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Googlesheet to JSON -> S3

This Lambda function opens a Google Sheet using a Google API Service Account (https://console.developers.google.com/apis/credentials). The sheet must be shared with the service account.

The program then reads all elements in columns A and B, to create a key=>value pair which is encoded into JSON and uploaded to S3.

Example

Google Sheet (with formulas calculating the values):

A B
wood 72
rubber 12
glass 34

Output:

{"rubber": "34", "glass": "12", "wood": "72"}

Configuration

The python script requires two configuration files, config.json and credentials.json, as explained below.

config.json

The config.json file should contain the s3 and sheet parameters of the Google Sheet you wish to open (...spreadsheets/d/SHEETID/edit...)

{
  "s3_bucket": "spreadsheet-archive",
  "s3_key": "latest.json",
  "sheet_id": "1SyH5Np4cAAAAtQqMbI9yKylYsdH0AsX2dRaaaav3L4",
  "worksheet_name": "Statistics"
}

credentials.json

The credentials.json file should contain the JSON private key configuration downloaded for the service account when created in Google API Manager (within a certain project). See: https://developers.google.com/identity/protocols/OAuth2ServiceAccount

{
  "type": "service_account",
  "project_id": "my-really-cool-project",
  "private_key_id": "someprivatekeyid",
  "private_key": "-----BEGIN PRIVATE KEY-----\n my very private key -----END PRIVATE KEY-----\n",
  "client_email": "myserviceaccount@myproject.iam.gserviceaccount.com",
  "client_id": "00000000000000",
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": "https://accounts.google.com/o/oauth2/token",
  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/lambda%40ft-security-issue-monitor.iam.gserviceaccount.com"
}

Testing locally

It is possible to test the script locally by running:

/usr/bin/python2.7 main.py

Deployment onto Lambda

The main.py, config.json and credentials.json file should be uploaded to Lambda in a ZIP file. The environment should be set to Python 2.7 with a timeout of ~30 seconds. RAM requirements depends on the data you are extracting, however 128MB will be plenty for most scenarios. To prepare the ZIP for upload, ensure you have the latest libraries in your project directory.

pip install gspread oauth2client -t .

Other Deployments

You can easily adapt the code to output the JSON locally (using file write), or upload to S3 when running locally on your machine if required.