Python Flask server connected to Bigtable to serve up data needed for MLab Visualization.

Required packages can be installed via:

pip install -r requirements.txt

Suggestion: Have a conda environment active before installing packages.

Start Flask server via

python main.py

We can deploy to flexibe App Engine!

To deploy to app engine, run this simple command:

make deploy

Well, its not really that simple. For this to work, it requires a few things:

1 - access to your Google Service Account JSON file. It currently looks for it in:

../mlab-keys/mlab-cred.json

So ensure that directory and file is present.

2 - copies of the bigtable config files. It looks for them in:

../mlab-vis-pipeline/dataflow/data/bigtable/

You can use make prepare to copy the appropriate config files from the pipeline to the api.

So make sure they are present and up-to-date

3 - the gcloud command line tool.

Currently, gcloud app deploy is used to deploy. Ensure you have this tool installed and configured properly.

The app will be deployed and accessible from:

http://mlab-api-dot-mlab-oti.appspot.com/

The API is documented at this url as well.

Test requirements are stored in a separate requirements-test.txt file.

(So that the deploy code does not need to download these additional requirements).

Install with:

pip install -r requirements-test.txt

Then run tests with:

make test

This code depends heavily on the Flask-RESTPlus package.

It uses the google api python client for communicating with BigTable.