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cloud-sql: add Cloud Run support to sqlalchemy sample (GoogleCloudPlatform#2449)
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‎cloud-sql/mysql/sqlalchemy/.dockerignore

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Dockerfile
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.dockerignore
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__pycache__
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.pytest_cache

‎cloud-sql/mysql/sqlalchemy/.gitignore

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__pycache__
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.pytest_cache

‎cloud-sql/mysql/sqlalchemy/Dockerfile

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# Copyright 2019 Google, LLC.
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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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# Use the official Python image.
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# https://hub.docker.com/_/python
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FROM python:3.7
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# Copy application dependency manifests to the container image.
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# Copying this separately prevents re-running pip install on every code change.
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COPY requirements.txt ./
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# Install production dependencies.
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RUN set -ex; \
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pip install -r requirements.txt; \
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pip install gunicorn
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# Copy local code to the container image.
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ENV APP_HOME /app
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WORKDIR $APP_HOME
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COPY . ./
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# Run the web service on container startup. Here we use the gunicorn
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# webserver, with one worker process and 8 threads.
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# For environments with multiple CPU cores, increase the number of workers
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# to be equal to the cores available.
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CMD exec gunicorn --bind :$PORT --workers 1 --threads 8 main:app

‎cloud-sql/mysql/sqlalchemy/README.md

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```bash
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gcloud app deploy
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```
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## Deploy to Cloud Run
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See the [Cloud Run documentation](https://cloud.google.com/run/docs/configuring/connect-cloudsql)
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for more details on connecting a Cloud Run service to Cloud SQL.
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1. Build the container image:
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```sh
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gcloud builds submit --tag gcr.io/[YOUR_PROJECT_ID]/run-mysql
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```
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2. Deploy the service to Cloud Run:
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```sh
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gcloud beta run deploy run-mysql --image gcr.io/[YOUR_PROJECT_ID]/run-mysql
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```
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Take note of the URL output at the end of the deployment process.
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3. Configure the service for use with Cloud Run
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```sh
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gcloud beta run services update run-mysql \
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--add-cloudsql-instances [INSTANCE_CONNECTION_NAME] \
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--set-env-vars CLOUD_SQL_CONNECTION_NAME=[INSTANCE_CONNECTION_NAME],\
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DB_USER=[MY_DB_USER],DB_PASS=[MY_DB_PASS],DB_NAME=[MY_DB]
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```
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Replace environment variables with the correct values for your Cloud SQL
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instance configuration.
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This step can be done as part of deployment but is separated for clarity.
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4. Navigate your browser to the URL noted in step 2.
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For more details about using Cloud Run see http://cloud.run.
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Review other [Python on Cloud Run samples](../../../run/).

‎run/README.md

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| ------------------------------- | ------------------------ | ------------- |
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|[Hello World][helloworld]&nbsp;&#10149; | Quickstart | [<img src="https://storage.googleapis.com/cloudrun/button.svg" alt="Run on Google Cloud" height="30">][run_button_helloworld] |
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|[Cloud Pub/Sub][pubsub] | Handling Pub/Sub push messages | [<img src="https://storage.googleapis.com/cloudrun/button.svg" alt="Run on Google Cloud" height="30">][run_button_pubsub] |
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|[Cloud SQL (MySQL)[mysql] | Use MySQL with Cloud Run | - |
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For more Cloud Run samples beyond Python, see the main list in the [Cloud Run Samples repository](https://github.com/GoogleCloudPlatform/cloud-run-samples).
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[run_deploy]: https://cloud.google.com/run/docs/deploying
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[helloworld]: https://github.com/knative/docs/tree/master/docs/serving/samples/hello-world/helloworld-python
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[pubsub]: pubsub/
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[mysql]: ../cloud-sql/mysql/sqlalchemy
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[run_button_helloworld]: https://console.cloud.google.com/cloudshell/editor?shellonly=true&cloudshell_image=gcr.io/cloudrun/button&cloudshell_git_repo=https://github.com/knative/docs&cloudshell_working_dir=docs/serving/samples/hello-world/helloworld-python
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[run_button_pubsub]: https://console.cloud.google.com/cloudshell/editor?shellonly=true&cloudshell_image=gcr.io/cloudrun/button&cloudshell_git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&cloudshell_working_dir=run/pubsub
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[testing]: https://cloud.google.com/run/docs/testing/local#running_locally_using_docker_with_access_to_services

‎run/pubsub/Dockerfile

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# Copy local code to the container image.
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ENV APP_HOME /app
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WORKDIR $APP_HOME
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COPY . .
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COPY . ./
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# Run the web service on container startup. Here we use the gunicorn
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# webserver, with one worker process and 8 threads.
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# Run the web service on container startup.
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# Use gunicorn webserver with one worker process and 8 threads.
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# For environments with multiple CPU cores, increase the number of workers
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# to be equal to the cores available.
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CMD exec gunicorn --bind :$PORT --workers 1 --threads 8 main:app

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