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.