Sill in storage.py, in the the upload_file(...) function, remove the existing pass statement, then use the Cloud Storage client to upload a file to your Cloud Storage bucket and make it publicly available.
2. Get a reference to a Cloud Storage blob object in the bucket.
3. Use the blob object to upload the image.
4. Make the file public.
5. Return the blob's public URL.

quiz/gcp/storage.py upload_file(...) function:

6. Save storage.py.

Write code to use the Cloud Storage functionality

1. In the editor, move to the top of the ...quiz/webapp/questions.py file.
2. Modify the import statement to use your storage client as well as the datastore client.
3. Move to the upload_file(...) function and use your storage client to upload a file, and assign the returned public URL to a variable.
4. Modify the return statement to return the public URL.
5. Move to the save_question(...) function and write an if test to see if the image_file is present.
6. If it is, then call the upload_file(...) function, and assign the public URL to a entity property named imageUrl.
7. If not, then assign an empty string to the entity imageUrl property.

quiz/webapp/questions.py:

8. Save questions.py.

Run the application and create a Cloud Storage object

1. Return to Cloud Shell to run the application:

2. Download the storage logo image file to your local machine.

3. In Cloud Shell, click Web preview > Preview on port 8080 to preview the Quiz application.

4. Click the Create Question link.

5. Complete the form with the following values, and then click Save:

   Form Field	Value
   Author	Your name
   Quiz	Google Cloud Platform
   Title	Which product does this logo relate to?
   Image	Upload the Google_Cloud_Storage_logo.png file you previously downloaded
   Answer 1	App Engine
   Answer 2	Cloud Storage (Select the Answer 2 radio button)
   Answer 3	Compute Engine
   Answer 4	Kubernetes Engine

6. Return to the Cloud Console and navigate to Navigation menu > Cloud Storage.

7. On the Cloud Storage > Buckets page, click the correct bucket (named <Project ID>-media).

You should see your new object named Google_Cloud_Storage_logo.png.

Click Check my progress to verify the objective. Upload objects to your bucket

Run the client application and test the Cloud Storage public URL

1. Add /api/quizzes/gcp to the end of the application's URL.

   You should see that JSON data has been returned to the client corresponding to the Question you added in the web application.

   The imageUrl property should have a value corresponding to the object in Cloud Storage.

2. Return to the application home page and click the Take Test link.

3. Click GCP, and answer each question.

   When you get to the question you just added, you should see the image has been formatted inside the client-side web application!

End your lab

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