Python Flask Skeleton taken from https://github.com/GoogleCloudPlatform/appengine-try-python-flask.git Goal is to have this working to fetch data from Google BigQuery Public Dataset as seen in my video demo . I will get to that in the next few days
Naresh Ganatra ... added code/module to work with api.ai
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Install the App Engine Python SDK. See the README file for directions. You'll need python 2.7 and pip 1.4 or later installed too.
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Clone this repo with
git clone https://github.com/GoogleCloudPlatform/appengine-flask-skeleton.git -
Install dependencies in the project's lib directory. Note: App Engine can only import libraries from inside your project directory.
cd appengine-flask-skeleton pip install -r requirements.txt -t lib -
Run this project locally from the command line:
dev_appserver.py .
Visit the application http://localhost:8080
See the development server documentation for options when running dev_appserver.
To deploy the application:
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Use the Admin Console to create a project/app id. (App id and project id are identical)
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appcfg.py update -A <your-project-id> -V v1 .If this isn't your first deployment, you will need to set the new version as the default version with
appcfg.py set_default_version -V v1 -A <your-project-id> -
Congratulations! Your application is now live at your-app-id.appspot.com
This skeleton includes TODO markers to help you find basic areas you will want
to customize.
To add persistence to your models, use NDB for scale. Consider CloudSQL if you need a relational database.
See the Third party libraries page for libraries that are already included in the SDK. To include SDK libraries, add them in your app.yaml file. Other than libraries included in the SDK, only pure python libraries may be added to an App Engine project.
Star this repo if you found it useful. Use the github issue tracker to give feedback on this repo.
See LICENSE