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Commit b00f1dc

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Jonathan Wayne Parrott
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Merge pull request GoogleCloudPlatform#156 from GoogleCloudPlatform/managedvms-samples
Adding new Managed VMs samples.
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‎managed_vms/.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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env/
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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*.egg-info/
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.installed.cfg
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*.egg
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*,cover
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# Django stuff:
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*.log
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/

‎managed_vms/README.md

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## Google App Engine Managed VMs Python Samples
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These are samples for using Python on Google App Engine Managed VMs. These samples are typically referenced from the [docs](https://cloud.google.com/appengine/docs).
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See our other [Google Cloud Platform github repos](https://github.com/GoogleCloudPlatform) for sample applications and
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scaffolding for other frameworks and use cases.
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## Run Locally
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Some samples have specific instructions. If there is a README in the sample folder, pleaese refer to it for any additional steps required to run the sample.
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In general, the samples typically require:
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1. Install the [Google Cloud SDK](https://cloud.google.com/sdk/), including the [gcloud tool](https://cloud.google.com/sdk/gcloud/), and [gcloud app component](https://cloud.google.com/sdk/gcloud-app).
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2. Setup the gcloud tool. This provides authentication to Google Cloud APIs and services.
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```
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gcloud init
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```
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3. Clone this repo.
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```
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git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
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cd python-docs-samples/managed_vms
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```
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4. Open a sample folder, create a virtualenv, install dependencies, and run the sample:
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```
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cd hello-world
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virtualenv env
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source env/bin/activate
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pip install -r requirements.txt
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python main.py
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```
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5. Visit the application at [http://localhost:8080](http://localhost:8080).
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## Deploying
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Some samples in this repositories may have special deployment instructions. Refer to the readme in the sample directory.
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1. Use the [Google Developers Console](https://console.developer.google.com) to create a project/app id. (App id and project id are identical)
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2. Setup the gcloud tool, if you haven't already.
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```
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gcloud init
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```
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3. Use gcloud to deploy your app.
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```
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gcloud preview app deploy app.yaml
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```
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4. Congratulations! Your application is now live at `your-app-id.appspot.com`
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## Contributing changes
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* See [CONTRIBUTING.md](../CONTRIBUTING.md)
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## Licensing
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* See [LICENSE](../LICENSE)

‎managed_vms/analytics/.dockerignore

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.dockerignore
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Dockerfile
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.git
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.hg
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.svn
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env
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*.pyc
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__pycache__

‎managed_vms/analytics/Dockerfile

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FROM gcr.io/google_appengine/python
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# Change the -p argument to use Python 2.7 if desired.
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RUN virtualenv /env -p python3.4
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# Set virtualenv environment variables. This is equivalent to running
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# source /env/bin/activate.
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ENV VIRTUAL_ENV /env
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ENV PATH /env/bin:$PATH
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ADD requirements.txt /app/
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RUN pip install -r requirements.txt
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ADD . /app/
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CMD gunicorn -b :$PORT main:app

‎managed_vms/analytics/README.md

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# Google Analytics Measurement Protocol sample for Google App Engine Managed VMs
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This sample demonstrates how to use the [Google Analytics Measurement Protocol](https://developers.google.com/analytics/devguides/collection/protocol/v1/) (or any other SQL server) on [Google App Engine Managed VMs](https://cloud.google.com/appengine).
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## Setup
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Before you can run or deploy the sample, you will need to do the following:
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1. Create a Google Analytics Property and obtain the Tracking ID.
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2. Update the environment variables in in ``app.yaml`` with your Tracking ID.
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## Running locally
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Refer to the [top-level README](../README.md) for instructions on running and deploying.
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You will need to set the following environment variables via your shell before running the sample:
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$ export GA_TRACKING_ID=[your Tracking ID]
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$ python main.py

‎managed_vms/analytics/app.yaml

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runtime: custom
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vm: true
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#[START env]
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env_variables:
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GA_TRACKING_ID: your-tracking-id
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#[END env]

