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Lambdasheets

Process google sheets with Pandas on AWS lambda

##Installaion

Prerequisite

Install pipenv

Python environment and dependencies

Clone the repository, then from the repository directory:

pipenv install --dev
pipenv shell

Configuration

Configure zappa with:

zappa init

Choose lambdasheets.app for the application.

Create a project in your google developer console. Add access to 'Google Drive' and 'Google sheets' APIs. Create a service account: note the service account email. Download the account key and copy it in the project directory.

Note: You may choose to use OAuth2 instead Read more on pygsheet's docs here.

Create the config file:

cp config_template.py config.py

Edit the config.py file and set the the service file name.

Spreadhseet

Create a new spreadsheet with first columns named start and end. Share it with the service account email. Set the spreadsheet name in the config.py file.

You can use this spreadsheet as a template.

You can test that the service account has access to the spreadsheet by launching the flask server locally:

python lambdasheets.py

Head to http://127.0.0.1:5000/ in your browser. You should see OK.

Deploy function

zappa deploy

Note the deployment url returned by zappa.

Triggering updates from the Google sheets UI.

We are going to add a menu item to trigger a run of our lambda function.

In Tools > Script Editor

Copy the code from script.gs, replace [deployed_url] by the one given by zapp, save and reload. You should see a new Lambda Sheets menu that you can use to trigger updates.

You will be asked an authorization when running for the first time.

Your function

Edit lambdasheets.py to do the processing you want.

Check pygsheets for more details on how to interact with the spreadsheet from python.

To redeploy:

zappa update

Trigger modes

  • on menu click: this the one we covered
  • Spreadsheet driven: in the google script editor, choose Edit -> Current project's trigger and choose the auto execution mode you want
  • AWS driven: configure triggers from your AWS console using CLoudFront, S3 ...