CGP Dev 3. Storing Image/Video Files in Cloud Storage - Python

1_quiz_gcp_storage.py

# Get the Bucket name from the GCLOUD_BUCKET environment variable
bucket_name = os.getenv('GCLOUD_BUCKET')

# Import the storage module
from google.cloud import storage

# Create a client for Cloud Storage
storage_client = storage.Client()

# Use the client to get the Cloud Storage bucket
bucket = storage_client.get_bucket(bucket_name)

"""
Uploads a file to a given Cloud Storage bucket and returns the public url
to the new object.
"""
def upload_file(image_file, public):
    # Use the bucket to get a blob object
    blob = bucket.blob(image_file.filename)
    
    # Use the blob to upload the file
    blob.upload_from_string(
        image_file.read(),
        content_type=image_file.content_type)
    
    # Make the object public
    if public:
        blob.make_public()

    # Modify to return the blob's Public URL
    return blob.public_url

2_quiz_webapp_questions.py

# Import the storage module
from quiz.gcp import storage, datastore

"""
uploads file into google cloud storage
- upload file
- return public_url
"""
def upload_file(image_file, public):
    if not image_file:
        return None

    # Use the storage client to Upload the file
    # The second argument is a boolean
    public_url = storage.upload_file(
       image_file,
       public
    )

    # Return the public URL for the object
    return public_url

"""
uploads file into google cloud storage
- call method to upload file (public=true)
- call datastore helper method to save question
"""
def save_question(data, image_file):
    # If there is an image file, then upload it
    # And assign the result to a new Datastore
    # property imageUrl
    # If there isn't, assign an empty string
    if image_file:
        data['imageUrl'] = unicode(
                  upload_file(image_file, True))
    else:
        data['imageUrl'] = u''

    data['correctAnswer'] = int(data['correctAnswer'])
    datastore.save_question(data)
    return

3_GCP_Console.sh

git clone https://github.com/GoogleCloudPlatform/training-data-analyst
cd ~/training-data-analyst/courses/developingapps/python/cloudstorage/start
# Run prepare_environment.sh, ie Create an App Engine application, 
# export an environment variable, GCLOUD_PROJECT.
# Update pip, then run pip install -r requirements.txt.
# Create entities in Cloud Datastore.
# Print out the Google Cloud Platform Project ID.
. prepare_environment.sh
python run_server.py

gsutil mb gs://$DEVSHELL_PROJECT_ID-media
export GCLOUD_BUCKET=$DEVSHELL_PROJECT_ID-media

4_prepare_environment.sh

#!/bin/bash

# Copyright 2017 Google Inc.
#
# 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.

echo "Creating Datastore/App Engine instance"
gcloud app create --region "us-central"

echo "Exporting GCLOUD_PROJECT"
export GCLOUD_PROJECT=$DEVSHELL_PROJECT_ID

#echo "Creating virtual environment"
#mkdir ~/venvs
#virtualenv ~/venvs/developingapps
#source ~/venvs/developingapps/bin/activate

echo "Installing Python libraries"
sudo pip install --upgrade pip
sudo pip install -r requirements.txt

echo "Creating Datastore entities"
python add_entities.py

echo "Project ID: $DEVSHELL_PROJECT_ID"