‎managed_vms/analytics/main.py

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# Copyright 2015 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# [START app]
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import os
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from flask import Flask
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import requests
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app = Flask(__name__)
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# Environment variables are defined in app.yaml.
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GA_TRACKING_ID = os.environ['GA_TRACKING_ID']
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def track_event(category, action, label=None, value=None):
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data = {
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'v': '1', # API Version.
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'tid': GA_TRACKING_ID, # Tracking ID / Property ID.
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# Anonymous Client Identifier. Ideally, this should be a UUID that
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# is associated with particular user, device, or browser instance.
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'cid': '555',
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't': 'event', # Event hit type.
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'ec': category, # Event category.
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'ea': action, # Event action.
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'el': label, # Event label.
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'ev': value, # Event valueself.
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}
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response = requests.post(
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'http://www.google-analytics.com/collect', data=data)
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# If the request fails, this will raise a RequestException. Depending
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# on your application's needs, this may be a non-error and can be caught
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# by the caller.
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response.raise_for_status()
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@app.route('/')
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def track_example():
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track_event(
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category='Example',
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action='test action')
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return 'Event tracked.'
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if __name__ == '__main__':
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# This is used when running locally. Gunicorn is used to run the
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# application on Google App Engine. See CMD in Dockerfile.
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app.run(host='127.0.0.1', port=8080, debug=True)
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# [END app]

‎managed_vms/analytics/requirements.txt

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Flask==0.10.1
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gunicorn==19.4.5
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requests[security]==2.9.1

‎managed_vms/cloudsql/.dockerignore

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.dockerignore
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Dockerfile
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.git
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.hg
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.svn
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env
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*.pyc
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__pycache__

‎managed_vms/cloudsql/Dockerfile

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FROM gcr.io/google_appengine/python
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# Change the -p argument to use Python 2.7 if desired.
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RUN virtualenv /env -p python3.4
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# Set virtualenv environment variables. This is equivalent to running
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# source /env/bin/activate.
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ENV VIRTUAL_ENV /env
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ENV PATH /env/bin:$PATH
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ADD requirements.txt /app/
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RUN pip install -r requirements.txt
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ADD . /app/
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CMD gunicorn -b :$PORT main:app

‎managed_vms/cloudsql/README.md

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# Python Google Cloud SQL sample for Google App Engine Managed VMs
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This sample demonstrates how to use [Google Cloud SQL](https://cloud.google.com/sql/) (or any other SQL server) on [Google App Engine Managed VMs](https://cloud.google.com/appengine).
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## Setup
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Before you can run or deploy the sample, you will need to do the following:
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1. Create a Cloud SQL instance. You can do this from the [Google Developers Console](https://console.developers.google.com) or via the [Cloud SDK](https://cloud.google.com/sdk). To create it via the SDK use the following command:
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$ gcloud sql instances create [your-instance-name] \
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--assign-ip \
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--authorized-networks 0.0.0.0/0 \
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--tier D0
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2. Create a new user and database for the application. The easiest way to do this is via the [Google Developers Console](https://console.developers.google.com/project/_/sql/instances/example-instance2/access-control/users). Alternatively, you can use MySQL tools such as the command line client or workbench, but you will need to set a root password for your database using `gcloud sql instances set-root-password`.
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3. Update the connection string in ``app.yaml`` with your instance values.
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4. Finally, run ``create_tables.py`` to ensure that the database is properly configured and to create the tables needed for the sample.
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## Running locally
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Refer to the [top-level README](../README.md) for instructions on running and deploying.
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You will need to set the following environment variables via your shell before running the sample:
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$ export SQLALCHEMY_DATABASE_URI=[your connection string]
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$ python main.py

‎managed_vms/cloudsql/app.yaml

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runtime: custom
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vm: true
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#[START env]
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env_variables:
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# Replace user, password, and host with the values obtained when
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# configuring your Cloud SQL instance.
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SQLALCHEMY_DATABASE_URI: mysql+pymysql://user:password@host/db
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# If you are connecting over SSL, you can specify your certificates by
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# using a connection string such as:
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# > mysql+pymysql://user:password@host/db?
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# ssl_key=client-key.pem?ssl_cert=client-cert.pem?ssl_ca=server-ca.pem
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#[END env]

‎managed_vms/cloudsql/create_tables.py

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#! /usr/bin/env python
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# Copyright 2015 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# [START all]
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from main import db
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if __name__ == '__main__':
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print('Creating all database tables...')
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db.create_all()
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print('Done!')
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# [END all]

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